A Minimum Cost Resource Allocation Approach for Cloud Data Centers

1. 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

2. Outline • Introduction • Related work • Phase 1: A branch and bound algorithm • Phase 2: A server/VM chain algorithm • Conclusion

3. 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.

4. Related Work

5. 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.

6. A Server/VM Chain Algorithm • A chain representation of server/VM in space-time diagram. • We face some troubles in proving its optimality.

7. 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.

8. Hw2 - Hadoop • Setup the Hadoop environment on the virtual machines inherited from Hw1. • Modify the code from Hw1 to a multinodesHadoop version • Performance comparison between single node, multinodes.