A big data correlation orchestrator for Internet of Things

Connecting embedded sensors with cloud infrastructure could open enormous possibility for creating new services which eventually could have unprecedented impact in our way of living. To provide robust and reliable services, embedded sensor generally need to produce significant amount of data which could easily exceed storage capability of micro-servers. To address this problem, in this paper, we present BigCO: a big data correlation orchestrator for internet of things. This orchestrator is implemented in a micro cloud server whose role is to manage centralized as well as distributed wireless sensor nodes. In this paper, we address how multifaceted data could be interrelated and analyzed using 3D modeling and present a streaming compression algorithm (extending Ramer-Douglas-Peucker heuristic). Applying our proposed compression algorithm, we have achieved as high as 99.86% compression of sensor data.