A survey on IoT task offloading decisions in multi-access edge computing: a decision content perspective

• Main Authors: Dayong, Wang, Abu Bakar, Kamalrulnizam, Isyaku, Babangida
• Format: Article
• Language: English
• Published: Qubahan Organization for Development 2023
• Subjects: QA75 Electronic computers. Computer science; T58.5-58.64 Information technology
• Online Access: http://eprints.utm.my/106638/1/WangDayong2023_ASurveyonIoTTaskOffloadingDecisions.pdf; http://eprints.utm.my/106638/; http://dx.doi.org/10.58429/qaj.v3n4a220

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.