The Average Message Complexity Analysis for Different Distributed Mutual Exclusion Site-Tolerant Ways

Article Preview

Abstract:

Many schemes have been proposed to implementation the distributed mutual exclusion. All those algorithms or schemes can be dived into two types based on the fault-tolerant operation. To any type algorithm, the size of the intersection of any two quorums will impact the number of average messages exchanged per Critical Section (CS) execution importantly if the sites are not always operational. In this paper, Basing on the discussions about the average messages in different cases of different algorithms, we get the average messages in the two types algorithm have the same monotony properties to k. and when N and k are all constants, the average messages functions are monotony descend to p. The average messages are more when k=1 than k=N if p is small enough. The minimum of the average messages is When p=1.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 171-172)

Pages:

675-678

Citation:

Online since:

December 2010

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2011 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] L. Lamport, Time, Clocks and Ordering of Events in Distributed Systems, Comm. ACM, vol. 21, no. 7, pp.558-565, July (1978).

DOI: 10.1145/359545.359563

Google Scholar

[2] Ricart, G. and Agrawala, A. K, An Optimal Algorithm for Mutual Exclusion in Computer Networks, Communications of the ACM, 24 (1), pp.9-17, Jan. (1981).

DOI: 10.1145/358527.358537

Google Scholar

[3] M. Maekawa, A Algorithm for Mutual Exclusion in Decentralized Systems, ACM Trans. Computer Systems, May (1985).

Google Scholar

[4] Y. -I. Chang and M. Singhal, and M. Liu, A Hybrid Approach to Mutual Exclusion for Distributed Systems, Proc. Ann. Int'l Computer Software and Application Conf., pp.289-294, Oct. (1990).

Google Scholar

[5] M. Naimi and M. Trehel, An Improvement of the Log(n) Distributed Algorithm for Mutual Exclusion, Proc. Seventh Int'l Conf. Distributed Computing System, pp.371-375, (1987).

Google Scholar

[6] A. Kumar, Hierarchical Quorum Consensus: A New Algorithm for Managing Replicated Data, IEEE Trans. Computers. pp.996-1004, Sept. (1991).

DOI: 10.1109/12.83661

Google Scholar

[7] Y. -C. Kuo and S. -T. Huang, A Geometric Approach for Constructing Coteries and k-Coteries, IEEE Trans. Parallel and Distributed Systems, vol. 8, no. 4, pp.402-411, Apr. (1997).

DOI: 10.1109/71.588618

Google Scholar

[8] Rangarajan S. and Setia S. ,A Fault-tolerant Algorithm for Replicated Data Management,Parallel and Distributed Systems, IEEE Transactions on , Volume: 6 , Issue: 12 , Dec. 1995,pp.1271-1282.

DOI: 10.1109/71.476168

Google Scholar

[9] Guohong Cao and Singhal M., A delay-optimal quorum-based mutual exclusion algorithm for distributed systems, Parallel and Distributed Systems, IEEE Transactions on , Vol. 12 , no. 12 , p.1256 – 1268, Dec. (2001).

DOI: 10.1109/71.970560

Google Scholar