A bio-inspired method for distributed deployment of services

We look at the well-known problem of allocating software components to compute resources (nodes) in a network, given resource constraints on the infrastructure and the quality of service requirements of the components to be allocated to nodes. This problem has many twists and angles, and has been studied extensively in the literature. Solving it is particularly problematic when there is extensive dynamism and scale involved. Typically, heuristics are needed. In this paper, we present a new breed of heuristics for solving this problem. The distinguishing feature of our approach is a decentralized optimization framework aimed at finding near optimal mappings within reasonable time and for large scale. Three different incarnations of the problem are explored through simulations. For one problem instance, we also provide exact solutions, and show that our technique is able to find near optimal solutions with low variance. In the largest example, a public-private cloud computing scenario is used, where different clouds are associated with financial costs, and we show that our approach is capable of balancing the load as expected for such a scenario.