Mobile-edge computing framework with data compression for wireless network in energy internet
Mobile-edge computing framework with data compression for wireless network in energy internet
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DOI：
10.26599/tst.2018.9010124
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发表时间：
2019-03
影响因子：
6.6
通讯作者：
Luning Liu;C. Xin;Zhaoming Lu;Luhan Wang;X. Wen
中科院分区：
文献类型：
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作者：
Luning Liu;C. Xin;Zhaoming Lu;Luhan Wang;X. Wen
在能源困境的背景下，能源互联网已成为国际学术界和产业界关注的热点技术之一。然而，来自用户的大量小数据过于分散且不适合压缩，容易耗尽计算资源并降低随机访问的可能性，从而降低系统性能。此外，变电站对诸如控制信息的用户数据的传输延迟敏感。然而，传统的能源互联网通常不能满足要求。集成移动边缘计算使能源互联网便于数据采集，处理，管理和访问。在本文中，我们提出了一种新的能源互联网框架，以提高随机接入的可能性，减少传输延迟。该框架利用局域网从用户处收集数据，并使得为能源互联网进行数据压缩成为可能。仿真结果表明，该结构在不增加额外能耗开销的情况下，可以大幅度提高随机接入概率，降低传输延迟。
Under the situations of energy dilemma, energy Internet has become one of the most important technologies in international academic and industrial areas. However, massive small data from users, which are too scattered and unsuitable for compression, can easily exhaust computational resources and lower random access possibility, thereby reducing system performance. Moreover, electric substations are sensitive to transmission latency of user data, such as controlling information. However, the traditional energy Internet usually could not meet requirements. Integrating mobile-edge computing makes energy Internet convenient for data acquisition, processing, management, and accessing. In this paper, we propose a novel framework for energy Internet to improve random access possibility and reduce transmission latency. This framework utilizes the local area network to collect data from users and makes conducting data compression for energy Internet possible. Simulation results show that this architecture can enhance random access possibility by a large margin and reduce transmission latency without extra energy consumption overhead.