46734639
A Framework of Safe Stabilization
Classical stabilizing systems do not take into consideration safety issues. This paper examines two different safety models for stabilizing distributed systems, and studies the cost of enforcing safety requirements in the context of various kinds of failures.
17834776
Self-stabilizing algorithms for finding centers and medians of trees
Locating a center or a median in a graph is a fundamental graph-theoretic problem. Centers and medians are especially important in distributed systems because they are ideal locations for placing resources that need to be shared among dierent processes in a network. This paper presents simple self-stabilizing algorithms for locating centers and medians of trees. Since these algorithms are self-stabilizing, they can tolerate transient failures. In addition, they can automatically adjust to a dynamically changing tree topology. After the algorithms are presented, their correctness is proven and upper bounds on their time complexity are established. Finally, extensions of our algorithms to trees with arbitrary, positive edge costs are sketched.
43770248
Self-Stabilizing Algorithms for Finding Centers and Medians of Trees
Locating a center or a median in a graph is a fundamental graph-theoretic problem. Centers and medians are especially important in distributed systems because they are ideal locations for placing resources that need to be shared among different processes in a network. This paper presents simple self-stabilizing algorithms for locating centers and medians of trees. Since these algorithms are self-stabilizing, they can tolerate transient failures. In addition, they can automatically adjust to a dynamically changing tree topology. After the algorithms are presented, their correctness is proven and upper bounds on their time complexity are established. Finally, extensions of our algorithms to trees with arbitrary, positive edge costs are sketched.
3086074
An Exercise in Fault-Containment: Self-Stabilizing Leader Election
Self-stabilizing algorithms are designed to guarantee convergence to some desired stable state from arbitrary initial states arising out of an arbitrarily large number of faults. However, in a well-designed system, the simultaneous occurrence of a large number of faults is rare. It is therefore desirable to design algorithms that are not only self-stabilizing, but also have the ability to recover very fast from a bounded number of faults. As an illustration, we present a simple self-stabilizing leader election protocol that recovers in O(1) time from a state with a single transient fault on oriented rings. Only the faulty node and its two neighbors change their state during convergence to a stable state. Thus, the effect of a single fault is tightly contained around the fault. The technique for transforming a self-stabilizing algorithm into its fault-contained version is simple and general, and can be applied to other problems as well that satisfy certain properties.
9120365
A self-stabilizing algorithm for the maximum flow problem
Summary. The maximum flow problem is a fundamental problem in graph theory and combinatorial optimization with a variety of important applications. Known distributed algorithms for this problem do not tolerate faults or adjust to dynamic changes in network topology. This paper presents a distributed self-stabilizing algorithm for the maximum flow problem. Starting from an arbitrary state, the algorithm computes the maximum flow in an acyclic network in finitely many steps. Since the algorithm is self-stabilizing, it is inherently tolerant to transient faults. It can automatically adjust to topology changes and to changes in other parameters of the problem. The paper presents results obtained by extensively experimenting with the algorithm. Two main observations based on these results are (1) the algorithm requires fewer than n2 moves for almost all test cases and (2) the algorithm consistently performs at least as well as a distributed implementation of the well-known Goldberg-Tarjan algorithm for almost all test cases. The paper ends with the conjecture that the algorithm correctly computes a maximum flow even in networks that contain cycles.
11125013
A self-stabilizing algorithm for coloring planar graphs
SummaryThis paper describes an algorithm for coloring the nodes of a planar graph with no more than six colors using a self-stabilizing approach. The first part illustrates the coloring algorithm on a directed acyclic version of the given planar graph. The second part describes a selfstabilizing algorithm for generating the directed acyclic version of the planar graph, and combines the two algorithms into one.
6735470
FraNtiC: A Fractal Geometric Framework for Mesh-Based Wireless Access Networks
The design of the access networks of next generation broadband wireless systems requires special attention in the light of changing network characteristics. In this paper, we present a mesh-based distributed radio access network (RAN) framework for future wireless systems. Using short, high bandwidth optical wireless links to interconnect the various network elements, we identify a generic fractal or self similar structure in the network. A mathematical model for the framework is presented and the benefits of its scale-invariant properties on robustness, reliability and flexibility analyzed. We focus on three design parameters - carrier-class network reliability, network exposure due to failure conditions and system cost. The dynamics of these parameters on our proposed architecture are studied and compared against existing access network topologies like tree/ring and square-grid. The generality and recursive nature of our framework lends itself to be applied in interconnecting various heterogeneous broadband wireless access networks of the future
14429447
iSimBioSys: a discrete event simulation platform for 'in silico' study of biological systems
With the availability of huge databases cataloguing the various molecular "parts" of complex biological systems, researchers from multiple disciplines have focused on developing modeling and simulation tools for studying the variability of cellular behavior at a system level - encompassing the dynamics arising from many species of interacting molecules. In this work, we present a system engineering approach to model biological processes. In this approach, a biological process is modeled as a collection of interacting functions driven in time by a set of discrete events. We focus on the discrete event simulation platform, called "iSimBioSys", which we have developed for studying the dynamics of cellular processes in silico. As a test-bed for studying our approach we model the two component PhoPQ system, responsible for the expression of several virulence genes in Salmonella Typhimurium. We analyzed the effect of extra cellular magnesium on the behavioral dynamics of this pathway using our framework and compared the results with an experimental system. We also analyze the performance of iSimBioSys, based on the model biological system, in terms of system usage and response.
5608135
Low-power weighted pseudo-random BIST using special scan cells
In this paper, a technique for weighted pseudo-random built-in self-test (BIST) of VLSI circuits is proposed, which uses special scan cells and a new weight selection algorithm to achieve low power dissipation. It is based on weighted pseudo-random scan testing in which only 3 weight values are used - 2 fixed values (0 or 1) and 1 random value (0.5). A new weight selection algorithm is used to select a set of weights that achieves high fault coverage while reducing power. The idea is to minimize power by careful selection of the set of scan cells having fixed values (0 or 1) in order to reduce switching activity. To implement this in hardware, a new scan cell design is proposed that can do scan and capture in the normal mode as well as fixed-bit mode. The new scan cell hardware increases the area of a typical circuit by less than 4%, but reduces power by as much as 96%, as indicated in experiments performed on benchmark circuits.
1283500
GaMa: an evolutionary algorithmic approach for the design of mesh-based radio access networks
Wireless mesh based access networks are destined to play a pivotal role in next generation broadband systems. With the proliferation of mesh networks, a key issue for network designers is the design of an optimal mesh topology which minimizes cost while maintaining carrier-class features. In this paper, we formulate the design of an optimal mesh, taking network deployment cost, topological properties and carrier-grade reliability into account. Next, we present a genetic algorithm based algorithm (GaMa) for mesh topology design. We show that GaMa is capable of determining a generic mesh topology with carrier-class network features. The performance of the algorithm is compared with existing mesh topologies and gives improved results without the constraints of maintaining a regular topology
6555367
Selecting Error Correcting Codes to Minimize Power in Memory Checker Circuits
The approach proposed in this paper reduces power consumption in single-error correcting, double error-detecting checker circuits that perform memory ECC. Power is minimized with little or no impact on area and delay, using the degrees of freedom in selecting the parity check matrix of the error correcting code. The non-linear power optimization problem is solved using two methods, genetic algorithms and simulated annealing. Both the methods are applied to two SEC-DED codes: standard Hamming codes and odd-column-weight Hsiao codes. Experiments on actual memory traces of Spec and MediaBench benchmarks indicate that considering power along with area and delay when selecting the parity check matrix can result in power reductions of up to 27% for Hsiao codes and up to 41% for Hamming codes. Experiments are also performed to motivate the choice of parameters of the non-linear optimization algorithms, using sensitivity analysis of the low-power solutions to the choice of the different parameters of each algorithm.