Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/656
Title: An Implementation of Energy-efficient Routing Algorithms for Software Defined Networks
Authors: Yousef M. Rafique 
Supervisor: Dr. Mohamad Awad
Keywords: Energy-efficient
Issue Date: 2017
Publisher:  Kuwait university - college of graduate studies
Abstract: The increase in demand for high network bandwidth has significantly increased the network energy consumption; hence, capital expenditure and operational expenditure costs. Service providers are investigating various approaches to reduce operational and management costs, while delivering richer services across their networks. However, because of the vertical integration of the control and data planes in conventional networks, optimizing energy consumption in such networks is challenging. Software-defined networking (SDN) is an emerging networking paradigm that decouples the control plane from the data plane and introduces network programmability for the development of network applications. In this work, we propose an energy-aware integral flow-routing solution to improve the energy efficiency of the SDN routing application. We consider a practical constraint, that is, discreteness of link rates and limited flow rules. We pose the routing problem as a mixed integer programming (MIP) problem, which is known to be NP complete. In this work we provide an implementation of a benchmark for the centralized power-aware routing problem in General Algebraic Modeling System (GAMS) and demonstrate the impact of practical constraints on routing. We then provide a heuristic implementation of the Benders decomposition method, which is computationally efficient. Performance evaluation results demonstrate that the proposed solution achieves a close-to-optimal performance (within 3.27% error) compared to CPLEX on various real topologies with less than 0.056% of CPLEX average computation time. Heuristic solution outperforms traditional shortest path algorithms and provides up to 54.35% power savings.
URI: http://hdl.handle.net/123456789/656
Appears in Programs:0612 Computer Engineering

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