1. Implementation of a testbed for testing Energy Efficiency by server consolidation using Vmware

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1 1. Implementation of a testbed for testing Energy Efficiency by server consolidation using Vmware Cloud Data centers used by service providers for offering Cloud Computing services are one of the major energy consuming sources nowadays. A huge amount of energy is required for powering servers, switches and storage units, as well as devices for cooling them. Following the world wide trend of Green Computing, new techniques are required for optimizing the performance of cloud data centers while reducing the amount of consumed power. An algorithm has been developed which reduces the amount of consumed energy by Cloud DCs using the method of server consolidation and adapting the number of active servers to the current load. The algorithm has been tested using analytical methods and simulations with promising results. In this thesis, the student is required to set-up a test bed for testing the algorithm using the servers at the GUC-EMC lab. Experimental results obtained by running scripts on the test bed are required for verifying analytical results. Weeks 3-6: Understanding work environment Week 7: Start algorithm implementation Very good programming skills

2 2. Implementation of a testbed for testing Load Balancing by a two-server system using Vmware the performance of the whole DC. An algorithm has been developed for balancing the distribution of requests among cloud DCs/servers, and is required to be tested using a test bed built on the servers at the GUC-EMC lab. Weeks 3-6: Understanding work environment Week 7: Start algorithm implementation Very good programming skills

3 3. Implementation of a testbed for comparing load balancing approaches between servers in cloud DCs using Vmware the performance of the whole DC. In this project the student is required to set-up a test bed on the servers at the GUC-EMC lab for testing and comparing various load balancing techniques. Weeks 3-6: Understanding work environment Week 7: Start algorithm implementation Very good programming skills

4 4. A study on Energy-efficiency by server consolidation between servers in Cloud DCs using OmNet++ Cloud Data centers used by service providers for offering Cloud Computing services are one of the major energy consuming sources nowadays. A huge amount of energy is required for powering servers, switches and storage units, as well as devices for cooling them. Following the world wide trend of Green Computing, new techniques are required for optimizing the performance of cloud data centers while reducing the amount of consumed power. An algorithm has been developed which reduces the amount of consumed energy by Cloud DCs using the method of server consolidation and adapting the number of active servers to the current load. The algorithm has been tested using analytical methods and simulations with promising results. In this thesis, the student is required to implement the algorithm using OmNet++ simulator for results verification as well as extending test cases of the algorithm to realistic assumptions that theoretical solutions cannot solve. Weeks 3-4: Getting familiar with OmNet++ Week 5: Start algorithm implementation -Very good programming skills -Basic knowledge of Queuing Systems

5 5. A study on Load Balancing approaches between servers in Cloud DCs using OmNet++ customers are routed to the server within the DC that will fulfill their SLAs, and at the same time optimize the performance of the whole DC. An algorithm has been developed for balancing the distribution of requests among two servers in the DCs, and is required to be implemented using OmNet++ simulator for testing its performance. The simulation is also required for extending the algorithm to include more than two servers, which is the limiting case for theoretical analysis. Weeks 3-4: Getting familiar with OmNet++ Week 5: Start algorithm implementation -Very good programming skills -Basic knowledge of Queuing Systems

6 6. A study on Load Balancing approaches between Cloud DCs using OmNet++ the performance of the whole DC. In this project the student is required to implement and compare different approaches for load balancing between cloud DCs and compare their performance in terms of fulfilling customers SLAs while enhancing the performance of the DC. Weeks 3-4: Getting familiar with OmNet++ Week 5: Start algorithm implementation -Very good programming skills -Basic knowledge of Queuing Systems

7 7. Numerical analysis of Shortest-Response time first Load balancing method between servers in Cloud DCs using Gauss-Seidel Iteration method with Successive Overrelaxation are served with certain delay percentiles, loss probabilities, etc. For maintaining these the performance of the whole DC. One approach for achieving this goal is by Shortest-Response time First method, where customers not in order of their arrivals, but according to their response times. In this project the before-mentioned load balancing method in DCs is modeled using Markov chains, and is required to be analyzed using the method of Gauss-Seidel Iteration. Results should be used to obtain significant performance metrics of the system in order to evaluate this load balancing method. Weeks 3-4: Understanding the required method of Analysis Week 5: Start model analysis -Very good knowledge of Queuing Systems -Interest in mathematical analysis