An abstract interpretation toolkit for μCRL

This paper describes a toolkit that assists in the task of generating abstract approximations of process algebraic specifications written in the language μCRL. Abstractions are represented by Modal Labelled Transition Systems, which are mixed transition systems with may and must modalities. The approach permits to infer the satisfaction or refutation of safety and liveness properties expressed in the (action-based) μ-calculus. The tool supports the abstraction of states and action labels, which allows to deal with infinitely branching systems.     

A bandwidth allocation scheme for compositional real-time systems with periodic resources

Allocation of bandwidth among components is a fundamental problem in compositional real-time systems. State-of-the-art algorithms for bandwidth allocation use either exponential-time or pseudo-polynomial-time techniques for exact allocation, or linear-time, utilization-based techniques which may over-provision bandwidth. In this paper, we propose research into a third possible approach: parametric approximation algorithms for bandwidth allocation in compositional real-time systems. We develop a fully-polynomial-time approximation scheme (FPTAS) for allocating bandwidth for sporadic task systems scheduled by earliest-deadline first (EDF) upon an Explicit-Deadline Periodic (EDP) resource. Our algorithm takes, as parameters, the task system and an accuracy parameter ϵ>0, and returns a bandwidth which is guaranteed to be at most a factor (1+ϵ) more than the optimal minimum bandwidth required to successfully schedule the task system. Furthermore, the algorithm has time complexity that is polynomial in the number of tasks and 1/ϵ.     

Cluster scheduling for real-time systems: utilization bounds and run-time overhead

Cluster scheduling, where processors are grouped into clusters and the tasks that are allocated to one cluster are scheduled by a global scheduler, has attracted attention in multiprocessor real-time systems research recently. In this paper, assuming that an optimal global scheduler is adopted within each cluster, we investigate the worst-case utilization bounds for cluster scheduling with different task allocation/partitioning heuristics. First, we develop a lower limit on the utilization bounds for cluster scheduling with any reasonable task allocation scheme. Then, the lower limit is shown to be the exact utilization bound for cluster scheduling with the worst-fit task allocation scheme. For other task allocation heuristics (such as first-fit, best-fit, first-fit decreasing, best-fit decreasing and worst-fit decreasing), higher utilization bounds are derived for systems with both homogeneous clusters (where each cluster has the same number of processors) and heterogeneous clusters (where clusters have different number of processors). In addition, focusing on an efficient optimal global scheduler, namely the boundary-fair (Bfair) algorithm, we propose a period-aware task allocation heuristic with the goal of reducing the scheduling overhead (e.g., the number of scheduling points, context switches and task migrations). Simulation results indicate that the percentage of task sets that can be scheduled is significantly improved under cluster scheduling even for small-size clusters, compared to that of the partitioned scheduling. Moreover, when comparing to the simple generic task allocation scheme (e.g., first-fit), the proposed period-aware task allocation heuristic markedly reduces the scheduling overhead of cluster scheduling with the Bfair scheduler.     

Allocating hard real-time tasks: An NP-Hard problem made easy

A distributed hard real time system can be composed from a number of communicating tasks. One of the difficulties with building such systems is the problem of where to place the tasks. In general there are P ^T ways of allocating T tasks to P processors, and the problem of finding an optimal feasible allocation (where all tasks meet physical and timing constraints) is known to be NP-Hard. This paper describes an approach to solving the task allocation problem using a technique known as simulated annealing. It also defines a distributed hard real-time architecture and presents new analysis which enables timing requirements to be guaranteed.This work was supported in part by British Aerospace (Commercial Aircraft) Ltd, and the UK Department of Trade and Industry.     

LOCAL++: A C++ framework for local search algorithms

Local search is an emerging paradigm for combinatorial search which has recently been shown to be very effective for a large number of combinatorial problems. It is based on the idea of navigating the search space by iteratively stepping from one solution to one of its neighbors, which are obtained by applying a simple local change to it. In this paper we present LOCAL++, an object‐oriented framework to be used as a general tool for the development and implementation of local search algorithms in C++. The framework comprises a hierarchy of abstract template classes, one for each local search technique taken into account (i.e. hill‐climbing, simulated annealing and tabu search). Each class specifies and implements the invariant part of the algorithm built according to the technique, and is supposed to be specialized by a concrete class once a given search problem is considered, so as to implement the problem‐dependent part of the algorithm. LOCAL++ comprises also a set of abstract classes for creating new techniques by combining different search techniques and different neighborhood relations. The architecture of LOCAL++ provides a principled modularization for the solution of combinatorial search problems, and helps the designer deriving a neat conceptual scheme of the application, thus facilitating the development and debugging phases. LOCAL++ proved to be flexible enough for the implementation of the algorithms solving various scheduling problems. Copyright © 2000 John Wiley & Sons, Ltd.     

Analysing situated interaction hazards: an activity-based awareness approach

This paper presents a case for the usefulness of activity theory (AT) for the analysis of situated interaction hazards in safety-related systems. It is suggested here that situation awareness is a safety critical attribute that is acquired and maintained through situated activity or actions. We introduce an activity-based awareness model based on this fundamental premise and we show how the model is consistent with the principles of AT. We also provide an example of the usefulness of AT as a theoretical and practical foundation for the analysis of situated interaction hazards in complex, safety-related systems. Specifically, we describe how the activity-based awareness model and AT principles were applied to an investigation of situation awareness in a military air traffic control system. We show how this approach can also be used to support analyses of general interactive systems use. We suggest that this general approach can be used to support analyses of interactive system use, to inform system design, and mitigate against the situated interaction hazards inherent in safety-related systems, and that this provides evidence that AT can be a useful way of looking at situational hazards in safety-related systems use.     

Planning Proofs of Equations in CCS

Most efforts to automate formal verification of communicating systems have centred around finite-state systems (FSSs). However, FSSs are incapable of modelling many practical communicating systems, including a novel class of problems, which we call VIPS. VIPSs are value-passing, infinite-state, parameterised systems. Existing approaches using model checking over FSSs are insufficient for VIPSs. This is due to their inability both to reason with and about domain-specific theories, and to cope with systems having an unbounded or arbitrary state space.We use the Calculus of Communicating Systems (CCS) (Communication and Concurrency. London: Prentice Hall, 1989) to express and specify VIPSs. We take program verification to be proving the program and its intended specification equivalent. We use the laws of CCS to conduct the verification task. This approach allows us to study communicating systems and the data such systems communicate. Automating theorem proving in this context is an extremely difficult task.We provide automated methods for CCS analysis; they are applicable to both FSSs and VIPSs. Adding these methods to the CL ^A M proof planner (Lecture Notes in Artificial Intelligence, Vol. 449, Springer, 1990, pp. 647, 648), we have implemented an automated verification planner capable of dealing with problems that previously required human interaction. This paper describes these methods, gives an account as to why they work, and provides a short summary of experimental results.     

User-oriented problem abstractions in scheduling

In this paper we describe a modeling framework aimed at facilitating the customization and deployment of artificial intelligence (AI) scheduling technology in real-world contexts. Specifically, we describe an architecture aimed at facilitating software product line development in the context of scheduling systems. The framework is based on two layers of abstraction: a first layer providing an interface with the scheduling technology, on top of which we define a formalism to abstract domain-specific concepts. We show how this two-layer modeling framework provides a versatile formalism for defining user-oriented problem abstractions, which is pivotal for facilitating interaction between domain experts and technologists. Moreover, we describe a graphical user interface (GUI)-enhanced tool which allows the domain expert to interact with the underlying core scheduling technology in domain-specific terms. This is achieved by automatically instantiating an abstract GUI template on top of the second modeling layer.     

Socially Distributed Perception: GRACE plays social tag at AAAI 2005

This paper presents a robot search task (social tag) that uses social interaction, in the form of asking for help, as an integral component of task completion. Socially distributed perception is defined as a robot's ability to augment its limited sensory capacities through social interaction. We describe the task of social tag and its implementation on the robot GRACE for the AAAI 2005 Mobile Robot Competition & Exhibition. We then discuss our observations and analyses of GRACE's performance as a situated interaction with conference participants. Our results suggest we were successful in promoting a form of social interaction that allowed people to help the robot achieve its goal. Furthermore, we found that different social uses of the physical space had an effect on the nature of the interaction. Finally, we discuss the implications of this design approach for effective and compelling human-robot interaction, considering its relationship to concepts such as dependency, mixed initiative, and socially distributed cognition. An erratum to this article can be found at

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Projective virtual reality as a basis for on‐line control of complex systems‐not only‐over the internet

Already in 1994 the term Projective Virtual Reality was coined and a first implementation was used to control a complex multirobot system in Germany over the Internet from California. Building on this foundation, the general aim of the development of virtual reality technology for automation applications at the Institute of Robotics Research (IRF) today is to provide the framework for Projective Virtual Reality for a broad range of applications. The general idea of Projective Virtual Reality is to allow users to “project” actions carried out in the virtual world into the real world by means of robots or other means of automation. The framework is based on a task‐oriented approach which builds on the “task deduction” capabilities of a newly developed virtual reality system and a task planning component. The advantage of this approach is that robots which work at great distances from the control station can be controlled as easily and intuitively as robots that work right next to the control station. Robot control technology now provides the user in the virtual world with a “prolonged arm” into the physical environment, thus paving the way for intuitive control of complex systems over the Internet—and in general for a new quality of user‐friendly man‐machine interfaces for automation applications. Lately, this work has been enhanced by a new structure that allows one to distribute the virtual reality application over multiple computers on a network. With this new feature, it is now possible for multiple users to share the same virtual room, although they may physically be thousands of miles apart. They only need an Internet connection to share this new experience. Lately, the network distribution techniques have been further developed to not just allow users to cooperate over networked PCs but also to be able to set up a panorama projection or a cave running of a networked cluster of PCs. This approach cuts down the costs for such a high‐end visualization environment drastically and allows for a new range of applications. © 2005 Wiley Periodicals, Inc.     

Coalition Formation for Multi-Robot Task Allocation via Correlation Clustering

Abstract

The complexity of a vast number of real world tasks provides a great challenge for the currently available robots due to their limited capabilities. Thus, multiple robots would need to form coalitions for the completion of such tasks. In this paper, we examine the multi-robot coalition formation problem for task allocation where a group of robots needs to be allocated to a set of tasks. Our approach for this problem is to use a correlation clustering technique enabling similar robots to form coalitions. The algorithm presented in this paper is fast and scales better in comparison to two existing algorithms.     

A formal mathematical framework for modeling probabilistic hybrid systems

The development of autonomous agents, such as mobile robots and software agents, has generated considerable research in recent years. Robotic systems, which are usually built from a mixture of continuous (analog) and discrete (digital) components, are often referred to as hybrid dynamical systems. Traditional approaches to real-time hybrid systems usually define behaviors purely in terms of determinism or sometimes non-determinism. However, this is insufficient as real-time dynamical systems very often exhibit uncertain behavior. To address this issue, we develop a semantic model, Probabilistic Constraint Nets (PCN), for probabilistic hybrid systems. PCN captures the most general structure of dynamic systems, allowing systems with discrete and continuous time/variables, synchronous as well as asynchronous event structures and uncertain dynamics to be modeled in a unitary framework. Based on a formal mathematical paradigm exploiting abstract algebra, topology and measure theory, PCN provides a rigorous formal programming semantics for the design of hybrid real-time embedded systems exhibiting uncertainty.      

A Compiler-Directed Approach to Network Latency Reduction for Distributed Shared Memory Multiprocessors

In distributed shared memory multiprocessor systems, parallel tasks communicate through sharing memory data. As the system size increases, such communication cost becomes the main factor that limits the overall parallelism and performance. In this paper, we propose a new solution to the problem through judiciously managing the relevant resource, namely, the shared data and the interconnection network (IN) through which the sharing is carried out. In this approach, communication cost is minimized by means of data migration/allocation which is based on analyzing general layered task graphs, sharing behavior of parallel tasks, and network topology. Our method is not applicable for read only variables. Further, for the time being, the usefulness of the method is limited to multiprocessors where no cache coherence mechanism is implemented. Four typical interconnection topologies for multiprocessors are considered, namely, shared-bus, hierarchical-bus, 2-D mesh, and fat-tree structures. Efficient data allocation algorithms for each of the four network topologies are developed that make decision on data allocation/migration at the compile time. The complexity of one algorithm isO(np) for shared-bus andO(n²p) for the remaining three in a system withnprocessors executing ap-layer task graph for one shared variable. We have also given an algorithm to determine optimal allocation/migration scheme for multiple shared variables. However, the cost of the algorithm become prohibitive when the number of shared variables is high. Therefore, a heuristic of low complexity is suggested. The heuristic is optimal for some topologies.     

Fault tolerant control design using adaptive control allocation based on the pseudo inverse along the null space

Fault‐tolerant control systems are vital in many industrial systems. Actuator redundancy is employed in advanced control strategies to increase system maneuverability, flexibility, safety, and fault tolerability. Management of control signals among redundant actuators is the task of control allocation algorithms. Simplicity, accuracy and low computational cost are key issues in control allocation implementations. In this paper, an adaptive control allocation method based on the pseudo inverse along the null space of the control matrix (PAN) is introduced in order to adaptively tolerate actuator faults. The proposed method solves the control allocation problem with an exact solution and optimized l_∞ norm of the control signal. This method also handles input limitations and is computationally efficient. Simulation results are used to show the effectiveness of the proposed method. Copyright © 2016 John Wiley & Sons, Ltd.     

Shaping multi-agent systems with gradient reinforcement learning

An original reinforcement learning (RL) methodology is proposed for the design of multi-agent systems. In the realistic setting of situated agents with local perception, the task of automatically building a coordinated system is of crucial importance. To that end, we design simple reactive agents in a decentralized way as independent learners. But to cope with the difficulties inherent to RL used in that framework, we have developed an incremental learning algorithm where agents face a sequence of progressively more complex tasks. We illustrate this general framework by computer experiments where agents have to coordinate to reach a global goal. This work has been conducted in part in NICTA’s Canberra laboratory.     

A comparison of task pools for dynamic load balancing of irregular algorithms

Since a static work distribution does not allow for satisfactory speed‐ups of parallel irregular algorithms, there is a need for a dynamic distribution of work and data that can be adapted to the runtime behavior of the algorithm. Task pools are data structures which can distribute tasks dynamically to different processors where each task specifies computations to be performed and provides the data for these computations. This paper discusses the characteristics of task‐based algorithms and describes the implementation of selected types of task pools for shared‐memory multiprocessors. Several task pools have been implemented in C with POSIX threads and in Java. The task pools differ in the data structures to store the tasks, the mechanism to achieve load balance, and the memory manager used to store the tasks. Runtime experiments have been performed on three different shared‐memory systems using a synthetic algorithm, the hierarchical radiosity method, and a volume rendering algorithm. Copyright © 2004 John Wiley & Sons, Ltd.     

A massively parallel fault-tolerant architecture for time-critical computing

Building large-scale parallel computer systems for time-critical applications is a challenging task since the designers of such systems need to consider a number of related factors such as proper support for fault tolerance, efficient task allocation and reallocation strategies, and scalability. In this paper we propose a massively parallel fault-tolerant architecture using hundreds or thousands of processors for critical applications with timing constraints. The proposed architecture is based on an interconnection network called thebisectional network. A bisectional network is isomorphic to a hypercube in that a binary hypercube network can be easily extended as a bisectional network by adding additional links. These additional links add to the network some rich topological properties such as node symmetry, small diameter, small internode distance, and partitionability. The important property of partitioning is exploited to propose a redundant task allocation and a task redistribution strategy under realtime constraints. The system is partitioned into symmetric regions (spheres) such that each sphere has a central control point. The central points, calledfault control points (FCPs), are distributed throughout the entire system in an optimal fashion and provide two-level task redundancy and efficiently redistribute the loads of failed nodes. FCPs are assigned to the processing nodes such that each node is assigned two types of FCPs for storing two redundant copies of every task present at the node. Similarly, the number of nodes assigned to each FCP is the same. For a failure-repair system environment the performance of the proposed system has been evaluated and compared with a hypercube-based system. Simulation results indicate that the proposed system can yield improved performance in the presence of a high number of node failures.     

Achieving Self-Management via Utility Functions

Self-management in accordance with high-level objectives that users can specify is a hallmark of autonomic computing systems. The authors advocate utility functions as a principled, practical, and general way of representing such objectives. In an effort to bring the promise of utility-based frameworks to the marketplace, they describe how they've implemented them in two commercial products so as to achieve efficient resource allocation in a prototype data center. They also address several challenges to commercialization stemming from the need to reconcile the two products' fundamentally different types of objectives     

Token-Passing Nets: Call-by-Need for Free

Recently, encodings in interaction nets of the call-by-name and call-by-value strategies of the λ-calculus have been proposed. The purpose of these encodings was to bridge the gap between interaction nets and traditional abstract machines, which are both used to provide lower-level specifications of strategies of the λ-calculus, but in radically different ways. The strength of these encodings is their simplicity, which comes from the simple idea of introducing an explicit syntactic object to represent the flow of evaluation. In particular, no artifact to represent boxes is needed. However, these encodings purposefully follow as closely as possible the implemented strategies, call-by-name and call-by-value, hence do not benefit from the ability of interaction nets to easily represent sharing. The aim of this note is to show that sharing can indeed be achieved without adding any structure. We thus present the call-by-need strategy following the same philosophy, which is indeed not any more complicated than call-by-name. This continues the task of bridging the gap between interaction nets and abstract machines, thus pushing forward a more uniform framework for implementations of the λ-calculus.