1,929 research outputs found
Quantifying fault recovery in multiprocessor systems
Various aspects of reliable computing are formalized and quantified with emphasis on efficient fault recovery. The mathematical model which proves to be most appropriate is provided by the theory of graphs. New measures for fault recovery are developed and the value of elements of the fault recovery vector are observed to depend not only on the computation graph H and the architecture graph G, but also on the specific location of a fault. In the examples, a hypercube is chosen as a representative of parallel computer architecture, and a pipeline as a typical configuration for program execution. Dependability qualities of such a system is defined with or without a fault. These qualities are determined by the resiliency triple defined by three parameters: multiplicity, robustness, and configurability. Parameters for measuring the recovery effectiveness are also introduced in terms of distance, time, and the number of new, used, and moved nodes and edges
On the Equivalence of Observation Structures for Petri Net Generators
Observation structures considered for Petri net generators usually assume that the firing of transitions may be observed through a static mask and that the marking of some places may be measurable. These observation structures, however, are rather limited, namely they do not cover all cases of practical interest where complex observations are possible. We consider in this paper more general ones, by correspondingly defining two new classes of Petri net generators: labeled Petri nets with outputs (LPNOs) and adaptive labeled Petri nets (ALPNs). To compare the modeling power of different Petri net generators, the notion of observation equivalence is proposed. ALPNs are shown to be the class of bounded generators possessing the highest modeling power. Looking for bridges between the different formalisms, we first present a general procedure to convert a bounded LPNO into an equivalent ALPN or even into an equivalent labeled Petri net (if any exists). Finally, we discuss the possibility of converting an unbounded LPNO into an equivalent ALPN
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Artificial Immune Systems - Models, algorithms and applications
Copyright © 2010 Academic Research Publishing Agency.This article has been made available through the Brunel Open Access Publishing Fund.Artificial Immune Systems (AIS) are computational paradigms that belong to the computational intelligence family and are inspired by the biological immune system. During the past decade, they have attracted a lot of interest from researchers aiming to develop immune-based models and techniques to solve complex computational or engineering problems. This work presents a survey of existing AIS models and algorithms with a focus on the last five years.This article is available through the Brunel Open Access Publishing Fun
Randomized Algorithms for Determining the Majority on Graphs
Every node of an undirected connected graph is colored white or black. Adjacent nodes can be compared and the outcome of each comparison is either 0 (same color) or 1 (different colors). The aim is to discover a node of the majority color, or to conclude that there is the same number of black and white nodes. We consider randomized algorithms for this task and establish upper and lower bounds on their expected running time. Our main contribution are lower bounds showing that some simple and natural algorithms for this problem cannot be improved in general
Testing Layered Interconnection Networks
We present an approach for fault detection in layered interconnection networks (LINs). An LIN is a generalized multistage interconnection network commonly used in reconfigurable systems; the nets (links) are arranged in sets (referred to as layers) of different size. Switching elements (made of simple switches such as transmission-gate-like devices) are arranged in a cascade to connect pairs of layers. The switching elements of an LIN have the same number of switches, but the switching patterns may not be uniform. A comprehensive fault model for the nets and switches is assumed at physical and behavioral levels. Testing requires configuring the LIN multiple times. Using a graph approach, it is proven that the minimal set of configurations corresponds to the node disjoint path sets. The proposed approach is based on two novel results in the execution of the network flow algorithm to find node disjoint path sets, while retaining optimality in the number of configurations. These objectives are accomplished by finding a feasible flow such that the maximal degree can be iteratively decreased, while guaranteeing the existence of an appropriate circulation. Net adjacencies are also tested for possible bridge faults (shorts). To account for 100 percent fault coverage of bridge faults a postprocessing algorithm may be required; bounds on its complexity are provided. The execution complexity of the proposed approach (inclusive of test vector generation and post-processing) is O(N4WL), where N is the total number of nets, W is the number of switches per switching element, and L is the number of layers. Extensive simulation results are provided
A novel evolutionary formulation of the maximum independent set problem
We introduce a novel evolutionary formulation of the problem of finding a
maximum independent set of a graph. The new formulation is based on the
relationship that exists between a graph's independence number and its acyclic
orientations. It views such orientations as individuals and evolves them with
the aid of evolutionary operators that are very heavily based on the structure
of the graph and its acyclic orientations. The resulting heuristic has been
tested on some of the Second DIMACS Implementation Challenge benchmark graphs,
and has been found to be competitive when compared to several of the other
heuristics that have also been tested on those graphs
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