Abstract
With the evolution of the Internet of Things (IoT), edge computing technology is using to process data rapidly increasing from various IoT devices efficiently. Edge computing offloading reduces data processing time and bandwidth usage by processing data in real-time on the device where the data is generating or on a nearby server. Previous studies have proposed offloading between IoT devices through local-edge collaboration from resource-constrained edge servers. However, they did not consider nearby edge servers in the same layer with computing resources. Consequently, quality of service (QoS) degrade due to restricted resources of edge computing and higher execution latency due to congestion. To handle offloaded tasks in a rapidly changing dynamic environment, finding an optimal target server is still challenging. Therefore, a new cooperative offloading method to control edge computing resources is needed to allocate limited resources between distributed edges efficiently. This paper suggests the LODO (linked-object dynamic offloading) algorithm that provides an ideal balance between edges by considering the ready state or running state. LODO algorithm carries out tasks in the list in the order of high correlation between data and tasks through linked objects. Furthermore, dynamic offloading considers the running status of all cooperative terminals and decides to schedule task distribution. That can decrease the average delayed time and average power consumption of terminals. In addition, the resource shortage problem can settle by reducing task processing using its distributions.
Highlights
Nowadays, with the rapid evolution of technology and a vast number of Internet of things (IoT) devices, including individual units, have improved processing ability with various embedded sensors
We propose a Dynamic offloading method (DOM) with hybrid states that contains the resource requirements of offloading tasks and real-time resource availability information of each edge node
The LODO algorithm can offload computation tasks to suitable edge node according to the real-time computing resources status of the edge nodes
Summary
With the rapid evolution of technology and a vast number of Internet of things (IoT) devices, including individual units, have improved processing ability (robust computing environment) with various embedded sensors. The total service time may become unacceptable when performing large tasks at the close but slow (low computing power) edge nodes In this case, the LODO algorithm can offload computation tasks to suitable edge node according to the real-time computing resources status of the edge nodes. The following section describes whole activity states (hybrid states) through discussion and formulation about overload issues according to data and task of an edge node using DOM. Depending on the hybrid state of the edge node, the dynamic offloading method (DOM) defines an overload range that considers the correlation/relationship between data and tasks. +Slack Space{Ci, Mi}, Equation (1a) shows the current activation state, where Ci is CPU and Mi is Memory This definition is a sum of the data received by the process of edge node and the computing process of data and tasks.
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