Optimized Resource Allocation in IoT Using Fuzzy Logic and Bio-Inspired Algorithms

IoT smart devices are a confluence of microprocessors, sensors, power source and transceiver modules to effectively sense, communicate transfer data. Energy efficiency is key governing value the network performance in distributed networks. Low discrete limited amount memory finite number resources form some major bottlenecks workflow. Dynamic load balancing, reliability flexibility heavily relied upon by cloud computing for its accessibility. Resources dynamically provided end client an as-come on-demand fashion with global that Internet. Proportionally need services increasing at rate astonishing compared any other forms development. Load balancing seems challenge faced due architecture modular nature our environment. Loads be all nodes. In this paper, we have introduced technique combines fuzzy logic various inspired algorithms—grey wolf algorithm firefly balance devices. The performances algorithms brute force approach based on energy efficiency, lifetime maximization, node failure packet delivery ratio.