SwePub - sökning: L773:9781467348812

Numrering	Referens	Omslagsbild	Hitta
1.	Lakew, Ewnetu Bayuh, et al. (författare) Management of distributed resource allocations in multi-cluster environments 2012 Ingår i: Performance Computing and Communications Conference (IPCCC) 2012, 31st International, IEEE. - New York, USA : IEEE. - 9781467348812 ; , s. 275-284 Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract We present a fully distributed solution for managing resource allocation for services running across multiple clusters in a large-scale cloud computing environment. Our solution allows individual services running across clusters to compete dynamically for allocations based on their rate of consumption while maintaining the global cloud level allocation limits. The solution monitors resource consumption by services that are spread over a number of clusters. Global polls are triggered only when the allocated balance in a cluster decreases below a threshold and allocations are reassigned in a manner that avoids further immediate global polls. Our solution achieves scalability by minimizing global message exchanges, increases performance by distributing requests, and improves availability by avoiding a single point of failure. We perform a range of simulations to verify the accuracy of our approach, to validate our theoretical results, and to evaluate against competing approaches.

Lakew, Ewnetu Bayuh, et al. (författare)
Management of distributed resource allocations in multi-cluster environments
2012
Ingår i: Performance Computing and Communications Conference (IPCCC) 2012, 31st International, IEEE. - New York, USA : IEEE. - 9781467348812 ; , s. 275-284
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- We present a fully distributed solution for managing resource allocation for services running across multiple clusters in a large-scale cloud computing environment. Our solution allows individual services running across clusters to compete dynamically for allocations based on their rate of consumption while maintaining the global cloud level allocation limits. The solution monitors resource consumption by services that are spread over a number of clusters. Global polls are triggered only when the allocated balance in a cluster decreases below a threshold and allocations are reassigned in a manner that avoids further immediate global polls. Our solution achieves scalability by minimizing global message exchanges, increases performance by distributing requests, and improves availability by avoiding a single point of failure. We perform a range of simulations to verify the accuracy of our approach, to validate our theoretical results, and to evaluate against competing approaches.

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