Virtual Machine Resource Allocation for Service Hosting on Heterogeneous Distributed Platforms

We propose algorithms for allocating multiple resources to competing services running in virtual machines on heterogeneous distributed platforms. We develop a theoretical problem formulation and compare these algorithms via simulation experiments based in part on workload data supplied by Google. Ou...

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Vydáno v:2012 IEEE 26th International Parallel and Distributed Processing Symposium s. 786 - 797
Hlavní autoři: Stillwell, M., Vivien, F., Casanova, H.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.05.2012
Témata:
Aggregates
cluster
Greedy algorithms
heterogeneous
Random access memory
Resource management
scheduler
Sorting
vector packing
Vectors
virtual machine
Virtual machining
ISBN:1467309753, 9781467309752
ISSN:1530-2075
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Abstract We propose algorithms for allocating multiple resources to competing services running in virtual machines on heterogeneous distributed platforms. We develop a theoretical problem formulation and compare these algorithms via simulation experiments based in part on workload data supplied by Google. Our main finding is that vector packing approaches proposed in the homogeneous case can be extended to provide high-quality solutions in the heterogeneous case, and combined to provide a single efficient algorithm. We also consider the case when there may be bounded errors in estimates of performance-related resource needs. We provide a heuristic for compensating for such errors that performs well in simulation, as well as a proof of the worst-case competitive ratio for the single-resource, single-node case when there is no bound on the error.
AbstractList We propose algorithms for allocating multiple resources to competing services running in virtual machines on heterogeneous distributed platforms. We develop a theoretical problem formulation and compare these algorithms via simulation experiments based in part on workload data supplied by Google. Our main finding is that vector packing approaches proposed in the homogeneous case can be extended to provide high-quality solutions in the heterogeneous case, and combined to provide a single efficient algorithm. We also consider the case when there may be bounded errors in estimates of performance-related resource needs. We provide a heuristic for compensating for such errors that performs well in simulation, as well as a proof of the worst-case competitive ratio for the single-resource, single-node case when there is no bound on the error.
Author Casanova, H.
Vivien, F.
Stillwell, M.
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  organization: INRIA, France
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  surname: Casanova
  fullname: Casanova, H.
  organization: Dept. of Inf. & Comput. Sci., Univ. of Hawai`i at Manoa, Honolulu, HI, USA
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SubjectTerms Aggregates
cluster
Greedy algorithms
heterogeneous
Random access memory
Resource management
scheduler
Sorting
vector packing
Vectors
virtual machine
Virtual machining
Title Virtual Machine Resource Allocation for Service Hosting on Heterogeneous Distributed Platforms
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