| 摘要(英) |
Bluetooth Low Energy (BLE) technologies are popular in IoT environments. Lots of BLE-enabled sensor devices must access the Internet by a central controller. Different sensor devices will cause different speeds of energy dissipation due to different sensor positions and distances. Thus, those devices cannot synchronize power drains simultaneously between distal and proximal sensors. Current energy leveling techniques are apt to deploy an increasing number of sensors closer to the central sink of data flows to process the increasing amount of data from outer regions, this manner which aims to strike a balance of power consumption and bandwidth utilization. However, this sort of techniques can induce a considerable increase of sensor devices and induce unscaled cost expense for sensor deployment in a large application field.
This paper proposes a balancing mechanism for power dissipation in BLE-based wireless sensor networks. The mechanism design is to divide the positions of all sensors into m coronas, and the bandwidth of a transmission can be divided into k basins. Sensors in an inner corona use a larger portion of transmission bandwidth, while data loading in an outer corona is relatively less. Thus, the proposed mechanism can differentiate the usages of transmission bandwidth between inner and outer coronas. With the information of differentiated data load and bandwidth usage, this mechanism can specify different transmission powers and convert the difference into separate transmission distances. Particularly, sensors in an outer corona can consume higher power using a larger wireless radius, and also provide a larger range of wireless coverage. By contrast, the inner circle does not require a wide range of wireless coverage, but requires higher bandwidth to cope with the convergence of incoming data streams from other outer areas. Finally, the simulation results show that adjusting the antenna transmission power and controlling the bandwidth usage can obtain the goal. Those sensors in both inner and outer areas can have similar power consumptions.
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| 參考文獻 |
[1] Huei-Wen Ferng, Mardianto Soebagio Hadiputro, Arief Kurniawan, “Design of Novel Node Distribution Strategiesin Corona-Based Wireless Sensor Networks,” in IEEE Transactions on Mobile Computing, Vol. 10, No. 9, pp. 297 – 1311, September 2011.
[2] Jian Li and Pransant Mohapatra, “An Analytical Model for the Energy Hole Problem in Many-to-One Sensor Networks,” in Proc. IEEE VTC-Fall’05, pp. 2721-2725, 2005.
[3] John A. Stankovic, “Wireless Sensor Networks,” IEEE Computer Magazine, Vol. 41, No. 10, pp. 92-95, October 2008.
[4] STMicroelectronics, STSW-BNRG001 2016, BlueNRG Current Consumption Estimation Tool. Available online: https://www.st.com. [(accessed on 12 December 2017)].
[5] BluetoothSIG, Specification of the Bluetooth System, Covered Core Package Version: 5.0. The Bluetooth Special Interest Group; Kirkland, WA, USA: 2016. [(accessed on 12 December 2017)]. Vol 6: Core System Package [Low Energy Specification], Part A: Physical Layer Specification; pp. 2532–2546. Available online: https://www.bluetooth.org/
[6] Bluetooth SIG (2016). Bluetooth Low Energy. Available at: https://www.blue-tooth.com/what-is-bluetooth-technology/bluetooth-technology-basics/low-energy. Ac-cessed 1 April 2016
[7] Henrik Snellman, Mikko Savolainen, Jere Knaappila, Pasi Rahikkal, “Bluetooth® 5, Refined for the IoT,” available at: https://www.silabs.com/whitepapers/bluetooth-5-refined-for-the-iot
[8] Bluetooth SIG, Bluetooth 5 Core Specification. See https://www.bluetooth.com/specifications/bluetooth-core-specification
[9] Xiaobing Wu, Guihai Chen, and Sajal K. Das, “Avoiding Energy Holes in Wireless Sensor Networks with Nonuniform Node Distribution.” in IEEE Transactions on Parallel and Distributed Systems, Vol. 19, Issue 5, pp. 710–720, May 2008.
[10] Hassan Hamid Ekal and J. Abdullah, A. Jamil, L. Audah, R. Alias, “Energy Balance Mechanism for Improving the Lifetime in Dense Centric Wireless Sensor Networks,” in Proc. IEEE 7th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), 2016.
[11] ChengFang Zhen, Wenyi Liu, Yongrui Liu, and Anbin Yan, “An Energy-Efficient Sleep/Wake Scheduling for Acoustic Localization Wireless Sensor Network Node.” International Journal of Distributed Sensor Network, 2014.
[12]Natale Guzzo, Nathalie Mitton, Pascal Daragon, and Arulnambi Nandagoban. “A Cluster-based and On-demand routing algorithm for Large-Scale Multi-hop Wireless Sensor Networks.” International Conference on Ad Hoc Networks, pp. 98-109. ISBN: 978-3-319-13328-7, DOI: https://doi.org/10.1007/978-3-319-13329-4_9
[13]Punyasha Chatterjee, and Nabanita Das. “Multiple Sink Deployment in Multi-Hop Wireless Sensor Networks to Enhance Lifetime,” in Proc. of 2015 Internation Conference on Applications and Innovations in Mobile Computing (AIMoC), pp. 48-54, IEEE INSPEC Accession Number: 15072640, DOI: 10.1109/AIMOC.2015.7083829.
[14] Robin Heydon, The Physical Layer. In: Goodwin B., editor. Bluetooth Low Energy—The Developer’s Handbook. Prentice Hall-Pearson Education, Inc.; Upper Saddle River, NJ, USA: 2012. pp. 59–69. ISBN：9780132888363
[15] STMicroelectronic. BlueNRG-2 Bluetooth LE wireless network processor Datasheet DS12166 Rv 5.2018
Available at: https://www.st.com/resource/en/datasheet/bluenrg-2.pdf
[16] Wei Kuang Lai and Chung-Shuo Fan, “Novel Node Deployment Strategies in Corona Structure for Wireless Sensor Networks,”in IEEE Access, Vol. 5, pp. 3889 – 3899, March 2017, Available at https://ieeexplore.ieee.org/document/7875436
[17] STMicroelectronics . Data brief STEVAL-IDB008V2. STMicroelectronics; 2018. Bluetooth low energy wireless system-on-chip . Available online: https://www.st.com/ |
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