Using Lagrangean Relaxation for Service Location Planning with QoS constraints in large-scale networks

Current trends in computing indicate that there is a great potential for service oriented computing and similar technologies, such as Cisco's Application Oriented Networks, where services provide a higher-level of abstraction to traditional applications. In such cases, providing and consuming services and establishing a relationship between consumers (users of services) and producers (providers of services) are still challenging and vastly researched aspects. We define a Service Location Planning Problem (SLP) that is novel in the approach it takes to match consumers to producers, such that the cost of providing services is minimized while taking into account quality of service constraints of throughput and delay. In previous work, we presented an Integer Linear Programming (ILP) model to formulate the service location planning problem. In this paper, we present Lagrangean Relaxation of the model for large-scale networks. We use the approach of Trick [3] to decrease computational overheads.