Computation Offloading for Industrial Internet of Things: A Cooperative Approach

The term ‘’Industrial Internet of Things’’ (IIoT) was created to describe a specific area of the Internet of Things (IoT) that integrates Information and Communication Technologies (ICT) like cloud/edge computing, wireless sensor/actuator networks, connected objects, etc. to enable and accelerate the development of industry 4.0. Industry standards for IoT device connectivity and operation set it apart. A few of the properties of Industrial IoT include its high levels of resilience, communication availability, enormous data collecting, security, accuracy, automation, and interoperability. IIoT is also used for complicated task delegation, data-driven decision-making, and remote control of equipment. The IIoT applications also have various levels of criticality and quality of service requirements. Hence, it is very challenging to respect the specificity of each application and guarantee the required QoS. In this paper, we offload computationally demanding tasks to edge and cloud servers with stronger computational capabilities. Our suggested model tries to maximize the number of tasks completed before their tolerant deadlines while minimizing each IIoT device’s energy consumption. Furthermore, we introduce a distributed cooperative game that enables each device to choose whether to offload its tasks or locally execute them based on task completion and energy consumption. We demonstrate the existence of the Nash equilibrium by demonstrating that the proposed game is a weighted potential game. We also propose a practical implementation of the game using a distributed mechanism. Finally, we evaluate the proposal using simulation to show the benefits of computation offloading in terms of latency and energy consumption.