Embedding Spatial Software Visualization in the IDE: an Exploratory Study

Abstract: Software visualization can be of great use for understanding and exploring a software system in an intuitive manner. Spatial representation of software is a promising approach of increasing interest. However, little is known about how developers interact with spatial visualizations that are embedded in the IDE. In this paper, we present a pilot study that explores the use of Software Cartography for program comprehension of an unknown system. We investigated whether developers establish a spatial memory of the system, whether clustering by topic offers a sound base layout, and how developers interact with maps. We report our results in the form of observations, hypotheses, and implications. Key findings are a) that developers made good use of the map to inspect search results and call graphs, and b) that developers found the base layout surprising and often confusing. We conclude with concrete advice for the design of embedded software maps.


Clustering Unstructured Data (Flat Files) - An Implementation in Text Mining Tool

Abstract: With the advancement of technology and reduced storage costs, individuals and organizations are tending towards the usage of electronic media for storing textual information and documents. It is time consuming for readers to retrieve relevant information from unstructured document collection. It is easier and less time consuming to find documents from a large collection when the collection is ordered or classified by group or category. The problem of finding best such grouping is still there. This paper discusses the implementation of k-Means clustering algorithm for clustering unstructured text documents that we implemented, beginning with the representation of unstructured text and reaching the resulting set of clusters. Based on the analysis of resulting clusters for a sample set of documents, we have also proposed a technique to represent documents that can further improve the clustering result.


AntiJam: Efficient Medium Access despite Adaptive and Reactive Jamming

Abstract: Intentional interference constitutes a major threat for communication networks operating over a shared medium where availability is imperative. Jamming attacks are often simple and cheap to implement. In particular, today's jammers can perform physical carrier sensing in order to disrupt communication more efficiently, specially in a network of simple wireless devices such as sensor nodes, which usually operate over a single frequency (or a limited frequency band) and which cannot benefit from the use of spread spectrum or other more advanced technologies. This article proposes the medium access (MAC) protocol \textsc{AntiJam} that is provably robust against a powerful reactive adversary who can jam a $(1-\epsilon)$-portion of the time steps, where $\epsilon$ is an arbitrary constant. The adversary uses carrier sensing to make informed decisions on when it is most harmful to disrupt communications; moreover, we allow the adversary to be adaptive and to have complete knowledge of the entire protocol history. Our MAC protocol is able to make efficient use of the non-jammed time periods and achieves an asymptotically optimal, $\Theta{(1)}$-competitive throughput in this harsh scenario. In addition, \textsc{AntiJam} features a low convergence time and has good fairness properties. Our simulation results validate our theoretical results and also show that our algorithm manages to guarantee constant throughput where the 802.11 MAC protocol basically fails to deliver any packets.


On the Security of Non-Linear HB (NLHB) Protocol Against Passive Attack

Abstract: As a variant of the HB authentication protocol for RFID systems, which relies on the complexity of decoding linear codes against passive attacks, Madhavan et al. presented Non-Linear HB(NLHB) protocol. In contrast to HB, NLHB relies on the complexity of decoding a class of non-linear codes to render the passive attacks proposed against HB ineffective. In this paper, we show that passive attacks against HB protocol can still be applicable to NLHB and this protocol does not provide the desired security margin. In our attack, we first linearize the non-linear part of NLHB to obtain a HB equivalent for NLHB, and then exploit the passive attack techniques proposed for the HB to evaluate the security margin of NLHB. The results show that although NLHB's security margin is relatively higher than HB against similar passive attack techniques, it has been overestimated and, in contrary to what is claimed, NLHB is vulnerable to passive attacks against HB, especially when the noise vector in the protocol has a low weight.


Threads and Or-Parallelism Unified

Abstract: One of the main advantages of Logic Programming (LP) is that it provides an excellent framework for the parallel execution of programs. In this work we investigate novel techniques to efficiently exploit parallelism from real-world applications in low cost multi-core architectures. To achieve these goals, we revive and redesign the YapOr system to exploit or-parallelism based on a multi-threaded implementation. Our new approach takes full advantage of the state-of-the-art fast and optimized YAP Prolog engine and shares the underlying execution environment, scheduler and most of the data structures used to support YapOr's model. Initial experiments with our new approach consistently achieve almost linear speedups for most of the applications, proving itself as a good alternative for exploiting implicit parallelism in the currently available low cost multi-core architectures.


Abstracting Abstract Machines

Abstract: We describe a derivational approach to abstract interpretation that yields novel and transparently sound static analyses when applied to well-established abstract machines. To demonstrate the technique and support our claim, we transform the CEK machine of Felleisen and Friedman, a lazy variant of Krivine's machine, and the stack-inspecting CM machine of Clements and Felleisen into abstract interpretations of themselves. The resulting analyses bound temporal ordering of program events; predict return-flow and stack-inspection behavior; and approximate the flow and evaluation of by-need parameters. For all of these machines, we find that a series of well-known concrete machine refactorings, plus a technique we call store-allocated continuations, leads to machines that abstract into static analyses simply by bounding their stores. We demonstrate that the technique scales up uniformly to allow static analysis of realistic language features, including tail calls, conditionals, side effects, exceptions, first-class continuations, and even garbage collection.


FPGA Implementation of a Reconfigurable Viterbi Decoder for WiMAX Receiver

Abstract: Field Programmable Gate Array technology (FPGA) is a highly configurable option for implementing many sophisticated signal processing tasks in Software Defined Radios (SDRs). Those types of radios are realized using highly configurable hardware platforms. Convolutional codes are used in every robust digital communication system and Viterbi algorithm is employed in wireless communications to decode the convolutional codes. Such decoders are complex and dissipate large amount of power. In this paper, a low power-reconfigurable Viterbi decoder for WiMAX receiver is described using a VHDL code for FPGA implementation. The proposed design is implemented on Xilinx Virtex-II Pro, XC2vpx30 FPGA using the FPGA Advantage Pro package provided by Mentor Graphics and ISE 10.1 by Xilinx.


Decidability properties for fragments of CHR

Abstract: We study the decidability of termination for two CHR dialects which, similarly to the Datalog like languages, are defined by using a signature which does not allow function symbols (of arity >0). Both languages allow the use of the = built-in in the body of rules, thus are built on a host language that supports unification. However each imposes one further restriction. The first CHR dialect allows only range-restricted rules, that is, it does not allow the use of variables in the body or in the guard of a rule if they do not appear in the head. We show that the existence of an infinite computation is decidable for this dialect. The second dialect instead limits the number of atoms in the head of rules to one. We prove that in this case, the existence of a terminating computation is decidable. These results show that both dialects are strictly less expressive than Turing Machines. It is worth noting that the language (without function symbols) without these restrictions is as expressive as Turing Machines.


Piecewise Convex-Concave Approximation in the $\ell_{\infty}$ Norm

Abstract: Suppose that $\ff \in \reals^{n}$ is a vector of $n$ error-contaminated measurements of $n$ smooth values measured at distinct and strictly ascending abscissae. The following projective technique is proposed for obtaining a vector of smooth approximations to these values. Find \yy\ minimizing $\| \yy - \ff \|_{\infty}$ subject to the constraints that the second order consecutive divided differences of the components of \yy\ change sign at most $q$ times. This optimization problem (which is also of general geometrical interest) does not suffer from the disadvantage of the existence of purely local minima and allows a solution to be constructed in $O(nq)$ operations. A new algorithm for doing this is developed and its effectiveness is proved. Some of the results of applying it to undulating and peaky data are presented, showing that it is economical and can give very good results, particularly for large densely-packed data, even when the errors are quite large.


Equilibrium Pricing of Semantically Substitutable Digital Goods

Abstract: The problem of arriving at a principled method of pricing goods and services was very satisfactorily solved for conventional goods; however, this solution is not applicable to digital goods. This paper studies pricing of a special class of digital goods, which we call {\em semantically substitutable digital goods}. After taking into consideration idiosyncrasies of goods in this class, we define a market model for it, together with a notion of equilibrium. We prove existence of equilibrium prices for our market model using Kakutani's fixed point theorem. The far reaching significance of a competitive equilibrium is made explicit in the Fundamental Theorems of Welfare Economics. There are basic reasons due to which these theorems are not applicable to digital goods. This naturally leads to the question of whether the allocations of conventional goods are rendered inefficient or "socially unfair" in the mixed economy we have proposed. We prove that that is not the case and that in this sense, the intended goal of Welfare Economics is still achieved in the mixed economy.


Gbits/s physical-layer stream ciphers based on chaotic light

Abstract: We propose a novel high-speed stream cipher encryption scheme based on the true random key generated by a chaotic semiconductor laser. A 5-Gbits/s non-return-to-zero plaintext is successfully encrypted and decrypted using this cryptography. The scheme can be applied in the areas of real-time high-speed physical encryption.


Computational Complexity Analysis of Simple Genetic Programming On Two Problems Modeling Isolated Program Semantics

Abstract: Analyzing the computational complexity of evolutionary algorithms for binary search spaces has significantly increased their theoretical understanding. With this paper, we start the computational complexity analysis of genetic programming. We set up several simplified genetic programming algorithms and analyze them on two separable model problems, ORDER and MAJORITY, each of which captures an important facet of typical genetic programming problems. Both analyses give first rigorous insights on aspects of genetic programming design, highlighting in particular the impact of accepting or rejecting neutral moves and the importance of a local mutation operator.


About functions where function input describes inner working of the function

Abstract: This paper argues an existence of a class of functions where function own input makes function description. That fact have impact to the wide spectrum of phenomena such as negative findings of Random Oracle Model in cryptography, complexity in some rules of cellular automata (Wolfram rule 30) and determinism in the true randomness to name just a few.


Simple Max-Min Ant Systems and the Optimization of Linear Pseudo-Boolean Functions

Abstract: With this paper, we contribute to the understanding of ant colony optimization (ACO) algorithms by formally analyzing their runtime behavior. We study simple MAX-MIN ant systems on the class of linear pseudo-Boolean functions defined on binary strings of length 'n'. Our investigations point out how the progress according to function values is stored in pheromone. We provide a general upper bound of O((n^3 \log n)/ \rho) for two ACO variants on all linear functions, where (\rho) determines the pheromone update strength. Furthermore, we show improved bounds for two well-known linear pseudo-Boolean functions called OneMax and BinVal and give additional insights using an experimental study.


Public Infrastructure for Monte Carlo Simulation: publicMC@BATAN

Abstract: The first cluster-based public computing for Monte Carlo simulation in Indonesia is introduced. The system has been developed to enable public to perform Monte Carlo simulation on a parallel computer through an integrated and user friendly dynamic web interface. The beta version, so called publicMC@BATAN, has been released and implemented for internal users at the National Nuclear Energy Agency (BATAN). In this paper the concept and architecture of publicMC@BATAN are presented.


CapEst: A Measurement-based Approach to Estimating Link Capacity in Wireless Networks

Abstract: Estimating link capacity in a wireless network is a complex task because the available capacity at a link is a function of not only the current arrival rate at that link, but also of the arrival rate at links which interfere with that link as well as of the nature of interference between these links. Models which accurately characterize this dependence are either too computationally complex to be useful or lack accuracy. Further, they have a high implementation overhead and make restrictive assumptions, which makes them inapplicable to real networks. In this paper, we propose CapEst, a general, simple yet accurate, measurement-based approach to estimating link capacity in a wireless network. To be computationally light, CapEst allows inaccuracy in estimation; however, using measurements, it can correct this inaccuracy in an iterative fashion and converge to the correct estimate. Our evaluation shows that CapEst always converged to within 5% of the correct value in less than 18 iterations. CapEst is model-independent, hence, is applicable to any MAC/PHY layer and works with auto-rate adaptation. Moreover, it has a low implementation overhead, can be used with any application which requires an estimate of residual capacity on a wireless link and can be implemented completely at the network layer without any support from the underlying chipset.


Detecting influenza outbreaks by analyzing Twitter messages

Abstract: We analyze over 500 million Twitter messages from an eight month period and find that tracking a small number of flu-related keywords allows us to forecast future influenza rates with high accuracy, obtaining a 95% correlation with national health statistics. We then analyze the robustness of this approach to spurious keyword matches, and we propose a document classification component to filter these misleading messages. We find that this document classifier can reduce error rates by over half in simulated false alarm experiments, though more research is needed to develop methods that are robust in cases of extremely high noise.


Propositional Dynamic Logic for Message-Passing Systems

Abstract: We examine a bidirectional propositional dynamic logic (PDL) for finite and infinite message sequence charts (MSCs) extending LTL and TLC-. By this kind of multi-modal logic we can express properties both in the entire future and in the past of an event. Path expressions strengthen the classical until operator of temporal logic. For every formula defining an MSC language, we construct a communicating finite-state machine (CFM) accepting the same language. The CFM obtained has size exponential in the size of the formula. This synthesis problem is solved in full generality, i.e., also for MSCs with unbounded channels. The model checking problem for CFMs and HMSCs turns out to be in PSPACE for existentially bounded MSCs. Finally, we show that, for PDL with intersection, the semantics of a formula cannot be captured by a CFM anymore.


Formalization of Psychological Knowledge in Answer Set Programming and its Application

Abstract: In this paper we explore the use of Answer Set Programming (ASP) to formalize, and reason about, psychological knowledge. In the field of psychology, a considerable amount of knowledge is still expressed using only natural language. This lack of a formalization complicates accurate studies, comparisons, and verification of theories. We believe that ASP, a knowledge representation formalism allowing for concise and simple representation of defaults, uncertainty, and evolving domains, can be used successfully for the formalization of psychological knowledge. To demonstrate the viability of ASP for this task, in this paper we develop an ASP-based formalization of the mechanics of Short-Term Memory. We also show that our approach can have rather immediate practical uses by demonstrating an application of our formalization to the task of predicting a user's interaction with a graphical interface.


Short Note on Complexity of Multi-Value Byzantine Agreement

Abstract: Randomized algorithm that achieves multi-valued Byzantine agreement with high probability, and achieves optimal complexity.


Braess's Paradox for Flows Over Time

Abstract: We study the properties of Braess's paradox in the context of the model of congestion games with flow over time introduced by Koch and Skutella. We compare them to the well known properties of Braess's paradox for Wardrop's model of games with static flows. We show that there are networks which do not admit Braess's paradox in Wardrop's model, but which admit it in the model with flow over time. Moreover, there is a topology that admits a much more severe Braess's ratio for this model. Further, despite its symmetry for games with static flow, we show that Braess's paradox is not symmetric for flows over time. We illustrate that there are network topologies which exhibit Braess's paradox, but for which the transpose does not. Finally, we conjecture a necessary and sufficient condition of existence of Braess's paradox in a network, and prove the condition of existence of the paradox either in the network or in its transpose.


Predicting Suicide Attacks: A Fuzzy Soft Set Approach

Abstract: This paper models a decision support system to predict the occurance of suicide attack in a given collection of cities. The system comprises two parts. First part analyzes and identifies the factors which affect the prediction. Admitting incomplete information and use of linguistic terms by experts, as two characteristic features of this peculiar prediction problem we exploit the Theory of Fuzzy Soft Sets. Hence the Part 2 of the model is an algorithm vz. FSP which takes the assessment of factors given in Part 1 as its input and produces a possibility profile of cities likely to receive the accident. The algorithm is of O(2^n) complexity. It has been illustrated by an example solved in detail. Simulation results for the algorithm have been presented which give insight into the strengths and weaknesses of FSP. Three different decision making measures have been simulated and compared in our discussion.


PowerTracer: Tracing requests in multi-tier services to save cluster power consumption

Abstract: As energy proportional computing gradually extends the success of DVFS (Dynamic voltage and frequency scaling) to the entire system, DVFS control algorithms will play a key role in reducing server clusters' power consumption. The focus of this paper is to provide accurate cluster-level DVFS control for power saving in a server cluster. To achieve this goal, we propose a request tracing approach that online classifies the major causal path patterns of a multi-tier service and monitors their performance data as a guide for accurate DVFS control. The request tracing approach significantly decreases the time cost of performance profiling experiments that aim to establish the empirical performance model. Moreover, it decreases the controller complexity so that we can introduce a much simpler feedback controller, which only relies on the single-node DVFS modulation at a time as opposed to varying multiple CPU frequencies simultaneously. Based on the request tracing approach, we present a hybrid DVFS control system that combines an empirical performance model for fast modulation at different load levels and a simpler feedback controller for adaption. We implement a prototype of the proposed system, called PowerTracer, and conduct extensive experiments on a 3-tier platform. Our experimental results show that PowerTracer outperforms its peer in terms of power saving and system performance.


Automated Termination Analysis for Logic Programs with Cut

Abstract: Termination is an important and well-studied property for logic programs. However, almost all approaches for automated termination analysis focus on definite logic programs, whereas real-world Prolog programs typically use the cut operator. We introduce a novel pre-processing method which automatically transforms Prolog programs into logic programs without cuts, where termination of the cut-free program implies termination of the original program. Hence after this pre-processing, any technique for proving termination of definite logic programs can be applied. We implemented this pre-processing in our termination prover AProVE and evaluated it successfully with extensive experiments.


Optimal Base Encodings for Pseudo-Boolean Constraints

Abstract: This paper formalizes the optimal base problem, presents an algorithm to solve it, and describes its application to the encoding of Pseudo-Boolean constraints to SAT. We demonstrate the impact of integrating our algorithm within the Pseudo-Boolean constraint solver MINISAT+. Experimentation indicates that our algorithm scales to bases involving numbers up to 1,000,000, improving on the restriction in MINISAT+ to prime numbers up to 17. We show that, while for many examples primes up to 17 do suffice, encoding with respect to optimal bases reduces the CNF sizes and improves the subsequent SAT solving time for many examples.


Algorithmic Verification of Single-Pass List Processing Programs

Abstract: We introduce streaming data string transducers that map input data strings to output data strings in a single left-to-right pass in linear time. Data strings are (unbounded) sequences of data values, tagged with symbols from a finite set, over a potentially infinite data domain that supports only the operations of equality and ordering. The transducer uses a finite set of states, a finite set of variables ranging over the data domain, and a finite set of variables ranging over data strings. At every step, it can make decisions based on the next input symbol, updating its state, remembering the input data value in its data variables, and updating data-string variables by concatenating data-string variables and new symbols formed from data variables, while avoiding duplication. We establish that the problems of checking functional equivalence of two streaming transducers, and of checking whether a streaming transducer satisfies pre/post verification conditions specified by streaming acceptors over input/output data-strings, are in PSPACE. We identify a class of imperative and a class of functional programs, manipulating lists of data items, which can be effectively translated to streaming data-string transducers. The imperative programs dynamically modify a singly-linked heap by changing next-pointers of heap-nodes and by adding new nodes. The main restriction specifies how the next-pointers can be used for traversal. We also identify an expressively equivalent fragment of functional programs that traverse a list using syntactically restricted recursive calls. Our results lead to algorithms for assertion checking and for checking functional equivalence of two programs, written possibly in different programming styles, for commonly used routines such as insert, delete, and reverse.


The System Kato: Detecting Cases of Plagiarism for Answer-Set Programs

Abstract: Plagiarism detection is a growing need among educational institutions and solutions for different purposes exist. An important field in this direction is detecting cases of source-code plagiarism. In this paper, we present the tool Kato for supporting the detection of this kind of plagiarism in the area of answer-set programming (ASP). Currently, the tool is implemented for DLV programs but it is designed to handle other logic-programming dialects as well. We review the basic features of Kato, introduce its theoretical underpinnings, and discuss an application of Kato for plagiarism detection in the context of courses on logic programming at the Vienna University of Technology.


Catching the Ouroboros: On Debugging Non-ground Answer-Set Programs

Abstract: An important issue towards a broader acceptance of answer-set programming (ASP) is the deployment of tools which support the programmer during the coding phase. In particular, methods for debugging an answer-set program are recognised as a crucial step in this regard. Initial work on debugging in ASP mainly focused on propositional programs, yet practical debuggers need to handle programs with variables as well. In this paper, we discuss a debugging technique that is directly geared towards non-ground programs. Following previous work, we address the central debugging question why some interpretation is not an answer set. The explanations provided by our method are computed by means of a meta-programming technique, using a uniform encoding of a debugging request in terms of ASP itself. Our method also permits programs containing comparison predicates and integer arithmetics, thus covering a relevant language class commonly supported by all state-of-the-art ASP solvers.


Proceedings Ninth International Workshop on the Foundations of Coordination Languages and Software Architectures

Abstract: This volume contains the proceedings of FOCLASA 2010, the 9th International Workshop on the Foundations of Coordination Languages and Software Architectures. FOCLASA 2010 was held in Paris, France on July 30th, 2010 as a satellite event of the 21st International Conference on Concurrency Theory, CONCUR 2010. The papers presented in this proceedings tackle different issues that are currently central to our community, namely software adaptation, sensor networks, distributed control, non-functional aspects of coordination such as resources, timing and stochastics.


A Program-Level Approach to Revising Logic Programs under the Answer Set Semantics

Abstract: An approach to the revision of logic programs under the answer set semantics is presented. For programs P and Q, the goal is to determine the answer sets that correspond to the revision of P by Q, denoted P * Q. A fundamental principle of classical (AGM) revision, and the one that guides the approach here, is the success postulate. In AGM revision, this stipulates that A is in K * A. By analogy with the success postulate, for programs P and Q, this means that the answer sets of Q will in some sense be contained in those of P * Q. The essential idea is that for P * Q, a three-valued answer set for Q, consisting of positive and negative literals, is first determined. The positive literals constitute a regular answer set, while the negated literals make up a minimal set of naf literals required to produce the answer set from Q. These literals are propagated to the program P, along with those rules of Q that are not decided by these literals. The approach differs from work in update logic programs in two main respects. First, we ensure that the revising logic program has higher priority, and so we satisfy the success postulate; second, for the preference implicit in a revision P * Q, the program Q as a whole takes precedence over P, unlike update logic programs, since answer sets of Q are propagated to P. We show that a core group of the AGM postulates are satisfied, as are the postulates that have been proposed for update logic programs.


Approximation Algorithms for Secondary Spectrum Auctions

Abstract: We study combinatorial auctions for the secondary spectrum market. In this market, short-term licenses shall be given to wireless nodes for communication in their local neighborhood. In contrast to the primary market, channels can be assigned to multiple bidders, provided that the corresponding devices are well separated such that the interference is sufficiently low. Interference conflicts are described in terms of a conflict graph in which the nodes represent the bidders and the edges represent conflicts such that the feasible allocations for a channel correspond to the independent sets in the conflict graph. In this paper, we suggest a novel LP formulation for combinatorial auctions with conflict graph using a non-standard graph parameter, the so-called inductive independence number. Taking into account this parameter enables us to bypass the well-known lower bound of \Omega(n^{1-\epsilon}) on the approximability of independent set in general graphs with n nodes (bidders). We achieve significantly better approximation results by showing that interference constraints for wireless networks yield conflict graphs with bounded inductive independence number. Our framework covers various established models of wireless communication, e.g., the protocol or the physical model. For the protocol model, we achieve an O(\sqrt{k})-approximation, where k is the number of available channels. For the more realistic physical model, we achieve an O(\sqrt{k} \log^2 n) approximation based on edge-weighted conflict graphs. Combining our approach with the the LP-based framework of Lavi and Swamy, we obtain incentive compatible mechanisms for general bidders with arbitrary valuations on bundles of channels specified in terms of demand oracles.


Simplified Distributed Programming with Micro Objects

Abstract: Developing large-scale distributed applications can be a daunting task. object-based environments have attempted to alleviate problems by providing distributed objects that look like local objects. We advocate that this approach has actually only made matters worse, as the developer needs to be aware of many intricate internal details in order to adequately handle partial failures. The result is an increase of application complexity. We present an alternative in which distribution transparency is lessened in favor of clearer semantics. In particular, we argue that a developer should always be offered the unambiguous semantics of local objects, and that distribution comes from copying those objects to where they are needed. We claim that it is often sufficient to provide only small, immutable objects, along with facilities to group objects into clusters.


CREOLE: a Universal Language for Creating, Requesting, Updating and Deleting Resources

Abstract: In the context of Service-Oriented Computing, applications can be developed following the REST (Representation State Transfer) architectural style. This style corresponds to a resource-oriented model, where resources are manipulated via CRUD (Create, Request, Update, Delete) interfaces. The diversity of CRUD languages due to the absence of a standard leads to composition problems related to adaptation, integration and coordination of services. To overcome these problems, we propose a pivot architecture built around a universal language to manipulate resources, called CREOLE, a CRUD Language for Resource Edition. In this architecture, scripts written in existing CRUD languages, like SQL, are compiled into Creole and then executed over different CRUD interfaces. After stating the requirements for a universal language for manipulating resources, we formally describe the language and informally motivate its definition with respect to the requirements. We then concretely show how the architecture solves adaptation, integration and coordination problems in the case of photo management in Flickr and Picasa, two well-known service-oriented applications. Finally, we propose a roadmap for future work.


Implementing Distributed Controllers for Systems with Priorities

Abstract: Implementing a component-based system in a distributed way so that it ensures some global constraints is a challenging problem. We consider here abstract specifications consisting of a composition of components and a controller given in the form of a set of interactions and a priority order amongst them. In the context of distributed systems, such a controller must be executed in a distributed fashion while still respecting the global constraints imposed by interactions and priorities. We present in this paper an implementation of an algorithm that allows a distributed execution of systems with (binary) interactions and priorities. We also present a comprehensive simulation analysis that shows how sensitive to changes our algorithm is, in particular changes related to the degree of conflict in the system.


Self-Recovering Sensor-Actor Networks

Abstract: Wireless sensor-actor networks are a recent development of wireless networks where both ordinary sensor nodes and more sophisticated and powerful nodes, called actors, are present. In this paper we formalize a recently introduced algorithm that recovers failed actor communication links via the existing sensor infrastructure. We prove via refinement that the recovery is terminating in a finite number of steps and is distributed, thus self-performed by the actors. Most importantly, we prove that the recovery can be done at different levels, via different types of links, such as direct actor links or indirect links between the actors, in the latter case reusing the wireless infrastructure of sensors. This leads to identifying coordination classes, e.g., for delegating the most security sensitive coordination to the direct actor-actor coordination links, the least real-time constrained coordination to indirect links, and the safety critical coordination to both direct actor links and indirect sensor paths between actors. Our formalization is done using the theorem prover in the RODIN platform.


Handling Data-Based Concurrency in Context-Aware Service Protocols

Abstract: Dependency analysis is a technique to identify and determine data dependencies between service protocols. Protocols evolving concurrently in the service composition need to impose an order in their execution if there exist data dependencies. In this work, we describe a model to formalise context-aware service protocols. We also present a composition language to handle dynamically the concurrent execution of protocols. This language addresses data dependency issues among several protocols concurrently executed on the same user device, using mechanisms based on data semantic matching. Our approach aims at assisting the user in establishing priorities between these dependencies, avoiding the occurrence of deadlock situations. Nevertheless, this process is error-prone, since it requires human intervention. Therefore, we also propose verification techniques to automatically detect possible inconsistencies specified by the user while building the data dependency set. Our approach is supported by a prototype tool we have implemented.


On Coordinating Collaborative Objects

Abstract: A collaborative object represents a data type (such as a text document) designed to be shared by a group of dispersed users. The Operational Transformation (OT) is a coordination approach used for supporting optimistic replication for these objects. It allows the users to concurrently update the shared data and exchange their updates in any order since the convergence of all replicas, i.e. the fact that all users view the same data, is ensured in all cases. However, designing algorithms for achieving convergence with the OT approach is a critical and challenging issue. In this paper, we propose a formal compositional method for specifying complex collaborative objects. The most important feature of our method is that designing an OT algorithm for the composed collaborative object can be done by reusing the OT algorithms of component collaborative objects. By using our method, we can start from correct small collaborative objects which are relatively easy to handle and incrementally combine them to build more complex collaborative objects.


A Compositional Semantics for Stochastic Reo Connectors

Abstract: In this paper we present a compositional semantics for the channel-based coordination language Reo which enables the analysis of quality of service (QoS) properties of service compositions. For this purpose, we annotate Reo channels with stochastic delay rates and explicitly model data-arrival rates at the boundary of a connector, to capture its interaction with the services that comprise its environment. We propose Stochastic Reo automata as an extension of Reo automata, in order to compositionally derive a QoS-aware semantics for Reo. We further present a translation of Stochastic Reo automata to Continuous-Time Markov Chains (CTMCs). This translation enables us to use third-party CTMC verification tools to do an end-to-end performance analysis of service compositions.


Timed Automata Semantics for Analyzing Creol

Abstract: We give a real-time semantics for the concurrent, object-oriented modeling language Creol, by mapping Creol processes to a network of timed automata. We can use our semantics to verify real time properties of Creol objects, in particular to see whether processes can be scheduled correctly and meet their end-to-end deadlines. Real-time Creol can be useful for analyzing, for instance, abstract models of multi-core embedded systems. We show how analysis can be done in Uppaal.


An Empirical Study of Borda Manipulation

Abstract: We study the problem of coalitional manipulation in elections using the unweighted Borda rule. We provide empirical evidence of the manipulability of Borda elections in the form of two new greedy manipulation algorithms based on intuitions from the bin-packing and multiprocessor scheduling domains. Although we have not been able to show that these algorithms beat existing methods in the worst-case, our empirical evaluation shows that they significantly outperform the existing method and are able to find optimal manipulations in the vast majority of the randomly generated elections that we tested. These empirical results provide further evidence that the Borda rule provides little defense against coalitional manipulation.


Fully Dynamic Data Structure for Top-k Queries on Uncertain Data

Abstract: Top-$k$ queries allow end-users to focus on the most important (top-$k$) answers amongst those which satisfy the query. In traditional databases, a user defined score function assigns a score value to each tuple and a top-$k$ query returns $k$ tuples with the highest score. In uncertain database, top-$k$ answer depends not only on the scores but also on the membership probabilities of tuples. Several top-$k$ definitions covering different aspects of score-probability interplay have been proposed in recent past~\cite{R10,R4,R2,R8}. Most of the existing work in this research field is focused on developing efficient algorithms for answering top-$k$ queries on static uncertain data. Any change (insertion, deletion of a tuple or change in membership probability, score of a tuple) in underlying data forces re-computation of query answers. Such re-computations are not practical considering the dynamic nature of data in many applications. In this paper, we propose a fully dynamic data structure that uses ranking function $PRF^e(\alpha)$ proposed by Li et al.~\cite{R8} under the generally adopted model of $x$-relations~\cite{R11}. $PRF^e$ can effectively approximate various other top-$k$ definitions on uncertain data based on the value of parameter $\alpha$. An $x$-relation consists of a number of $x$-tuples, where $x$-tuple is a set of mutually exclusive tuples (up to a constant number) called alternatives. Each $x$-tuple in a relation randomly instantiates into one tuple from its alternatives. For an uncertain relation with $N$ tuples, our structure can answer top-$k$ queries in $O(k\log N)$ time, handles an update in $O(\log N)$ time and takes $O(N)$ space. Finally, we evaluate practical efficiency of our structure on both synthetic and real data.


Where are the hard manipulation problems?

Abstract: One possible escape from the Gibbard-Satterthwaite theorem is computational complexity. For example, it is NP-hard to compute if the STV rule can be manipulated. However, there is increasing concern that such results may not re ect the difficulty of manipulation in practice. In this tutorial, I survey recent results in this area.


Bayesian Network Based XP Process Modelling

Abstract: A Bayesian Network based mathematical model has been used for modelling Extreme Programming software development process. The model is capable of predicting the expected finish time and the expected defect rate for each XP release. Therefore, it can be used to determine the success/failure of any XP Project. The model takes into account the effect of three XP practices, namely: Pair Programming, Test Driven Development and Onsite Customer practices. The model's predictions were validated against two case studies. Results show the precision of our model especially in Predicting the project finish time.


Code Quality Evaluation Methodology Using The ISO/IEC 9126 Standard

Abstract: This work proposes a methodology for source code quality and static behaviour evaluation of a software system, based on the standard ISO/IEC-9126. It uses elements automatically derived from source code enhanced with expert knowledge in the form of quality characteristic rankings, allowing software engineers to assign weights to source code attributes. It is flexible in terms of the set of metrics and source code attributes employed, even in terms of the ISO/IEC-9126 characteristics to be assessed. We applied the methodology to two case studies, involving five open source and one proprietary system. Results demonstrated that the methodology can capture software quality trends and express expert perceptions concerning system quality in a quantitative and systematic manner.


Stable marriage problems with quantitative preferences

Abstract: The stable marriage problem is a well-known problem of matching men to women so that no man and woman, who are not married to each other, both prefer each other. Such a problem has a wide variety of practical applications, ranging from matching resident doctors to hospitals, to matching students to schools or more generally to any two-sided market. In the classical stable marriage problem, both men and women express a strict preference order over the members of the other sex, in a qualitative way. Here we consider stable marriage problems with quantitative preferences: each man (resp., woman) provides a score for each woman (resp., man). Such problems are more expressive than the classical stable marriage problems. Moreover, in some real-life situations it is more natural to express scores (to model, for example, profits or costs) rather than a qualitative preference ordering. In this context, we define new notions of stability and optimality, and we provide algorithms to find marriages which are stable and/or optimal according to these notions. While expressivity greatly increases by adopting quantitative preferences, we show that in most cases the desired solutions can be found by adapting existing algorithms for the classical stable marriage problem.


Building Reusable Software Component For Optimization Check in ABAP Coding

Abstract: Software component reuse is the software engineering practice of developing new software products from existing components. A reuse library or component reuse repository organizes stores and manages reusable components. This paper describes how a reusable component is created, how it reuses the function and checking if optimized code is being used in building programs and applications. Finally providing coding guidelines, standards and best practices used for creating reusable components and guidelines and best practices for making configurable and easy to use.


Examining Requirements Change Rework Effort: A Study

Abstract: Although software managers are generally good at new project estimation, their experience of scheduling rework tends to be poor. Inconsistent or incorrect effort estimation can increase the risk that the completion time for a project will be problematic. To continually alter software maintenance schedules during software maintenance is a daunting task. Our proposed framework, validated in a case study confirms that the variables resulting from requirements changes suffer from a number of problems, e.g., the coding used, end user involvement and user documentation. Our results clearly show a significant impact on rework effort as a result of unexpected errors that correlate with 1) weak characteristics and attributes as described in the program's source lines of code, especially in data declarations and data statements, 2) lack of communication between developers and users on a change effects, and 3) unavailability of user documentation. To keep rework effort under control, new criteria in change request forms are proposed. These criteria are shown in a proposed framework; the more case studies that are validated, the more reliable the result will be in determining the outcome of effort rework estimation.


Towards Performance Measurement And Metrics Based Analysis of PLA Applications

Abstract: This article is about a measurement analysis based approach to help software practitioners in managing the additional level complexities and variabilities in software product line applications. The architecture of the proposed approach i.e. ZAC is designed and implemented to perform preprocessesed source code analysis, calculate traditional and product line metrics and visualize results in two and three dimensional diagrams. Experiments using real time data sets are performed which concluded with the results that the ZAC can be very helpful for the software practitioners in understanding the overall structure and complexity of product line applications. Moreover the obtained results prove strong positive correlation between calculated traditional and product line measures.


An Efficient Automatic Mass Classification Method In Digitized Mammograms Using Artificial Neural Network

Abstract: In this paper we present an efficient computer aided mass classification method in digitized mammograms using Artificial Neural Network (ANN), which performs benign-malignant classification on region of interest (ROI) that contains mass. One of the major mammographic characteristics for mass classification is texture. ANN exploits this important factor to classify the mass into benign or malignant. The statistical textural features used in characterizing the masses are mean, standard deviation, entropy, skewness, kurtosis and uniformity. The main aim of the method is to increase the effectiveness and efficiency of the classification process in an objective manner to reduce the numbers of false-positive of malignancies. Three layers artificial neural network (ANN) with seven features was proposed for classifying the marked regions into benign and malignant and 90.91% sensitivity and 83.87% specificity is achieved that is very much promising compare to the radiologist's sensitivity 75%.


Resource-Optimal Planning For An Autonomous Planetary Vehicle

Abstract: Autonomous planetary vehicles, also known as rovers, are small autonomous vehicles equipped with a variety of sensors used to perform exploration and experiments on a planet's surface. Rovers work in a partially unknown environment, with narrow energy/time/movement constraints and, typically, small computational resources that limit the complexity of on-line planning and scheduling, thus they represent a great challenge in the field of autonomous vehicles. Indeed, formal models for such vehicles usually involve hybrid systems with nonlinear dynamics, which are difficult to handle by most of the current planning algorithms and tools. Therefore, when offline planning of the vehicle activities is required, for example for rovers that operate without a continuous Earth supervision, such planning is often performed on simplified models that are not completely realistic. In this paper we show how the UPMurphi model checking based planning tool can be used to generate resource-optimal plans to control the engine of an autonomous planetary vehicle, working directly on its hybrid model and taking into account several safety constraints, thus achieving very accurate results.


Comparison of Support Vector Machine and Back Propagation Neural Network in Evaluating the Enterprise Financial Distress

Abstract: Recently, applying the novel data mining techniques for evaluating enterprise financial distress has received much research alternation. Support Vector Machine (SVM) and back propagation neural (BPN) network has been applied successfully in many areas with excellent generalization results, such as rule extraction, classification and evaluation. In this paper, a model based on SVM with Gaussian RBF kernel is proposed here for enterprise financial distress evaluation. BPN network is considered one of the simplest and are most general methods used for supervised training of multilayered neural network. The comparative results show that through the difference between the performance measures is marginal; SVM gives higher precision and lower error rates.


Perceptual Copyright Protection Using Multiresolution Wavelet-Based Watermarking And Fuzzy Logic

Abstract: In this paper, an efficiently DWT-based watermarking technique is proposed to embed signatures in images to attest the owner identification and discourage the unauthorized copying. This paper deals with a fuzzy inference filter to choose the larger entropy of coefficients to embed watermarks. Unlike most previous watermarking frameworks which embedded watermarks in the larger coefficients of inner coarser subbands, the proposed technique is based on utilizing a context model and fuzzy inference filter by embedding watermarks in the larger-entropy coefficients of coarser DWT subbands. The proposed approaches allow us to embed adaptive casting degree of watermarks for transparency and robustness to the general image-processing attacks such as smoothing, sharpening, and JPEG compression. The approach has no need the original host image to extract watermarks. Our schemes have been shown to provide very good results in both image transparency and robustness.


Comparison Of Modified Dual Ternary Indexing And Multi-Key Hashing Algorithms For Music Information Retrieval

Abstract: In this work we have compared two indexing algorithms that have been used to index and retrieve Carnatic music songs. We have compared a modified algorithm of the Dual ternary indexing algorithm for music indexing and retrieval with the multi-key hashing indexing algorithm proposed by us. The modification in the dual ternary algorithm was essential to handle variable length query phrase and to accommodate features specific to Carnatic music. The dual ternary indexing algorithm is adapted for Carnatic music by segmenting using the segmentation technique for Carnatic music. The dual ternary algorithm is compared with the multi-key hashing algorithm designed by us for indexing and retrieval in which features like MFCC, spectral flux, melody string and spectral centroid are used as features for indexing data into a hash table. The way in which collision resolution was handled by this hash table is different than the normal hash table approaches. It was observed that multi-key hashing based retrieval had a lesser time complexity than dual-ternary based indexing The algorithms were also compared for their precision and recall in which multi-key hashing had a better recall than modified dual ternary indexing for the sample data considered.


Reputation-Based Attack-Resistant Cooperation Stimulation (RACS) For Mobile Ad hoc Networks

Abstract: In mobile ad hoc networks (MANET), nodes usually belong to different authorities and pursue different goals. In order to maximize their own performance, nodes in such networks tend to be selfish and are not willing to forward packets for benefit of others. Meanwhile, some nodes may behave maliciously and try to disrupt the network through wasting other nodes resources in a very large scale. In this article, we present a reputation-based attack resistant cooperation stimulation (RACS) system which ensures that damage caused by malicious nodes can be bounded and cooperation among the selfish nodes can be enforced. Mathematical analyses of the system as well as the simulation results have confirmed effectiveness of our proposed system. RACS is completely self-organizing and distributed. It does not require any tamper-proof hardware or central management policy.


Interaction With Tilting Gestures In Ubiquitous Environments

Abstract: In this paper, we introduce a tilting interface that controls direction based applications in ubiquitous environments. A tilt interface is useful for situations that require remote and quick interactions or that are executed in public spaces. We explored the proposed tilting interface with different application types and classified the tilting interaction techniques. Augmenting objects with sensors can potentially address the problem of the lack of intuitive and natural input devices in ubiquitous environments. We have conducted an experiment to test the usability of the proposed tilting interface to compare it with conventional input devices and hand gestures. The experiment results showed greater improvement of the tilt gestures in comparison with hand gestures in terms of speed, accuracy, and user satisfaction.


Security Enhancement With Optimal QOS Using EAP-AKA In Hybrid Coupled 3G-WLAN Convergence Network

Abstract: The third generation partnership project (3GPP) has addressed the feasibility of interworking and specified the interworking architecture and security architecture for third generation (3G)-wireless local area network (WLAN), it is developing, system architecture evolution (SAE)/ long term evolution (LTE) architecture, for the next generation mobile communication system. To provide a secure 3G-WLAN interworking in the SAE/LTE architecture, Extensible authentication protocol-authentication and key agreement (EAP-AKA) is used. However, EAP-AKA have several vulnerabilities. Therefore, this paper not only analyses the threats and attacks in 3G-WLAN interworking but also proposes a new authentication and key agreement protocol based on EAP-AKA. The proposed protocol combines elliptic curve Diffie-Hellman (ECDH) with symmetric key cryptosystem to overcome the vulnerabilities. The proposed protocol is used in hybrid coupled 3G-WLAN convergence network to analyse its efficiency in terms of QoS metrics, the results obtained using OPNET 14.5 shows that the proposed protocol outperforms existing interworking protocols both in security and QoS.


A Non-Cooperative Game Theoretical Approach For Power Control In Virtual MIMO Wireless Sensor Network

Abstract: Power management is one of the vital issue in wireless sensor networks, where the lifetime of the network relies on battery powered nodes. Transmitting at high power reduces the lifetime of both the nodes and the network. One efficient way of power management is to control the power at which the nodes transmit. In this paper, a virtual multiple input multiple output wireless sensor network (VMIMO-WSN)communication architecture is considered and the power control of sensor nodes based on the approach of game theory is formulated. The use of game theory has proliferated, with a broad range of applications in wireless sensor networking. Approaches from game theory can be used to optimize node level as well as network wide performance. The game here is categorized as an incomplete information game, in which the nodes do not have complete information about the strategies taken by other nodes. For virtual multiple input multiple output wireless sensor network architecture considered, the Nash equilibrium is used to decide the optimal power level at which a node needs to transmit, to maximize its utility. Outcome shows that the game theoretic approach considered for VMIMO-WSN architecture achieves the best utility, by consuming less power.


Satisfaction Equilibrium: A General Framework for QoS Provisioning in Self-Configuring Networks

Abstract: This paper is concerned with the concept of equilibrium and quality of service (QoS) provisioning in self-configuring wireless networks with non-cooperative radio devices (RD). In contrast with the Nash equilibrium (NE), where RDs are interested in selfishly maximizing its QoS, we present a concept of equilibrium, named satisfaction equilibrium (SE), where RDs are interested only in guaranteing a minimum QoS. We provide the conditions for the existence and the uniqueness of the SE. Later, in order to provide an equilibrium selection framework for the SE, we introduce the concept of effort or cost of satisfaction, for instance, in terms of transmit power levels, constellation sizes, etc. Using the idea of effort, the set of efficient SE (ESE) is defined. At the ESE, transmitters satisfy their minimum QoS incurring in the lowest effort. We prove that contrary to the (generalized) NE, at least one ESE always exists whenever the network is able to simultaneously support the individual QoS requests. Finally, we provide a fully decentralized algorithm to allow self-configuring networks to converge to one of the SE relying only on local information.


I-Interaction: An Intelligent In-Vehicle User Interaction Model

Abstract: The automobile is always a point of interest where new technology has been deployed. Because of this interest, human-vehicle interaction has been an appealing area for much research in recent years. The current in-vehicle design has been improved but still possesses some of the design from the traditional interaction style. In this paper, we propose a new user-oriented model for in-vehicle interaction model known as i-Interaction. The i-Interaction model provides user with an intuitive approach to interact with the In-Vehicle Information System (IVIS) by the keypad entry. It is the intent that the proposed usability testing for this model will help improve the way research and development is implemented from this topic. This model does not only provide the user with a direct interaction in vehicles but also introduce a new prospective that other research has not addressed.


Characterising Probabilistic Processes Logically

Abstract: In this paper we work on (bi)simulation semantics of processes that exhibit both nondeterministic and probabilistic behaviour. We propose a probabilistic extension of the modal mu-calculus and show how to derive characteristic formulae for various simulation-like preorders over finite-state processes without divergence. In addition, we show that even without the fixpoint operators this probabilistic mu-calculus can be used to characterise these behavioural relations in the sense that two states are equivalent if and only if they satisfy the same set of formulae.


Test Case Generation for Object-Oriented Imperative Languages in CLP

Abstract: Testing is a vital part of the software development process. Test Case Generation (TCG) is the process of automatically generating a collection of test cases which are applied to a system under test. White-box TCG is usually performed by means of symbolic execution, i.e., instead of executing the program on normal values (e.g., numbers), the program is executed on symbolic values representing arbitrary values. When dealing with an object-oriented (OO) imperative language, symbolic execution becomes challenging as, among other things, it must be able to backtrack, complex heap-allocated data structures should be created during the TCG process and features like inheritance, virtual invocations and exceptions have to be taken into account. Due to its inherent symbolic execution mechanism, we pursue in this paper that Constraint Logic Programming (CLP) has a promising unexploited application field in TCG. We will support our claim by developing a fully CLP-based framework to TCG of an OO imperative language, and by assessing it on a corresponding implementation on a set of challenging Java programs. A unique characteristic of our approach is that it handles all language features using only CLP and without the need of developing specific constraint operators (e.g., to model the heap).


Applications of Belief Propagation in CSMA Wireless Networks

Abstract: The belief propagation (BP) algorithm is an efficient way to solve "inference" problems in graphical models, such as Bayesian networks and Markov random fields. The system-state probability distribution of CSMA wireless networks is a Markov random field. An interesting question is how BP can help the analysis and design of CSMA wireless networks. This paper explores three such applications. First, we show how BP can be used to compute the throughputs of different links in the network given their access intensities, defined as the mean packet transmission time divided by the mean backoff countdown time. Second, we propose an inverse-BP algorithm to solve the reverse problem: how to set the access intensities of different links to meet their target throughputs? Third, we introduce a BP-adaptive CSMA algorithm to find the link access intensities that can achieve optimal system utility. BP solves the three problems with exact results in tree networks. It may, however, lose accuracy in networks with a loopy contention graph. We show how a generalized version of BP, GBP, can be designed to solve the three problems with high accuracy for networks with a loopy contention graph. Importantly, we show how the BP and GBP algorithms in this paper can be implemented in a distributed manner, making them useful in practical CSMA network opera-tion.


TCP Reno over Adaptive CSMA

Abstract: An interesting distributed adaptive CSMA MAC protocol, called adaptive CSMA, was proposed recently to schedule any strictly feasible achievable rates inside the capacity region. Of particular interest is the fact that the adaptive CSMA can achieve a system utility arbitrarily close to that is achievable under a central scheduler. However, a specially designed transport-layer rate controller is needed for this result. An outstanding question is whether the widely-installed TCP Reno is compatible with adaptive CSMA and can achieve the same result. The answer to this question will determine how close to practical deployment adaptive CSMA is. Our answer is yes and no. First, we observe that running TCP Reno directly over adaptive CSMA results in severe starvation problems. Effectively, its performance is no better than that of TCP Reno over legacy CSMA (IEEE 802.11), and the potentials of adaptive CSMA cannot be realized. Fortunately, we find that multi-connection TCP Reno over adaptive CSMA with active queue management can materialize the advantages of adaptive CSMA. NS-2 simulations demonstrate that our solution can alleviate starvation and achieve fair and efficient rate allocation. Multi-connection TCP can be implemented at either application or transport layer. Application-layer implementation requires no kernel modification, making the solution readily deployable in networks running adaptive CSMA.


Social-Aware Forwarding Improves Routing Performance in Pocket Switched Networks

Abstract: Several social-aware forwarding strategies have been recently introduced in opportunistic networks, and proved effective in considerably in- creasing routing performance through extensive simulation studies based on real-world data. However, this performance improvement comes at the expense of storing a considerable amount of state information (e.g, history of past encounters) at the nodes. Hence, whether the benefits on routing performance comes directly from the social-aware forwarding mechanism, or indirectly by the fact state information is exploited is not clear. Thus, the question of whether social-aware forwarding by itself is effective in improving opportunistic network routing performance remained unaddressed so far. In this paper, we give a first, positive answer to the above question, by investigating the expected message delivery time as the size of the net- work grows larger.


Analysis of Frequency-Agile CSMA Wireless Networks

Abstract: This paper proposes and analyzes the performance of a simple frequency-agile CSMA MAC protocol. In this MAC, a node carrier-senses multiple frequency channels simultaneously, and it takes the first opportunity to transmit on any one of the channels when allowed by the CSMA backoff mechanism. We show that the frequency-agile MAC can effectively 1) boost throughput and 2) remove temporal starvation. Furthermore, the MAC can be implemented on the existing multiple-frequency setup in Wi-Fi using multi-radio technology, and it can co-exist with the legacy MAC using single radio. This paper provides exact stationary throughput analysis for regular 1D and thin-strip 2D CSMA networks using a "transfer-matrix" approach. In addition, accurate approximations are given for 2D grid networks. Our closed-form formulas accurately quantify the throughput gain of frequency-agile CSMA. To characterize temporal starvation, we use the metric of "mean residual access time" (MRAT). Our simulations and closed-form approximations indicate that the frequency-agile MAC can totally eliminate temporal starvation in 2D grid networks, reducing its MRAT by orders of magnitude. Finally, this paper presents a "coloring theorem" to justify the use of the frequency-agile MAC in general network topologies. Our analysis and theorem suggest that with enough frequency channels, the frequency-agile MAC can effectively decouple the detrimental interactions between neighboring links responsible for low throughput and starvation.


Intrinsic Dimensionality

Abstract: This entry for the SIGSPATIAL Special July 2010 issue on Similarity Searching in Metric Spaces discusses the notion of intrinsic dimensionality of data in the context of similarity search.


Scalable distributed service migration via Complex Networks Analysis

Abstract: With social networking sites providing increasingly richer context, User-Centric Service (UCS) creation is expected to explode following a similar success path to User-Generated Content. One of the major challenges in this emerging highly user-centric networking paradigm is how to make these exploding in numbers yet, individually, of vanishing demand services available in a cost-effective manner. Of prime importance to the latter (and focus of this paper) is the determination of the optimal location for hosting a UCS. Taking into account the particular characteristics of UCS, we formulate the problem as a facility location problem and devise a distributed and highly scalable heuristic solution to it. Key to the proposed approach is the introduction of a novel metric drawing on Complex Network Analysis. Given a current location of UCS, this metric helps to a) identify a small subgraph of nodes with high capacity to act as service demand concentrators; b) project on them a reduced yet accurate view of the global demand distribution that preserves the key attraction forces on UCS; and, ultimately, c) pave the service migration path towards its optimal location in the network. The proposed iterative UCS migration algorithm, called cDSMA, is extensively evaluated over synthetic and real-world network topologies. Our results show that cDSMA achieves high accuracy, fast convergence, remarkable insensitivity to the size and diameter of the network and resilience to inaccurate estimates of demands for UCS across the network. It is also shown to clearly outperform local-search heuristics for service migration that constrain the subgraph to the immediate neighbourhood of the node currently hosting UCS.


Tree structure compression with RePair

Abstract: In this work we introduce a new linear time compression algorithm, called "Re-pair for Trees", which compresses ranked ordered trees using linear straight-line context-free tree grammars. Such grammars generalize straight-line context-free string grammars and allow basic tree operations, like traversal along edges, to be executed without prior decompression. Our algorithm can be considered as a generalization of the "Re-pair" algorithm developed by N. Jesper Larsson and Alistair Moffat in 2000. The latter algorithm is a dictionary-based compression algorithm for strings. We also introduce a succinct coding which is specialized in further compressing the grammars generated by our algorithm. This is accomplished without loosing the ability do directly execute queries on this compressed representation of the input tree. Finally, we compare the grammars and output files generated by a prototype of the Re-pair for Trees algorithm with those of similar compression algorithms. The obtained results show that that our algorithm outperforms its competitors in terms of compression ratio, runtime and memory usage.


Inference with Constrained Hidden Markov Models in PRISM

Abstract: A Hidden Markov Model (HMM) is a common statistical model which is widely used for analysis of biological sequence data and other sequential phenomena. In the present paper we show how HMMs can be extended with side-constraints and present constraint solving techniques for efficient inference. Defining HMMs with side-constraints in Constraint Logic Programming have advantages in terms of more compact expression and pruning opportunities during inference. We present a PRISM-based framework for extending HMMs with side-constraints and show how well-known constraints such as cardinality and all different are integrated. We experimentally validate our approach on the biologically motivated problem of global pairwise alignment.


Distributed Demand Response and User Adaptation in Smart Grids

Abstract: This paper proposes a distributed framework for demand response and user adaptation in smart grid networks. In particular, we borrow the concept of congestion pricing in Internet traffic control and show that pricing information is very useful to regulate user demand and hence balance network load. User preference is modeled as a willingness to pay parameter which can be seen as an indicator of differential quality of service. Both analysis and simulation results are presented to demonstrate the dynamics and convergence behavior of the algorithm.


Known Algorithms on Graphs of Bounded Treewidth are Probably Optimal

Abstract: We obtain a number of lower bounds on the running time of algorithms solving problems on graphs of bounded treewidth. We prove the results under the Strong Exponential Time Hypothesis of Impagliazzo and Paturi. In particular, assuming that SAT cannot be solved in (2-\epsilon)^{n}m^{O(1)} time, we show that for any e > 0; {\sc Independent Set} cannot be solved in (2-e)^{tw(G)}|V(G)|^{O(1)} time, {\sc Dominating Set} cannot be solved in (3-e)^{tw(G)}|V(G)|^{O(1)} time, {\sc Max Cut} cannot be solved in (2-e)^{tw(G)}|V(G)|^{O(1)} time, {\sc Odd Cycle Transversal} cannot be solved in (3-e)^{tw(G)}|V(G)|^{O(1)} time, For any $q \geq 3$, $q$-{\sc Coloring} cannot be solved in (q-e)^{tw(G)}|V(G)|^{O(1)} time, {\sc Partition Into Triangles} cannot be solved in (2-e)^{tw(G)}|V(G)|^{O(1)} time. Our lower bounds match the running times for the best known algorithms for the problems, up to the e in the base.


Relieving the Wireless Infrastructure: When Opportunistic Networks Meet Guaranteed Delays

Abstract: Major wireless operators are nowadays facing network capacity issues in striving to meet the growing demands of mobile users. At the same time, 3G-enabled devices increasingly benefit from ad hoc radio connectivity (e.g., Wi-Fi). In this context of hybrid connectivity, we propose Push-and-track, a content dissemination framework that harnesses ad hoc communication opportunities to minimize the load on the wireless infrastructure while guaranteeing tight delivery delays. It achieves this through a control loop that collects user-sent acknowledgements to determine if new copies need to be reinjected into the network through the 3G interface. Push-and-Track includes multiple strategies to determine how many copies of the content should be injected, when, and to whom. The short delay-tolerance of common content, such as news or road traffic updates, make them suitable for such a system. Based on a realistic large-scale vehicular dataset from the city of Bologna composed of more than 10,000 vehicles, we demonstrate that Push-and-Track consistently meets its delivery objectives while reducing the use of the 3G network by over 90%.


Balanced Combinations of Solutions in Multi-Objective Optimization

Abstract: For every list of integers x_1, ..., x_m there is some j such that x_1 + ... + x_j - x_{j+1} - ... - x_m \approx 0. So the list can be nearly balanced and for this we only need one alternation between addition and subtraction. But what if the x_i are k-dimensional integer vectors? Using results from topological degree theory we show that balancing is still possible, now with k alternations. This result is useful in multi-objective optimization, as it allows a polynomial-time computable balance of two alternatives with conflicting costs. The application to two multi-objective optimization problems yields the following results: - A randomized 1/2-approximation for multi-objective maximum asymmetric traveling salesman, which improves and simplifies the best known approximation for this problem. - A deterministic 1/2-approximation for multi-objective maximum weighted satisfiability.


On CSP and the Algebraic Theory of Effects

Abstract: We consider CSP from the point of view of the algebraic theory of effects, which classifies operations as effect constructors or effect deconstructors; it also provides a link with functional programming, being a refinement of Moggi's seminal monadic point of view. There is a natural algebraic theory of the constructors whose free algebra functor is Moggi's monad; we illustrate this by characterising free and initial algebras in terms of two versions of the stable failures model of CSP, one more general than the other. Deconstructors are dealt with as homomorphisms to (possibly non-free) algebras. One can view CSP's action and choice operators as constructors and the rest, such as concealment and concurrency, as deconstructors. Carrying this programme out results in taking deterministic external choice as constructor rather than general external choice. However, binary deconstructors, such as the CSP concurrency operator, provide unresolved difficulties. We conclude by presenting a combination of CSP with Moggi's computational {\lambda}-calculus, in which the operators, including concurrency, are polymorphic. While the paper mainly concerns CSP, it ought to be possible to carry over similar ideas to other process calculi.


The Coarsest Precongruences Respecting Safety and Liveness Properties

Abstract: This paper characterises the coarsest refinement preorders on labelled transition systems that are precongruences for renaming and partially synchronous interleaving operators, and respect all safety, liveness, and conditional liveness properties, respectively.


Parallel and distributed Gr\"obner bases computation in JAS

Abstract: This paper considers parallel Gr\"obner bases algorithms on distributed memory parallel computers with multi-core compute nodes. We summarize three different Gr\"obner bases implementations: shared memory parallel, pure distributed memory parallel and distributed memory combined with shared memory parallelism. The last algorithm, called distributed hybrid, uses only one control communication channel between the master node and the worker nodes and keeps polynomials in shared memory on a node. The polynomials are transported asynchronous to the control-flow of the algorithm in a separate distributed data structure. The implementation is generic and works for all implemented (exact) fields. We present new performance measurements and discuss the performance of the algorithms.


A Foundation for Stochastic Bandwidth Estimation of Networks with Random Service

Abstract: We develop a stochastic foundation for bandwidth estimation of networks with random service, where bandwidth availability is expressed in terms of bounding functions with a defined violation probability. Exploiting properties of a stochastic max-plus algebra and system theory, the task of bandwidth estimation is formulated as inferring an unknown bounding function from measurements of probing traffic. We derive an estimation methodology that is based on iterative constant rate probes. Our solution provides evidence for the utility of packet trains for bandwidth estimation in the presence of variable cross traffic. Taking advantage of statistical methods, we show how our estimation method can be realized in practice, with adaptive train lengths of probe packets, probing rates, and replicated measurements required to achieve both high accuracy and confidence levels. We evaluate our method in a controlled testbed network, where we show the impact of cross traffic variability on the time-scales of service availability, and provide a comparison with existing bandwidth estimation tools.


Achieving the Scaling Law of SNR-Monitoring in Dynamic Wireless Networks

Abstract: The characteristics of wireless communication channels may vary with time due to fading, environmental changes and movement of mobile wireless devices. Tracking and estimating channel gains of wireless channels is therefore a fundamentally important element of many wireless communication systems. In particular, the receivers in many wireless networks need to estimate the channel gains by means of a training sequence. This paper studies the scaling law (on the network size) of the overhead for channel gain monitoring in wireless network. We first investigate the scenario in which a receiver needs to track the channel gains with respect to multiple transmitters. To be concrete, suppose that there are n transmitters, and that in the current round of channel-gain estimation, no more than k channels suffer significant variations since the last round. We proves that "\Theta(k\log((n+1)/k)) time slots" is the minimum number of time slots needed to catch up with the k varied channels. At the same time, we propose a novel channel-gain monitoring scheme named ADMOT to achieve the overhead lower-bound. ADMOT leverages recent advances in compressive sensing in signal processing and interference processing in wireless communication, to enable the receiver to estimate all n channels in a reliable and computationally efficient manner within O(k\log((n+1)/k)) time slots. To our best knowledge, all previous channel-tracking schemes require \Theta(n) time slots regardless of k. Note that based on above results for single receiver scenario, the scaling law of general setting is achieved in which there are multiple transmitters, relay nodes and receivers.


Belief Propagation Methods for Intercell Interference Coordination

Abstract: We consider a broad class of interference coordination and resource allocation problems for wireless links where the goal is to maximize the sum of functions of individual link rates. Such problems arise in the context of, for example, fractional frequency reuse (FFR) for macro-cellular networks and dynamic interference management in femtocells. The resulting optimization problems are typically hard to solve optimally even using centralized algorithms but are an essential computational step in implementing rate-fair and queue stabilizing scheduling policies in wireless networks. We consider a belief propagation framework to solve such problems approximately. In particular, we construct approximations to the belief propagation iterations to obtain computationally simple and distributed algorithms with low communication overhead. Notably, our methods are very general and apply to, for example, the optimization of transmit powers, transmit beamforming vectors, and sub-band allocation to maximize the above objective. Numerical results for femtocell deployments demonstrate that such algorithms compute a very good operating point in typically just a couple of iterations.


Evolutionary Approach to Test Generation for Functional BIST

Abstract: In the paper, an evolutionary approach to test generation for functional BIST is considered. The aim of the proposed scheme is to minimize the test data volume by allowing the device's microprogram to test its logic, providing an observation structure to the system, and generating appropriate test data for the given architecture. Two methods of deriving a deterministic test set at functional level are suggested. The first method is based on the classical genetic algorithm with binary and arithmetic crossover and mutation operators. The second one uses genetic programming, where test is represented as a sequence of microoperations. In the latter case, we apply two-point crossover based on exchanging test subsequences and mutation implemented as random replacement of microoperations or operands. Experimental data of the program realization showing the efficiency of the proposed methods are presented.


Self-repairing Homomorphic Codes for Distributed Storage Systems

Abstract: Erasure codes provide a storage efficient alternative to replication based redundancy in (networked) storage systems. They however entail high communication overhead for maintenance, when some of the encoded fragments are lost and need to be replenished. Such overheads arise from the fundamental need to recreate (or keep separately) first a copy of the whole object before any individual encoded fragment can be generated and replenished. There has been recently intense interest to explore alternatives, most prominent ones being regenerating codes (RGC) and hierarchical codes (HC). We propose as an alternative a new family of codes to improve the maintenance process, which we call self-repairing codes (SRC), with the following salient features: (a) encoded fragments can be repaired directly from other subsets of encoded fragments without having to reconstruct first the original data, ensuring that (b) a fragment is repaired from a fixed number of encoded fragments, the number depending only on how many encoded blocks are missing and independent of which specific blocks are missing. These properties allow for not only low communication overhead to recreate a missing fragment, but also independent reconstruction of different missing fragments in parallel, possibly in different parts of the network. We analyze the static resilience of SRCs with respect to traditional erasure codes, and observe that SRCs incur marginally larger storage overhead in order to achieve the aforementioned properties. The salient SRC properties naturally translate to low communication overheads for reconstruction of lost fragments, and allow reconstruction with lower latency by facilitating repairs in parallel. These desirable properties make self-repairing codes a good and practical candidate for networked distributed storage systems.


Stable partitions in additively separable hedonic games

Abstract: An important aspect in systems of multiple autonomous agents is the exploitation of synergies via coalition formation. In this paper, we solve various open problems concerning the computational complexity of stable partitions in additively separable hedonic games. First, we propose a polynomial-time algorithm to compute a contractually individually stable partition. This contrasts with previous results such as the NP-hardness of computing individually stable or Nash stable partitions. Secondly, we prove that checking whether the core or the strict core exists is NP-hard in the strong sense even if the preferences of the players are symmetric. Finally, it is shown that verifying whether a partition consisting of the grand coalition is contractually strict core stable or Pareto optimal is coNP-complete.


WLAN PIDS

Abstract: This paper discuss two structures of WLAN system fit to Passenger Information Display System which is partly of subway.


When Both Transmitting and Receiving Energies Matter: An Application of Network Coding in Wireless Body Area Networks

Abstract: A network coding scheme for practical implementations of wireless body area networks is presented, with the objective of providing reliability under low-energy constraints. We propose a simple network layer protocol for star networks, adapting redundancy based on both transmission and reception energies for data and control packets, as well as channel conditions. Our numerical results show that even for small networks, the amount of energy reduction achievable can range from 29% to 87%, as the receiving energy per control packet increases from equal to much larger than the transmitting energy per data packet. The achievable gains increase as a) more nodes are added to the network, and/or b) the channels seen by different sensor nodes become more asymmetric.


Intervention Mechanism Design for Networks With Selfish Users

Abstract: We consider a multi-user network where a network manager and selfish users interact. The network manager monitors the behavior of users and intervenes in the interaction among users if necessary, while users make decisions independently to optimize their individual objectives. In this paper, we develop a framework of intervention mechanism design, which is aimed to optimize the objective of the manager, or the network performance, taking the incentives of selfish users into account. Our framework is general enough to cover a wide range of application scenarios, and it has advantages over existing approaches such as Stackelberg strategies and pricing. To design an intervention mechanism and to predict the resulting operating point, we formulate a new class of games called intervention games and a new solution concept called intervention equilibrium. We provide analytic results about intervention equilibrium and optimal intervention mechanisms in the case of a benevolent manager with perfect monitoring. We illustrate these results with a random access model. Our illustrative example suggests that intervention requires less knowledge about users than pricing.


Symmetric categorial grammar: residuation and Galois connections

Abstract: The Lambek-Grishin calculus is a symmetric extension of the Lambek calculus: in addition to the residuated family of product, left and right division operations of Lambek's original calculus, one also considers a family of coproduct, right and left difference operations, related to the former by an arrow-reversing duality. Communication between the two families is implemented in terms of linear distributivity principles. The aim of this paper is to complement the symmetry between (dual) residuated type-forming operations with an orthogonal opposition that contrasts residuated and Galois connected operations. Whereas the (dual) residuated operations are monotone, the Galois connected operations (and their duals) are antitone. We discuss the algebraic properties of the (dual) Galois connected operations, and generalize the (co)product distributivity principles to include the negative operations. We give a continuation-passing-style translation for the new type-forming operations, and discuss some linguistic applications.


An FPTAS for Bargaining Networks with Unequal Bargaining Powers

Abstract: Bargaining networks model social or economic situations in which agents seek to form the most lucrative partnership with another agent from among several alternatives. There has been a flurry of recent research studying Nash bargaining solutions (also called 'balanced outcomes') in bargaining networks, so that we now know when such solutions exist, and also that they can be computed efficiently, even by market agents behaving in a natural manner. In this work we study a generalization of Nash bargaining, that models the possibility of unequal 'bargaining powers'. This generalization was introduced in [KB+10], where it was shown that the corresponding 'unequal division' (UD) solutions exist if and only if Nash bargaining solutions exist, and also that a certain local dynamics converges to UD solutions when they exist. However, the bound on convergence time obtained for that dynamics was exponential in network size for the unequal division case. This bound is tight, in the sense that there exists instances on which the dynamics of [KB+10] converges only after exponential time. Other approaches, such as the one of Kleinberg and Tardos, do not generalize to the unsymmetrical case. Thus, the question of computational tractability of UD solutions has remained open. In this paper, we provide an FPTAS for the computation of UD solutions, when such solutions exist. On a graph G=(V,E) with weights (i.e. pairwise profit opportunities) uniformly bounded above by 1, our FPTAS finds an \eps-UD solution in time poly(|V|,1/\eps). We also provide a fast local algorithm for finding \eps-UD solution, providing further justification that a market can find such a solution.


Improved Parameterized Algorithms for Constraint Satisfaction

Abstract: For many constraint satisfaction problems, the algorithm which chooses a random assignment achieves the best possible approximation ratio. For instance, a simple random assignment for {\sc Max-E3-Sat} allows 7/8-approximation and for every $\eps >0$ there is no polynomial-time ($7/8+\eps$)-approximation unless P=NP. Another example is the {\sc Permutation CSP} of bounded arity. Given the expected fraction $\rho$ of the constraints satisfied by a random assignment (i.e. permutation), there is no $(\rho+\eps)$-approximation algorithm for every $\eps >0$, assuming the Unique Games Conjecture (UGC). In this work, we consider the following parameterization of constraint satisfaction problems. Given a set of $m$ constraints of constant arity, can we satisfy at least $\rho m +k$ constraint, where $\rho$ is the expected fraction of constraints satisfied by a random assignment? {\sc Constraint Satisfaction Problems above Average} have been posed in different forms in the literature \cite{Niedermeier2006,MahajanRamanSikdar09}. We present a faster parameterized algorithm for deciding whether $m/2+k/2$ equations can be simultaneously satisfied over ${\mathbb F}_2$. As a consequence, we obtain $O(k)$-variable bikernels for {\sc boolean CSPs} of arity $c$ for every fixed $c$, and for {\sc permutation CSPs} of arity 3. This implies linear bikernels for many problems under the "above average" parameterization, such as {\sc Max-$c$-Sat}, {\sc Set-Splitting}, {\sc Betweenness} and {\sc Max Acyclic Subgraph}. As a result, all the parameterized problems we consider in this paper admit $2^{O(k)}$-time algorithms. We also obtain non-trivial hybrid algorithms for every Max $c$-CSP: for every instance $I$, we can either approximate $I$ beyond the random assignment threshold in polynomial time, or we can find an optimal solution to $I$ in subexponential time.


Fast Mixing of Parallel Glauber Dynamics and Low-Delay CSMA Scheduling

Abstract: Glauber dynamics is a powerful tool to generate randomized, approximate solutions to combinatorially difficult problems. It has been used to analyze and design distributed CSMA (Carrier Sense Multiple Access) scheduling algorithms for multi-hop wireless networks. In this paper we derive bounds on the mixing time of a generalization of Glauber dynamics where multiple links are allowed to update their states in parallel and the fugacity of each link can be different. The results can be used to prove that the average queue length (and hence, the delay) under the parallel Glauber dynamics based CSMA grows polynomially in the number of links for wireless networks with bounded-degree interference graphs when the arrival rate lies in a fraction of the capacity region. We also show that in specific network topologies, the low-delay capacity region can be further improved.


Impossibility of Differentially Private Universally Optimal Mechanisms

Abstract: The notion of a universally utility-maximizing privacy mechanism was recently introduced by Ghosh, Roughgarden, and Sundararajan [STOC 2009]. These are mechanisms that guarantee optimal utility to a large class of information consumers, simultaneously, while preserving Differential Privacy [Dwork, McSherry, Nissim, and Smith, TCC 2006]. Ghosh et al. have demonstrated, quite surprisingly, a case where such a universally-optimal differentially-private mechanisms exists, when the information consumers are Bayesian. This result was recently extended by Gupte and Sundararajan [PODS 2010] to risk-averse consumers. Both positive results deal with mechanisms (approximately) computing a single count query (i.e., the number of individuals satisfying a specific property in a given population), and the starting point of our work is a trial at extending these results to similar settings, such as sum queries with non-binary individual values, histograms, and two (or more) count queries. We show, however, that universally-optimal mechanisms do not exist for all these queries, both for Bayesian and risk-averse consumers. For the Bayesian case, we go further, and give a characterization of those functions that admit universally-optimal mechanisms, showing that a universally-optimal mechanism exists, essentially, only for a (single) count query. At the heart of our proof is a representation of a query function $f$ by its privacy constraint graph $G_f$ whose edges correspond to values resulting by applying $f$ to neighboring databases.


A Non-Cooperative Method for Path Loss Estimation in Femtocell Networks

Abstract: A macrocell superposed by indoor deployed femtocells forms a geography-overlapped and spectrum-shared two tier network, which can efficiently improve coverage and enhance system capacity. It is important for reducing inter-tier co-channel interference that any femtocell user (FU) can select suitable access channel according to the path losses between itself and the macrocell users (MUs). Path loss should be estimated non-cooperatively since information exchange is difficult between macrocell and femtocells. In this paper, a novel method is proposed for FU to estimate the path loss between itself and any MU independently. According to the adaptive modulation and coding (AMC) mode information broadcasted by the macrocell base station (BS), FU first estimates the path loss between BS and a MU by using Maximum a Posteriori (MAP) method. The probability distribution function (PDF) and statistics of the transmission power of the MU is then derived. According to the sequence of received powers from the MU, FU estimates the path loss between itself and the MU by using minimum mean square error (MMSE) method. Simulation results show that the proposed method can efficiently estimate the path loss between any FU and any MU in all kinds of conditions.


Threat assessment of a possible Vehicle-Born Improvised Explosive Device using DSmT

Abstract: This paper presents the solution about the threat of a VBIED (Vehicle-Born Improvised Explosive Device) obtained with the DSmT (Dezert-Smarandache Theory). This problem has been proposed recently to the authors by Simon Maskell and John Lavery as a typical illustrative example to try to compare the different approaches for dealing with uncertainty for decision-making support. The purpose of this paper is to show in details how a solid justified solution can be obtained from DSmT approach and its fusion rules thanks to a proper modeling of the belief functions involved in this problem.


Close Clustering Based Automated Color Image Annotation

Abstract: Most image-search approaches today are based on the text based tags associated with the images which are mostly human generated and are subject to various kinds of errors. The results of a query to the image database thus can often be misleading and may not satisfy the requirements of the user. In this work we propose our approach to automate this tagging process of images, where image results generated can be fine filtered based on a probabilistic tagging mechanism. We implement a tool which helps to automate the tagging process by maintaining a training database, wherein the system is trained to identify certain set of input images, the results generated from which are used to create a probabilistic tagging mechanism. Given a certain set of segments in an image it calculates the probability of presence of particular keywords. This probability table is further used to generate the candidate tags for input images.


Preserving HTTP Sessions in Vehicular Environments

Abstract: Wireless Internet in the in-vehicle environment is an evolving reality that reflects the gradual maturity of wireless technologies. Its complexity is reflected in the diversity of wireless technologies and dynamically changing network environments. The ability to adapt to the dynamics of such environments and to survive transient failures due to network handoffs are fundamentally important in failure-prone vehicular environments. In this paper we identify several new issues arising from network heterogeneity in vehicular environments and concentrate on designing and implementing a network-aware prototype system that supports HTTP session continuity in the presence of network volatility, with the emphasis on the following specifically tailored features: (1) automatic and transparent HTTP failure recovery, (2) network awareness and adaptation, (3) application-layer preemptive network handoff. Experimental results gathered from real application environments based on CDMA {\it 1xRTT} and IEEE 802 networks are presented and analyzed.