Name
Abstract | ||
|---|---|---|
A significant amount of energy is consumed to render high-level computation tasks in large scale cloud computing applications. The state-of-the-art energy saving techniques based on centralized job placement approaches reduce the reliability of operation due to a single point of failure. Moreover, the existing works do not consider energy consumption cost for communication devices and network appliances which contribute a lot. In this paper, we have proposed a mechanism for cluster formation based on network vicinity among the data servers. We have developed two distributed and localized intra-cluster and inter-cluster VM scheduling algorithms based on energy calculation, resource requirement and availability. Our proposed scheduling algorithms manage VMs to reduce the energy consumption of both the servers and networking devices. Simulation results show that our proposed distributed VM scheduling algorithms can conserve significant amount of energy compared to state-of-the-art works. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/HPCC.and.EUC.2013.244 | 2013 IEEE 15TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS & 2013 IEEE INTERNATIONAL CONFERENCE ON EMBEDDED AND UBIQUITOUS COMPUTING (HPCC_EUC) |
Keywords | Field | DocType |
clustering algorithms,resource management,servers,bandwidth,scheduling algorithms | Fair-share scheduling,Computer science,Server,Computer network,Real-time computing,Two-level scheduling,Rate-monotonic scheduling,Dynamic priority scheduling,Energy consumption,Round-robin scheduling,Cloud computing,Distributed computing | Conference |
Citations | PageRank | References |
5 | 0.44 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tamal Adhikary | 1 | 33 | 4.48 |
| Amit Kumar Das | 2 | 190 | 30.00 |
| Md. Abdur Razzaque | 3 | 278 | 30.25 |
| A. K. Sarkar | 4 | 41 | 4.20 |