Augmentation of Intelligent Agent for Multiple Access Protocols in Wireless Sensor Networks

In any wired or wireless network, the huge data introduced into it are the data generated by the sensors placed in the environment. Wireless Sensor Networks play an important role in capturing the data (including big data), performing the computation and returning the result back to the user. (viz.,a Healthcare Information System). Due to the enormous access of internet by the users distributed geographically, the logical channel must be granted access in an even fashion. Multiple access protocols gain their importance in resolving the access conflict to the shared medium by the sender, receiver and the other intermediate nodes. When two nodes decide to transmit data at the same time, access is granted by dividing the channel to slots based on frequency, time or code. If packets collide in the network, collision avoidance is enhanced by Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol. An intelligent agent is incorporated in the multiple access protocols for knowledge based collision avoidance. In particular, the learning agent feeds the system by observing the environment, feeds data into the inference engine, processes data, fetches the output. The learning element is responsible for making improvements like efficient bandwidth allocation and energy conservation. It uses feedback from the critic. The performance element is authoritative for selecting external actions. It takes in percepts and decides on actions. Hence the network support system built on Multi Protocol Label Switching (MPLS) identifies the unique traffic being sent from diverse sources. Network Virtualization ensures the data are aggregated and segregated at the respective ingress and egress routers.