Low-Complexity and Efficient Dependent Subtask Offloading Strategy in IoT Integrated With Multi-Access Edge Computing

Multi-access edge computing (MEC) has been booming in recent years, as it promises to fulfill the growing low-latency requirements of applications on large amounts of Internet of Things (IoT) devices. Nevertheless, as latency-sensitive applications tend to become more complicated, existing schemes are too sophisticated, which may result in exceeding the real-time requirements of IoT systems. In this paper, we investigate the task offloading problem for the multi-device multi-edge server IoT system integrated with MEC. Firstly, according to the performance gains obtained by offloading different subtasks, we formalize a system latency minimization problem with energy utilization consideration, which has been proven to be NP-hard. Then, to address it, we propose a heuristic computation offloading scheduling scheme, which offloads appropriate subtasks to edge servers such that the system latency is minimized. Additionally, we theoretically prove the upper and lower boundaries of the system latency. Extensive simulation results corroborate that the proposed algorithm is low-complexity yet effective in decreasing the system latency by 16.15% (and up to 51.18%), improving the energy efficiency of local devices by 8.97% (and up to 21.69%) and shortening the offloading strategy execution time by 96.33% (and up to 98.95%).

I. Introduction

With the continuous improvement of intelligence level of IoT devices in recent years, they are expected to host perception related applications, such as face/gesture recognition [1], virtual/augmented reality [2], highly-interactive online gaming [3], etc. Nevertheless, due to the limitations of battery capacity, processing power, communication ability and physical size of IoT devices, some latency-sensitive applications may not be performed properly. Fortunately, the emergence of MEC [4], [5] provides a beam of light to the gap between resource-constrained IoT devices and latency-sensitive applications. Thanks to the advantages of MEC in strengthening processing and storage capability, shortening execution latency, providing high bandwidth and prolonging battery lifetime at the edge of IoT systems [6]. All these strengths make offloading tasks from IoT devices to more resourceful edge servers effective in decreasing system latency and saving energy consumption of IoT devices.