An energy sensitive system framework for cloud robotic network

Abstract

Cloud robotic network (CRN) is an extension of the traditional robots, and its important significance is to use the Internet and cloud computing to overcome the limitations of single robot and enhance its computing power. As the core technology of CRN, how to achieve the full potential of computation off-loading is a critical issue. Starting from the basic models of CRN, this paper studies the network architecture and the computation off-loading method to solve this problem. Firstly, a relatively detailed system model is designed based on the characteristics of CRN to provide theoretical and quantitative basis for subsequent research. Then, based on the theory of connected dominating set, a distributed CDS construction algorithm PCDS is proposed, which provides a virtual backbone with more power for the network. Finally, an energy sensitive computation off-loading method is proposed to improve the lifetime of the whole network while ensuring the execution time and energy loss of computational tasks. Simulation results show that the proposed framework can effectively improve the performance of CRN and prolong the lifetime to a certain extent. KEYWORDSCDS, cloud robotic network, computation off-loading, energy sensitive INTRODUCTION"Robots," a concept which shows up first in science fiction films, can be seen everywhere nowadays, such as household sweeping robots, industrial assembly robots, and commercial UAVs (Unmanned Aerial Vehicles). However, due to the slow development of power technology and the limitation of robot body shape, traditional robots have some drawbacks, such as endurance capacity and computing power; hence, the function of a single robot is relatively simple, which cannot meet people's demands gradually.With the development of wireless network technology and cloud computing, cloud robots emerge at the historic moment. Cloud robots can make full use of the ubiquity of the network and enhance the capabilities of traditional robots, thus expanding the robots' application field, simplifying the development process of robotic systems and even reducing the energy cost of robots. As the core technology of CRN, computation off-loading can make robots and cloud cooperatively process tasks, which can effectively improve the performance of the robots.However, cloud robots are often highly heterogeneous, self-organizing, and weak-coupling system. There still are some problems in CRN, such as network instability and inefficient off-loading. In order to make the full use of CRN, a few challenges need to be tackled: Int J Commun Syst. 2019;32:e4028.wileyonlinelibrary.com/journal/dac