The service overlay network design problem for interactive internet applications

• Published in: Computers & operations research Vol. 57; pp. 73 - 82
• Main Authors: Chen, Yuh-Rong, Radhakrishnan, Sridhar, Dhall, Sudarshan, Karabuk, Suleyman
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.05.2015; Pergamon Press Inc
• Subjects: Algorithms; Clients; Communication network; Heuristic; Heuristic methods; Integer programming; Interactive network application; Internet; Internet access; Large scale optimization; Mathematical models; Network design; Network flow problem; Networks; Online entertainment; Optimization; Partitioning; Servers; Service overlay network; Studies; Large scale optimization; Interactive network application; Network design; Communication network; Service overlay network
• ISSN: 0305-0548; 1873-765X; 0305-0548
• DOI: 10.1016/j.cor.2014.11.003

Consider a private network of geographically dispersed computers with fast and high capacity connections, and an Internet application session, such as a massive multiplayer online game, with a server and a set of clients. We refer to the former as a service overlay network (SON), and assume that it could be connected to the Internet. The problem is to decide how to configure and utilize the SON in support of this application, such that the clients׳ speed of communication with the server is within given communication performance requirements. We provide an Integer Programming formulation of this problem, and prove that it is NP-Hard. In an attempt to solve the problem within strict computational time requirements of actual applications, we develop a solution framework based on partitioning and enumerating the solution space into smaller subproblems, one or more of which contains an optimal solution. In this framework, we develop and test an optimal seeking exact, and a fast polynomial time heuristic algorithm with success. The exact algorithm sets optimally solvable sizes of the subject problem, whereas the heuristic algorithm sets the size of solvable instances in a real application.