Title: Energy efficiency optimisation modelling for security robots by edge computing

Authors: Muchun Zhou; Baochuan Fu; Baoping Jiang

Addresses: School of Electronics and Information Engineering, Suzhou University of Science and Technology, Suzhou 215009, China; Anhui Jianzhu University, Hefei 230022, China ' School of Electronics and Information Engineering, Suzhou University of Science and Technology, Suzhou 215009, China; Anhui Jianzhu University, Hefei 230022, China ' School of Electronics and Information Engineering, Suzhou University of Science and Technology, Suzhou 215009, China; Anhui Jianzhu University, Hefei 230022, China

Abstract: In recent years, as indoor security robots are widely used in large public building places, robots have shouldered the pressure of solving security risks, patrol monitoring and fire warning. Mobile robots with rich sensors accomplish many computation-intensive tasks which account for a large proportion of the total energy consumption, thus affecting the service life of their batteries. Most security robots use micro-control units to maintain low energy consumption and hardware complexity, greatly limiting the local computing capacity of robots. In the case of analysing real-time video data and a large amount of sensor data, offloading a numerous intensive computing tasks to edge servers has become an extensive solution. This paper proposes a system model containing multi-robot terminals and multi-edge servers which uses a simulated annealing algorithm based on exchanging two different edge servers. This algorithm realises energy efficiency optimisation for security robots under minimum latency and power limitation by offloading partial computation-intensive tasks to edge servers. The feasibility of the proposed algorithm is also verified by the simulation results.

Keywords: edge computing; security robot; computation offloading; energy efficiency optimisation.

DOI: 10.1504/IJSPM.2022.123473

International Journal of Simulation and Process Modelling, 2022 Vol.18 No.1, pp.36 - 44

Received: 04 Oct 2021
Accepted: 01 Dec 2021
Published online: 22 Jun 2022 *