Membership overlay design optimization with resource constraints (accelerated on GPU)

Centralized overlay network management, such as for Service Overlay Networks, is an important topicfor Internet based services. The computational efficiency of the central controller node is of paramount importance to guarantee the quality of the service. The paper considers the problem where the network can be also asymmetric and each node requires to be connected with nodes which provide some given resources. This work proposes a comparison of alternative approaches to the parallelization of a dynamic overlay network reconfiguration algorithm, implemented as a distributed Lagrangian algorithm. The proposed approach is based on a subgradient algorithm which makes use of the quasi-constant step-size rule specifically studied for a parallel/distributed implementation. The method is implemented using MPI, OpenMP and CUDA on GPU and was focussed on the membership overlay reconfiguration for test instances up to 1000 nodes.