A Privacy-Aware Approach for Managing the Energy of Cloud-Based IoT Resources Using an Improved Optimization Algorithm

Abstract

Cloud-based Internet of Things (IoT) is a network of physical things controlled and monitored via the Internet to develop numerous smart systems. In this network, numerous physical things with different types of sensors are created that can be linked to the Internet. IoT devices need to work with limited energy sources for a long time, and wireless communications are the primary source of energy usage. As a result, the lifespan of IoT devices can be extended by minimizing radio communications. Because of the great capability of the IoT, the issue of resource energy consumption is raised. On the other hand, privacy concerns must be considered when designing cloud-based IoT applications. The current article introduces programming formulations of the mentioned issues using an improved ant colony optimization (IACO) algorithm. The method is combined with a new kind of local search algorithm to obtain higher-quality responses. Also, for responding to privacy concerns, a privacy-preserving method has been suggested. The suggested approach has been tested widely, and the outcomes have been compared to the genetic and particle swarm optimization (PSO) algorithms. The results indicated the good ability of the proposed method in terms of network lifespan and energy consumption.