Adaptive Distributed Data Storage for Context-Aware Applications

Abstract

Context-aware computing is a paradigm that relies on the active use of information coming from a variety of sources, ranging from smartphones to sensors. The paradigm usually leads to storing large volumes of data that need to be processed to derive higher-level context information. The paper presents a cloud-based storage layer for managing sensitive context data. To handle the storage and aggregation of context data for context-aware applications, Clouds are perfect candidates. But a Cloud platform for context-aware computing needs to cope with several requirements: high concurrent access (all data needs to be available to potentially a large number of users), mobility support (such platform should actively use the caches on mobile devices whenever possible, but also cope with storage size limitations), real-time access guarantees – local caches should be located closer to the end-user whenever possible, and persistency (for traceability, a history of the context data should remain available). BlobSeer, a framework for Cloud data storage, is a perfect candidate for storing context data for large-scale applications. It offers capabilities such as persistency, concurrency and support for flexible storage schema requirement. On top of BlobSeer, Context Aware Framework is designed as an extension that offers context-aware data management to higherlevel applications, and enables scalable high-throughput under high-concurrency. On a logical level, the most important capabilities offered by Context Aware Framework are transparency, support for mobility, real-time guarantees and support for access based on meta-information. On the physical layer, the most important capability is persistent Cloud storage.