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DC Field | Value | Language |
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dc.contributor.author | Kulkarni, A.K. | |
dc.contributor.author | Annappa, B. | |
dc.date.accessioned | 2020-03-30T10:18:38Z | - |
dc.date.available | 2020-03-30T10:18:38Z | - |
dc.date.issued | 2015 | |
dc.identifier.citation | 2015 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems, SPICES 2015, 2015, Vol., , pp.- | en_US |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/8417 | - |
dc.description.abstract | Cloud computing is a growing computing model that is influencing every other entity in the global business industry. Efficient load balancing techniques plays a major role in cloud computing by allocating requests to computing resources efficiently to prevent under/over-allocation of Virtual Machines (VMs) and improve the response time to clients. It is observed that during peak hours when request frequency is high, active VM load balancer (packaged in cloudAnalyst) over-allocates initial VMs and under-allocates later ones creating load imbalance. In this paper we propose a novel VM load balancing algorithm that ensures uniform allocation of requests to virtual machines even during peak hours when frequency of requests received in data center is very high to ensure faster response times to users. The simulations results suggest that our algorithm allocates requests to VM uniformly even during peak traffic situations. � 2015 IEEE. | en_US |
dc.title | Load balancing strategy for optimal peak hour performance in cloud datacenters | en_US |
dc.type | Book chapter | en_US |
Appears in Collections: | 2. Conference Papers |
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