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首页> 外文期刊>IEEE Transactions on Cognitive Communications and Networking >Intelligent Optimization of Availability and Communication Cost in Satellite-UAV Mobile Edge Caching System With Fault-Tolerant Codes
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Intelligent Optimization of Availability and Communication Cost in Satellite-UAV Mobile Edge Caching System With Fault-Tolerant Codes

机译:具有容错代码的卫星-UAV移动边缘缓存系统可用性和通信成本的智能优化

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摘要

Mobile computing provides storage and computation resources of proximal devices to satisfy the real-time and low-energy communication demands of the Internet of Things (IoT). However, in the areas without terrestrial base station infrastructures, the IoT sensors have trouble implementing reliable and stable connections, which results in the difficulties of data gathering and data caching. In this paper, we consider a space-air-ground integrated mobile edge caching IoT system composed of satellite and unmanned aerial vehicles (UAVs), where LEO satellite broadcasts data, and UAVs collect the data from decentralized ground sensors. Since the sensors' low-power property leads data loss, fault-tolerant codes are employed for availability protection. We first derive the exact expressions of system availability and communication cost for data repair and collection. Then, to address the problems of the lower availability, we exploit an intelligent optimization to determine the erasure coding parameters. Lastly, we further optimize the system parameters, i.e., communication ranges and unit power costs of UAV and decentralized sensors, to minimize the total communication cost. Simulation results show that, compared to MDS codes and regenerating codes, adaptive minimum storage regenerating (AMSR) codes with optimized parameters can significantly reduce total communication cost and maintain availability of the system.
机译:移动计算提供了近端设备的存储和计算资源,以满足物联网的实时和低能量通信需求(IOT)。然而,在没有地面基站基础设施的区域中,IOT传感器在实现可靠和稳定的连接中遇到了麻烦,这导致数据收集和数据缓存的困难。在本文中,我们考虑由卫星和无人机(UAV)组成的空中地面集成移动边缘缓存IOT系统,其中Leo卫星广播数据,并且无人机收集来自分散的地面传感器的数据。由于传感器的低功耗性质引导数据丢失,因此采用容错代码用于可用性保护。我们首先导出系统可用性和数据维修和集合的通信成本的确切表达。然后,为了解决可用性较低的问题,我们利用智能优化来确定擦除编码参数。最后,我们进一步优化了UAV和分散式传感器的系统参数,即通信范围和单位功率成本,以最大限度地减少总通信成本。仿真结果表明,与MDS代码和再生代码相比,具有优化参数的自适应最小存储再生(AMSR)代码可以显着降低总通信成本并保持系统的可用性。

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