Studying Offloading Optimization for Energy-Latency Tradeoff with Collaborative Edge Computing

Since the past few years, mobile communication technology is developing very rapidly, Internet of Things (IoT) are getting very popular. Simultaneously, the idea of being smart city and smart home is growing which implies the popularization of smart cars with the ability to drive autonomously. To meet the needs of these rapidly developing industries, huge amount of computing resources are needed to be consumed. Mobile edge computing is one of the most effective solution to the problem of consuming huge amount of power for the complex computations. Elements of mobile edge cloud computing are small to large mobile user devices including IoT-enabled devices. These devices mostly rely on the battery for computational tasks and if the tasks are complex, battery is drained quickly. So to tackle the complex application tasks, a much more advanced computation is required. Additionally, storage, data communication and efficient energy consuming techniques must be used. One of the major challenges while developing energy efficient network is computation offloading and latency minimization. Previous work shows that any one of the challenges can only be achieved if there is good energy efficiency then the latency is more and if there is minimum latency, but the energy consumed is more. In this paper, we are going to suggest specific areas in the collaborative cloud architecture that needs to be improved for achieving both energy efficiency as well as latency minimization. For that, we have implemented various scenarios and observe the areas of improvement.