Mobile edge computing(MEC) deployment in a multi-robot cooperation(MRC) system is an effective way to accomplish the tasks in terms of energy consumption and implementation latency. However, the computation and commun...Mobile edge computing(MEC) deployment in a multi-robot cooperation(MRC) system is an effective way to accomplish the tasks in terms of energy consumption and implementation latency. However, the computation and communication resources need to be considered jointly to fully exploit the advantages brought by the MEC technology. In this paper, the scenario where multi robots cooperate to accomplish the time-critical tasks is studied, where an intelligent master robot(MR) acts as an edge server to provide services to multiple slave robots(SRs) and the SRs are responsible for the environment sensing and data collection. To save energy and prolong the function time of the system, two schemes are proposed to optimize the computation and communication resources, respectively. In the first scheme, the energy consumption of SRs is minimized and balanced while guaranteeing that the tasks are accomplished under a time constraint. In the second scheme, not only the energy consumption, but also the remaining energies of the SRs are considered to enhance the robustness of the system. Through the analysis and numerical simulations, we demonstrate that even though the first policy may guarantee the minimization on the total SRs’ energy consumption, the function time of MRC system by the second scheme is longer than that by the first one.展开更多
基金supported in part by the National Natural Science Foundation of China (Grant No. 61771429)in part by The Okawa Foundation for Information and Telecommunications, in part by G7 Scholarship Foundation+3 种基金in part by the Zhejiang Lab Open Program under Grant 2021LC0AB06in part by the Academy of Finland under Grant 319759, Zhejiang University City College Scientific Research Foundation (No. JZD18002)in part by ROIS NII Open Collaborative Research 21S0601in part by JSPS KAKENHI (Grant No. 18KK0279, 19H04093, 20H00592, and 21H03424)。
文摘Mobile edge computing(MEC) deployment in a multi-robot cooperation(MRC) system is an effective way to accomplish the tasks in terms of energy consumption and implementation latency. However, the computation and communication resources need to be considered jointly to fully exploit the advantages brought by the MEC technology. In this paper, the scenario where multi robots cooperate to accomplish the time-critical tasks is studied, where an intelligent master robot(MR) acts as an edge server to provide services to multiple slave robots(SRs) and the SRs are responsible for the environment sensing and data collection. To save energy and prolong the function time of the system, two schemes are proposed to optimize the computation and communication resources, respectively. In the first scheme, the energy consumption of SRs is minimized and balanced while guaranteeing that the tasks are accomplished under a time constraint. In the second scheme, not only the energy consumption, but also the remaining energies of the SRs are considered to enhance the robustness of the system. Through the analysis and numerical simulations, we demonstrate that even though the first policy may guarantee the minimization on the total SRs’ energy consumption, the function time of MRC system by the second scheme is longer than that by the first one.
