Collaborative Caching for Energy Optimization in Content-Centric Internet of Things

Author(s):  
Shupeng Wang ◽  
Handi Chen ◽  
Yongjian Wang
IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 183665-183677 ◽  
Author(s):  
Mamoona Humayun ◽  
Nz Jhanjhi ◽  
Madallah Alruwaili ◽  
Sagaya Sabestinal Amalathas ◽  
Venki Balasubramanian ◽  
...  

Sensors ◽  
2017 ◽  
Vol 17 (8) ◽  
pp. 1799 ◽  
Author(s):  
Yuling Fang ◽  
Qingkui Chen ◽  
Neal N. Xiong ◽  
Deyu Zhao ◽  
Jingjuan Wang

Author(s):  
Mugunthan S. R ◽  
Vijayakumar T

There is a rapid development in Internet of Things and Smart Grid technologies in the recent days. In this paper, an extensive survey of Internet of Things (IoT) based Smart grid environments is done. These technologies, when used in combination offer energy optimization and user friendliness in terms on monitoring and controlling of electronic devices. The software solutions, challenges such as stability in connection, communication, cost and information privacy and security is also discussed broadly. This work exposes new perspectives and knowledge for researchers who work on interdisciplinary domains.


2019 ◽  
Vol 14 (4) ◽  
pp. 503-517 ◽  
Author(s):  
Wei Hu ◽  
Huanhao Li ◽  
Wenhui Yao ◽  
Yawei Hu

This paper attempts to solve the problems of uneven energy consumption and premature death of nodes in the traditional routing algorithm of rechargeable wireless sensor network in the ubiquitous power Internet of things. Under the application environment of the UPIoT, a multipath routing algorithm and an opportunistic routing algorithm were put forward to optimize the network energy and ensure the success of information transmission. Inspired by the electromagnetic propagation theory, the author constructed a charging model for a single node in the wireless sensor network (WSN). On this basis, the network energy optimization problem was transformed into the network lifecycle problem, considering the energy consumption of wireless sensor nodes. Meanwhile, the traffic of each link was computed through linear programming to guide the distribution of data traffic in the network. Finally, an energy optimization algorithm was proposed based on opportunistic routing, in a more realistic low power mode. The experimental results show that the two proposed algorithms achieved better energy efficiency, network lifecycle and network reliability than the shortest path routing (SPR) and the expected duty-cycled wakeups minimal routing (EDC). The research findings provide a reference for the data transmission of UPIoT nodes.


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