Distributed mutual exclusion on hypercubes

The authors present a dynamic token-based mutual exclusion algorithm for distributed systems. In the algorithm, a site invoking mutual exclusion sends token request messages to a set of sites possibly holding the token as opposed to all the sites as in the algorithm proposed by I. Suzuki and T. Kasami (1985). A request set is used to record the identifiers of such a set of sites in the system. The algorithm is dynamic because the request set is dynamically changed as the algorithm is executed. As the size of the request set is reduced, the number of the messages exchanged per critical section (CS) execution is reduced. Compared with Suzuki and Kasami's algorithm, the proposed algorithm can reduce the number of the messages exchanged by 40% when the traffic is light. Finally, the authors discuss relationship between the token-based and non-token-based mutual exclusion algorithms. This relationship motivated the authors to design such a dynamic token-based algorithm. >

A mutual exclusion (ME) algorithm consists of a trying protocol (TP)and exit protocol (EP)that surround a critical section (CS)and satisfy the following properties: mutual exclusion : at most one process is allowed to use the CS at a given time; lockout freedom : any process that enters the TP eventually enters the CS; and bounded exit : a process can complete the EP in a bounded number of its own steps. A First-Come-First-Served (FCFS) ME algorithm [1] additionally requires processes to enter the CS in roughly the order in which they start the TP. Once a process has started executing the TP of a ME algorithm, it has committed itself to entering the CS, since the correctness of the algorithm may depend on every process properly completing its TP and EP.

Mutual exclusion is one of the most commonly used techniques to handle contention in concurrent systems. Traditionally, mutual exclusion algorithms have been designed under the assumption that a process does not fail while acquiring/releasing a lock or while executing its critical section. However, failures do occur in real life, potentially leaving the lock in an inconsistent state. This gives rise to the problem of recoverable mutual exclusion (RME) , which involves designing a mutual exclusion (ME) algorithm that can tolerate failures while maintaining required safety and liveness properties. In this work, we present a framework that transforms any algorithm that solves the RME problem into an algorithm that can also simultaneously adapt to (i) the number of processes concurrently competing for the lock, as well as (ii) the number of unresolved failures in the system, while maintaining the correctness properties and performance characteristics of the underlying RME algorithm. Additionally, the algorithm constructed as a result of this transformation adds certain desirable properties such as bounded recovery and fairness. One of the important performance measures of any ME algorithm, including an RME algorithm, is the number of remote memory references (RMRs) made by a process—to acquire and release a lock, as well as to recover the lock structure after a failure. Let R(n) denote the RMR complexity of a critical section request in the underlying RME algorithm, where n denotes the number of processes in the system. Then, our framework yields an RME algorithm for which the RMR complexity of a critical section request is given by \(\mathcal {O}(\min \lbrace \ddot{c},\sqrt {F+1},\ R(n) \rbrace)\) , where \(\ddot{c}\) denotes the point contention of the request and F denotes the failure-density of the request. We further extend our framework by presenting a novel memory reclamation algorithm to bound the space complexity of the RME algorithm. Our memory reclamation algorithm maintains the correctness, performance, and fairness properties of our transformation. Our approach is general enough that it may also be used to bound the space complexity of other RME algorithms. In addition to read and write instructions, our algorithm uses compare-and-swap ( CAS ) and fetch-and-store ( FAS ) hardware instructions, both of which are commonly available in most modern processors.

Distributed algorithms for multiple entries to a critical section with priority

While symmetric mutual exclusion algorithms are easy to implement, message complexity per critical section (CS) access to such approaches in a distributed system is typically high. There exist works that handle this issue but to a limited extent. In this paper, we propose a new symmetric algorithm for mutual exclusion. The proposed approach is essentially a prioritized version of the well-known Ricart–Agrawala algorithm for mutual exclusion in distributed systems. The solution proposed uses one or more priority levels, such that different participating processes are placed at different priority levels depending on the initial priority of the processes. The proposed algorithm maintains safety, liveness, and fairness properties toward implementation in a distributed system.

Given a mutual exclusion algorithm MXd for {d geq 2} threads, a mutual exclusion algorithm for {N > d} threads can be built in a tree of degree d with N leaves, with the critical section at the root of the tree. This tournament solution seems obviously correct and efficient. The present note proves the correctness, and formalizes the efficiency in terms of concurrent complexity by means of Bounded Unity. If the tree is balanced, the throughput is logarithmic in N. If moreover MXd satisfies FCFS (first-come first-served), the worst case individual delay of the tournament algorithm is of order N. This is optimal.

The group mutual exclusion problem is a generalization of mutual exclusion problem such that a set of processes in the same group can enter critical section simultaneously. In this paper, we propose a distributed algorithm for the group mutual exclusion problem in asynchronous message passing distributed systems. Our algorithm is based on tokens, and a process that obtains a token can enter critical section. For reducing message complexity, it uses coterie as a communication structure when a process sends a request messages. Informally, coterie is a set of quorums, each of which is a subset of the process set, and any two quorums share at least one process. The message complexity of our algorithm is O(|Q|) in the worst case, where |Q| is a quorum size that the algorithm adopts. Performance of the proposed algorithm is presented by analysis and discrete event simulation. Especially, the proposed algorithm achieves high concurrency, which is a performance measure for the number of processes that can be in critical section simultaneously.

We present tradeoffs between RMR complexity and memory word size for recoverable mutual exclusion (RME) algorithms using arbitrary synchronization primitives. Assuming that each memory location stores w bits, we show that n-process mutual exclusion has an RMR complexity of at least Ω (min{logw n, log n/log log n}) on the DSM and the CC model. For w = (log n)Ω(1), our lower bound asymptotically matches an upper bound by Katzan and Morrison [19], whose RME mutual exclusion algorithm employs w-bit fetch-and-add operations. Our lower bound is the first one that does not restrict the type of atomic operations that can be executed on a memory location.

First-Come-First-Served (FCFS) mutual exclusion (ME) is the problem of ensuring that processes attempting to concurrently access a shared resource do so one by one, in a fair order. In this paper, we close the complexity gap between FCFS ME and ME in the asynchronous shared memory model where processes communicate using atomic reads and writes only, and do not fail. Our main result is the first known FCFS ME algorithm that makes O(log N) remote memory references (RMRs) per passage and uses only atomic reads and writes. Our algorithm is also adaptive to point contention. More precisely, the number of RMRs a process makes per passage in our algorithm is Θ(min(k, log N)), where k is the point contention. Our algorithm matches known RMR complexity lower bounds for the class of ME algorithms that use reads and writes only, and beats the RMR complexity of prior algorithms in this class that have the FCFS property.

Clustering in WSN proves to be phenomenal in maximizing network life. This paper comes up with a new clustering scheme with a mutual exclusion feature. A number of clustering protocols are employed in WSN, but none of the protocol has ensured or focused on mutual exclusion of a cluster head role over range of communication. The objective of this paper is to propose a new distributive clustering protocol which will also work like mutual exclusion algorithms. This mutual exclusive distributive protocol forms the cluster of sensors, and selects a cluster head which possesses the mutual exclusion property. Keywords: Distributive clustering, mutual exclusion, WSN clustering.

In distributed systems,cooperating process essh are both local and remoter sources. Chance is very high that multiple processes makesimultaneous requests to the same resource. If the resourcerequires mutually exclusive access (critical section - CS), then some regulation is needed to access it for ensuring synchronizedaccess of the resources thatonly one process could use the resource at a given time. This is the distributed mutual exclusion problem. The problem of coordinating the execution of critical sections by eachprocessissolved by providing mutually exclusive access to the CS. Mutual exclusion ensures that concurrent processes make a serialized access to shared resources.Quorum-based algorithms offer the advantage of protocol symmetry, spreading effort and responsibility uniformly across the distributed systems. In thispaper, we have proposed a permission baseddistributedmutual exclusion algorithmwhichis an improvement of Maekawa’s algorithm. The number of messages required by the improvisedalgorithmis in the range 3Mto 5Mper critical section invocation whereMis the number of intersection nodes1 in the system. A reduction in number of message by restricting the communication of anynodewith the intersection nodes of the quorums, withoutany modification of the basic structure of the algorithm.

Mutual exclusion is one of the fundamental problems in mobile ad hoc networks (MANETs). The solutions to the mutual exclusion problem ensure exclusive access to a shared resource(s). In MANETs, one of the variants of mutual exclusion problem is local mutual exclusion (LME) problem. In LME problem, the non-neighboring nodes may enter CS simultaneously. Whereas, the group local mutual exclusion (GLME) problem in MANETs is the generalization of LME problem, where, unlike LME problem, the processes requesting same group (resource) may be in a critical section (CS) simultaneously. In the presented exposition, an extension of GLME problem, named h-group local mutual exclusion (h-GLME), has been proposed. The h-GLME problem, where the number of active groups can be h (h ≥ 1) and the processes requesting any of h groups may be in their respective CS simultaneously. It is applicable to MANETs. To the best of our knowledge, h-GLME is the first wireless extension of the GLME problem.

A mutual exclusion algorithm with optimally bounded bypasses

Mutual exclusion is one of the most fundamental issues in the study of distributed systems. The problem arises when two or more processes are competing to use a mutual exclusive resource concurrently, i.e., the resource can only be used by at most one process at a time. Synchronizations adopting quorum systems are an important class of distributed algorithms since they are gracefully and significantly tolerate process and communication failures that may lead to network partitioning. Coterie based algorithm is a typical quorum based algorithm for mutual exclusion: A process can use the resource only if it obtains permissions from all processes in any quorum ofcoterie, and since each quorum intersects with each other and each process only issues one permission, the mutual exclusion can be guaranteed. Many quorum systems have been defined based on the relaxation of the properties of coterie system. Each of them is designed to resolve its corresponding problem, e.g., k -coterie based algorithm to resolve the k -mutual exclusion, local coterie for the generalized mutual exclusion, ( h , k )-arbiter for h -out of- k resource allocation problem, etc. Therefore, design an algorithm for any distributed conflict resolution problem is only meant to define a new quorum system which can be implemented to the corresponding problem. Since most of distributed conflict resolution problems are designed based on the relaxation of the safety property of mutual exclusion, understanding the way to relaxing the safety property and its quorum system is important to study any kind of conflict resolution problem in distributed systems.

Time/Contention Trade-Offs for Multiprocessor Synchronization