Name
Abstract | ||
|---|---|---|
Resource over subscription brings the risk of resource overload. This paper proposes a mechanism to remediate overload without assuming there is always resource available for migration. A work value notion is introduced to compare importance of VMs, and the overload remediation problem is formulated as a variant of Removable Online Multi-Knapsack Problem. An algorithm is proposed to solve this optimization problem. The mechanism is implemented in a large commercial Cloud environment. Experiments and model-based studies demonstrate the effectiveness of the proposed mechanism in remediating overload and its performance in maximizing work values provided by computing environments (27% higher work values than the baseline algorithm in our study). |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/CLOUD.2012.53 | IEEE CLOUD |
Keywords | Field | DocType |
remediating overload,work value notion,higher work value,resource overload,overload remediation problem,baseline algorithm,optimization problem,over-subscribed computing environments,large commercial cloud environment,removable online multi-knapsack problem,proposed mechanism,memory management,virtual machines,computational modeling,servers,resource allocation,throughput,cloud computing,optimization | Virtual machine,Computer science,Server,Real-time computing,Memory management,Resource allocation,Throughput,Optimization problem,Cloud computing,Distributed computing | Conference |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Long Wang | 1 | 1 | 0.35 |
| Rafah A. Hosn | 2 | 7 | 1.61 |
| Chunqiang Tang | 3 | 1287 | 75.09 |