Abstract
Mobile terminal users applications, such as smartphones or laptops, have frequent computational task demanding but limited battery power. Edge computing is introduced to offload terminals' tasks to meet the quality of service requirements such as low delay and energy consumption. By offloading computation tasks, edge servers can enable terminals to collaboratively run the highly demanding applications in acceptable delay requirements. However, existing schemes barely consider the characteristics of the edge server, which leads to random assignment of tasks among servers and big tasks with high computational intensity (named as “big task”) may be assigned to servers with low ability. In this paper, a task is divided into several subtasks and subtasks are offloaded according to characteristics of edge servers, such as transmission distance and central processing unit (CPU) capacity. With this multi-subtasks-to-multi-servers model, an adaptive offloading scheme based on Hungarian algorithm is proposed with low complexity. Extensive simulations are conducted to show the efficiency of the scheme on reducing the offloading latency with low energy consumption.
Highlights
Mobile terminal devices are connected through the internet to accomplish many different applications and services, such as smartphones, laptops, sensors, machines, and vehicles, etc[1]
Light-weighted servers are deployed on the edge around terminals to bring computation and storage resource from the centralized cloud (CC), which is called as Mobile Edge Computing (MEC) [8]
Wang et al.: Energy-Efficient Off-Loading Scheme for Low Latency in Collaborative Edge Computing intensity caused by different types of demand are rarely taken into account in existing designs
Summary
Mobile terminal devices are connected through the internet to accomplish many different applications and services, such as smartphones, laptops, sensors, machines, and vehicles, etc[1]. More and more researchers considered the difference of tasks, such as computation-intensive task, delay-sensitive task, etc For these scenarios, relationships between servers are considered, such as the hierarchical servers, called as collaborative edge computing (CEC). CEC allows multiple servers to collaboratively offload different type of tasks to efficiently reduce time and energy consumption. J. Wang et al.: Energy-Efficient Off-Loading Scheme for Low Latency in Collaborative Edge Computing intensity caused by different types of demand are rarely taken into account in existing designs. An adaptable offloading scheme based on Hungarian algorithm is designed to allocate subtasks to edge servers to reduce offloading latency and energy consumption. The main contributions of this paper are as follows: 1) A collaborative task offloading model is proposed in edge computing system.
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