Centrality-driven scalable service migration

TLDR: The proposed iterative service migration algorithm, called cDSMA, is extensively evaluated over both synthetic and real-world network topologies and achieves remarkable accuracy and robustness, clearly outperforming typical local-search heuristics for service migration.

Abstract: As social networking sites provide increasingly richer context, user-centric service development is expected to explode following the example of User-Generated Content. A major challenge for this emerging paradigm is how to make these exploding in numbers, yet individually of vanishing demand, services available in a cost-effective manner; central to this task is the determination of the optimal service host location. We formulate this problem as a facility location problem and devise a distributed and highly scalable heuristic to solve it. Key to our approach is the introduction of a novel centrality metric. Wherever the service is generated, this metric helps to a) identify a small subgraph of candidate service host nodes with high service demand concentration capacity; b) project on them a reduced yet accurate view of the global demand distribution; and, ultimately, c) pave the service migration path towards the location that minimizes its aggregate access cost over the whole network. The proposed iterative service migration algorithm, called cDSMA, is extensively evaluated over both synthetic and real-world network topologies. In all cases, it achieves remarkable accuracy and robustness, clearly outperforming typical local-search heuristics for service migration. Finally, we outline a realistic cDSMA protocol implementation with complexity up to two orders of magnitude lower than that of centralized solutions.