Offloading Energy Efficiency with Delay Constraint for Cooperative Mobile Edge Computing Networks

Abstract

We propose a novel edge computing network architecture that enables edge nodes to cooperate in sharing computing and radio resources to minimize the total energy consumption of mobile users while meeting their delay requirements. To find the optimal task offloading decisions for mobile users, we first formulate the joint task offloading and resource allocation optimization problem as a mixed integer non-linear programming (MINLP). The optimization involves both binary (offloading decisions) and real variables (resource allocations), making it an NP-hard and computational intractable problem. To circumvent, we relax the binary decision variables to transform the MINLP to a relaxed optimization problem with real variables. After proving that the relaxed problem is a convex one, we propose two solutions namely ROP and IBBA. ROP is adopted from the interior point method and IBBA is developed from the branch and bound algorithm. Through the numerical results, we show that our proposed approaches allow minimizing the total energy consumption and meet all delay requirements for mobile users.

Delay Optimization Strategy for Service Cache and Task Offloading in Three-Tier Architecture Mobile Edge Computing System

“…But these efforts usually ignore the limited computing power of edge servers compared to remote cloud servers. In [25], Thai T. Vu et al combined the task offloading and resource allocation optimization problems, and formulated the problem as a mixed-integer nonlinear programming. The problem was finally solved by the proposed ROP and IBBA and finally realized the lowest total energy consumption of the users under the delay constraint guarantee.…”

Load Optimization Based on Edge Collaboration in Software Defined Ultra-Dense Networks

“…Reduce the weighted sum of equipment energy consumption and keep the execution latency below the latency requirement. Vu et al [30] proposed a novel edge computing network architecture that enables edge nodes to collaboratively share computing and radio resources to minimize the total energy consumption of mobile users while meeting their latency requirements. In the research work that considers energy consumption and delay together, most researchers consider the scenario of multi-user single server.…”

Computation offloading and resource allocation for mobile edge computing with multiple access points

“…In [22], the system delay and cost were minimised by utilising queueing and convex optimisation theories. By jointly optimising the offloading decisions of all users as well as the allocation of computation and communication resources, the authors in [23] minimised the overall cost of energy, computation, and delay for all users, Du et al in [24] minimised the maximum cost among users to ensure the fairness of all mobile users, the total energy consumption of all users was minimised in [25].…”

“…Unfortunately, the studies in [18–20] did not optimise the transmission power and computation resource allocation, and the works in [23, 25] disregarded the optimal transmission power assignment. Meanwhile, aforementioned studies mainly investigated computation offloading problem from the perspective a single wireless access point (WAP) [18–25]. Actually, wireless local area networks has been widely deployed, where each MD usually connects to the Internet via more than one WAP, e.g.…”

“…On the one hand, notwithstanding some studies related to MEC computation offloading jointly considered offloading decision making and resource allocation [18–25], these works generally investigated computation offloading problem under the setting of a single WAP, and it did not consider the overlapping networks. In reality, there may exist the case that multiple WAPs connect to a common MEC server.…”