Joint optimization of energy saving and load balancing for data center networks based on software defined networks. (8th December 2020)

• Record Type: Journal Article
• Authors: He, Yihao; Lu, Zebin; Lei, Junru; Deng, Shuhua; Gao, Xieping
• Is Part Of: Concurrency and computation. Volume 33:Number 9(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-12-08
• Subjects: data center networks -- energy optimization -- load balancing -- software defined networks; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.6134
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: To meet the surging demand for artificial intelligence and cloud service, data centers have been expanding rapidly on recent years. Therefore, data center networks have received great attention recently and more challenges gradually emerged. The exiting technology of data center networks (DCNs) has presented two problems: high energy consumption and network load imbalance. Traditionally, the middle‐box hardware is dedicated and complexly merged, such as network load balancer and network energy optimizer. As an emerging architecture, software defined networks (SDNs) brings an opportunity to accomplish load balancing and energy optimization simultaneously with its characteristics. In this article, we propose a traffic flow management strategy which jointly considers energy optimization and load balancing. The strategy forwards traffic flows with maximum available bandwidth multipath routing to balance network load. We minimize activated links and switches to save energy by scheduling traffic flows. We jointly formulate these as an integer linear programming (ILP) problem. We propose a heuristic algorithm to handle the problem. The full simulation results reveal the high efficiency of our algorithm and the coexistence of network energy optimization and load balancing.