SOS: Socially Omitting Selfishness in Internet of Things for Smart and Connected Communities

Abstract

The Internet of Things (IoT) refers to the global network of interconnected entities that permit any path, any network, and any platform to link people or things anytime, anywhere, with anything and everyone. One of the new areas of IoT is Smart and Connected Communities (SCC) that has useful applications for improving human life. The development could be in the context of the preservation, revitalization, quality of life, and stability of a community. SCC has some restrictions on the devices and nodes in it. It does not allow them to cooperate to save their own resources like memory, power, and buffer to enhance their performance, manipulation and self-centeredness etc,. Therefore, to motivate the nodes to discourage selfish behavior, various studies have been conducted to detect and omit the selfish behavior of nodes in this regard. However, to avoid the selfish behavior of nodes, improvement is still desired. To stimulate nodes for cooperation, SCC requires an innovative and well-organized approach. The purpose of this thesis is to address the problem of selfish behaviors in SCC and to stimulate cooperation between the nodes. Using the democratic process of a socially-oriented system, a newly introduced socially omitting selfishness (SOS) framework is used to omit and control selfish behavior of nodes. This democratic process elects many heads based on weight and cooperation. When a weight-tie situation occurs in a network, cooperation is considered as an alternate criterion for node nomination for election. The elected heads and incentive mechanism introduced induced the member nodes to cooperate in the community. A modified version of the Dempster-Shafer model is also used here to inhibit the selfish behavior of the contributing nodes in the SOS scheme. To effectively employ the proposed framework, it utilizes various monitoring and gateway nodes to constantly monitored the behavior of all the nodes in the community. With repeated selfish actions, the elected community head may also punish the nodes. In order to evaluate the performance of SOS, a mathematical model is developed to assess SOS performance for above all features through the NS2 simulation environment. To test the variations of different percentages of selfish nodes, various protocols are used to evaluate it. In the simulation process, 4% to 90% selfish nodes are incorporated into the network. In terms of average delivery delay, packet delivery ratio, throughput, and average energy, the outcomes of the proposed scheme outperform the current schemes.