Adaptive solutions to the mutual exclusion problem

Summary Algorithms for mutual exclusion that adapt to the current degree of contention are developed. Afilter and a leader election algorithm form the basic building blocks. The algorithms achieve system response times that are independent of the total number of processes and governed instead by the current degree of contention. The final algorithm achieves a constant amortized system response time. Manhoi Choy was born in 1967 in Hong Kong. He received his B.Sc. in Electrical and Electronic Engineerings from the University of Hong Kong in 1989, and his M.Sc. in Computer Science from the University of California at Santa Barbara in 1991. Currently, he is working on his Ph.D. in Computer Science at the University of California at Santa Barbara. His research interests are in the areas of parallel and distributed systems, and distributed algorithms. Ambuj K. Singh is an Assistant Professor in the Department of Computer Science at the University of California, Santa Barbara. He received a Ph.D. in Computer Science from the University of Texas at Austin in 1989, an M.S. in Computer Science from Iowa State University in 1984, and a B.Tech. from the Indian Institute of Technology at Kharagpur in 1982. His research interests are in the areas of adaptive resource allocation, concurrent program development, and distributed shared memory.A preliminary version of the paper appeared in the 12th Annual ACM Symposium on Principles of Distributed ComputingWork supported in part by NSF grants CCR-9008628 and CCR-9223094     

Necessary and sufficient conditions for broadcast consensus protocols

Summary We consider consensus protocols in asynchronous distributed systems that are based on broadcast communication. We show that a necessary and sufficient condition for the existence of a deterministic consensus protocol is delivery of each broadcast message to at least (n+k+1)/2 processes in ann-process system subject tok crash failures with either eventual fair broadcasting or eventual full broadcasting. The broadcast model captures the idea of a broadcast communication medium, such as the Ethernet, in which messages, if delivered, are delivered immediately and in order but not necessarily to all processes. Louise E. Moser received the Ph.D. degree in mathematics from the University of Wisconsin, Madison, in 1970. From 1970 to 1987 she was a professor of mathematics and computer science at California State University, Hayward. In 1987 she moved to the University of California, Santa Barbara, where is currently on the faculty of the Department of Electrical and Computer Engineering. Her current research interests include parallel and distributed systems, network architectures and communication protocols, and formal methods in software engineering. P.M. Melliar-Smith received the Ph.D. degree in computer science from the University of Cambridge, Cambridge, England, in 1987. He was a senior research scientist and program director at SRI International in Menlo Park (1976–1987), senior research associate at the University of Newcastle Upon Tyne (1973–1976), and principal designer for GEC Computers Ltd. in England (1964–1973). He is currently a professor in the Department of Electrical and Computer Engineering at the University of California, Santa Barbara. His research interests include fault-tolerant distributed systems, high-speed communication networks and protocols, and formal specification and verification. Vivek Agrawala received the B.Tech. degree in chemical engineering in 1984 and the M. Tech. degree in computer technology in 1986, both from the Indian Institute of Technology, Delhi, and a Ph.D. in computer science in 1991 from the University of California, Santa Barbara. Since then he has been a Research Scientist at Siemens Corporate Research, Princeton, New Jersey. His major research interests are distributed algorithms, software design methods, and distributed systems.This research was supported by the National Science Foundation, Grant Numbers CCR-8908515 and NCR-9016361. V. Agrawala's current address is Siemens Corporate Research, 755 College Road East, Princeton, NJ 08540, USA     

A fast,scalable mutual exclusion algorithm

Summary This paper is concerned with synchornization under read/write atomicity in shared memory multi-processors. We present a new algorithm forN-process mutual exclusion that requires only read and write operations and that hasO(logN) time complexity, where time is measured by counting remote memory references. The time complexity of this algorithm is better than that of all prior solutions to the mutual exclusion problem that are based upon atomic read and write instructions; in fact, the time complexity of most prior solutions is unbounded. Performance studies are presented that show that our mutual exclusion algorithm exhibits scalable performance under heavy contention. In fact, its performance rivals that of the fastest queue-based spin locks based on strong primitives such as compare-and-swap and fetch-and-add. We also present a modified version of our algorithm that generates onlyO(1) memory references in the absence of contention. Jae-Heon Yang received the B.S. and M. S. degrees in Computer Engineering from Seoul National University in 1985 and 1987, respectively, and the Ph.D. degree in Computer Science from the University of Maryland at College Park in 1994. Since June 1994, he has been an Assistant Professor of Computer Science at Mills College in Oakland, California. From 1987 to 1989, he was a junior researcher at the Korea Telecommunication Authority Research Center. His research interests include distributed computing and operating systems. James H. Anderson received the M. S. degree in Computer Science from Michigan State University in 1982, the M.S. degree in Computer Science from Purdue University in 1983, and the Ph.D. degree in Computer Sciences from the University of Texas at Austin in 1990. Since August 1993, he has been an Assistant Professor of Computer Science at the University of North Carolina at Chapel Hill. Prior to joining the University of North Carolina, he was an Assistant Professor of Computer Science for three years at the University of Maryland at College Park Professor Anderson's main research interests are within the area of coneurrent and distributed computing. His current interests include wait-free algorithms, scalabde synchronization mechanisms for shared-memory systems, and object-sharing strategies for hard real-time applications.Preliminary version was presented at the Twelfth Annual ACM Symposium on Principles of Distributed Computing Ithaca, New York, August 1993 [15]. Work supported, in part, by NSF Contracts CCR-9109497 and CCR-9216421 and by the Center for Excellence in Space Data and Information Sciences (CESDIS)     

One-bit algorithms

Many algorithms in distributed systems assume that the size of a single message depends on the number of processors. In this paper, we assume in contrast that messages consist of a single bit. Our main goal is to explore how the one-bit translation of unbounded message algorithms can be sped up by pipelining. We consider two problems. The first is routing between two processors in an arbitrary network and in some special networks (ring, grid, hypercube). The second problem is coloring a synchronous ring with three colors. The routing problem is a very basic subroutine in many distributed algorithms; the three coloring problem demonstrates that pipelining is not always useful. Amotz Bar-Noy received his B.Sc. degree in Mathematics and Computer Science in 1981, and his Ph.D. degree in Computer Science in 1987, both from the Hebrew University of Jerusalem, Israel. Between 1987 and 1989 he was a post-doctoral fellow in the Department of Computer Science at Stanford University. He is currently a visiting scientist at the IBM Thomas J. Watson Research Center. His current research interests include the theoretical aspects of distributed and parallel computing, computational complexity and combinatorial optimization. Joseph (Seffi) Naor received his B.A. degree in Computer Science in 1981 from the Technion, Israel Institute of Technology. He received his M.Sc. in 1983 and Ph.D. in 1987 in Computer Science, both from the Hebrew University of Jerusalem, Israel. Between 1987 and 1988 he was a post-doctoral fellow at the University of Southern California, Los Angeles, CA. Since 1988 he has been a post-doctoral fellow in the Department of Computer Science at Stanford University. His research interests include combinatorial optimization, randomized algorithms, computational complexity and the theoretical aspects of parallel and distributed computing. Moni Naor received his B.A. in Computer Science from the Technion, Israel Institute of Technology, in 1985, and his Ph.D. in Computer Science from the University of California at Berkeley in 1989. He is currently a visiting scientist at the IBM Almaden Research Center. His research interests include computational complexity, data structures, cryptography, and parallel and distributed computation.Supported in part by a Weizmann fellowship and by contract ONR N00014-85-C-0731Supported by contract ONR N00014-88-K-0166 and by a grant from Stanford's Center for Integrated Systems. This work was done while the author was a post-doctoral fellow at the University of Southern California, Los Angeles, CAThis work was done while the author was with the Computer Science Division, University of California at Berkeley, and Supported by NSF grant DCR 85-13926     

Adaptive component composition and load balancing for distributed stream processing applications

Providing real-time and QoS support to stream processing applications running on top of large-scale overlays is challenging due to the inherent heterogeneity and resource limitations of the nodes and the multiple QoS demands of the applications that must concurrently be met. In this paper we propose an integrated adaptive component composition and load balancing mechanism that (1) allows the composition of distributed stream processing applications on the fly across a large-scale system, while satisfying their QoS demands and distributing the load fairly on the resources, and (2) adapts dynamically to changes in the resource utilization or the QoS requirements of the applications. Our extensive experimental results using both simulations as well as a prototype deployment illustrate the efficiency, performance and scalability of our approach.

The distributed simulation of clustered processes

An efficient method for use in the discrete-event distributed simulation of large systems is presented. A conservative distributed simulation as well as the mapping of several simulated processes onto the same processor is assumed. The method consits of two algorithms: an algorithm for computing the lower bounds on times of future events, and a distributed algorithm that resolves deadlocks. The performance of the method is demonstrated by comparing it to the Chandy-Misra-Bryant simulation and by presenting some experimental results. Bojan Groelj received his B.EE. and M.EE. degrees from the University of Ljubljana, Slovenia (Yugoslavia), in 1978 and 1981, respectively. His Ph.D. degree in Computer Science is from McGill University, Montreal, Canada (1988). In 1988, he joined the Center for Advanced Computer Studies, University of Southwestern Louisiana, where he is currently an Assistant Professor. His current research interests include distributed simulation, distributed computing in general, program proving, and sorting. For the last two years, the author has been proving a distributed deadlock-detection algorithm using the UNITY approach. Carl Tropper is an Associate Professor of Computer Science at McGill University, Montreal, Canada. His major area of research at present is distributed discrete-event simulation. He has also worked in the area of performance evaluation of computer networks. Formerly, he was with BBN Communications Corporation, Cambridge, Mass., where he contributed to the design and evaluation of various widearea network protocols.This research was supported in part by the National Science Foundation under Grant CCR-8909098. An extended version of this work will appear in Progress in Simulation, vol. II, Ablex Publishing Corporation     

Efficient algorithms for optimistic crash recovery

Summary Recovery from transient processor failures can be achieved by using optimistic message logging and checkpointing. The faulty processorsroll back, and some/all of the non-faulty processors also may have to roll back. This paper formulates the rollback problem as a closure problem. A centralized closure algorithm is presented together with two efficient distributed implementations. Several related problems are also considered and distributed algorithms are presented for solving them. S. Venkatesan received the B. Tech. and M. Tech degrees from the Indian Institute of Technology, Madras in 1981 and 1983, respectively and the M.S. and Ph.D. degrees in Computer Science from the University of Pittsburgh in 1985 and 1988. He joined the University of Texas at Dallas in January 1989, where he is currently an Assistant Professor of Computer Science. His research interests are in fault-tolerant distributed systems, distributed algorithms, testing and debugging distributed programs, fault-tolerant telecommunication networks, and mobile computing. Tony Tony-Ying Juang is an Associate Professor of Computer Science at the Chung-Hwa Polytechnic Institute. He received the B.S. degree in Naval Architecture from the National Taiwan University in 1983 and his M.S. and Ph.D. degrees in Computer Science from the University of Texas at Dallas in 1989 and 1992, respectively. His research interests include distributed algorithms, fault-tolerant distributed computing, distributed operating systems and computer communications.This research was supported in part by NSF under Grant No. CCR-9110177 and by the Texas Advanced Technology Program under Grant No. 9741-036     

On optimizing the satisfiability (SAT) problem

1IntroductionThesatisfiability(SAT)problemistodeterminewhetherthereexistsanassignmentofvaluesin{0,1}toasetofBooleanvariables{x1,xm}thatmakesaconjunctivenormalform(CNF)formulatrue.ThesatisfiabilityproblemofaCNFformulawithatmostlliteralsineachclauseiscalledthel-SATproblem.Theoretically,for>3,theSATproblemisawell-knownNP-completeproblem.Andthus,thereexistsnopolynomialtimealgorithmfortheSATproblemontheassumptionthatPNP.Ontheotherhand,theSATproblemisfundamentalinsolvingmanypracticalprob…     

A self-stabilizing algorithm for coloring planar graphs

Summary This 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. Sukumar Ghosh received his Ph.D. degree in Computer Science from Calcutta University in 1971. From 1969 to 1984, he taught at Jadavpur University, Calcutta. During 1976–77, he was a Fellow of the Alexander von Humboldt Foundation at the University of Dortmund, Germany. Since 1984, he is with the Department of Computer Science of the University of Iowa. His current research interests are in the areas of Distributed Systems, Petri Nets and Self-Stabilizating Systems. Mehmet Hakan Karaata received the Sc. B. degree in Computer Science and Engineering from Hacettepe University in Turkey in 1987, and the M.S. degree in Computer Science from the University of Iowa in 1990. He is currently studying towards his Ph.D. at the same university. His research interests are in the areas of Distributed Systems, Self-Stabilizing Systems and Database Systems.This research was supported in part by the National Science Foundation under grant CCR-9109078, and the Old Gold Summer Fellowship of the University of Iowa. An abstract of this paper was presented at the 29th Allerton Conference on Control, Communication & Computing in October 1991.     

Using mappings to prove timing properties

Summary A new technique for proving timing properties for timing-based algorithms is described; it is an extension of the mapping techniques previously used in proofs of safety properties for asynchronous concurrent systems. The key to the method is a way of representing a system with timing constraints as an automaton whose state includes predictive timing information. Timing assumptions and timing requirements for the system are both represented in this way. A multi-valued mapping from the assumptions automaton to the requirements automaton is then used to show that the given system satisfies the requirements. One type of mapping is based on a collection of progress functions providing measures of progress toward timing goals. The technique is illustrated with two examples, a simple resource manager and a two-process race system. Nancy A. Lynch received the B.S. degree in mathematics from Brooklyn College, Brooklyn, NY, in 1968, and the Ph.D. degree in mathematics from the Massachusetts Institute of Technology, Cambridge, MA, in 1972. She is presently a professor of computer science and electrical engineering at Massachusetts Institute of Technology. She has also been on the computer science faculty at Georgia Institute of Technology and on the mathematics faculty at Tufts University and the University of Southern California. Her research interests are in distributed and real-time computing and theoretical computer science. In particular, she has worked on formal models and verification methods, on algorithm design and analysis, and on impossibility results. She also likes to hike and ski. Hagit Attiya received the B.Sc. degree in 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 department 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.This work was supported by ONR contracts N00014-85-K-0168 and N00014-91-J-1046, by NSF grants CCR-8611442 and CCR-8915206, and by DARPA contracts N00014-87-K-0825 and N00014-89-J-1988     

Shape Estimation from Support and Diameter Functions

We address the problem of reconstructing a planar shape from a finite number of noisy measurements of its support function or its diameter function. New linear and non-linear algorithms are proposed, based on the parametrization of the shape by its Extended Gaussian Image. This parametrization facilitates a systematic statistical analysis of the problem via the Cramér-Rao lower bound (CRLB), which provides a fundamental lower bound on the performance of estimation algorithms. Using CRLB, we also generate confidence regions which conveniently display the effect of parameters like eccentricity, scale, noise, and measurement direction set, on the quality of the estimated shapes, as well as allow a performance analysis of the algorithms. Supported in part by U.S. National Science Foundation grants CCR-9984246 and DMS-0203527. Amyn Poonawala received the B.E. degree from the University of Mumbai, India, in 2001, and the M.S. degree from the University of California, Santa Cruz (UCSC), in 2004, both in computer engineering. He is currently pursuing the Ph.D. degree in computer engineering at UCSC. His technical interests include statistical signal and image processing and inverse problems in microlithography. Peyman Milanfar received the B.S. degree in electrical engineering/mathematics from the University of California, Berkeley, in 1988, and the S.M., E.E., and Ph.D. degrees in electrical engineering from the Massachusetts Institute of Technology, in 1990, 1992, and 1993, respectively. Until 1999, he was a Senior Research Engineer at SRI International, Menlo Park, CA. He is currently Associate Professor of Electrical Engineering at the University of California, Santa Cruz. He was a Consulting Assistant Professor of computer science at Stanford University from 1998-2000, and a visiting Associate Professor there in 2002. His technical interests are in statistical signal and image processing, and inverse problems. He won a National Science Foundation CAREER award in 2000, was associate editor for the IEEE Signal Processing Letters from 1998 to 2001, and is a Senior member of the IEEE. Richard Gardner holds B.Sc. and Ph.D. degrees in mathematics from University College London and was awarded a D.Sc. degree from the University of London in 1988 for contributions to measure theory and convex geometry. He has held positions at universities and research institutions in several countries and has been Professor of Mathematics at Western Washington University since 1991. He founded geometric tomography, an area of geometric inverse problems involving data concerning sections by and projections on lines or planes, and published a book on the subject in 1995.     

Binary-coding-based ant colony optimization and its convergence

Ant colony optimization (ACO for short) is a meta-heuristics for hard combinatorial optimization problems. It is a population-based approach that uses exploitation of positive feedback as well as greedy search. In this paper, genetic algorithm's (GA for short) ideas are introduced into ACO to present a new binary-coding based ant colony optimization. Compared with the typical ACO, the algorithm is intended to replace the problem's parameter-space with coding-space, which links ACO with GA so that the fruits of GA can be applied to ACO directly. Furthermore, it can not only solve general combinatorial optimization problems, but also other problems such as function optimization. Based on the algorithm, it is proved that if the pheromone remainder factor ρ is under the condition of ρ≥1, the algorithm can promise to converge at the optimal, whereas if 0<ρ<1, it does not. This work is supported by the Science Foundation of Shanghai Municipal Commission of Science and Technology under Grant No.00JC14052. Tian-Ming Bu received the M.S. degree in computer software and theory from Shanghai University, China, in 2003. And now he is a Ph.D. candidate of Fudan University in the same area of theory computer science. His research interests include algorithms, especially, heuristic algorithms and heuristic algorithms and parallel algorithms, quantum computing and computational complexity. Song-Nian Yu received the B.S. degree in mathematics from Xi'an University of Science and Technology, Xi'an, China, in 1981, the Ph.D. degree under Prof. L. Lovasz's guidance and from Lorand University, Budapest, Hungary, in 1990. Dr. Yu is a professor in the School of Computer Engineering and Science at Shanghai University. He was a visiting professor as a faculty member in Department of Computer Science at Nelson College of Engineering, West Virginia University, from 1998 to 1999. His current research interests include parallel algorithms' design and analyses, graph theory, combinatorial optimization, wavelet analyses, and grid computing. Hui-Wei Guan received the B.S. degree in electronic engineering from Shanghai University, China, in 1982, the M.S. degree in computer engineering from China Textile University, China, in 1989, and the Ph.D. degree in computer science and engineering from Shanghai Jiaotong University, China, in 1993. He is an associate professor in the Department of Computer Science at North Shore Community College, USA. He is a member of IEEE. His current research interests are parallel and distributed computing, high performance computing, distributed database, massively parallel processing system, and intelligent control.     

Fast and simple distributed consensus

Summary The problem of fault-tolerant agreement is fundamental to distributed computing. When agreement is to be reached in spite of arbitrary behavior by faulty processors, this problem is calledDistributed Consensus. By requiring that the number of faulty processors be , wheren is the number of processors in the system, we are able to derive two new protocols forDistributed Consensus. Both are simple and use messages that are only one bit in length, and both provide forearly stopping: the fewer failures there are, the fewer rounds of communication are required. One protocol is optimal with respect to the number of rounds of communication required, and the other is asymptotically optimal with respect to the total number of message bits exchanged. James E. Burns received the B.S. degree in mathematics from the California Institute of Technology, the M.B.I.S. degree from Georgia State University, and the M.S. and Ph.D. degrees in information and computer science from the Georgia Institute of Technology. He served on the faculty of Computer Science at Indiana University and the College of Computing at the Georgia Institute of Technology before joining Bellcore in 1993. He is currently a Member of Technical Staff in the Network Control Research Department, where he is studying the telephone control network with special interest in behavior when faults occur. He also has research interests in theoretical issues of distributed and parallel computing, especially relating to problems of synchronization and fault tolerance. Gil Neiger was born on February 19, 1957 in New York, New York. In June 1979, he received an A.B. in Mathematics and Psycholinguistics from Brown University in Proidence, Rhode Island. In February 1985, he spent two weeks picking cotton in Nicaragua in a brigade of international volunteers. In January 1986, he received an M.S. in Computer Science from Cornell University in Ithaca, New York and, in August 1988, he received a Ph.D. in Computer Science, also from Cornell University. On August 20, 1988, Dr. Neiger married Hilary Lombard in Lansing, New York. Since August 1988, he has been an Assistant Professor in the College of Computing (formely School of Information and Computer Science) at the Georgia Institute of Technology in Atlanta, Georgia. Dr. Neiger is a member of the editorial board of theChicago Journal of Theoretical Computer Science and theJournal of Parallel and Distributed Computing.This author was supported in part by the National Science Foundation under grants CCR-8909663, CCR-9106627, and CCR-9301454.     

Distributed election in complete networks

An improved version of Afek and Gafni's synchronous algorithm for distributed election in complete networks is given and anO(n) expected message complexity is shown. M.Y. Chan received her Ph.D. in 1988 from the University of Hong Kong, and her M.S. and B.A. degrees in computer science from the University of California, San Diego in 1980 and 1981, respectively. She is currently an Assistant Professor at the University of Texas at Dallas. Francis Y.L. Chin (S71-M76-SM85) received the B.Sc. degree in engineering science from the University of Toronto, Toronto, Canada, in 1972, and the M.S., M.A., and Ph.D. degrees in electrical engineering and computer science from Princeton University, New Jersey, in 1974, 1975, and 1976, respectively. Since 1975, he has taught at the University of Maryland, Baltimore Country, University of California, San Diego, University of Alberta, and Chinese University of Hong Kong. He is currently Head of the Department of Computer Science, University of Hong Kong. He has served as a program co-chairman of the 1988 International Conference on Computer Processing of Chinese and Oriental Languages (Toronto) and the International Computer Science Conference '88 (Hong Kong). His current research interests include algorithm design and analysis, parallel and distributed computing.     

Fault-tolerant atomic computations in an object-based distributed system

A distributed system can support fault-tolerant applications by replicating data and computation at nodes that have independent failure modes. We present a scheme called parallel execution threads (PET) which can be used to implement fault-tolerant computations in an object-based distributed system. In a system that replicates objects, the PET scheme can be used to replicate a computation by creating a number of parallel threads which execute with different replicas of the invoked objects. A computation can be completed successfully if at least one thread does not encounter any failed nodes and its completion preserves the consistency of the objects. The PET scheme can tolerate failures that occur during the execution of the computation as long as all threads are not affected by the failures. We present the algorithms required to implement the PET scheme and also address some performance issues. Mustaque Ahamad received his B.E. (Hons.) degree in Electrical Engineering from the Birla Institute of Technology and Science, Pilani, India. He obtained his M.S. and Ph.D. degrees in Computer Science from the State University of New York at Stony Brook in 1983 and 1985 respectively. Since September 1985, he is an Assistant Professor in the School of Information and Computer Science at the Georgia Institute of Technology, Atlanta. His research interests include distributed operating systems, distributed algorithms, faulttolerant systems and performance evaluation. Partha Dasgupta is an Assistant Professor at Georgia Tech since 1984. He has a Ph.D. in Computer Science from the State University of New York at Stony Brook. He is the technical project director of the Clouds distributed operating systems project, as well as a coprincipal investigator of Georgia Tech's NSF-CER award. His research interests include building distributed operating systems, distributed algorithms, fault-tolerant systems and distributed programming support. Richard J. LeBlanc, Jr. received the B.S. degree in physics from Louisiana State University in 1972 and the M.S. and Ph.D. degrees in computer sciences from the University of Wisconsin-Madison in 1974 and 1977, respectively. He is currently a Professor in the School of Information and Computer Science of the Georgia Institute of Technology. His research interests include programming language design and implementation, programming environments, and software engineering. Dr. LeBlanc's current research work involves application of these interests in distributed processing systems. As co-director of the Clouds Project, he is studying language concepts and software engineering methodology for utilizing a highly reliable, object-based distributed system. He is also interested in specification-based software development methodologies and tools. Dr. LeBlanc is a member of the Association for Computing Machinery, the IEEE Computer Society and Sigma Xi.This work was supported in part by NSF grants CCR-8619886 and CCR-8806358, and RADC contract number F30602-86-C-0032     

Efficient emulation of single-hop radio network with collision detection on multi-hop radio network with no collision detection

Summary This paper presents an efficient randomized emulation ofsingle-hop radio networkwith collision detection onmulti-hop radio networkwithout collision detection. Each step of the single-hop network is emulated by rounds of the multi-hop network and succeeds with probability 1–. (n is the number of processors,D the diameter and the maximum degree). It is shown how to emulate any polynomial algorithm such that the probability of failure remains . A consequence of the emulation is an efficient randomized algorithm for choosing a leader in a multi-hop network. Reuven Bar-Yehuda was born in Iran, on July 17th 1951. Received B.A., M.Sc., and D.Sc. in Computer Science from the Technion — Israel Institute of Technology, Haifa, Israel, in 1978, 1980, and 1983, respectively. He is currently a Senior Lecturer of Computer Science at the Technion. From 1984 to 1986, he was a visiting assistant professor in the Computer Science Dept. at the Duke Univesity His research interests include computational geometry, VLSI, graph algorithms and distributed algorithms. Oded Goldreich was born in Tel-Aviv, Israel, on February 4th 1957. Received B.A., M.Sc., and D.Sc. in Computer Science from the Technion — Israel Institute of Technology, Haifa, Israel, in 1980, 1982, and 1983, respectively. He is currently an Associate Professor of Computer Science at the Technion. From 1983 to 1986, he was a postdoctoral fellow at MIT's Laboratory for Computer Science. His research interests include cryptography and related areas, relation between randomness and algorithms, and distributed computation. Alon Itai was born in Scotland, on December 12th 1946. Received B.Sc. in Mathematics from the Hebrew University in Jerusalem in 1969. M.Sc., and Ph.D. in Computer Science from the Weizmann Institute of Science, Rehovot, Israel in 1971 and 1976. He is currently an Associate Professor of Computer Science at the Technion. His research interests include randomized and distributed algorithms, computational learning theory and performance evaluation.The second author was partially supported by grant No. 86-00301 from the United States—Israel Bi-national Science Foundation BSF), Jerusalem, Israel.     

Fast evaluation of Bounded Slice-line Grid

Bounded Slice-line Grid (BSG) is an elegant representation of block placement, because it is very intuitionistic and has the advantage of handling various placement constraints. However, BSG has attracted little attention because its evaluation is very time-consuming. This paper proposes a simple algorithm independent of the BSG size to evaluate the BSG representation in O(nloglogn) time, where n is the number of blocks. In the algorithm, the BSG-rooms are assigned with integral coordinates firstly, and then a linear sorting algorithm is applied on the BSG-rooms where blocks are assigned to compute two block sequences, from which the block placement can be obtained in O(n log logn) time. As a consequence, the evaluation of the BSG is completed in O(nloglogn) time, where n is the number of blocks. The proposed algorithm is much faster than the previous graph-based O(n^2) algorithm. The experimental results demonstrate the efficiency of the algorithm.     

An Algorithm Based on Tabu Search for Satisfiability Problem

In this paper,a computationally effective algorithm based on tabu search for solving the satisfiability problem(TSSAT)is proposed.Some novel and efficient heuristic strategies for generating candidate neighborhood of the curred assignment and selecting varibables to be flipped are presented. Especially,the aspiration criterion and tabu list tructure of TSSAT are different from those of traditional tabu search.Computational experiments on a class of problem insteances show that,TSSAT,in a reasonable amount of computer time ,yields better results than Novelty which is currently among the fastest known.Therefore TSSAT is feasible and effective.     

Practical uses of synchronized clocks in distributed systems

Summary Synchronized clocks are interesting because they can be used to improve performance of a distributed system by reducing communications. Since they have only recently become a reality in distributed systems, their use in distributed algorithms has received relatively little attention. This paper discusses a number of distributed algorithms that make use of synchronized clocks and analyzes how clocks are used in these algorithms Barbara Liskov received her B.A. in mathematics from the University of California at Berkeley and her M.S. and Ph.D. in computer science from Stanford University. She is currently a member of the faculty at the Massachusetts Institute of Technology, where she is NEC Professor of Software Science and Engineering. Her research and teaching interests include programming languages, programming methodology, distributed computing, and parallel computing. Her work on data abstraction led to the development of the CLU programming language and to a programming methodology based on data abstraction and specifications. This work is described in her book Abstraction and Specification in Program Development. Her subsequent research in distributed computing resulted in the Argus programming language, which supports robust distributed programs that survive hardware failures, and the Mercury communications mechanism, which supports efficient communication in a heterogeneous distributed system. At present Prof. Liskov is continuing her work in distributed computing, including development of replication algorithms for implementing highly-available systems. She is working on Harp, a replicated Unix file system for use via NFS, and on the design and implementation of Thor, a highly available object repository for use in a heterogeneous distributed environment. She is a member of ACM, IEEE, the National Academy of Engineering, and is a fellow of the American Academy of Arts and Sciences.This research was supported in part by the Advanced Research Projects Agency of the Department of Defense, monitored by the Office of Naval Research under contract N00014-89-J-1988, and in part by the National Science Foundation under grant CCR-8822158.     

New Meta-Heuristic for Combinatorial Optimization Problems: Intersection Based Scaling

Combinatorial optimization problems are found in many application fields such as computer science,engineering and economy. In this paper, a new efficient meta-heuristic, Intersection-Based Scaling (IBS for abbreviation), is proposed and it can be applied to the combinatorial optimization problems. The main idea of IBS is to scale the size of the instance based on the intersection of some local optima, and to simplify the search space by extracting the intersection from the instance, which makes the search more efficient. The combination of IBS with some local search heuristics of different combinatorial optimization problems such as Traveling Salesman Problem (TSP) and Graph Partitioning Problem (GPP) is studied, and comparisons are made with some of the best heuristic algorithms and meta-heuristic algorithms. It is found that it has significantly improved the performance of existing local search heuristics and significantly outperforms the known best algorithms.