Scheduling for atomic broadcast operation in?heterogeneous networks with one port model

With the emergence of the network technologies, heterogeneous computing has become a wide accept paradigm for distributed and network computing. In this paper, we present different algorithms aiming to efficiently perform atomic one-to-all broadcast in a heterogeneous network with a one port model. The proposed algorithms are divided into graph-based and tree-based ones. In graph-based algorithms, we present Nearest Neighbor First and Maximum Degree Neighbor First schemes. A prescheduling strategy with constructing a message forwarding table for avoiding redundant transmissions is applied as runtime support. In the tree- based approaches, there are five heuristic algorithms: Nearest Neighbor First, Maximum Degree Neighbor First, Maximum Height Subtree First, Maximum Subtree First, and Maximum Weighted Subtree First, proposed based on different network characteristics. To evaluate the performance of the proposed techniques, we have developed a simulator that contains a parametric graph generator for generating network graphs with various characteristics. We have implemented all of the proposed scheduling algorithms on the simulator. The performance results show that the Maximum Weighted Subtree First performs best in high degree heterogeneous environments. On the contrary, with homogeneous-like environments, the graph-based Nearest Neighbor First will be the best choice. In summary, contribution of this study relies on informing significant suggestions for adapting proper broadcasting mechanism in different heterogeneous platforms.     

Approximating the Maximum Agreement Forest on k trees

The Maximum Agreement Forest problem (MAF) asks for the largest common subforest of a set of binary trees. This problem is known to be MAXSNP-complete for instances consisting of 2 trees. We show that it remains MAXSNP-complete for k?2 trees.     

Asymptotically optimal algorithms for approximate agreement

This paper introduces some algorithms to solve crash-failure, failure-by-omission and Byzantine failure versions of the Byzantine Generals or consensus problem, where non-faulty processors need only arrive at values that are close together rather than identical. For each failure model and each value ofS, we give at-resilient algorithm usingS rounds of communication. IfS=t+1, exact agreement is obtained. In the algorithms for the failure-by-omission and Byzantine failure models, each processor attempts to identify the faulty processors and corrects values transmited by them to reduce the amount of disagreement. We also prove lower bounds for each model, to show that each of our algorithms has a convergence rate that is asymptotic to the best possible in that model as the number of processors increases. Alan Fekete was born in Sydney Australia in 1959. He studied Pure Mathematics and Computer Science at the University of Sydney, obtaining a B.Sc.(Hons) in 1982. He then moved to Cambridge, Massachusetts, where he obtained a distributed Ph.D. degree, awarded by Harvard University's Mathematics department for work supervised by Nancy Lynch in M.I.T.'s Laboratory for Computer Science. He spend the year 1987–1988 at M.I.T. as a postdoctoral Research Associate, and is now Lecturer in Computer Science at the University of Sydney. His research concentrates on understanding the modularity in distributed algorithms, especially those used for concurrency control in distributed databases.A preliminary version of this paper has appeared in the Proceedings of the 5th ACM Symposium on Principles of Distributed Computing (August 1986). This work was begun in the Department of Mathematics, Harvard University, and completed at the Laboratory for Computer Science at Massachusetts Institute of Technology. The work was supported in part (through Professor N. Lynch) by the Office of Naval Research under Contract N00014-85-K-0168, by the Office of Army Research under contract DAAG29-84-K-0058, by the National Science Foundation under Grants MCS-8306854, DCR-83-02391, and CCR-8611442, and by the Defense Advanced Research Projects Agency (DARPA) under Contract N00014-83-K-0125     

Resilient-optimal interactive consistency in constant time

For a complete network of n processors within which communication lines are private, we show how to achieve concurrently many Byzantine Agreements within constant expected time both on synchronous and asynchronous networks. As an immediate consequence, this provides a solution to the Interactive Consistency problem. Our algorithms tolerate up to (n-1)/3 faulty processors in both the synchronous and asynchronous cases and are therefore resilient-optimal. In terms of time complexity, our results improve a time bound of (for n concurrent agreements) which is immediately implied by the constant expected time Byzantine Agreement of Feldman and Micali (synchronous systems) and of Canetti and Rabin (asynchronous systems). In terms of resiliency, our results improve the resiliency bound of the constant time, -resilient algorithm of Ben-Or. An immediate application of our protocols is a constant expected time simulation of simultaneous broadcast channels over a network with private lines.Received: April 2001, Accepted: September 2002, Michael Ben-Or: Research supported by Israel Academy of Sciences and by United States - Israel Binational Science Foundation grant BSF-87-00082     

Polynomial-Time Algorithms for the Ordered Maximum Agreement Subtree Problem

For a set of rooted, unordered, distinctly leaf-labeled trees, the NP-hard maximum agreement subtree problem (MAST) asks for a tree contained (up to isomorphism or homeomorphism) in all of the input trees with as many labeled leaves as possible. We study the ordered variants of MAST where the trees are uniformly or non-uniformly ordered. We provide the first known polynomial-time algorithms for the uniformly and non-uniformly ordered homeomorphic variants as well as the uniformly and non-uniformly ordered isomorphic variants of MAST. Our algorithms run in time , , , and , respectively, where n is the number of leaf labels and k is the number of input trees.     

Approximating Satisfiable Satisfiability Problems

We study the approximability of the Maximum Satisfiability Problem (MAX SAT) and of the boolean k -ary Constraint Satisfaction Problem (MAX k CSP) restricted to satisfiable instances. For both problems we improve on the performance ratios of known algorithms for the unrestricted case. Our approximation for satisfiable MAX 3CSP instances is better than any possible approximation for the unrestricted version of the problem (unless P=NP). This result implies that the requirement of perfect completeness weakens the acceptance power of non-adaptive PCP verifiers that read 3 bits. We also present the first non-trivial results about PCP classes defined in terms of free bits that collapse to P. Received August 1997; revised February 1999.     

Algorithms for the maximum satisfiability problem

Old and new algorithms for the Maximum Satisfiability problem are studied. We first summarize the different heuristics previously proposed, i.e., the approximation algorithms of Johnson and of Lieberherr for the general Maximum Satisfiability problem, and the heuristics of Lieberherr and Specker, Poljak and Turzik for the Maximum 2-Satisfiability problem. We then consider two recent local search algorithmic schemes, the Simulated Annealing method of Kirkpatrick, Gelatt and Vecchi and the Steepest Ascent Mildest Descent method, and adapt them to the Maximum Satisfiability problem. The resulting algorithms, which avoid being blocked as soon as a local optimum has been found, are shown empirically to be more efficient than the heuristics previously proposed in the literature.     

New applications of clique separator decomposition for the Maximum Weight Stable Set problem

Graph decompositions such as decomposition by clique separators and modular decomposition are of crucial importance for designing efficient graph algorithms. Clique separators in graphs were used by Tarjan as a divide-and-conquer approach for solving various problems such as the Maximum Weight Stable Set (MWS) problem, Colouring and Minimum Fill-in. The basic tool is a decomposition tree of the graph whose leaves have no clique separator (so-called atoms), and the problem can be solved efficiently on the graph if it is efficiently solvable on its atoms. We give new examples where the clique separator decomposition works well for the MWS problem; our results improve and extend various recently published results. In particular, we describe the atom structure for some new classes of graphs whose atoms are P₅-free (the P₅ is the induced path with five vertices) and obtain new polynomial time results for the MWS problem. The complexity of this problem on the class of P₅-free graphs is still unknown.     

Atomic snapshots using lattice agreement

Summary Thesnapshot object is an important tool for constructing wait-free asynchronous algorithms. We relate the snapshot object to thelattice agreement decision problem. It is shown that any algorithm for solving lattice agreement can be transformed into an implementation of a snapshot object. The overhead cost of this transformation is only a linear number of read and write operations on atomic single-writer multi-reader registers. The transformation uses an unbounded amount of shared memory. We present a deterministic algorithm for lattice agreement that usedO (log² n) operations on 2-processorTest & Set registers, plusO (n) operations on atomic single-writer multi-reader registers. The shared objects are used by the algorithm in adynamic mode, that is, the identity of the processors that access each of the shared objects is determined dynamically during the execution of the algorithm. By a randomized implementation of 2-processorsTest & Set registers from atomic registers, this algorithm implies a randomized algorthm for lattice agreement that uses an expected number ofO (n) operations on (dynamic) atomic single-writer multi-reader registers. Combined with our transformation this yields implementations of atomic snapshots with the same complexity.Cambridge Research Laboratory, Digital Equipment Corporation Hagit Attiya received the B.Sc. degreeiin Mathematics and Computer Science from the Hebrew University of Jerusalem, in 1981, the M.Sc. and Ph.D. degrees in Computer Science from the Hebrew University of Jerusalem, in 1983 and 1987, respectively. She is presently a senior lecturer at the departtment of Computer Science at the Technion, Israel Institute of Technology. Prior to this, she has been a post-doctoral research associate at the Laboratory for Computer Science at M.I.T. Her general research interests are distributed computation and theoretical computer science. More specific interests include fault-tolerance, timing-based and asynchronous algorithms. Maurice Herlihy received the A.B. degree in Mathematics from Harvard University, and the M.S. and the Ph.D. degrees in Computer Science from M.I.T. From 1984 to 1989 he was a faculty member in the Computer Science Department at Carnegie Mellon University in Pittsburgh, PA. In 1989 he joined the research staff at the Digital Equipment Corporation's Cambridge Research Laboratory in Cambridge MA. Since 1994, he has been on the faculty at the Computer Science Department at Brown University. Dr. Herlihy's research interests encompass practical and theoretical aspects of distributed and concurrent computation. Ophir achman received a B.A. in computer science from the Technion, Haifa, Israel in 1989 and M.Sc. in computer science from the Technion, Haifa, Israel, in 1992. He is now studying for a D.Sc. in computer science at the Technion. His currentarea of research is distributed computing, and in particular, asynchronous shared memory systems.This work appeared in preliminary form in proceedings ofthe 6th International Workshop on Distributed Algorithms [12]. This research was partially supported by grant No. 92-0233 from the United States-Israel Binational Science Foundation (BSF), Jerusalem, Technion V.P.R. funds — B. and G. Greenberg Research Fund (Ottawa), and the fund for the promotion of research in the TechnionPart of the work of this author was performed while visiting DEC Cambridge Research Laboratory     

Labeled Search Trees and Amortized Analysis: Improved Upper Bounds for NP-Hard Problems

A sequence of exact algorithms to solve the Vertex Cover and Maximum Independent Set problems have been proposed in the literature. All these algorithms appeal to a very conservative analysis that considers the size of the search tree, under a worst-case scenario, to derive an upper bound on the running time of the algorithm. In this paper we propose a different approach to analyze the size of the search tree. We use amortized analysis to show how simple algorithms, if analyzed properly, may perform much better than the upper bounds on their running time derived by considering only a worst-case scenario. This approach allows us to present a simple algorithm of running time O(1.194^kk² + n) for the parameterized Vertex Cover problem on degree-3 graphs, and a simple algorithm of running time O(1.1255ⁿ) for the Maximum Independent Set problem on degree-3 graphs. Both algorithms improve the previous best algorithms for the problems.     

Data migration on parallel disks: Algorithms and evaluation

Our work is motivated by the problem of managing data on storage devices, typically a set of disks. Such storage servers are used as web servers or multimedia servers, for handling high demand for data. As the system is running, to exhibit good performance, it needs to respond dynamically to changes in demand for different data items. There are known algorithms for mapping demand to a layout. When the demand changes, a new layout can be computed. In this work we study thedata migration problem, which arises when we need to change one layout to another quickly. This problem has been studied earlier where for each disk a new layout has been prescribed. However, to apply these algorithms effectively, we identify another problem that we refer to as the correspondence problem, whose solution has a significant impact on the overall solution for the data migration problem. We study algorithms for the data migration problem in more detail and identify variations of the basic algorithm that seem to improve performance in practice, even though some of the variations have poor worst-case behavior. This research was supported by the NSF Awards CCR-0113192 and EIA-0091474 as well as the Okawa Research Award. This work made use of Integrated Media Systems Center Shared Facilities supported by the National Science Foundation under Cooperative Agreement No. EEC-9529152; any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect those of the National Science Foundation. This work was done while Svetlana Shargorodskaya was at the University of Maryland.     

A simulated annealing‐based maximum‐margin clustering algorithm

Maximum‐margin clustering is an extension of the support vector machine (SVM) to clustering. It partitions a set of unlabeled data into multiple groups by finding hyperplanes with the largest margins. Although existing algorithms have shown promising results, there is no guarantee of convergence of these algorithms to global solutions due to the nonconvexity of the optimization problem. In this paper, we propose a simulated annealing‐based algorithm that is able to mitigate the issue of local minima in the maximum‐margin clustering problem. The novelty of our algorithm is twofold, ie, (i) it comprises a comprehensive cluster modification scheme based on simulated annealing, and (ii) it introduces a new approach based on the combination of k‐means++ and SVM at each step of the annealing process. More precisely, k‐means++ is initially applied to extract subsets of the data points. Then, an unsupervised SVM is applied to improve the clustering results. Experimental results on various benchmark data sets (of up to over a million points) give evidence that the proposed algorithm is more effective at solving the clustering problem than a number of popular clustering algorithms.     

On Lazy Bin Covering and Packing problems

In this paper, we study two interesting variants of the classical bin packing problem, called Lazy Bin Covering (LBC) and Cardinality Constrained Maximum Resource Bin Packing (CCMRBP) problems. For the offline LBC problem, we first prove the approximation ratio of the First-Fit-Decreasing and First-Fit-Increasing algorithms, then present an APTAS. For the online LBC problem, we give a competitive analysis for the algorithms of Next-Fit, Worst-Fit, First-Fit, and a modified HARMONIC_M algorithm. The CCMRBP problem is a generalization of the Maximum Resource Bin Packing (MRBP) problem Boyar et al. (2006) [1]. For this problem, we prove that its offline version is no harder to approximate than the offline MRBP problem.     

Conditions for Set Agreement with an Application to Synchronous Systems

The k-set agreement problem is a generalization of the consensus problem:considering a system made up of n processes where each process proposes a value,each non-faulty process has to decide a value such that a decided value is a proposed value,and no more than k different values are decided.While this problem cannot be solved in an asynchronous system prone to t process crashes when t≥k,it can always be solved in a synchronous system;(?)+1 is then a lower bound on the number of rounds(consecutive commun...     

The incremental agreement

To achieve reliable distributed systems, the fault-tolerance must be studied. One of the most important problems of fault-tolerance issues lies in the Byzantine Agreement (BA) problem. The primary issue surrounding BA is that fault-free processors must obtain common agreement even in cases where faults persist. In this field, the fault diagnosis protocol has been proposed so that each fault-free processor detects/locates a common set of faulty processors. However, in this study, the incremental agreement is invoked to make each processor able to agreement upon executing the fault diagnosis protocol using minimal rounds of message exchange in the presence of dual failure characteristics of processors.     

Efficiently enumerating results of keyword search over data graphs

Various approaches for keyword search in different settings (e.g., relational databases and XML) actually deal with the problem of enumerating K-fragments. For a given set of keywords K, a K-fragment is a subtree T of the given data graph, such that T contains all the keywords of K and no proper subtree of T has this property. There are three types of K-fragments: directed, undirected and strong. This paper describes efficient algorithms for enumerating K-fragments. Specifically, for all three types of K-fragments, algorithms are given for enumerating all K-fragments with polynomial delay and polynomial space. It is shown how these algorithms can be enhanced to enumerate K-fragments in a heuristic order. For directed K-fragments and acyclic data graphs, an algorithm is given for enumerating with polynomial delay in the order of increasing weight (i.e., the ranked order), assuming that K is of a fixed size.     

A new polynomial-time algorithm for the maximum weighted (χ(G) — 1)-coloring problem in comparability graphs

For a weighted graph G = (V, E), the maximum weightedk-coloring problem is to color a set of vertices of maximum weight usingk colors. In this paper we are interested in solving this problem in comparability graphs. For these graphs, as shown by Cameron, the problem can be translated into a dual transportation problem. Let (G) denote the chromatic number of a comparability graphG. We prove that whenk is equal to (G) — 1, the problem can be solved more efficiently by finding a maximum weighted stable set in a bipartite graph. Maximum matching algorithms can be used in the unweighted case.This work was supported by an NSERC International Fellowship to the University of Montréal, and by NSERC #OGP0105384.     

A self-adjusting algorithm for byzantine agreement

Summary Byzantine Agreement is important both in the theory and practice of distributed computing. However, protocols to reach Byzantine Agreement are usually expensive both in the time required as well as in the number of messages exchanged. In this paper, we present a self-adjusting approach to the problem. The Mostly Byzantine Agreement is proposed as a more restrictive agreement problem that requires that in the consecutive attempts to reach agreement, the number of disagreements (i.e., failures to reach Byzantine Agreement) is finite. Fort faulty processes, we give an algorithm that has at mostt disagreements for 4t or more processes. Another algorithm is given forn3t+1 processes with the number of disagreements belowt ²/2. Both algorithms useO(n ³) message bits for binary value agreement. Yi Zhao is currently working on his Ph.D. degree in Computer Science at University of Houston. His research interests include fault tolerance, distributed computing, parallel computation and neural networks. He obtained his M.S. from University of Houston in 1988 and B.S. from Beijing University of Aeronautics and Astronautics in 1984, both in computer science. Farokh B. Bastani received the B. Tech. degree in electrical engineering from the Indian Institute of Technology, Bombay, India, and the M.S. and Ph.D. degrees in electrical engineering and computer science from the University of California, Berkeley. He joined the University of Houston in 1980, where he is currently an Associate Professor of Computer Science. His research interests include software design and validation techniques, distributed systems, and fault-tolerant systems. He is a member of the ACM and the IEEE and is on the editorial board of theIEEE Transactions on Software Engineering.     

基于Modbus协议的锅炉监控系统设计

所研究的问题是Modbus协议如何在锅炉监控系统中得到有效的实现。首先对Modbus协议的技术要点和具体规定作了详细的阐述,然后通过基于Modbus协议的锅炉监控系统实例,说明了整个监控系统的硬件构成,监控软件的相关设计和开发,以及Modbus协议的实现。目前,基于Modbus协议锅炉监控系统已经开发完毕,在实际应用中得到了良好的应用。     

Image Restoration in Optical-Acoustic Tomography

We consider the optical-acoustic tomography problem. In the general case, the problem is to reconstruct a real-valued function with a compact support in the n-dimensional Euclidean space via its spherical integrals, i.e., integrals over all (n – 1)-dimensional spheres centered at points on some (n – 1)-dimensional hypersurface. We deal with the cases n = 2 and n = 3, which are of the most practical interest from the standpoint of possible medical applications. We suggest a new effective method of reconstruction, develop restoration algorithms, and investigate the quality of the algorithms for these cases. The main result of the paper is construction of explicit approximate reconstruction formulas; from the mathematical standpoint, these formulas give the parametrix for the optical-acoustic tomography problem. The formulas constructed is a background for the restoration algorithms. We performed mathematical experiments to investigate the quality of the restoration algorithms using the generally accepted tomography quality criteria. The results obtain lead to the general conclusion: the quality of the restoration algorithms developed for optical-acoustic tomography is only slightly lower then the quality of the convolution and back projection algorithm used in Radon tomography, which is a standard de facto.