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.
34174199
Selfish Stabilization
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.
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.
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.
1421735
Scalable Self-Stabilization
This paper presents a methodology for a synchronous non-reactive distributed system on a tree topology to stabilize from a k-faulty configuration in a time independent of the size n of the system. In the proposed methodology, processes first measure and compare the sizes of the faulty regions, and then use this information to schedule actions in such a way that the size of the faulty regions progressively shrink, until they completely disappear. We demonstrate that when k processes fail, the stabilization time is O(k2). Apart from its applicability to a wide class of problems, the proposed method achieves scalability with a low space complexity of O(�.(�.k+log2n)) per process, where � is the maximum degree of a node.
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.
29763170
Fractal image compression: a randomized approach
The fractal image compression is inherently time intensive and thus there is a growing need to increase its speedup. This paper presents a fast encoding scheme where the domain blocks are searched randomly for every range block. An analysis of the basic fractal image compression method has been carried out and on the basis of the analysis a method for image characterization has been proposed. Then a detailed theoretical analysis of this randomized fractal compression scheme has been presented and the results are validated with the experimental ones. The random approach has been found to be quite efficient giving considerable increase in speed-up compared to several other approaches.
972043
Stochastic Modeling of Cytoplasmic Reactions in Complex Biological Systems
The use of “in silico” stochastic event based modeling can identify the dynamic interactions of different processes in a complex biological system. This requires the computation of the time taken by different events in the system based on their biological functions. One such important event is the reactions between the molecules inside the cytoplasm of a cell. We present a mathematical formulation for the estimation of the reaction time between two molecules within a cell based on the system state. We derive expressions for the average and second moment of the time for reaction to be used by our stochastic event-based simulation. Unlike rate equations, the proposed model does not require the assumption of concentration stability for multiple molecule reactions.
1980879
Quantitative Quality Control in Microarray Experiments and the Application in Data Filtering, Normalization and False Positive Rate Prediction
Data preprocessing including proper normalization and adequate quality control before complex data mining is crucial for studies using the cDNA microarray technology. We have developed a simple procedure that integrates data filtering and normalization with quantitative quality control of microarray experiments. Previously we have shown that data variability in a microarray experiment can be very well captured by a quality score q(com) that is defined for every spot, and the ratio distribution depends on q(com). Utilizing this knowledge, our data-filtering scheme allows the investigator to decide on the filtering stringency according to desired data variability, and our normalization procedure corrects the q(com)-dependent dye biases in terms of both the location and the spread of the ratio distribution. In addition, we propose a statistical model for false positive rate determination based on the design and the quality of a microarray experiment. The model predicts that a lower limit of 0.5 for the replicate concordance rate is needed in order to be certain of true positives. Our work demonstrates the importance and advantages of having a quantitative quality control scheme for microarrays.
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.