Towards Context Caches in the Clouds

Context information is traditionally collected from distributed digital artifacts and services and made available to similarly distributed, and often mobile, context consuming applications via context brokers or servers. Contextual data has a strong temporal element i.e. it remains valid for a period of time, and hence is an ideal candidate for caching strategies that aim to exploit such locality of reference. However, different types of contextual information have varying temporal validity durations and a varied spectrum of access frequencies as well. An ideal caching mechanism should utilize dynamic strategies based on the type of context data, quality of service heuristics and access patterns and request frequencies of the context consuming applications. This paper presents an investigation of the utility of various context-caching strategies and proposes a bipartite caching mechanism in a Cloud based context broker that facilitates context provisioning between context providing services and consuming applications. The results demonstrate the relative benefits of different caching strategies under varying context usage scenarios and the utility of the bipartite context caching mechanism in a context provisioning system.