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Upgrading a legacy network to a Software Defined Network in stages, and minimizing the energy consumption of a network are now of great interest to operators. To this end, this paper addresses a novel problem: minimize the energy consumption of a network by upgrading switches over multiple stages subject to the available monetary budget at each stage. Our problem considers (i) bundled links that can be powered-off individually, (ii) decreasing upgrade cost and increasing traffic demands over multiple stages, and (iii) rerouting demands to an alternative path with a delay that is within a predefined limit. Additionally, the link load on the path is no larger than a given maximum utilization. We formulate the problem as an Integer Linear Program and propose a greedy heuristic called Green Multi-Stage Switch Upgrade (GMSU). Experiment results on five actual network topologies show that: 1) our approaches reduce the energy consumption by up to 73.98%; 2) rerouting traffic demand via longer paths improves the energy saving by up to 9.6%; 3) GMSU produces results that are at most 4.83% from the optimal result; and 4) increasing the budget and the number of stages affect the total energy saved and the number of upgraded switches.

This paper considers the novel problem of upgrading a legacy network into a Software Defined Network (SDN) over multiple stages and saving energy in the upgraded network, or hybrid SDN. That is, in each stage, the problem at hand is to select and replace legacy switches with SDN switches and reroute traffic to power off as many unused cables as possible to save energy. Also, the operator must consider: (i) the available budget at each stage, (ii) maximum path delays, (iii) maximum link utilization, (iv) per-stage increase (decrease) in traffic size (upgrade cost), and (v) the Open Shortest Path First - Equal Cost Multi-Path protocol. This paper addresses two multi-path routing scenarios: 1) non-link-disjoint and 2) link-disjoint. It outlines a Mixed Integer Program and a heuristic algorithm for each scenario. The experimental results show that: (i) both solutions produce only up to 0.63% higher energy saving in scenario-1 than in scenario-2, (ii) the mixed integer program (heuristic algorithm) for both scenarios give an energy saving up to 71.93% (71.64%), (iii) using a larger budget and/or number of stages can increase the energy saving, and (iv) the saving achieved by the heuristic solution for each scenario is within 4% from the optimal saving.

This paper considers the problem of upgrading a legacy network into a Software Defined Network (SDN) over multiple stages and maximizing energy saving (ES) in the resulting upgraded network or hybrid SDN. In each stage, an operator needs to select and replace legacy switches with SDN switches and seek to switch off as many cables as possible over each link. This paper addresses the said problem where it considers (i) the available budget at each stage, (ii) maximum path delays, (iii) maximum link utilization, (iv) per-stage increase (decrease) in traffic size (upgrade cost), and (v) each non SDN switch must comply with the Open Shortest Path First (OSPF)-Equal Cost Multi-Path (ECMP) protocol. It outlines a Mixed Integer Program (MIP) and a heuristic algorithm called M-GMSU. The results show that (i) MIP and M-GMSU achieve ES of up to 71.93%, (ii) using a larger budget and/or number of stages increases ES, and (iii) the ES of M-GMSU is within 3.55% away from the optimal ES computed by MIP.

Upgrading a legacy network into a Software Defined Network (SDN) in stages, and minimizing the energy consumption of a network are now of great interests to operators. To this end, this paper addresses a novel problem: minimize the energy consumption of a network by upgrading switches over multiple stages subject to the available monetary budget at each stage. Our problem considers (i) bundled links that can be powered-off individually only if they are adjacent to a SDN switch, and (ii) decreasing upgrade cost and increasing traffic demands over multiple stages. We formulate the problem as an Integer Linear Program (ILP) and propose a greedy heuristic called Green Multi-stage Switch Upgrade (GMSU). Experiment results show that increasing budget as well as number of stages affect the total energy saved and number of upgraded switches. GMSU produces results that are up to 5.8% off the optimal result. Moreover, on large networks, in which ILP becomes computationally intractable, GMSU uses less than 0.1 second to compute a solution.