Energy Efficient SWIPT Based Mobile Edge Computing Framework for WSN-Assisted IoT
With the increasing deployment of IoT devices and applications, a large number of devices that can sense and monitor the environment in IoT network are needed. This trend also brings great challenges, such as data explosion and energy insufficiency. This paper proposes a system that integrates mobil...
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| Veröffentlicht in: | Sensors (Basel, Switzerland) Switzerland), 2021-07, Vol.21 (14), p.4798, Article 4798 |
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| creator | Chen, Fangni Wang, Anding Zhang, Yu Ni, Zhengwei Hua, Jingyu |
| description | With the increasing deployment of IoT devices and applications, a large number of devices that can sense and monitor the environment in IoT network are needed. This trend also brings great challenges, such as data explosion and energy insufficiency. This paper proposes a system that integrates mobile edge computing (MEC) technology and simultaneous wireless information and power transfer (SWIPT) technology to improve the service supply capability of WSN-assisted IoT applications. A novel optimization problem is formulated to minimize the total system energy consumption under the constraints of data transmission rate and transmitting power requirements by jointly considering power allocation, CPU frequency, offloading weight factor and energy harvest weight factor. Since the problem is non-convex, we propose a novel alternate group iteration optimization (AGIO) algorithm, which decomposes the original problem into three subproblems, and alternately optimizes each subproblem using the group interior point iterative algorithm. Numerical simulations validate that the energy consumption of our proposed design is much lower than the two benchmark algorithms. The relationship between system variables and energy consumption of the system is also discussed. |
| doi_str_mv | 10.3390/s21144798 |
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This trend also brings great challenges, such as data explosion and energy insufficiency. This paper proposes a system that integrates mobile edge computing (MEC) technology and simultaneous wireless information and power transfer (SWIPT) technology to improve the service supply capability of WSN-assisted IoT applications. A novel optimization problem is formulated to minimize the total system energy consumption under the constraints of data transmission rate and transmitting power requirements by jointly considering power allocation, CPU frequency, offloading weight factor and energy harvest weight factor. Since the problem is non-convex, we propose a novel alternate group iteration optimization (AGIO) algorithm, which decomposes the original problem into three subproblems, and alternately optimizes each subproblem using the group interior point iterative algorithm. Numerical simulations validate that the energy consumption of our proposed design is much lower than the two benchmark algorithms. 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Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). 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| subjects | Chemistry Chemistry, Analytical Communications systems Data transmission Energy consumption Energy efficiency Energy harvesting energy minimization Engineering Engineering, Electrical & Electronic Instruments & Instrumentation Internet of Things IoT mobile edge computaing Optimization Physical Sciences Power management Receivers & amplifiers Science & Technology Sensors simultaneous wireless information and power transfer Technology Technology transfer Transmission rate (communications) Variables Wireless networks wireless sensing network |
| title | Energy Efficient SWIPT Based Mobile Edge Computing Framework for WSN-Assisted IoT |
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