2000/03/12 by Adriana Iamnitchi, Ian Foster, Iamnitchi, Adriana +1
Computer Science · #C.2.4 #Cloud Computing and Resource Management #Distributed #Distributed systems and fault tolerance #FOS: Computer and information sciences #Interconnection Networks and Systems #Parallel #and Cluster Computing (cs.DC) #cs.DC
paper · pdf · doi:10.48550/arxiv.cs/0003054
17 pages, 6 figures
arxiv created 2000/03/12 · openalex publication_date 2000/03/12 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The idle computers on a local area, campus area, or even wide area network represent a significant computational resource---one that is, however, also unreliable, heterogeneous, and opportunistic. This type of resource has been used effectively for embarrassingly parallel problems but not for more tightly coupled problems. We describe an algorithm that allows branch-and-bound problems to be solved in such environments. In designing this algorithm, we faced two challenges: (1) scalability, to effectively exploit the variably sized pools of resources available, and (2) fault tolerance, to ensure the reliability of services. We achieve scalability through a fully decentralized algorithm, by using a membership protocol for managing dynamically available resources. However, this fully decentralized design makes achieving reliability even more challenging. We guarantee fault tolerance in the sense that the loss of up to all but one resource will not affect the quality of the solution. For propagating information efficiently, we use epidemic communication for both the membership protocol and the fault-tolerance mechanism. We have developed a simulation framework that allows us to evaluate design alternatives. Results obtained in this framework suggest that our techniques can execute scalably and reliably.