Drcm: Dynamic Relationship Creation and Management in Social Internet of Things

Abstract

As internet of things (IoT) is overpopulated with a multitude of objects, services and interactions locating the most relevant object is emerging as a major obstacle. Over the last few years, the social internet of things (SIoT) paradigm, where objects independently establish social relationships with the other things has become popular as it provides several new characteristics to carryout reliable discovery approaches. Given a large scale deployment of socially connected objects, finding the shortest path to reach the service provider remains as a fundamental challenge. Most of the existing techniques, search for a specific object or service utilising its friendship or friends of friends connections. As a result, each object has to manage a large set of friends, thus slowing down the search process. In this paper, we propose a similarity based object search mechanism that dynamically creates and manages relationships based on physical location proximity and social context of users in social communities. The result shows enhancement in the proposed method over the existing search techniques FSS, FSASV and LSFGA in terms of local cluster coefficients, the average degree of connections and average path length