Fuzzified swarm intelligence framework using FPSOR algorithm for high-speed MANET- Internet of Things (IoT)

Abstract

Internet of things (IoT) is an inventive technology which permit the association of physical things by means of the digital world throughout the use of heterogeneous networks and communication technologies. Ad-hoc routing protocols may be dispersed and involve every node in route discovery process by making routing data more reliable. Mobile-Adhoc-Networks (MANETs) consist of many portable nodes that can commune directly with each other or through intermediate nodes. Repeatedly, nodes in a MANETs operate with batteries and can roam freely, and thus, a node may exhaust its energy or move away without providing any notice to its cooperative nodes. IoT system using a combination of MANET, a route consists of numerous links in sequence, and so, its lifetime is based on the lifetime of every node and also the wireless links among adjacent nodes. In this research work Fuzzified Particle Swarm Optimization oriented Routing (FPSOR) algorithm is planned to minimize data loss and computational overhead, which in turn maximizes the lifetime of MANETs. Particle Swarm Optimization oriented Routing protocol (PSOR) have taken energy competence as significant criterion for processing routing and driving optimized path for the data accelerating and processing to the source node. The PSOR produces a fresh route for routing by considering fitness value of energy to evaluate diverse path and to choose best-optimized path whose energy consumption is less as compared to ant colony optimization routing paths. This algorithm utilizes a good approach focusing energy levels/status of the nodes through fuzzification and the lengths of the routed ways. NS2 simulator is casted for performance evaluation.

Keywords

• Network-centric
• Fuzzification
• Load balancing
• Arbitrary Trip Time
• Mobility and convergence speed