Abstract
Due to the explosive growth of the Internet of things (IoT) devices and the emergence of diverse new applications, network traffic volume is growing exponentially. The traditional centralized network architecture cannot fulfill IoT devices demand because of the heavy network traffic in industrial IoT. Moreover, IoT devices have limited computational ability and battery power. Energy consumption and time delay problems during computation offloading are fundamental issues. A new architecture known as mobile edge computing (MEC) was introduced to overcome these issues, which brings cloud services and its contents to the edge of the network. IoT devices can offload the data for computation to the cloud server or edge nodes. Different schemes have been proposed to overcome this problem under many scenarios (i.e., single-user, multiuser, and vehicular networks). In this paper, we proposed a modified delay mitigation Levenshtein distance algorithm (MDML). We consider an industrial scenario with multiple IoT devices and multiple servers (edge nodes). Each edge node consists of one MEC server. The proposed algorithm solves the offloading optimization problem of energy and mitigation of time delay with much lower complexity while significantly reducing offloading tasks’ execution time. It works on the basis of dynamic programming, where we break down a complex problem into subproblems. Performance evaluation of our proposed algorithm shows that it can achieve satisfactory energy efficiency and mitigate time delay in the industrial IoT environment.
Highlights
Smart industries called industry 4.0 are the future of the industrial revolution that will enable humanity to fulfill its manufacturing conditions with accuracy and efficiency in the industrial Internet of things (IoT) [1, 2]. e use of actuators, sensors, and IoT devices in the industrial IoT is increasing rapidly; devices communicate with each other to work efficiently [3]
We have proposed the modified delay mitigation Levenshtein distance algorithm (MDML) to optimize the energy efficiency and time delay. is algorithm solves the optimization problem, which is proved by the simulations using MATLAB
A new emerging paradigm known as mobile edge computing (MEC) is introduced to overcome these issues bringing cloud services and contents to the network edge
Summary
Smart industries called industry 4.0 are the future of the industrial revolution that will enable humanity to fulfill its manufacturing conditions with accuracy and efficiency in the industrial Internet of things (IoT) [1, 2]. e use of actuators, sensors, and IoT devices in the industrial IoT is increasing rapidly; devices communicate with each other to work efficiently [3]. New emerging network architecture is mobile edge computing (MEC); the concept of MEC is one that provides user equipment (UE) application at the edge of the network with cloud computing aptitude and Information technology (IT) service environment [5, 6] It can aggravate resource constraints at UEs by offloading computation tasks from UEs to MEC and can help them to secure the use of different IoT applications. In this revolutionary world of technology, IoT devices need to provide high performance within a short time and less energy with wireless networks to share data and information. While using advanced MEC servers at wireless access point and edge nodes leveraging MEC resources, IoT devices can offload their computation tasks partially to access point and edge nodes; these tasks can be computed remotely by the MEC servers and locally
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