Abstract
Nowadays, energy consumption has become an important issue in data center networks. The most promising energy-saving schemes are those that shut down unnecessary network devices and links while meeting the demand of traffic loads. Existing research mainly focuses on the strategies of energy savings in software-defined data center networks (SD-DCN). Few studies have considered both energy savings and the quality of service (QoS) of the traffic load. In this paper, we investigate the energy savings guaranteed by traffic load satisfaction ratio. To ensure the minimum-power consumption in data centers, we formulate the SD-DCN energy consumption optimization problem as an Integer Linear Programming model. To achieve a high success rate for traffic transmission, we propose three flow scheduling strategies. On this foundation, we propose a strategy-based Minimum Energy Consumption (MEC) heuristic algorithm to ensure the QoS satisfaction ratio in the process of energy optimization. The results show that our algorithm can save energy efficiently under the conditions of low traffic load and medium traffic load. Under high traffic load, our algorithm can achieve better network performance than existing solutions in terms of quality of service satisfaction ratio of flow allocation.
Highlights
In the past decade, with the development of big data, cloud computing, virtualization, and other data-intensive applications, data centers are growing rapidly
We study the quality of service (QoS)-guaranteed energy optimization problem in data center networks, which benefits from the flexible dynamic control of network devices by Software Defined Networking
We present three different strategies based on the order of flow scheduling, namely, Random-order
Summary
With the development of big data, cloud computing, virtualization, and other data-intensive applications, data centers are growing rapidly. Since a large-scale data center contains a large number of servers, links, and bandwidth-intensive applications, it is not easy to realize flexible scheduling of network resources in traditional distributed. Some studies incorporated SDN into DCNs, named software-defined data center networks (SD-DCNs), to optimize the data center energy consumption by utilizing the scalability and manageability of SDN technology [9,10]. The main idea of these works is to design some energy optimization models to save energy under the condition of using as few network resources as possible. We investigate the problem of how to ensure the efficiency of network traffic transmission while realizing the energy optimization of the data center network. We optimize SD-DCN energy consumption with the objective of minimizing the energy cost of switches and links under the constraint of network resources.
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