Energy-Efficient Task Offloading for Edge Computing-Based Smart Grid Networks Using Human Urbanization

A microgrid is a generating source used to decentralise the centralised power supply in a small community. It produces, distributes, and regulates the community's power. It can balance the load demands of clients with fluctuating power needs since it is adaptable, dependable, and able to deliver uninterrupted electricity. The utility grid is connected to smart Microgrids, which assist the powering industries‘ requirement for electricity. They rely heavily on contemporary, integrated information and communication technologies (such as edge computing, cloud computing, fog computing, IoT sensors, etc.). Despite the low cost of the services offered by cloud computing, response, processing, and resource management times are issues. As a supplement to cloud computing, edge computing develops, offering services and tackling issues like latency, security, and traffic. The edge servers are used by smart meters to offload their computational tasks. The energy usage is rising as more data is processed in the edge servers. In order to reduce energy usage, this article suggests optimized task scheduling to edge servers using human urbanization optimization algorithm (HUOA).