Journal
COMPUTER COMMUNICATIONS
Volume 181, Issue -, Pages 132-142Publisher
ELSEVIER
DOI: 10.1016/j.comcom.2021.09.027
Keywords
Device-to-device communication; Caching scheme; Robot helpers; Optimal location; Adaptive particle swarm optimization
Ask authors/readers for more resources
The paper investigates the optimal caching scheme for D2D networks with multiple robot helpers, proposing the RHAC scheme to optimize system performance through moving robots to optimal positions. It introduces the PAPSO algorithm and mobility-aware optimization strategy for robot helpers. Results show significant performance improvements with the RHAC scheme and provide insights for introducing robot helpers into scenarios like smart factories.
Mobile robots are playing an important role in modern industries. The deployment of robots which act as mobile helpers in a wireless network is rarely considered in the existing studies of the device-to-device (D2D) caching schemes. In this paper, we investigate the optimal caching scheme for D2D networks with multiple robot helpers with large cache size. An improved caching scheme named robot helper aided caching (RHAC) scheme is proposed to optimize the system performance by moving the robot helpers to the optimal positions. The optimal locations of the robot helpers can be found based on partitioned adaptive particle swarm optimization (PAPSO) algorithm. And based on these two algorithms, we propose a mobility-aware optimization strategy for the robot helpers. The simulation results demonstrate that compared with other conventional caching schemes, the proposed RHAC scheme can bring significant performance improvements in terms of hitting probability, cost, delay and energy consumption. Furthermore, the location distribution and mobility of the robot helpers are studied, which provides a reference for introducing robot helpers into different scenarios such as smart factories.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available