An Integrated Intelligent System for IoT Device Selection and Placement in Opportunistic Networks Using Fuzzy Logic and Genetic Algorithm

Abstract

The Internet is dramatically evolving and creating various connectivity methodologies. The Internet of Things (IoT) is one of these methodologies which transform current Internet communication to Machine-to-Machine (M2M) basis. The IoT can seamlessly connect the real world and cyberspace via physical objects that are embeded with various types of intelligent sensors. The opportunistic networks are the variants of Delay Tolerant Networks (DTNs). These networks can be useful for routing in places where there are few base stations and connected routes for long distances. In an opportunistic network, when nodes move away or turn off their power to conserve energy, links may be disrupted or shut down periodically. These events result in intermittent connectivity. When there is no path existing between the source and the destination, the network partition occurs. Therefore, nodes need to communicate with each other via opportunistic contacts through store-carry-forward operation. In this paper, we present the design of an integrated intelligent system for IoT device selection and placement in opportunistic networks using Fuzzy Logic and Genetic Algorithm. We introduce the system structure and present in details the design and implementation issues.