Cuts from proofs: a complete and practical technique for solving linear inequalities over integers

We propose a novel, sound, and complete Simplex-based algorithm for solving linear inequalities over integers. Our algorithm, which can be viewed as a semantic generalization of the branch-and-bound technique, systematically discovers and excludes entire subspaces of the solution space containing no integer points. Our main insight is that by focusing on the defining constraints of a vertex, we can compute a proof of unsatisfiability for the intersection of the defining constraints and use this proof to systematically exclude subspaces of the feasible region with no integer points. We show experimentally that our technique significantly outperforms the top four competitors in the QF-LIA category of the SMT-COMP ’08 when solving conjunctions of linear inequalities over integers.     

Computational steering of a multi-objective evolutionary algorithm for engineering design

The execution process of an evolutionary algorithm typically involves some trial and error. This is due to the difficulty in setting the initial parameters of the algorithm—especially when little is known about the problem domain. This problem is magnified when applied to many-objective optimisation, as care is needed to ensure that the final population of candidate solutions is representative of the trade-off surface. We propose a computational steering system that allows the engineer to interact with the optimisation routine during execution. This interaction can be as simple as monitoring the values of some parameters during the execution process, or could involve altering those parameters to influence the quality of the solutions produced by the optimisation process. The implementation of this steering system should provide the ability to tailor the client to the hardware available, for example providing a lightweight steering and visualisation client for use on a PDA.     

Dynamic Tag Reduction for Low-Power Caches in Embedded Systems with Virtual Memory

This paper presents a low-power tag organization for physically tagged caches in embedded processors with virtual memory support. An exceedingly small subset of tag bits is identified for each application hot-spot so that only these tag bits are used for cache access with no performance sacrifice as they provide complete address resolution. The minimal subset of physical tag bits is dynamically updated following the changes in the physical address space of the application. Operating system support is introduced in order to maintain the reduced tags during program execution. Efficient algorithms are incorporated within the memory allocator and the dynamic linker in order to achieve dynamic update of the reduced tags. The only hardware support needed within the I/D-caches is the support for disabling bitlines of the tag arrays. An extensive set of experimental results demonstrates the efficacy of the proposed approach.     

Numerical Analysis of Second Order,Fully Discrete Energy Stable Schemes for Phase Field Models of Two-Phase Incompressible Flows

In this paper, we propose several second order in time, fully discrete, linear and nonlinear numerical schemes for solving the phase field model of two-phase incompressible flows, in the framework of finite element method. The schemes are based on the second order Crank–Nicolson method for time discretization, projection method for Navier–Stokes equations, as well as several implicit–explicit treatments for phase field equations. The energy stability and unique solvability of the proposed schemes are proved. Ample numerical experiments are performed to validate the accuracy and efficiency of the proposed schemes.     

Agent Technologies for Sensor Networks

Wireless sensor networks are increasingly seen as a solution to the problem of performing continuous wide-area monitoring in many environmental, security, and military scenarios. The distributed nature of such networks and the autonomous behavior expected of them present many novel challenges. In this article, the authors argue that a new synthesis of electronic engineering and agent technology is required to address these challenges, and they describe three examples where this synthesis has succeeded. In more detail, they describe how these novel approaches address the need for communication and computationally efficient decentralized algorithms to coordinate the behavior of physically distributed sensors, how they enable the real-world deployment of sensor agent platforms in the field, and finally, how they facilitate the development of intelligent agents that can autonomously acquire data from these networks and perform information processing tasks such as fusion, inference, and prediction.     

Nonatomic dual bakery algorithm with bounded tokens

A simple mutual exclusion algorithm is presented that only uses nonatomic shared variables of bounded size, and that satisfies bounded overtaking. When the shared variables behave atomically, it has the first-come-first-served property (FCFS). Nonatomic access makes information vulnerable. The effects of this can be mitigated by minimizing the information and by spreading it over more variables. The design approach adopted here begins with such mitigating efforts. These resulted in an algorithm with a proof of correctness, first for atomic variables. This proof is then used as a blueprint for the simultaneous development of the algorithm for nonatomic variables and its proof. Mutual exclusion is proved by means of invariants. Bounded overtaking and liveness under weak fairness are proved with invariants and variant functions. Liveness under weak fairness is formalized and proved in a set-theoretic version of temporal logic. All these assertions are verified with the proof assistant PVS. We heavily rely on the possibility offered by a proof assistant like PVS to reuse proofs developed for one context in a different context.     

Privacy-sensitive recognition of group conversational context with sociometers

Recognizing the conversational context in which group interactions unfold has applications in machines that support collaborative work and perform automatic social inference using contextual knowledge. This paper addresses the task of discriminating one conversational context from another, specifically brainstorming from decision-making interactions, using easily computable nonverbal behavioral cues. Privacy-sensitive mobile sociometers are used to record the interaction data. We hypothesize that the difference in the conversational dynamics between brainstorming and decision-making discussions is significant and measurable using speaking activity-based nonverbal cues. We characterize the communication patterns of the entire group by the aggregation (both temporal and person-wise) of their nonverbal behavior. The results on our interaction data set show that the floor-occupation patterns in a brainstorming interaction are different from a decision-making interaction, and our method can obtain a classification accuracy as high as 87.5%.     

An Active Organisation System for Customised,Secure Agent Discovery

The area of software agents has experienced an exponential growth during the past decade, and is now being given a further boost by the introduction of global distributed computing services, such as Globus and Legion. The focus of the research has gradually shifted from single agent architectures to multi-agent systems and agent societies. In a Grid computing environment, agents should be able to discover efficiently other agents based on the computational services they offer or their characteristics (agent discovery). Existing systems either ignore this issue or use simplistic organisation models, which act as passive yellow pages thus keeping the discovery process separate from the computation. In this paper it is argued that the agent discovery can be coupled with several aspects of the computation such as access control and customisation resulting in a better sharing, use and management of the information held by the agent discovery system. A novel architecture is presented in which discovery messages and discovery paths are mutable, active entities, which interact with each other as peers making the organisation system dynamic in nature. Queries traversing the system can be reformulated while at the same time the system itself can change depending on the nature and volume of the query traffic. Furthermore it is shown that the organisation nodes of the proposed architecture can serve as re-usable components for building more complex, composite nodes from existing ones.