Efficient Multi-site Data Movement Using Constraint Programming for Data Hungry Science

Abstract: For the past decade, HENP experiments have been heading towards a distributed computing model in an effort to concurrently process tasks over enormous data sets that have been increasing in size as a function of time. In order to optimize all available resources (geographically spread) and minimize the processing time, it is necessary to face also the question of efficient data transfers and placements. A key question is whether the time penalty for moving the data to the computational resources is worth the presumed gain. Onward to the truly distributed task scheduling we present the technique using a Constraint Programming (CP) approach. The CP technique schedules data transfers from multiple resources considering all available paths of diverse characteristic (capacity, sharing and storage) having minimum user's waiting time as an objective. We introduce a model for planning data transfers to a single destination (data transfer) as well as its extension for an optimal data set spreading strategy (data placement). Several enhancements for a solver of the CP model will be shown, leading to a faster schedule computation time using symmetry breaking, branch cutting, well studied principles from job-shop scheduling field and several heuristics. Finally, we will present the design and implementation of a corner-stone application aimed at moving datasets according to the schedule. Results will include comparison of performance and trade-off between CP techniques and a Peer-2-Peer model from simulation framework as well as the real case scenario taken from a practical usage of a CP scheduler.


Lower Bounds for Pinning Lines by Balls

Abstract: A line L is a transversal to a family F of convex objects in R^d if it intersects every member of F. In this paper we show that for every integer d>2 there exists a family of 2d-1 pairwise disjoint unit balls in R^d with the property that every subfamily of size 2d-2 admits a transversal, yet any line misses at least one member of the family. This answers a question of Danzer from 1957.


Attacking an OT-Based Blind Signature Scheme

Abstract: In this paper, we describe an attack against one of the Oblivious-Transfer-based blind signatures scheme, proposed in [1]. An attacker with a primitive capability of producing specific-range random numbers, while exhibiting a partial MITM behavior, is able to corrupt the communication between the protocol participants. The attack is quite efficient as it leads to a protocol communication corruption and has a sound-minimal computational cost. We propose a solution to fix the security flaw.


Empirical evaluation of construction heuristics for the multidimensional assignment problem

Abstract: The multidimensional assignment problem (MAP) (abbreviated s-AP in the case of s dimensions) is an extension of the well-known assignment problem. The most studied case of MAP is 3-AP, though the problems with larger values of s have also a number of applications. In this paper we consider four fast construction heuristics for MAP. One of the heuristics is new. A modification of the heuristics is proposed to optimize the access to slow computer memory. The results of computational experiments for several instance families are provided and discussed.


Fragments of first-order logic over infinite words

Abstract: We give topological and algebraic characterizations as well as language theoretic descriptions of the following subclasses of first-order logic FO[<] for omega-languages: Sigma_2, FO^2, the intersection of FO^2 and Sigma_2, and Delta_2 (and by duality Pi_2 and the intersection of FO^2 and Pi_2). These descriptions extend the respective results for finite words. In particular, we relate the above fragments to language classes of certain (unambiguous) polynomials. An immediate consequence is the decidability of the membership problem of these classes, but this was shown before by Wilke and Bojanczyk and is therefore not our main focus. The paper is about the interplay of algebraic, topological, and language theoretic properties.


Mnesors for automatic control

Abstract: Mnesors are defined as elements of a semimodule over the min-plus integers. This two-sorted structure is able to merge graduation properties of vectors and idempotent properties of boolean numbers, which makes it appropriate for hybrid systems. We apply it to the control of an inverted pendulum and design a full logical controller, that is, without the usual algebra of real numbers.


A measurement driven, 802.11 anti-jamming system

Abstract: Dense, unmanaged 802.11 deployments tempt saboteurs into launching jamming attacks by injecting malicious interference. Nowadays, jammers can be portable devices that transmit intermittently at low power in order to conserve energy. In this paper, we first conduct extensive experiments on an indoor 802.11 network to assess the ability of two physical layer functions, rate adaptation and power control, in mitigating jamming. In the presence of a jammer we find that: (a) the use of popular rate adaptation algorithms can significantly degrade network performance and, (b) appropriate tuning of the carrier sensing threshold allows a transmitter to send packets even when being jammed and enables a receiver capture the desired signal. Based on our findings, we build ARES, an Anti-jamming REinforcement System, which tunes the parameters of rate adaptation and power control to improve the performance in the presence of jammers. ARES ensures that operations under benign conditions are unaffected. To demonstrate the effectiveness and generality of ARES, we evaluate it in three wireless testbeds: (a) an 802.11n WLAN with MIMO nodes, (b) an 802.11a/g mesh network with mobile jammers and (c) an 802.11a WLAN. We observe that ARES improves the network throughput across all testbeds by up to 150%.


Multi-Head Finite Automata: Characterizations, Concepts and Open Problems

Abstract: Multi-head finite automata were introduced in (Rabin, 1964) and (Rosenberg, 1966). Since that time, a vast literature on computational and descriptional complexity issues on multi-head finite automata documenting the importance of these devices has been developed. Although multi-head finite automata are a simple concept, their computational behavior can be already very complex and leads to undecidable or even non-semi-decidable problems on these devices such as, for example, emptiness, finiteness, universality, equivalence, etc. These strong negative results trigger the study of subclasses and alternative characterizations of multi-head finite automata for a better understanding of the nature of non-recursive trade-offs and, thus, the borderline between decidable and undecidable problems. In the present paper, we tour a fragment of this literature.


Approximating Scheduling Machines with Capacity Constraints

Abstract: In the Scheduling Machines with Capacity Constraints problem, we are given k identical machines, each of which can process at most m_i jobs. M jobs are also given, where job j has a non-negative processing time length t_j >= 0. The task is to find a schedule such that the makespan is minimized and the capacity constraints are met. In this paper, we present a 3-approximation algorithm using an extension of Iterative Rounding Method introduced by Jain. To the best of the authors' knowledge, this is the first attempt to apply Iterative Rounding Method to scheduling problem with capacity constraints.


Real Solution Isolation with Multiplicity of Zero-Dimensional Triangular Systems

Abstract: Existing algorithms for isolating real solutions of zero-dimensional polynomial systems do not compute the multiplicities of the solutions. In this paper, we define in a natural way the multiplicity of solutions of zero-dimensional triangular polynomial systems and prove that our definition is equivalent to the classical definition of local (intersection) multiplicity. Then we present an effective and complete algorithm for isolating real solutions with multiplicities of zero-dimensional triangular polynomial systems using our definition. The algorithm is based on interval arithmetic and square-free factorization of polynomials with real algebraic coefficients. The computational results on some examples from the literature are presented.


Deformable Model with a Complexity Independent from Image Resolution

Abstract: We present a parametric deformable model which recovers image components with a complexity independent from the resolution of input images. The proposed model also automatically changes its topology and remains fully compatible with the general framework of deformable models. More precisely, the image space is equipped with a metric that expands salient image details according to their strength and their curvature. During the whole evolution of the model, the sampling of the contour is kept regular with respect to this metric. By this way, the vertex density is reduced along most parts of the curve while a high quality of shape representation is preserved. The complexity of the deformable model is thus improved and is no longer influenced by feature-preserving changes in the resolution of input images. Building the metric requires a prior estimation of contour curvature. It is obtained using a robust estimator which investigates the local variations in the orientation of image gradient. Experimental results on both computer generated and biomedical images are presented to illustrate the advantages of our approach.


Feynman Algorithm Implementation for Comparison with Euler in a Uniform Elastic Two-Layer 2D and 3D Object Dynamic Deformation Framework in OpenGL with GUI

Abstract: We implement for comparative purposes the Feynman algorithm within a C++-based framework for two-layer uniform facet elastic object for real-time softbody simulation based on physics modeling methods. To facilitate the comparison, we implement initial timing measurements on the same hardware against that of Euler integrator in the softbody framework by varying different algorithm parameters. Due to a relatively large number of such variations we implement a GLUI-based user-interface to allow for much more finer control over the simulation process at real-time, which was lacking completely in the previous versions of the framework. We show our currents results based on the enhanced framework. The two-layered elastic object consists of inner and outer elastic mass-spring surfaces and compressible internal pressure. The density of the inner layer can be set differently from the density of the outer layer; the motion of the inner layer can be opposite to the motion of the outer layer. These special features, which cannot be achieved by a single layered object, result in improved imitation of a soft body, such as tissue's liquid non-uniform deformation. The inertial behavior of the elastic object is well illustrated in environments with gravity and collisions with walls, ceiling, and floor. The collision detection is defined by elastic collision penalty method and the motion of the object is guided by the Ordinary Differential Equation computation. Users can interact with the modeled objects, deform them, and observe the response to their action in real-time and we provide an extensible framework and its implementation for comparative studies of different physical-based modeling and integration algorithm implementations.


Instruction sequence notations with probabilistic instructions

Abstract: This paper concerns instruction sequences that contain probabilistic instructions, i.e. instructions that are themselves probabilistic by nature. We propose several kinds of probabilistic instructions, provide an informal operational meaning for each of them, and discuss related work. On purpose, we refrain from providing an ad hoc formal meaning for the proposed kinds of instructions. We also discuss the approach of projection semantics, which was introduced in earlier work on instruction sequences, in the light of probabilistic instruction sequences.


Activit\'es collectives et instrumentation. \'Etude de pratiques dans l'enseignement sup\'erieur

Abstract: This article presents the results of a study which concerns Instrumented Collective Learning Situations (ICLS) used in higher education and according to different actors's point of view (instructional designer and tutor). Considered actors have been involved in ICLS conception or in their use with students. We determine several forms of ICLS (in terms of scenario, tools, kind of activity) and what educational approaches are adopted by educational actors in their practices. We detail the results of our study, mainly by highlighting the "home-made" approach of the actors, that is based on an opportunist and pragmatic use of available tools in order to fit into the educational contexts.


Poset representation and similarity comparisons os systems in IR

Abstract: In this paper we are using the poset representation to describe the complex answers given by IR systems after a clustering and ranking processes. The answers considered may be given by cartographical representations or by thematic sub-lists of documents. The poset representation, with the graph theory and the relational representation opens many perspectives in the definition of new similarity measures capable of taking into account both the clustering and ranking processes. We present a general method for constructing new similarity measures and give several examples. These measures can be used for semi-ordered partitions; moreover, in the comparison of two sets of answers, the corresponding similarity indicator is an increasing function of the ranks of presentation of common answers.


Convex shapes and convergence speed of discrete tangent estimators

Abstract: Discrete geometric estimators aim at estimating geometric characteristics of a shape with only its digitization as input data. Such an estimator is multigrid convergent when its estimates tend toward the geometric characteristics of the shape as the digitization step h tends toward 0. This paper studies the multigrid convergence of tangent estimators based on maximal digital straight segment recognition. We show that such estimators are multigrid convergent for some family of convex shapes and that their speed of convergence is on average O(h^(2/3)). Experiments confirm this result and suggest that the bound is tight.


Fracture num\'erique chez les seniors du 4eme age. Observation d'une acculturation technique

Abstract: Very old people accumulate the "handicaps": social, physical, psychological or cognitive. Various research thus developed to determine there waiting and needs and also to see the benefit possibly produced by technologies (called ?gerontechnology?) on their living conditions. The object of this article is to present the numerical service offer to very old perople and to see how it takes part in a social justice according to the definition of Rawls (principle of equal freedom, principle of equal opportunity in the access). The adoption, the use and the benefit of technology are analyzed in a theoretical way through a state of the art and in an experimental way through a qualitative and quantitative investigation carried out with a population of very old people. We propose to identify dynamic technological acceptance of old people according to the TAM'S (Technology Acceptance Model) of Davis adapted by (Hamner and Qazi, 2008).


Object-Relational Database Representations for Text Indexing

Abstract: One of the distinctive features of Information Retrieval systems comparing to Database Management systems, is that they offer better compression for posting lists, resulting in better I/O performance and thus faster query evaluation. In this paper, we introduce database representations of the index that reduce the size (and thus the disk I/Os) of the posting lists. This is not achieved by redesigning the DBMS, but by exploiting the non 1NF features that existing Object-Relational DBM systems (ORDBMS) already offer. Specifically, four different database representations are described and detailed experimental results for one million pages are reported. Three of these representations are one order of magnitude more space efficient and faster (in query evaluation) than the plain relational representation.


Computational Power of P Systems with Small Size Insertion and Deletion Rules

Abstract: Recent investigations show insertion-deletion systems of small size that are not complete and cannot generate all recursively enumerable languages. However, if additional computational distribution mechanisms like P systems are added, then the computational completeness is achieved in some cases. In this article we take two insertion-deletion systems that are not computationally complete, consider them in the framework of P systems and show that the computational power is strictly increased by proving that any recursively enumerable language can be generated. At the end some open problems are presented.


Semi-Myopic Sensing Plans for Value Optimization

Abstract: We consider the following sequential decision problem. Given a set of items of unknown utility, we need to select one of as high a utility as possible (``the selection problem''). Measurements (possibly noisy) of item values prior to selection are allowed, at a known cost. The goal is to optimize the overall sequential decision process of measurements and selection. Value of information (VOI) is a well-known scheme for selecting measurements, but the intractability of the problem typically leads to using myopic VOI estimates. In the selection problem, myopic VOI frequently badly underestimates the value of information, leading to inferior sensing plans. We relax the strict myopic assumption into a scheme we term semi-myopic, providing a spectrum of methods that can improve the performance of sensing plans. In particular, we propose the efficiently computable method of ``blinkered'' VOI, and examine theoretical bounds for special cases. Empirical evaluation of ``blinkered'' VOI in the selection problem with normally distributed item values shows that is performs much better than pure myopic VOI.


Are stable instances easy?

Abstract: We introduce the notion of a stable instance for a discrete optimization problem, and argue that in many practical situations only sufficiently stable instances are of interest. The question then arises whether stable instances of NP--hard problems are easier to solve. In particular, whether there exist algorithms that solve correctly and in polynomial time all sufficiently stable instances of some NP--hard problem. The paper focuses on the Max--Cut problem, for which we show that this is indeed the case.


A General Notion of Useful Information

Abstract: In this paper we introduce a general framework for defining the depth of a sequence with respect to a class of observers. We show that our general framework captures all depth notions introduced in complexity theory so far. We review most such notions, show how they are particular cases of our general depth framework, and review some classical results about the different depth notions.


Complexity-Efficient Enumeration Techniques for Soft-Input, Soft-Output Sphere Decoding

Abstract: In this paper two complexity efficient soft sphere-decoder modifications are proposed for computing the max-log LLR values in iterative MIMO systems, which avoid the costly, typically needed, full enumeration and sorting (FES) procedure during the tree traversal without compromising the max-log performance. It is shown that despite the resulting increase in the number of expanded nodes, they can be more computationally efficient than the typical soft sphere decoders by avoiding the unnecessary complexity of FES.


On the injectivity of the global function of a cellular automaton in the hyperbolic plane (extended abstract)

Abstract: In this paper, we look at the following question. We consider cellular automata in the hyperbolic plane, (see Margenstern, 2000, 2007 and Margenstern, Morita, 2001) and we consider the global function defined on all possible configurations. Is the injectivity of this function undecidable? The problem was answered positively in the case of the Euclidean plane by Jarkko Kari, in 1994. In the present paper, we show that the answer is also positive for the hyperbolic plane: the problem is undecidable.


Some Considerations on Universality

Abstract: The paper puts into discussion the concept of universality, in particular for structures not of the power of Turing computability. The question arises if for such structures a universal structure of the same kind exists or not. For that the construction of universal Turing machines and those with some constraints are presented in some detail.


Representing a P-complete problem by small trellis automata

Abstract: A restricted case of the Circuit Value Problem known as the Sequential NOR Circuit Value Problem was recently used to obtain very succinct examples of conjunctive grammars, Boolean grammars and language equations representing P-complete languages (Okhotin, http://dx.doi.org/10.1007/978-3-540-74593-8_23 "A simple P-complete problem and its representations by language equations", MCU 2007). In this paper, a new encoding of the same problem is proposed, and a trellis automaton (one-way real-time cellular automaton) with 11 states solving this problem is constructed.


Intrinsically Universal Cellular Automata

Abstract: This talk advocates intrinsic universality as a notion to identify simple cellular automata with complex computational behavior. After an historical introduction and proper definitions of intrinsic universality, which is discussed with respect to Turing and circuit universality, we discuss construction methods for small intrinsically universal cellular automata before discussing techniques for proving non universality.


Detecting patterns in finite regular and context-free languages

Abstract: We consider variations on the following problem: given an NFA M and a pattern p, does there exist an x in L(M) such that p matches x? We consider the restricted problem where M only accepts a finite language. We also consider the variation where the pattern p is required only to match a factor of x. We show that both of these problems are NP-complete. We also consider the same problems for context-free grammars; in this case the problems become PSPACE-complete.


Personal applications, based on moveable / resizable elements

Abstract: All the modern day applications have the interface, absolutely defined by the developers. The use of adaptive interface or dynamic layout allows some variations, but even all of them are predetermined on the design stage, because the best reaction (from designer's view) on any possible users' movement was hardcoded. But there is a different world of applications, totally constructed on moveable / resizable elements; such applications turn the full control to the users. The crucial thing in such programs is that not something but everything must become moveable and resizable. This article describes the features of such applications and the algorithm behind their design.


Small Turing universal signal machines

Abstract: This article aims at providing signal machines as small as possible able to perform any computation (in the classical understanding). After presenting signal machines, it is shown how to get universal ones from Turing machines, cellular-automata and cyclic tag systems. Finally a halting universal signal machine with 13 meta-signals and 21 collision rules is presented.


A Particular Universal Cellular Automaton

Abstract: Signals are a classical tool used in cellular automata constructions that proved to be useful for language recognition or firing-squad synchronisation. Particles and collisions formalize this idea one step further, describing regular nets of colliding signals. In the present paper, we investigate the use of particles and collisions for constructions involving an infinite number of interacting particles. We obtain a high-level construction for a new smallest intrinsically universal cellular automaton with 4 states.


Computational Processes and Incompleteness

Abstract: We introduce a formal definition of Wolfram's notion of computational process based on cellular automata, a physics-like model of computation. There is a natural classification of these processes into decidable, intermediate and complete. It is shown that in the context of standard finite injury priority arguments one cannot establish the existence of an intermediate computational process.


New Choice for Small Universal Devices: Symport/Antiport P Systems

Abstract: Symport/antiport P systems provide a very simple machinery inspired by corresponding operations in the living cell. It turns out that systems of small descriptional complexity are needed to achieve the universality by these systems. This makes them a good candidate for small universal devices replacing register machines for different simulations, especially when a simulating parallel machinery is involved. This article contains survey of these systems and presents different trade-offs between parameters.


Minkowski Sum Construction and other Applications of Arrangements of Geodesic Arcs on the Sphere

Abstract: We present two exact implementations of efficient output-sensitive algorithms that compute Minkowski sums of two convex polyhedra in 3D. We do not assume general position. Namely, we handle degenerate input, and produce exact results. We provide a tight bound on the exact maximum complexity of Minkowski sums of polytopes in 3D in terms of the number of facets of the summand polytopes. The algorithms employ variants of a data structure that represents arrangements embedded on two-dimensional parametric surfaces in 3D, and they make use of many operations applied to arrangements in these representations. We have developed software components that support the arrangement data-structure variants and the operations applied to them. These software components are generic, as they can be instantiated with any number type. However, our algorithms require only (exact) rational arithmetic. These software components together with exact rational-arithmetic enable a robust, efficient, and elegant implementation of the Minkowski-sum constructions and the related applications. These software components are provided through a package of the Computational Geometry Algorithm Library (CGAL) called Arrangement_on_surface_2. We also present exact implementations of other applications that exploit arrangements of arcs of great circles embedded on the sphere. We use them as basic blocks in an exact implementation of an efficient algorithm that partitions an assembly of polyhedra in 3D with two hands using infinite translations. This application distinctly shows the importance of exact computation, as imprecise computation might result with dismissal of valid partitioning-motions.


Goal-oriented Data Warehouse Quality Measurement

Abstract: Requirements engineering is known to be a key factor for the success of software projects. Inside this discipline, goal-oriented requirements engineering approaches have shown specially suitable to deal with projects where it is necessary to capture the alignment between system requirements and stakeholders' needs, as is the case of data-warehousing projects. However, the mere alignment of data-warehouse system requirements with business goals is not enough to assure better data-warehousing products; measures and techniques are also needed to assure the data-warehouse quality. In this paper, we provide a modelling framework for data-warehouse quality measurement (i*DWQM). This framework, conceived as an i* extension, provides support for the definition of data-warehouse requirements analysis models that include quantifiable quality scenarios, defined in terms of well-formed measures. This extension has been defined by means of a UML profiling architecture. The resulting framework has been implemented in the Eclipse development platform.


A Concrete View of Rule 110 Computation

Abstract: Rule 110 is a cellular automaton that performs repeated simultaneous updates of an infinite row of binary values. The values are updated in the following way: 0s are changed to 1s at all positions where the value to the right is a 1, while 1s are changed to 0s at all positions where the values to the left and right are both 1. Though trivial to define, the behavior exhibited by Rule 110 is surprisingly intricate, and in (Cook, 2004) we showed that it is capable of emulating the activity of a Turing machine by encoding the Turing machine and its tape into a repeating left pattern, a central pattern, and a repeating right pattern, which Rule 110 then acts on. In this paper we provide an explicit compiler for converting a Turing machine into a Rule 110 initial state, and we present a general approach for proving that such constructions will work as intended. The simulation was originally assumed to require exponential time, but surprising results of Neary and Woods (2006) have shown that in fact, only polynomial time is required. We use the methods of Neary and Woods to exhibit a direct simulation of a Turing machine by a tag system in polynomial time.


Limitations of Self-Assembly at Temperature One (extended abstract)

Abstract: We prove that if a subset X of the integer Cartesian plane weakly self-assembles at temperature 1 in a deterministic (Winfree) tile assembly system satisfying a natural condition known as *pumpability*, then X is a finite union of doubly periodic sets. This shows that only the most simple of infinite shapes and patterns can be constructed using pumpable temperature 1 tile assembly systems, and gives strong evidence for the thesis that temperature 2 or higher is required to carry out general-purpose computation in a tile assembly system. Finally, we show that general-purpose computation is possible at temperature 1 if negative glue strengths are allowed in the tile assembly model.


Playing With Population Protocols

Abstract: Population protocols have been introduced as a model of sensor networks consisting of very limited mobile agents with no control over their own movement: A collection of anonymous agents, modeled by finite automata, interact in pairs according to some rules. Predicates on the initial configurations that can be computed by such protocols have been characterized under several hypotheses. We discuss here whether and when the rules of interactions between agents can be seen as a game from game theory. We do so by discussing several basic protocols.


Busy beavers gone wild

Abstract: We show some incompleteness results a la Chaitin using the busy beaver functions. Then, with the help of ordinal logics, we show how to obtain a theory in which the values of the busy beaver functions can be provably established and use this to reveal a structure on the provability of the values of these functions.


Communications in cellular automata

Abstract: The goal of this paper is to show why the framework of communication complexity seems suitable for the study of cellular automata. Researchers have tackled different algorithmic problems ranging from the complexity of predicting to the decidability of different dynamical properties of cellular automata. But the difference here is that we look for communication protocols arising in the dynamics itself. Our work is guided by the following idea: if we are able to give a protocol describing a cellular automaton, then we can understand its behavior.


The Pagoda Sequence: a Ramble through Linear Complexity, Number Walls, D0L Sequences, Finite State Automata, and Aperiodic Tilings

Abstract: We review the concept of the number wall as an alternative to the traditional linear complexity profile (LCP), and sketch the relationship to other topics such as linear feedback shift-register (LFSR) and context-free Lindenmayer (D0L) sequences. A remarkable ternary analogue of the Thue-Morse sequence is introduced having deficiency 2 modulo 3, and this property verified via the re-interpretation of the number wall as an aperiodic plane tiling.


Self-Assembly of Infinite Structures

Abstract: We review some recent results related to the self-assembly of infinite structures in the Tile Assembly Model. These results include impossibility results, as well as novel tile assembly systems in which shapes and patterns that represent various notions of computation self-assemble. Several open questions are also presented and motivated.


Adaptive Regularization of Ill-Posed Problems: Application to Non-rigid Image Registration

Abstract: We introduce an adaptive regularization approach. In contrast to conventional Tikhonov regularization, which specifies a fixed regularization operator, we estimate it simultaneously with parameters. From a Bayesian perspective we estimate the prior distribution on parameters assuming that it is close to some given model distribution. We constrain the prior distribution to be a Gauss-Markov random field (GMRF), which allows us to solve for the prior distribution analytically and provides a fast optimization algorithm. We apply our approach to non-rigid image registration to estimate the spatial transformation between two images. Our evaluation shows that the adaptive regularization approach significantly outperforms standard variational methods.


On acceptance conditions for membrane systems: characterisations of L and NL

Abstract: In this paper we investigate the affect of various acceptance conditions on recogniser membrane systems without dissolution. We demonstrate that two particular acceptance conditions (one easier to program, the other easier to prove correctness) both characterise the same complexity class, NL. We also find that by restricting the acceptance conditions we obtain a characterisation of L. We obtain these results by investigating the connectivity properties of dependency graphs that model membrane system computations.


On the boundaries of solvability and unsolvability in tag systems. Theoretical and Experimental Results

Abstract: Several older and more recent results on the boundaries of solvability and unsolvability in tag systems are surveyed. Emphasis will be put on the significance of computer experiments in research on very small tag systems.


Complexity through the Observation of Simple Systems

Abstract: We survey work on the paradigm called "computing by observing." Its central feature is that one considers the behavior of an evolving system as the result of a computation. To this end an observer records this behavior. It has turned out that the observed behavior of computationally simple systems can be very complex, when an appropriate observer is used. For example, a restricted version of context-free grammars with regular observers suffices to obtain computational completeness. As a second instantiation presented here, we apply an observer to sticker systems. Finally, some directions for further research are proposed.


Quantifying the Availability of TV White Spaces for Cognitive Radio Operation in the UK

Abstract: Cognitive radio is being intensively researched for opportunistic access to the so-called TV White Spaces (TVWS): large portions of the VHF/UHF TV bands which become available on a geographical basis after the digital switchover. Using accurate digital TV (DTV) coverage maps together with a database of DTV transmitters, we develop a methodology for identifying TVWS frequencies at any given location in the United Kingdom. We use our methodology to investigate variations in TVWS as a function of the location and transmit power of cognitive radios, and examine how constraints on adjacent channel interference imposed by regulators may affect the results. Our analysis provides a realistic view on the spectrum opportunity associated with cognitive devices, and presents the first quantitative study of the availability and frequency composition of TWVS outside the United States.


ModelTalk: A Framework for Developing Domain Specific Executable Models

Abstract: Developing and maintaining complex, large-scale, product line of highly customized software systems is difficult and costly. Part of the difficulty is due to the need to communicate business knowledge between domain experts and application programmers. Domain specific model driven development (MDD) addresses this difficulty by providing domain experts and developers with domain specific abstractions for communicating designs. Most MDD implementations take a generative approach. In contrast, we adopt an interpretive approach to domain specific model driven development. We present a framework, named ModelTalk, that integrates MDD, dependency injection and meta-modeling to form an interpretive, domain specific modeling framework. The framework is complemented by tool support that provides developers with the same advanced level of usability for modeling as they are accustomed to in programming environments. ModelTalk is used in a commercial setting for developing a product line of Telco grade business support systems (BSS).


Decentralized Traffic Management Strategies for Sensor-Enabled Cars

Abstract: Traffic Congestions and accidents are major concerns in today's transportation systems. This thesis investigates how to optimize traffic flow on highways, in particular for merging situations such as intersections where a ramp leads onto the highway. In our work, cars are equipped with sensors that can detect distance to neighboring cars, and communicate their velocity and acceleration readings with one another. Sensor-enabled cars can locally exchange sensed information about the traffic and adapt their behavior much earlier than regular cars. We propose proactive algorithms for merging different streams of sensor-enabled cars into a single stream. A proactive merging algorithm decouples the decision point from the actual merging point. Sensor-enabled cars allow us to decide where and when a car merges before it arrives at the actual merging point. This leads to a significant improvement in traffic flow as velocities can be adjusted appropriately. We compare proactive merging algorithms against the conventional priority-based merging algorithm in a controlled simulation environment. Experiment results show that proactive merging algorithms outperform the priority-based merging algorithm in terms of flow and delay.


AIS for Misbehavior Detection in Wireless Sensor Networks: Performance and Design Principles

Abstract: A sensor network is a collection of wireless devices that are able to monitor physical or environmental conditions. These devices (nodes) are expected to operate autonomously, be battery powered and have very limited computational capabilities. This makes the task of protecting a sensor network against misbehavior or possible malfunction a challenging problem. In this document we discuss performance of Artificial immune systems (AIS) when used as the mechanism for detecting misbehavior. We show that (i) mechanism of the AIS have to be carefully applied in order to avoid security weaknesses, (ii) the choice of genes and their interaction have a profound influence on the performance of the AIS, (iii) randomly created detectors do not comply with limitations imposed by communications protocols and (iv) the data traffic pattern seems not to impact significantly the overall performance. We identified a specific MAC layer based gene that showed to be especially useful for detection; genes measure a network's performance from a node's viewpoint. Furthermore, we identified an interesting complementarity property of genes; this property exploits the local nature of sensor networks and moves the burden of excessive communication from normally behaving nodes to misbehaving nodes. These results have a direct impact on the design of AIS for sensor networks and on engineering of sensor networks.


The parameterized complexity of some geometric problems in unbounded dimension

Abstract: We study the parameterized complexity of the following fundamental geometric problems with respect to the dimension $d$: i) Given $n$ points in $\Rd$, compute their minimum enclosing cylinder. ii) Given two $n$-point sets in $\Rd$, decide whether they can be separated by two hyperplanes. iii) Given a system of $n$ linear inequalities with $d$ variables, find a maximum-size feasible subsystem. We show that (the decision versions of) all these problems are W[1]-hard when parameterized by the dimension $d$. %and hence not solvable in ${O}(f(d)n^c)$ time, for any computable function $f$ and constant $c$ %(unless FPT=W[1]). Our reductions also give a $n^{\Omega(d)}$-time lower bound (under the Exponential Time Hypothesis).


Efficient Offline Algorithmic Techniques for Several Packet Routing Problems in Distributed Systems

Abstract: In this paper we consider several problems concerning packet routing in distributed systems. Each problem is formulated using terms from Graph Theory and for each problem we present efficient, novel, algorithmic techniques for computing optimal solutions. We address topics like: bottleneck paths (trees), optimal paths with non-linear costs, optimal paths with multiple optimization objectives, maintaining aggregate connectivity information under a sequence of network link failures, and several others.


Optimal Constrained Resource Allocation Strategies under Low Risk Circumstances

Abstract: In this paper we consider multiple constrained resource allocation problems, where the constraints can be specified by formulating activity dependency restrictions or by using game-theoretic models. All the problems are focused on generic resources, with a few exceptions which consider financial resources in particular. The problems consider low-risk circumstances and the values of the uncertain variables which are used by the algorithms are the expected values of the variables. For each of the considered problems we propose novel algorithmic solutions for computing optimal resource allocation strategies. The presented solutions are optimal or near-optimal from the perspective of their time complexity. The considered problems have applications in a broad range of domains, like workflow scheduling in industry (e.g. in the mining and metallurgical industry) or the financial sector, motion planning, facility location and data transfer or job scheduling and resource management in Grids, clouds or other distributed systems.


A universally fastest algorithm for Max 2-Sat, Max 2-CSP, and everything in between

Abstract: In this paper we introduce "hybrid" Max 2-CSP formulas consisting of "simple clauses", namely conjunctions and disjunctions of pairs of variables, and general 2-variable clauses, which can be any integer-valued functions of pairs of boolean variables. This allows an algorithm to use both efficient reductions specific to AND and OR clauses, and other powerful reductions that require the general CSP setting. We use new reductions introduced here, and recent reductions such as "clause-learning" and "2-reductions" generalized to our setting's mixture of simple and general clauses. Parametrizing an instance by the fraction p of non-simple clauses, we give an exact (exponential-time) algorithm that is the fastest known polynomial-space algorithm for p=0 (which includes the well-studied Max 2-Sat problem but also instances with arbitrary mixtures of AND and OR clauses); the only efficient algorithm for mixtures of AND, OR, and general integer-valued clauses; and tied for fastest for general Max 2-CSP (p=1). Since a pure 2-Sat input instance may be transformed to a general CSP instance in the course of being solved, the algorithm's efficiency and generality go hand in hand. Our algorithm analysis and optimization are a variation on the familiar measure-and-conquer approach, resulting in an optimizing mathematical program that is convex not merely quasi-convex, and thus can be solved efficiently and with a certificate of optimality. We produce a family of running-time upper-bound formulas, each optimized for instances with a particular value of p but valid for all instances.


Finding Significant Subregions in Large Image Databases

Abstract: Images have become an important data source in many scientific and commercial domains. Analysis and exploration of image collections often requires the retrieval of the best subregions matching a given query. The support of such content-based retrieval requires not only the formulation of an appropriate scoring function for defining relevant subregions but also the design of new access methods that can scale to large databases. In this paper, we propose a solution to this problem of querying significant image subregions. We design a scoring scheme to measure the similarity of subregions. Our similarity measure extends to any image descriptor. All the images are tiled and each alignment of the query and a database image produces a tile score matrix. We show that the problem of finding the best connected subregion from this matrix is NP-hard and develop a dynamic programming heuristic. With this heuristic, we develop two index based scalable search strategies, TARS and SPARS, to query patterns in a large image repository. These strategies are general enough to work with other scoring schemes and heuristics. Experimental results on real image datasets show that TARS saves more than 87% query time on small queries, and SPARS saves up to 52% query time on large queries as compared to linear search. Qualitative tests on synthetic and real datasets achieve precision of more than 80%.


Spanning connectivity games

Abstract: The Banzhaf index, Shapley-Shubik index and other voting power indices measure the importance of a player in a coalitional game. We consider a simple coalitional game called the spanning connectivity game (SCG) based on an undirected, unweighted multigraph, where edges are players. We examine the computational complexity of computing the voting power indices of edges in the SCG. It is shown that computing Banzhaf values and Shapley-Shubik indices is #P-complete for SCGs. Interestingly, Holler indices and Deegan-Packel indices can be computed in polynomial time. Among other results, it is proved that Banzhaf indices can be computed in polynomial time for graphs with bounded treewidth. It is also shown that for any reasonable representation of a simple game, a polynomial time algorithm to compute the Shapley-Shubik indices implies a polynomial time algorithm to compute the Banzhaf indices. As a corollary, computing the Shapley value is #P-complete for simple games represented by the set of minimal winning coalitions, Threshold Network Flow Games, Vertex Connectivity Games and Coalitional Skill Games.


Speedup for Natural Problems and Noncomputability

Abstract: A resource-bounded version of the statement "no algorithm recognizes all non-halting Turing machines" is equivalent to an infinitely often (i.o.) superpolynomial speedup for the time required to accept any coNP-complete language and also equivalent to a superpolynomial speedup in proof length in propositional proof systems for tautologies, each of which implies P!=NP. This suggests a correspondence between the properties 'has no algorithm at all' and 'has no best algorithm' which seems relevant to open problems in computational and proof complexity.


Defense Strategies Against Modern Botnets

Abstract: Botnets are networks of compromised computers with malicious code which are remotely controlled and which are used for starting distributed denial of service (DDoS) attacks, sending enormous number of e-mails (SPAM) and other sorts of attacks. Defense against modern Botnets is a real challenge. This paper offers several strategies for defense against Botnets with a list and description of measures and activities which should be carried out in order to establish successful defense. The paper also offers parallel preview of the strategies with their advantages and disadvantages considered in accordance with various criteria.


Using Agent to Coordinate Web Services

Abstract: Traditionally, agent and web service are two separate research areas. We figure that, through agent communication, agent is suitable to coordinate web services. However, there exist agent communication problems due to the lack of uniform, cross-platform vocabulary. Fortunately, ontology defines a vocabulary. We thus propose a new agent communication layer and present the web ontology language (OWL)-based operational ontologies that provides a declarative description. It can be accessed by various engines to facilitate agent communication. Further, in our operational ontologies, we define the mental attitudes of agents that can be shared among other agents. Our architecture enhanced the 3APL agent platform, and it is implemented as an agent communication framework. Finally, we extended the framework to be compatible with the web ontology language for service (OWL-S), and then develop a movie recommendation system with four OWL-S semantic web services on the framework. The benefits of this work are: 1) dynamic web service coordination, 2) ontological reasoning through uniform representation, namely, the declarative description, and 3) easy reuse and extension of both ontology and engine through extending ontology.


Automatic Defect Detection and Classification Technique from Image: A Special Case Using Ceramic Tiles

Abstract: Quality control is an important issue in the ceramic tile industry. On the other hand maintaining the rate of production with respect to time is also a major issue in ceramic tile manufacturing. Again, price of ceramic tiles also depends on purity of texture, accuracy of color, shape etc. Considering this criteria, an automated defect detection and classification technique has been proposed in this report that can have ensured the better quality of tiles in manufacturing process as well as production rate. Our proposed method plays an important role in ceramic tiles industries to detect the defects and to control the quality of ceramic tiles. This automated classification method helps us to acquire knowledge about the pattern of defect within a very short period of time and also to decide about the recovery process so that the defected tiles may not be mixed with the fresh tiles.


High Transmission Bit Rate of A thermal Arrayed Waveguide Grating (AWG) Module in Passive Optical Networks

Abstract: In the present paper, high transmission bit rate of a thermal arrayed waveguide grating (AWG) which is composed of lithium niobate (LiNbO3)/polymethyl metha acrylate (PMMA) hybrid materials on a silicon substrate in Passive Optical Networks (PONs) has parametrically analyzed and investigated over wide range of the affecting parameters. We have theoretically investigated the temperature dependent wavelength shift of the arrayed waveguide grating (AWG) depends on the refractive-indices of the materials and the size of the waveguide. A thermalization of the AWG can be realized by selecting proper values of the material and structural parameters of the device. Moreover, we have analyzed the data transmission bit rate of a thermal AWG in passsive optical networks (PONs) based on Maximum Time Division Multiplexing (MTDM) technique.


XML Data Integrity Based on Concatenated Hash Function

Abstract: Data integrity is the fundamental for data authentication. A major problem for XML data authentication is that signed XML data can be copied to another document but still keep signature valid. This is caused by XML data integrity protecting. Through investigation, the paper discovered that besides data content integrity, XML data integrity should also protect element location information, and context referential integrity under fine-grained security situation. The aim of this paper is to propose a model for XML data integrity considering XML data features. The paper presents an XML data integrity model named as CSR (content integrity, structure integrity, context referential integrity) based on a concatenated hash function. XML data content integrity is ensured using an iterative hash process, structure integrity is protected by hashing an absolute path string from root node, and context referential integrity is ensured by protecting context-related elements. Presented XML data integrity model can satisfy integrity requirements under situation of fine-grained security, and compatible with XML signature. Through evaluation, the integrity model presented has a higher efficiency on digest value-generation than the Merkle hash tree-based integrity model for XML data.


Hybrid Rules with Well-Founded Semantics

Abstract: A general framework is proposed for integration of rules and external first order theories. It is based on the well-founded semantics of normal logic programs and inspired by ideas of Constraint Logic Programming (CLP) and constructive negation for logic programs. Hybrid rules are normal clauses extended with constraints in the bodies; constraints are certain formulae in the language of the external theory. A hybrid program is a pair of a set of hybrid rules and an external theory. Instances of the framework are obtained by specifying the class of external theories, and the class of constraints. An example instance is integration of (non-disjunctive) Datalog with ontologies formalized as description logics. The paper defines a declarative semantics of hybrid programs and a goal-driven formal operational semantics. The latter can be seen as a generalization of SLS-resolution. It provides a basis for hybrid implementations combining Prolog with constraint solvers. Soundness of the operational semantics is proven. Sufficient conditions for decidability of the declarative semantics, and for completeness of the operational semantics are given.


Hardware Trojan by Hot Carrier Injection

Abstract: This paper discusses how hot carrier injection (HCI) can be exploited to create a trojan that will cause hardware failures. The trojan is produced not via additional logic circuitry but by controlled scenarios that maximize and accelerate the HCI effect in transistors. These scenarios range from manipulating the manufacturing process to varying the internal voltage distribution. This new type of trojan is difficult to test due to its gradual hardware degradation mechanism. This paper describes the HCI effect, detection techniques and discusses the possibility for maliciously induced HCI trojans.


Exploiting Semiconductor Properties for Hardware Trojans

Abstract: This paper discusses the possible introduction of hidden reliability defects during CMOS foundry fabrication processes that may lead to accelerated wearout of the devices. These hidden defects or hardware Trojans can be created by deviation from foundry design rules and processing parameters. The Trojans are produced by exploiting time-based wearing mechanisms (HCI, NBTI, TDDB and EM) and/or condition-based triggers (ESD, Latchup and Softerror). This class of latent damage is difficult to test due to its gradual degradation nature. The paper describes life-time expectancy results for various Trojan induced scenarios. Semiconductor properties, processing and design parameters critical for device reliability and Trojan creation are discussed.


Threshold Verification Technique for Network Intrusion Detection System

Abstract: Internet has played a vital role in this modern world, the possibilities and opportunities offered are limitless. Despite all the hype, Internet services are liable to intrusion attack that could tamper the confidentiality and integrity of important information. An attack started with gathering the information of the attack target, this gathering of information activity can be done as either fast or slow attack. The defensive measure network administrator can take to overcome this liability is by introducing Intrusion Detection Systems (IDSs) in their network. IDS have the capabilities to analyze the network traffic and recognize incoming and on-going intrusion. Unfortunately the combination of both modules in real time network traffic slowed down the detection process. In real time network, early detection of fast attack can prevent any further attack and reduce the unauthorized access on the targeted machine. The suitable set of feature selection and the correct threshold value, add an extra advantage for IDS to detect anomalies in the network. Therefore this paper discusses a new technique for selecting static threshold value from a minimum standard features in detecting fast attack from the victim perspective. In order to increase the confidence of the threshold value the result is verified using Statistical Process Control (SPC). The implementation of this approach shows that the threshold selected is suitable for identifying the fast attack in real time.


Neighbor-Specific BGP: More Flexible Routing Policies While Improving Global Stability

Abstract: Please Note: This document was written to summarize and facilitate discussion regarding (1) the benefits of changing the way BGP selects routes to selecting the most preferred route allowed by export policies, or more generally, to selecting BGP routes on a per-neighbor basis, (2) the safety condition that guarantees global routing stability under the Neighbor-Specific BGP model, and (3) ways of deploying this model in practice. A paper presenting the formal model and proof of the stability conditions was published at SIGMETRICS 2009 and is available online.


Aspects of enumeration and generation with a string automata representation

Abstract: In general, the representation of combinatorial objects is decisive for the feasibility of several enumerative tasks. In this work, we show how a (unique) string representation for (complete) initially-connected deterministic automata (ICDFAs) with n states over an alphabet of k symbols can be used for counting, exact enumeration, sampling and optimal coding, not only the set of ICDFAs but, to some extent, the set of regular languages. An exact generation algorithm can be used to partition the set of ICDFAs in order to parallelize the counting of minimal automata (and thus of regular languages). We present also a uniform random generator for ICDFAs that uses a table of pre-calculated values. Based on the same table it is also possible to obtain an optimal coding for ICDFAs.


Games for width parameters and monotonicity

Abstract: We introduce a search game for two players played on a "scenario" consisting of a ground set together with a collection of feasible partitions. This general setting allows us to obtain new characterisations of many width parameters such as rank-width and carving-width of graphs, matroid tree-width and GF(4)-rank-width. We show that the monotone game variant corresponds to a tree decomposition of the ground set along feasible partitions. Our framework also captures many other decompositions into "simple" subsets of the ground set, such as decompositions into planar subgraphs. Within our general framework, we take a step towards characterising monotone search games. We exhibit a large class of "monotone" scenarios, i.e. of scenarios where the game and its monotone variant coincide. As a consequence, determining the winner is in NP for these games. This result implies monotonicity for all our search games, that are equivalent to branch-width of a submodular function. Finally, we include a proof showing that the matroid tree-width of a graphic matroid is not larger than the tree-width of the corresponding graph. This proof is considerably shorter than the original proof and it is purely graph theoretic.


A Parallelism-Based Approach to Network Anonymization

Abstract: Considering topologies of anonymous networks we used to organizing anonymous communication into hard to trace paths hiding its origin or destination. In anonymity the company is crucial, however the serial transportation imposes a costly tradeoff between a level of privacy and a speed of communication. This paper introduces a framework of a novel architecture for anonymous networks that hides initiators of communications by parallelization of anonymous links. The new approach, which is based on the grounds of the anonymous P2P network called P2Priv, does not require content forwarding via a chain of proxy nodes to assure high degree of anonymity. Contrary to P2Priv, the new architecture can be suited to anonymization of various network communications, including anonymous access to distributed as well as client-server services. In particular, it can be considered as an anonymization platform for these network applications where both privacy and low delays are required.


Fixed-parameter tractability and lower bounds for stabbing problems

Abstract: We study the following general stabbing problem from a parameterized complexity point of view: Given a set $\mathcal S$ of $n$ translates of an object in $\Rd$, find a set of $k$ lines with the property that every object in $\mathcal S$ is ''stabbed'' (intersected) by at least one line. We show that when $S$ consists of axis-parallel unit squares in $\Rtwo$ the (decision) problem of stabbing $S$ with axis-parallel lines is W[1]-hard with respect to $k$ (and thus, not fixed-parameter tractable unless FPT=W[1]) while it becomes fixed-parameter tractable when the squares are disjoint. We also show that the problem of stabbing a set of disjoint unit squares in $\Rtwo$ with lines of arbitrary directions is W[1]--hard with respect to $k$. Several generalizations to other types of objects and lines with arbitrary directions are also presented. Finally, we show that deciding whether a set of unit balls in $\Rd$ can be stabbed by one line is W[1]--hard with respect to the dimension $d$.


Using the General Intensional Programming System (GIPSY) for Evaluation of Higher-Order Intensional Logic (HOIL) Expressions

Abstract: The General Intensional Programming System (GIPSY) has been built around the Lucid family of intensional programming languages that rely on the higher-order intensional logic (HOIL) to provide context-oriented multidimensional reasoning of intensional expressions. HOIL combines functional programming with various intensional logics to allow explicit context expressions to be evaluated as first-class values that can be passed as parameters to functions and return as results with an appropriate set of operators defined on contexts. GIPSY's frameworks are implemented in Java as a collection of replaceable components for the compilers of various Lucid dialects and the demand-driven eductive evaluation engine that can run distributively. GIPSY provides support for hybrid programming models that couple intensional and imperative languages for a variety of needs. Explicit context expressions limit the scope of evaluation of math expressions (effectively a Lucid program is a mathematics or physics expression constrained by the context) in tensor physics, regular math in multiple dimensions, etc., and for cyberforensic reasoning as one of the use-cases of interest. Thus, GIPSY is a support testbed for HOIL-based languages some of which enable such reasoning, as in formal cyberforensic case analysis with event reconstruction. In this paper we discuss the GIPSY architecture, its evaluation engine and example use-cases.


An Introduction to Simulation-Based Techniques for Automated Service Composition

Abstract: This work is an introduction to the author's contributions to the SOC area, resulting from his PhD research activity. It focuses on the problem of automatically composing a desired service, given a set of available ones and a target specification. As for description, services are represented as finite-state transition systems, so to provide an abstract account of their behavior, seen as the set of possible conversations with external clients. In addition, the presence of a finite shared memory is considered, that services can interact with and which provides a basic form of communication. Rather than describing technical details, we offer an informal overview of the whole work, and refer the reader to the original papers, referenced throughout this work, for all details.


A Type System Theory for Higher-Order Intensional Logic Support for Variable Bindings in Hybrid Intensional-Imperative Programs in GIPSY

Abstract: We describe a type system for a platform called the General Intensional Programming System (GIPSY), designed to support intensional programming languages built upon intensional logic and their imperative counter-parts for the intensional execution model. In GIPSY, the type system glues the static and dynamic typing between intensional and imperative languages in its compiler and run-time environments to support the intensional evaluation of expressions written in various dialects of the intensional programming language Lucid. The intensionality makes expressions to explicitly take into the account a multidimensional context of evaluation with the context being a first-class value that serves a number of applications that need the notion of context to proceed. We describe and discuss the properties of such a type system and the related type theory as well as particularities of the semantics, design and implementation of the GIPSY type system.


Reasoning About a Service-oriented Programming Paradigm

Abstract: This paper is about a new way for programming distributed applications: the service-oriented one. It is a concept paper based upon our experience in developing a theory and a language for programming services. Both the theoretical formalization and the language interpreter showed us the evidence that a new programming paradigm exists. In this paper we illustrate the basic features it is characterized by.


Fairness as a QoS Measure for Web Services

Abstract: Service Oriented Architectures (SOAs) are component-based architectures, characterized by reusability, modularization and composition, usually offered by HTTP (web services) and often equipped with a Quality of Services (QoS) measure. In order to guarantee the fairness property to each client requesting a service, we propose a fair version of the (Soft) Concurrent Constraint language to deal with the negotiation phases of the Service Level Agreement (SLA) protocol.


Bayesian Forecasting of WWW Traffic on the Time Varying Poisson Model

Abstract: Traffic forecasting from past observed traffic data with small calculation complexity is one of important problems for planning of servers and networks. Focusing on World Wide Web (WWW) traffic as fundamental investigation, this paper would deal with Bayesian forecasting of network traffic on the time varying Poisson model from a viewpoint from statistical decision theory. Under this model, we would show that the estimated forecasting value is obtained by simple arithmetic calculation and expresses real WWW traffic well from both theoretical and empirical points of view.


Service-oriented Context-aware Framework

Abstract: Location- and context-aware services are emerging technologies in mobile and desktop environments, however, most of them are difficult to use and do not seem to be beneficial enough. Our research focuses on designing and creating a service-oriented framework that helps location- and context-aware, client-service type application development and use. Location information is combined with other contexts such as the users' history, preferences and disabilities. The framework also handles the spatial model of the environment (e.g. map of a room or a building) as a context. The framework is built on a semantic backend where the ontologies are represented using the OWL description language. The use of ontologies enables the framework to run inference tasks and to easily adapt to new context types. The framework contains a compatibility layer for positioning devices, which hides the technical differences of positioning technologies and enables the combination of location data of various sources.


Towards Activity Context using Software Sensors

Abstract: Service-Oriented Computing delivers the promise of configuring and reconfiguring software systems to address user's needs in a dynamic way. Context-aware computing promises to capture the user's needs and hence the requirements they have on systems. The marriage of both can deliver ad-hoc software solutions relevant to the user in the most current fashion. However, here it is a key to gather information on the users' activity (that is what they are doing). Traditionally any context sensing was conducted with hardware sensors. However, software can also play the same role and in some situations will be more useful to sense the activity of the user. Furthermore they can make use of the fact that Service-oriented systems exchange information through standard protocols. In this paper we discuss our proposed approach to sense the activity of the user making use of software.


Soft Constraints for Quality Aspects in Service Oriented Architectures

Abstract: We propose the use of Soft Constraints as a natural way to model Service Oriented Architecture. In the framework, constraints are used to model components and connectors and constraint aggregation is used to represent their interactions. The "quality of a service" is measured and considered when performing queries to service providers. Some examples consist in the levels of cost, performance and availability required by clients. In our framework, the QoS scores are represented by the softness level of the constraint and the measure of complex (web) services is computed by combining the levels of the components.


Towards a Unifying View of QoS-Enhanced Web Service Description and Discovery Approaches

Abstract: The number of web services increased vastly in the last years. Various providers offer web services with the same functionality, so for web service consumers it is getting more complicated to select the web service, which best fits their requirements. That is why a lot of the research efforts point to discover semantic means for describing web services taking into account not only functional characteristics of services, but also the quality of service (QoS) properties such as availability, reliability, response time, trust, etc. This motivated us to research current approaches presenting complete solutions for QoS enabled web service description, publication and discovery. In this paper we present comparative analysis of these approaches according to their common principals. Based on such analysis we extract the essential aspects from them and propose a pattern for the development of QoS-aware service-oriented architectures.


Analysis of the various key management algorithms and new proposal in the secure multicast communications

Abstract: With the evolution of the Internet, multicast communications seem particularly well adapted for large scale commercial distribution applications, for example, the pay TV channels and secure videoconferencing. Key management for multicast remains an open topic in secure Communications today. Key management mainly has to do with the distribution and update of keying material during the group life. Several key tree based approach has been proposed by various authors to create and distribute the multicast group key in effective manner. There are different key management algorithms that facilitate efficient distribution and rekeying of the group key. These protocols normally add communication overhead as well as computation overhead at the group key controller and at the group members. This paper explores the various algorithms along with the performances and derives an improved method.


Application of non-uniform laxity to EDF for aperiodic tasks to improve task utilisation on multicore platforms

Abstract: This paper proposes a new scheduler applying the concept of non-uniform laxity to Earliest deadline first (EDF) approach for aperiodic tasks. This scheduler improves task utilisation (Execution time / deadline) and also increases the number of tasks that are being scheduled. Laxity is a measure of the spare time permitted for the task before it misses its deadline, and is computed using the expression (deadline - (current time + execution time)). Weight decides the priority of the task and is defined by the expression (quantum slice time / allocated time)*total core time for the task. Quantum slice time is the time actually used, allocated time is the time allocated by the scheduler, and total core time is the time actually reserved by the core for execution of one quantum of the task. Non-uniform laxity enables scheduling of tasks that have higher priority before the normal execution of other tasks and is computed by multiplying the weight of the task with its laxity. The algorithm presented in the paper has been simulated on Cheddar, a real time scheduling tool and also on SESC, an architectural simulator for multicore platforms, for upto 5000 random task sets, and upto 5000 cores. This scheduler improves task utilisation by 35% and the number of tasks being scheduled by 36%, compared to conventional EDF.


Quantitative testing semantics for non-interleaving

Abstract: This paper presents a non-interleaving denotational semantics for the ?-calculus. The basic idea is to define a notion of test where the outcome is not only whether a given process passes a given test, but also in how many different ways it can pass it. More abstractly, the set of possible outcomes for tests forms a semiring, and the set of process interpretations appears as a module over this semiring, in which basic syntactic constructs are affine operators. This notion of test leads to a trace semantics in which traces are partial orders, in the style of Mazurkiewicz traces, extended with readiness information. Our construction has standard may- and must-testing as special cases.


A Quantum-based Model for Interactive Information Retrieval (extended version)

Abstract: Even the best information retrieval model cannot always identify the most useful answers to a user query. This is in particular the case with web search systems, where it is known that users tend to minimise their effort to access relevant information. It is, however, believed that the interaction between users and a retrieval system, such as a web search engine, can be exploited to provide better answers to users. Interactive Information Retrieval (IR) systems, in which users access information through a series of interactions with the search system, are concerned with building models for IR, where interaction plays a central role. There are many possible interactions between a user and a search system, ranging from query (re)formulation to relevance feedback. However, capturing them within a single framework is difficult and previously proposed approaches have mostly focused on relevance feedback. In this paper, we propose a general framework for interactive IR that is able to capture the full interaction process in a principled way. Our approach relies upon a generalisation of the probability framework of quantum physics, whose strong geometric component can be a key towards a successful interactive IR model.


Bayesian two-sample tests

Abstract: In this paper, we present two classes of Bayesian approaches to the two-sample problem. Our first class of methods extends the Bayesian t-test to include all parametric models in the exponential family and their conjugate priors. Our second class of methods uses Dirichlet process mixtures (DPM) of such conjugate-exponential distributions as flexible nonparametric priors over the unknown distributions.


Physical Modeling Techniques in Active Contours for Image Segmentation

Abstract: Physical modeling method, represented by simulation and visualization of the principles in physics, is introduced in the shape extraction of the active contours. The objectives of adopting this concept are to address the several major difficulties in the application of Active Contours. Primarily, a technique is developed to realize the topological changes of Parametric Active Contours (Snakes). The key strategy is to imitate the process of a balloon expanding and filling in a closed space with several objects. After removing the touched balloon surfaces, the objects can be identified by surrounded remaining balloon surfaces. A burned region swept by Snakes is utilized to trace the contour and to give a criterion for stopping the movement of Snake curve. When the Snakes terminates evolution totally, through ignoring this criterion, it can form a connected area by evolving the Snakes again and continuing the region burning. The contours extracted from the boundaries of the burned area can represent the child snake of each object respectively. Secondly, a novel scheme is designed to solve the problems of leakage of the contour from the large gaps, and the segmentation error in Geometric Active Contours (GAC). It divides the segmentation procedure into two processing stages. By simulating the wave propagating in the isotropic substance at the final stage, it can significantly enhance the effect of image force in GAC based on Level Set and give the satisfied solutions to the two problems. Thirdly, to support the physical models for active contours above, we introduce a general image force field created on a template plane over the image plane. This force is more adaptable to noisy images with complicated geometric shapes.


Recommender Systems for the Conference Paper Assignment Problem

Abstract: Conference paper assignment, i.e., the task of assigning paper submissions to reviewers, presents multi-faceted issues for recommender systems research. Besides the traditional goal of predicting `who likes what?', a conference management system must take into account aspects such as: reviewer capacity constraints, adequate numbers of reviews for papers, expertise modeling, conflicts of interest, and an overall distribution of assignments that balances reviewer preferences with conference objectives. Among these, issues of modeling preferences and tastes in reviewing have traditionally been studied separately from the optimization of paper-reviewer assignment. In this paper, we present an integrated study of both these aspects. First, due to the paucity of data per reviewer or per paper (relative to other recommender systems applications) we show how we can integrate multiple sources of information to learn paper-reviewer preference models. Second, our models are evaluated not just in terms of prediction accuracy but in terms of the end-assignment quality. Using a linear programming-based assignment optimization formulation, we show how our approach better explores the space of unsupplied assignments to maximize the overall affinities of papers assigned to reviewers. We demonstrate our results on real reviewer preference data from the IEEE ICDM 2007 conference.


An Event Based Approach To Situational Representation

Abstract: Many application domains require representing interrelated real-world activities and/or evolving physical phenomena. In the crisis response domain, for instance, one may be interested in representing the state of the unfolding crisis (e.g., forest fire), the progress of the response activities such as evacuation and traffic control, and the state of the crisis site(s). Such a situation representation can then be used to support a multitude of applications including situation monitoring, analysis, and planning. In this paper, we make a case for an event based representation of situations where events are defined to be domain-specific significant occurrences in space and time. We argue that events offer a unifying and powerful abstraction to building situational awareness applications. We identify challenges in building an Event Management System (EMS) for which traditional data and knowledge management systems prove to be limited and suggest possible directions and technologies to address the challenges.


On computing the Hermite form of a matrix of differential polynomials

Abstract: Given an n x n matrix over the ring of differential polynomials F(t)[\D;\delta], we show how to compute the Hermite form H of A, and a unimodular matrix U such that UA=H. The algorithm requires a polynomial number of operations in terms of n, deg_D(A), and deg_t(A). When F is the field of rational numbers, it also requires time polynomial in the bit-length of the coefficients.


A Refined Experience Sampling Method to Capture Mobile User Experience

Abstract: This paper reviews research methods used to understand the user experience of mobile technology. The paper presents an improvement of the Experience Sampling Method and case studies supporting its design. The paper concludes with an agenda of future work for improving research in this field. Keywords: Research methods, topology, case study, contrasting graph, Experience Sampling Method


Automatic Spatially-Adaptive Balancing of Energy Terms for Image Segmentation

Abstract: Image segmentation techniques are predominately based on parameter-laden optimization. The objective function typically involves weights for balancing competing image fidelity and segmentation regularization cost terms. Setting these weights suitably has been a painstaking, empirical process. Even if such ideal weights are found for a novel image, most current approaches fix the weight across the whole image domain, ignoring the spatially-varying properties of object shape and image appearance. We propose a novel technique that autonomously balances these terms in a spatially-adaptive manner through the incorporation of image reliability in a graph-based segmentation framework. We validate on synthetic data achieving a reduction in mean error of 47% (p-value << 0.05) when compared to the best fixed parameter segmentation. We also present results on medical images (including segmentations of the corpus callosum and brain tissue in MRI data) and on natural images.


Adaptive Process Management in Highly Dynamic and Pervasive Scenarios

Abstract: Process Management Systems (PMSs) are currently more and more used as a supporting tool for cooperative processes in pervasive and highly dynamic situations, such as emergency situations, pervasive healthcare or domotics/home automation. But in all such situations, designed processes can be easily invalidated since the execution environment may change continuously due to frequent unforeseeable events. This paper aims at illustrating the theoretical framework and the concrete implementation of SmartPM, a PMS that features a set of sound and complete techniques to automatically cope with unplanned exceptions. PMS SmartPM is based on a general framework which adopts the Situation Calculus and Indigolog.


Distributed Fault Detection in Sensor Networks using a Recurrent Neural Network

Abstract: In long-term deployments of sensor networks, monitoring the quality of gathered data is a critical issue. Over the time of deployment, sensors are exposed to harsh conditions, causing some of them to fail or to deliver less accurate data. If such a degradation remains undetected, the usefulness of a sensor network can be greatly reduced. We present an approach that learns spatio-temporal correlations between different sensors, and makes use of the learned model to detect misbehaving sensors by using distributed computation and only local communication between nodes. We introduce SODESN, a distributed recurrent neural network architecture, and a learning method to train SODESN for fault detection in a distributed scenario. Our approach is evaluated using data from different types of sensors and is able to work well even with less-than-perfect link qualities and more than 50% of failed nodes.


Rough Set Model for Discovering Hybrid Association Rules

Abstract: In this paper, the mining of hybrid association rules with rough set approach is investigated as the algorithm RSHAR.The RSHAR algorithm is constituted of two steps mainly. At first, to join the participant tables into a general table to generate the rules which is expressing the relationship between two or more domains that belong to several different tables in a database. Then we apply the mapping code on selected dimension, which can be added directly into the information system as one certain attribute. To find the association rules, frequent itemsets are generated in second step where candidate itemsets are generated through equivalence classes and also transforming the mapping code in to real dimensions. The searching method for candidate itemset is similar to apriori algorithm. The analysis of the performance of algorithm has been carried out.


On the relation between size-based termination and semantic labelling

Abstract: We investigate the relationship between two independently developed termination techniques. On the one hand, sized-types based termination (SBT) uses types annotated with size expressions and Girard's reducibility candidates, and applies on systems using constructor matching only. On the other hand, semantic labelling transforms a rewrite system by annotating each function symbol with the semantics of its arguments, and applies to any rewrite system. First, we introduce a simplified version of SBT for the simply-typed lambda-calculus. Then, we give new proofs of the correctness of SBT using semantic labelling, both in the first and in the higher-order case. As a consequence, we show that SBT can be extended to systems using matching on defined symbols (e.g. associative functions).


On the Definition of Non-deterministic Mechanisms

Abstract: We present here three different approaches to the problem of modeling mathematically the concept of a non-deterministic mechanism. Each of these three approaches leads to a mathematical definition. We then show that all the three mathematical concepts are equivalent to one another. This insight gives us the option of approaching the wp-formalism of Dijkstra from a different viewpoint that is easier to understand and to teach.


A Performance Analysis of HICCUPS - a Steganographic System for WLAN

Abstract: The paper presents an analysis of performance features of the HICCUPS (HIdden Communication system for CorrUPted networkS) including the efficiency and the cost of the system in WLANs (Wireless Local Area Networks). The analysis relies on the original CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance) 802.11 Markov chain-based model.


On Chase Termination Beyond Stratification

Abstract: We study the termination problem of the chase algorithm, a central tool in various database problems such as the constraint implication problem, Conjunctive Query optimization, rewriting queries using views, data exchange, and data integration. The basic idea of the chase is, given a database instance and a set of constraints as input, to fix constraint violations in the database instance. It is well-known that, for an arbitrary set of constraints, the chase does not necessarily terminate (in general, it is even undecidable if it does or not). Addressing this issue, we review the limitations of existing sufficient termination conditions for the chase and develop new techniques that allow us to establish weaker sufficient conditions. In particular, we introduce two novel termination conditions called safety and inductive restriction, and use them to define the so-called T-hierarchy of termination conditions. We then study the interrelations of our termination conditions with previous conditions and the complexity of checking our conditions. This analysis leads to an algorithm that checks membership in a level of the T-hierarchy and accounts for the complexity of termination conditions. As another contribution, we study the problem of data-dependent chase termination and present sufficient termination conditions w.r.t. fixed instances. They might guarantee termination although the chase does not terminate in the general case. As an application of our techniques beyond those already mentioned, we transfer our results into the field of query answering over knowledge bases where the chase on the underlying database may not terminate, making existing algorithms applicable to broader classes of constraints.


A Peer to Peer Protocol for Online Dispute Resolution over Storage Consumption

Abstract: In bilateral accounting of resource consumption both the consumer and provider independently measure the amount of resources consumed by the consumer. The problem here is that potential disparities between the provider's and consumer's accountings, might lead to conflicts between the two parties that need to be resolved. We argue that with the proper mechanisms available, most of these conflicts can be solved online, as opposite to in court resolution; the design of such mechanisms is still a research topic; to help cover the gap, in this paper we propose a peer--to--peer protocol for online dispute resolution over storage consumption. The protocol is peer--to--peer and takes into consideration the possible causes (e.g, transmission delays, unsynchronized metric collectors, etc.) of the disparity between the provider's and consumer's accountings to make, if possible, the two results converge.


Knowledge-Based Synthesis of Distributed Systems Using Event Structures

Abstract: To produce a program guaranteed to satisfy a given specification one can synthesize it from a formal constructive proof that a computation satisfying that specification exists. This process is particularly effective if the specifications are written in a high-level language that makes it easy for designers to specify their goals. We consider a high-level specification language that results from adding knowledge to a fragment of Nuprl specifically tailored for specifying distributed protocols, called event theory. We then show how high-level knowledge-based programs can be synthesized from the knowledge-based specifications using a proof development system such as Nuprl. Methods of Halpern and Zuck then apply to convert these knowledge-based protocols to ordinary protocols. These methods can be expressed as heuristic transformation tactics in Nuprl.


Reasoning About Knowledge of Unawareness Revisited

Abstract: In earlier work, we proposed a logic that extends the Logic of General Awareness of Fagin and Halpern [1988] by allowing quantification over primitive propositions. This makes it possible to express the fact that an agent knows that there are some facts of which he is unaware. In that logic, it is not possible to model an agent who is uncertain about whether he is aware of all formulas. To overcome this problem, we keep the syntax of the earlier paper, but allow models where, with each world, a possibly different language is associated. We provide a sound and complete axiomatization for this logic and show that, under natural assumptions, the quantifier-free fragment of the logic is characterized by exactly the same axioms as the logic of Heifetz, Meier, and Schipper [2008].


A Logical Characterization of Iterated Admissibility

Abstract: Brandenburger, Friedenberg, and Keisler provide an epistemic characterization of iterated admissibility (i.e., iterated deletion of weakly dominated strategies) where uncertainty is represented using LPSs (lexicographic probability sequences). Their characterization holds in a rich structure called a complete structure, where all types are possible. Here, a logical charaacterization of iterated admisibility is given that involves only standard probability and holds in all structures, not just complete structures. A stronger notion of strong admissibility is then defined. Roughly speaking, strong admissibility is meant to capture the intuition that "all the agent knows" is that the other agents satisfy the appropriate rationality assumptions. Strong admissibility makes it possible to relate admissibility, canonical structures (as typically considered in completeness proofs in modal logic), complete structures, and the notion of ``all I know''.


A Rough Sets Partitioning Model for Mining Sequential Patterns with Time Constraint

Abstract: Now a days, data mining and knowledge discovery methods are applied to a variety of enterprise and engineering disciplines to uncover interesting patterns from databases. The study of Sequential patterns is an important data mining problem due to its wide applications to real world time dependent databases. Sequential patterns are inter-event patterns ordered over a time-period associated with specific objects under study. Analysis and discovery of frequent sequential patterns over a predetermined time-period are interesting data mining results, and can aid in decision support in many enterprise applications. The problem of sequential pattern mining poses computational challenges as a long frequent sequence contains enormous number of frequent subsequences. Also useful results depend on the right choice of event window. In this paper, we have studied the problem of sequential pattern mining through two perspectives, one the computational aspect of the problem and the other is incorporation and adjustability of time constraint. We have used Indiscernibility relation from theory of rough sets to partition the search space of sequential patterns and have proposed a novel algorithm that allows previsualization of patterns and allows adjustment of time constraint prior to execution of mining task. The algorithm Rough Set Partitioning is at least ten times faster than the naive time constraint based sequential pattern mining algorithm GSP. Besides this an additional knowledge of time interval of sequential patterns is also determined with the method.


Updating Sets of Probabilities

Abstract: There are several well-known justifications for conditioning as the appropriate method for updating a single probability measure, given an observation. However, there is a significant body of work arguing for sets of probability measures, rather than single measures, as a more realistic model of uncertainty. Conditioning still makes sense in this context--we can simply condition each measure in the set individually, then combine the results--and, indeed, it seems to be the preferred updating procedure in the literature. But how justified is conditioning in this richer setting? Here we show, by considering an axiomatic account of conditioning given by van Fraassen, that the single-measure and sets-of-measures cases are very different. We show that van Fraassen's axiomatization for the former case is nowhere near sufficient for updating sets of measures. We give a considerably longer (and not as compelling) list of axioms that together force conditioning in this setting, and describe other update methods that are allowed once any of these axioms is dropped.


The Complexity of Probabilistic Lobbying

Abstract: We propose models for lobbying in a probabilistic environment, in which an actor (called "The Lobby") seeks to influence voters' preferences of voting for or against multiple issues when the voters' preferences are represented in terms of probabilities. In particular, we provide two evaluation criteria and two bribery methods to formally describe these models, and we consider the resulting forms of lobbying with and without issue weighting. We provide a formal analysis for these problems of lobbying in a stochastic environment, and determine their classical and parameterized complexity depending on the given bribery/evaluation criteria and on various natural parameterizations. Specifically, we show that some of these problems can be solved in polynomial time, some are NP-complete but fixed-parameter tractable, and some are W[2]-complete. Finally, we provide approximability and inapproximability results for these problems and several variants.


As time goes by: Constraint Handling Rules - A survey of CHR research from 1998 to 2007

Abstract: Constraint Handling Rules (CHR) is a high-level programming language based on multi-headed multiset rewrite rules. Originally designed for writing user-defined constraint solvers, it is now recognized as an elegant general purpose language. CHR-related research has surged during the decade following the previous survey by Fruehwirth. Covering more than 180 publications, this new survey provides an overview of recent results in a wide range of research areas, from semantics and analysis to systems, extensions and applications.


Coarse-grained Dynamic Taint Analysis for Defeating Control and Non-control Data Attacks

Abstract: Memory corruption attacks remain the primary threat for computer security. Information flow tracking or taint analysis has been proven to be effective against most memory corruption attacks. However, there are two shortcomings with current taint analysis based techniques. First, these techniques cause application slowdown by about 76% thereby limiting their practicality. Second, these techniques cannot handle non-control data attacks i.e., attacks that do not overwrite control data such as return address, but instead overwrite critical application configuration data or user identity data. In this work, to address these problems, we describe a coarse-grained taint analysis technique that uses information flow tracking at the level of application data objects. We propagate a one-bit taint over each application object that is modified by untrusted data thereby reducing the taint management overhead considerably. We performed extensive experimental evaluation of our approach and show that it can detect all critical attacks such as buffer overflows, and format string attacks, including non-control data attacks. Unlike the currently known approaches that can detect such a wide range of attacks, our approach does not require the source code or any hardware extensions. Run-time performance overhead evaluation shows that, on an average, our approach causes application slowdown by only 37% which is an order of magnitude improvement over existing approaches. Finally, since our approach performs run-time binary instrumentation, it is easier to integrate it with existing applications and systems.