Reconfiguration models and algorithms for stateful interactive processes

Varvarigou, TA

dc.contributor.author	Varvarigou, TA	en
dc.date.accessioned	2014-03-01T01:48:42Z
dc.date.available	2014-03-01T01:48:42Z
dc.date.issued	1999	en
dc.identifier.issn	00985589	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/25576
dc.subject.other	Algorithms	en
dc.subject.other	Computational complexity	en
dc.subject.other	Interactive computer systems	en
dc.subject.other	Polynomials	en
dc.subject.other	Polynomial-time algorithms	en
dc.subject.other	Stateful interactive processes	en
dc.subject.other	Computer systems programming	en
dc.title	Reconfiguration models and algorithms for stateful interactive processes	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/32.798328	en
heal.identifier.secondary	http://dx.doi.org/10.1109/32.798328	en
heal.publicationDate	1999	en
heal.abstract	In this paper, we present new results in the area of reconfiguration of stateful interactive processes in the presence of faults. More precisely, we consider a set of servers/processes that have the same functionality, i.e., are able to perform the same tasks and provide the same set of services to their clients. In the case when several of them turn out to be faulty, we want to reconfigure the system so that the clients of the faulty servers/processes are served by some other, fault-free, servers of the system in a way that is transparent to all the system clients. We propose a new method for reconfiguring in the presence of faults: compensation paths. Compensation paths are an efficient way of shifting spare resources from where they are available to where they are needed. We also present optimal and suboptimal simple reconfiguration algorithms of low polynomial time complexity O(nmlog(n2/m)) for the optimal and O(m) for the suboptimal algorithms, where n is the number of processes and m is the number of primary-backup relationships. The optimal algorithms compute the way to reconfigure the system whenever the reconfiguration is possible. The suboptimal algorithms may sometimes fail to reconfigure the system, although reconfiguration would be possible by using the optimal centralized algorithms. However, suboptimal algorithms have other competitive advantages over the centralized optimal algorithms with regard to time complexity and communication overhead.	en
heal.publisher	IEEE, Piscataway, NJ, United States	en
heal.journalName	IEEE Transactions on Software Engineering	en
dc.identifier.doi	10.1109/32.798328	en
dc.identifier.volume	25	en
dc.identifier.issue	3	en
dc.identifier.spage	401	en
dc.identifier.epage	415	en