Self-Adaptive Context Data Management in Large-Scale Mobile Systems

Context awareness, intended as providing the current execution environment at the service level, is a fundamental capability in future mobile systems. Unfortunately, the real-world realization of such scenarios is currently undermined by inefficient context data delivery mechanisms, which introduce excessive overhead over bandwidth-constrained wireless fixed infrastructures. To efficiently offload context access from fixed infrastructures to mobile nodes, this paper presents a new data caching algorithm that exploits peculiar aspects of context distribution, mainly limited data lifetime and interests similarity between nodes in physical proximity, to properly select the data to evict when necessary. Our solution considers a history over past data accesses and information over data replication to better exploit the limited available space. Extensive simulation results, collected in NS2 simulator, support our assumptions and demonstrate that our caching solution improves system scalability while adding a limited management overhead.