DYNAMIC RESOURCE ALLOCATION AND ACTIVE PREDICTIVE MODELS FOR ENTERPRISE APPLICATIONS

M. Al Ghamdi, A. P. Chester, L. He, S. A. Jarvis

Abstract

This work is concerned with dynamic resource allocation for multi-tiered, cluster-based web hosting environments. Dynamic resource allocation is reactive, that is, when overloading occurs in one resource pool, servers are moved from another (quieter) pool to meet this demand. Switching servers comes with some overhead, so it is important to weigh up the costs of the switch against possible system gains. In this paper we combine the reactive behaviour of two well known switching policies – the Proportional Switching Policy (PSP) and the Bottleneck Aware Switching Policy (BSP) – with the proactive properties of several workload forecasting models. Seven forecasting models are used, including Last Observation, Simple Algorithm, Sample Moving Average, Exponential Moving Algorithm, Low Pass Filter and Autoregressive Moving Average. As each of the forecasting schemes has its own bias, we also develop three meta-forecasting algorithms (the Active Window Model, the Voting Model and the Selective Model) to ensure consistent and improved results. We show that request servicing capability can be improved by as much as 40% when the right combination of dynamic server switching and workload forecasting are used. As important is that we can generate consistently improved results, even when we apply this scheme to real-world, highly-variable workload traces from several sources.

References

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Paper Citation


in Harvard Style

Al Ghamdi M., P. Chester A., He L. and A. Jarvis S. (2011). DYNAMIC RESOURCE ALLOCATION AND ACTIVE PREDICTIVE MODELS FOR ENTERPRISE APPLICATIONS . In Proceedings of the 1st International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-8425-52-2, pages 551-562. DOI: 10.5220/0003388705510562


in Bibtex Style

@conference{closer11,
author={M. Al Ghamdi and A. P. Chester and L. He and S. A. Jarvis},
title={DYNAMIC RESOURCE ALLOCATION AND ACTIVE PREDICTIVE MODELS FOR ENTERPRISE APPLICATIONS},
booktitle={Proceedings of the 1st International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2011},
pages={551-562},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003388705510562},
isbn={978-989-8425-52-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - DYNAMIC RESOURCE ALLOCATION AND ACTIVE PREDICTIVE MODELS FOR ENTERPRISE APPLICATIONS
SN - 978-989-8425-52-2
AU - Al Ghamdi M.
AU - P. Chester A.
AU - He L.
AU - A. Jarvis S.
PY - 2011
SP - 551
EP - 562
DO - 10.5220/0003388705510562