QoS Routing in Internet of Things (IoT) by Context Aware Agent priority by Meta Computational Intelligence for Evidence-based E-Health Services

Abstract

Internet of Things (IoT) having taken giant leaps has emerged as one of the most promising fields with a plethora of E- Health applications. Due to burgeoning demands in data rates and Internet-enabled services, an evidence-based e-health is required in network traffic .Sudden and unforeseeable large-scale anomalies cause packet collisions and constant or sporadic interferences between multiple transmitters. Developing a ‘‘One-Queue-fits-all’’ solution is a great challenge. However, priority analysis for data services bolsters QoS. The proposed Context Aware Agent priority by Meta computational intelligence in IoT for evidence-based E- Health data service (CAAM -EH) aims to assign priority for packets from diverse networks based on their criticality levels. Data are estimated using attributes such as task, temporal, spatial and customized estimation. A Quad Tree structure is employed to organize the estimated data into various levels and priority is eventually set for transmission to the IoT. The Computational intelligence used to support event, time as well as query-based E health data from IoT.