A Tabu Search Algorithm for the Location of Data Centers and Software Components in Green Cloud Computing Networks

Abstract

The ubiquity of cloud applications requires the meticulous design of cloud networks with high quality of service, low costs, and low CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emissions. This paper presents a planning problem and an extremely efficient tabu search heuristic for optimizing the locations of cloud data centers and software components while simultaneously finding the information routing and network link capacities. The objectives are to optimize the network performance, the CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emissions, the capital expenditures (CAPEX), and the operational expenditures (OPEX). The problem is modeled using a mixed-integer programming model and solved with both an optimization solver and a tabu search heuristic. A case study of a web search engine is presented to explain and optimize the different aspects, showing how planners can use the model to direct the optimization and find the best solutions. The efficiency of the tabu search algorithm is presented for networks with up to 500 access nodes and 1,000 potential data center locations distributed around the globe.