Copyright © 2012, A Minimum Cost Resource Allocation Approach for Cloud Data Centers 指導教授：王國禎 學生：連懷恩 國立交通大學資訊工程系 行動計算與寬頻網路實驗室 1
Copyright © 2012, Outline Introduction Related work Phase 1: A branch and bound algorithm Phase 2: A server/VM chain algorithm Conclusion 2
Copyright © 2012, Introduction Existing approaches only consider come aspects of resource allocation problem(e.g., either for VM or for server level) in cloud data center. A complete resource allocation approach should include the following features: per application resource allocation, resizing on both VM and server level, transition cost, VM placement, and optimization over time domain. Our goal is a minimum cost (optimal) resource allocation approach in cloud data center. 3
Copyright © 2012, Related Work 4 Approach Number of active servers Number of VMs for each app Transition costVM placement Optimization over time domain Chunqiang Tang et al. XOXOX Norman Bobroff et al. OXXOO Minghong Lin et al. OXOXO Our proposed approach OOOOO
Copyright © 2012, A Branch and Bound Algorithm We use a branch and bound algorithm to deal with the resizing problem of VMs and servers. B&B can lead to an optimal solution but is usually in high complexity. In our modified version, we can make it more efficiently by introducing the break- even time condition and off-line migration. The algorithm itself is finished, but we still need to prove a necessary condition to bound its complexity. 5
Copyright © 2012, A Server/VM Chain Algorithm A chain representation of server/VM in space-time diagram. We face some troubles in proving its optimality. 6
Copyright © 2012, Conclusion The most complete resource allocation approach in cloud data center so far. It is theoretically optimal if we succeed, however the actual results still heavily rely on the quality of prediction. Some important necessary condition and optimality still needs to be proven. 7
Copyright © 2012, Hw2 - Hadoop 1.Setup the Hadoop environment on the virtual machines inherited from Hw1. 2.Modify the code from Hw1 to a multinodes Hadoop version 3.Performance comparison between single node, multinodes. 8