Abstract-The problem of energy consumption in data centers has attracted many researchers interest recently. This paper proposes an optimal energy consumption Software Defined Network (SDN) data center model using the dynamic activation of hosts and switches. We model switches and hosts as queues and formulate a Mixed Integer Linear Programming (MILP) model to minimize energy consumption while guaranteeing Quality of Service (QoS) of data center. Our purpose is minimizing static power, port power, and memory power of data centers. Since the problem is NP-hard, we adopt Simulated Annealing algorithm to obtain the solution. Through numerical experiment, we could observe that our model is able to save reasonable energy compared to the full operation data center model. Power consumption in data centers has recently received significant interest. Increase in data traffic with highend mobile devices and expansion of Cloud computing environment have demanded continuous growth in data center usage. As a result, data centers consumed 91 billion kilowatt-hours of electricity in 2013, which is equivalent to the energy from 34 large coal fire power plants. Internet traffic arriving to data center is not constant. The traffic is usually increased in the daytime and decreased during the night. Therefore, running data centers continuously will cause wastage of energy because data centers will be wasting many energy to operate unnecessary hosts and switches when there is low traffic input to data centers. Thus, dynamic operation of data center techniques have been suggested by many researchers that control the activation of hosts in data centers. However, they did not consider dynamic activation of switches in data center because of its complexity. Deciding the activation of switches and hosts is very important. If the data center is running a so small number of hosts compared to requests, it will not be able to cover all requests from users. Even if there are enough hosts, if the data center is operating too small number of switches for energy saving purposes, it will increase the latency in transferring data in the data center. Also, it is important to determine which switches we operate. Data centers are usually built with tree architectures, so if we do not activate necessary switches that connect core switches and hosts, this will cause failure of job allocation. We also activate memory dynamically because memory also consumes much energy in data center. According to [1] , DRAM consumes 25% of total power in data centers. In this paper, we develop an optimal energy consumption model in a Fat-tree architecture data center which depends on incoming job requests by using dynamic activation model. Our model guarantees Quality of Service (QoS) of data center by observing delay constraints and performance of data center with architecture constraint. In terms of memory constraint, our model estimates the number of jobs with high probability in each switch and host, and decides how much memory we need to activate.
Yoon et al. REF proposed a power minimization model in a Fat-Tree data center network, and adopted the Simulated Annealing algorithm to obtain the solution.
Power Minimization in Fat-Tree SDN Datacenter Operation
2015 IEEE Global Communications Conference (GLOBECOM)
2015 IEEE Global Communications Conference (GLOBECOM)
Computer Science