Offloading Decision Making in Mobile Edge Computing: A Survey

Abu-Taleb, Najlaa Abdulrahman; Abdulrazzak, Fuad Hasan; Zahary, Ammar; Al-Mqdashi, AbdulMajid

doi:10.1109/esmarta56775.2022.9935407

Cited by 7 publications

(3 citation statements)

References 50 publications

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“…The offloading decision [29] mainly solves the problem of how the mobile terminal decides how to offload, how much to offload, and what to offload. There are mainly two-part offloading and partial offloading.…”

Section: Related Workmentioning

confidence: 99%

An Improved Gravitational Search Algorithm for Task Offloading in a Mobile Edge Computing Network with Task Priority

Xu,

Liu,

Fan

et al. 2024

Electronics

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Mobile edge computing (MEC) distributes computing and storage resources to the edge of the network closer to the user and significantly reduces user task completion latency and system energy consumption. This paper investigates the problem of computation offloading in a three-tier mobile edge computing network composed of multiple users, multiple edge servers, and a cloud server. In this network, each user’s task can be divided into multiple subtasks with serial and parallel priority relationships existing among these subtasks. An optimization model is established with the objective of minimizing the total user delay and processor cost under constraints such as the available resources of users and servers and the interrelationships among the subtasks. An improved gravitational search algorithm (IGSA) is proposed to solve this optimization model. In contrast with the other gravitational search algorithm, the convergence factor is introduced in the calculation of the resultant force and the crossover operation in a genetic algorithm is performed when generating the new particles during each iteration. The simulation results show that the proposed IGSA greatly improves the system performance compared with the existing algorithms.

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Section: Related Workmentioning

confidence: 99%

An Improved Gravitational Search Algorithm for Task Offloading in a Mobile Edge Computing Network with Task Priority

Xu,

Liu,

Fan

et al. 2024

Electronics

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“…Algorithms for computation offloading include heuristic algorithms, meta-heuristic algorithms, game theory-based algorithms, etc. [ 28 ]. Algorithms for resource allocation include convex optimization algorithms, heuristic algorithms, game theory-based algorithms, etc.…”

Section: Related Workmentioning

confidence: 99%

Inter-Satellite Cooperative Offloading Decision and Resource Allocation in Mobile Edge Computing-Enabled Satellite–Terrestrial Networks

Tong

Wang

et al. 2023

Sensors

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Mobile edge computing (MEC)-enabled satellite–terrestrial networks (STNs) can provide task computing services for Internet of Things (IoT) devices. However, since some applications’ tasks require huge amounts of computing resources, sometimes the computing resources of a local satellite’s MEC server are insufficient, but the computing resources of neighboring satellites’ MEC servers are redundant. Therefore, we investigated inter-satellite cooperation in MEC-enabled STNs. First, we designed a system model of the MEC-enabled STN architecture, where the local satellite and the neighboring satellites assist IoT devices in computing tasks through inter-satellite cooperation. The local satellite migrates some tasks to the neighboring satellites to utilize their idle resources. Next, the task completion delay minimization problem for all IoT devices is formulated and decomposed. Then, we propose an inter-satellite cooperative joint offloading decision and resource allocation optimization scheme, which consists of a task offloading decision algorithm based on the Grey Wolf Optimizer (GWO) algorithm and a computing resource allocation algorithm based on the Lagrange multiplier method. The optimal solution is obtained by continuous iterations. Finally, simulation results demonstrate that the proposed scheme achieves relatively better performance than other baseline schemes.

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“…While some studies survey MEC enabled task offloading optimization, they mainly focus on high level scheduling that involves offloading decisions and resource allocation (Abu-Taleb et al, 2022;Shakarami, Ghobaei-Arani, & Shahidinejad, 2020). In such papers, the concepts of task offloading decision, task offloading scheduling, task allocation and resource allocation are not defined uniformly (H. .…”

Section: Introductionmentioning

confidence: 99%

A Survey on IoT Task Offloading Decisions in Multi-access Edge Computing: A Decision Content Perspective

Dayong,

Bin Abu Bakar,

Isyaku

2023

QAJ

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The rapid development of Internet of Things (IoT) technologies has led to increasingly complex software systems on Terminal Devices (TDs). This increases the computational load and battery consumption of TDs. The emergence of Multi-access Edge Computing (MEC) and computing offloading technology allows TDs to delegate computing-intensive tasks to the MEC network for remote execution. However, the computing and communication resources of MEC networks are limited and heterogeneous. In addition, some TDs may have a higher mobility. Therefore, IoT networks need to dynamically decide to offload some or all of the computational tasks to appropriate nodes in the MEC network. Existing reviews do not fully cover the multiple decision-making content of task offloading, and some studies do not clearly define the boundary between task offloading decision-making and task offloading scheduling optimization. This study investigates the similarities and differences between the enabling technologies, deployment architectures, and decision items of various decision mechanisms from the perspective of offloading decision content. Thus, the development and existing challenges of task offloading decision-making methods are comprehensively demonstrated, and future research directions are proposed for IoT task offloading decision-making in MEC.

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Offloading Decision Making in Mobile Edge Computing: A Survey

Cited by 7 publications

References 50 publications

An Improved Gravitational Search Algorithm for Task Offloading in a Mobile Edge Computing Network with Task Priority

An Improved Gravitational Search Algorithm for Task Offloading in a Mobile Edge Computing Network with Task Priority

Inter-Satellite Cooperative Offloading Decision and Resource Allocation in Mobile Edge Computing-Enabled Satellite–Terrestrial Networks

A Survey on IoT Task Offloading Decisions in Multi-access Edge Computing: A Decision Content Perspective

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