Metaheuristic task offloading approaches for minimization of energy consumption on edge computing: a systematic review
Abstract
With the evolution of edge computing, which complements the cloud computing environment, services are now provided to nearby customers. Although the computing capacity of edge computing seems limited, offloading tasks with higher computational demands for mobile edge computing to reduce mobile device computations can be challenging. In addition, outsourcing computing resources, on the other hand, is costly and can increase energy consumption due to congestion in networks and server queues. Moreover, a task offloading technique is required to reduce energy consumption through efficient provisioning of computing resources to meet the expectations of tasks with higher demands for resources. On the other hand, existing researchers have attempted to propose solutions using both heuristic and metaheuristic techniques to minimize energy consumption at the edge saver through various task offloading methods. However, it will be prudent to assume that these methods are different from the existing methods. This is because combining these strategies allows for a more global search while simultaneously benefiting from the efficiency of heuristics and the exploratory powers of metaheuristics. Therefore, to understand the existing techniques in terms of their methods, strengths and weaknesses, this paper reviews the literature on metaheuristic task offloading techniques used in the minimization of energy consumption in an edge computing environment. Literature from the Web of Science,…
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Evidence Hub reads this as a systematic review. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
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