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研究生: 陳靖禾
Jing-Ho Chen
論文名稱: 動態功率調整於低功耗藍芽系統
Online Power Management with Quality-of-Service Consideration for Bluetooth Low Energy
指導教授: 陳雅淑
Ya-Shu Chen
口試委員: 謝仁偉
Jen-Wei Hsieh
修丕承
Pi-Cheng Hsiu
吳晉賢
Chin-Hsien Wu
學位類別: 碩士
Master
系所名稱: 電資學院 - 電機工程系
Department of Electrical Engineering
論文出版年: 2016
畢業學年度: 104
語文別: 英文
論文頁數: 27
中文關鍵詞: 藍芽低功耗即時性功耗規劃無線感測網路
外文關鍵詞: Bluetooth Low Energy, Real-time, Power Management, Wireless Sensor Network
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無線感測網路應用隨著物聯網的需求日益受到重視,分布於各處的無線感測器需要即時回傳感測資訊以便中控端即時回應。然而,由於感測器大多是由電池供電,對於提升整體網路運作壽命將成為感測網路一大問題。此研究針對藍芽低功耗裝置的傳輸耗能進行電源管理並考慮封包即時需求。我們提出在多藍芽節點連接的情況下,於不同負載量做無線感測器上的設定連接係數並提出具品質保證的節點排程演算法,以延長感測網路的工作壽命並滿足封包即時性需求。藉由我們提出的方法將大大改善對於藍低功耗裝置上的傳輸耗能,相較於現今智慧型裝置的參數設定,本方法提升將近1.7 倍的蓄電力。


Bluetooth Low Energy, a wireless protocol tends to provide low power communication for battery-driven devices. A connection parameter is used by such protocol to extend the sleep time of BLE nodes. To provide the latency guarantee for sensing applications, the parameter is set in pessimistic and leads high energy consumption. In this paper, we present a power management framework for multiple BLE nodes having multiple applications with varied data rate and latency constraints. A connection parameter determination and a blocking-aware scheduler are proposed to enable the consideration of energy consumption and blocking. The proposed methodology is evaluated by extensive experiments and a real-life case study. The results indicate that the proposed algorithms registered 170% prolong in a lifetime performance compared with a simple pessimistic setting.

1 Introduction 2 Background and Related Work 2.1 The Connection Event in BLE Protocol 2.2 Multiple Slave Nodes with Star topology 2.3 Related Work 3 System Model and Problem Formulation 4 An Energy-efficient Scheduling Framework for Multiple BLE nodes 4.1 Multiple Event Energy Efficiency Interval 4.2 Energy Efficiency Interval Multiple Access 4.3 Shortest Interval First Scheduler 4.4 Example 5 Performance Evaluation 5.1 Experiment Setting 5.2 Connection interval setting with multiple packets 5.3 Connection interval setting with multiple nodes 5.4 Runtime scheduler 5.5 Varied number of node 6 Case Study 7 Conclusion

[1]Bluetooth Low Energy (BLE) 1.0, 2014.

[2]Ra´ul Aquino-Santos, Apolinar Gonz´alez Potes, V´ıctor Rangel-Licea, Miguel A Garc´ıa-Ruiz, LA Villase˜nor-Gonz´alez, and Arthur Edwards-Block. Wireless communication protocol based on edf for wireless body sensor networks. 2008.

[3]Bluegiga. Spp-over-ble application note@ONLINE, 2013. URL www.bluegiga.com.

[4]Octav Chipara, Chenyang Lu, and Gruia-Catalin Roman. Real-time query scheduling for wireless sensor networks. In Proceedings of Real-Time Systems Symposium, 2007. RTSS 2007. 28th IEEE International, pages 389–399. IEEE, 2007.

[5]Keuchul Cho, Gisu Park, Wooseong Cho, Jihun Seo, and Kijun Han. Performance analysis of device discovery of bluetooth low energy (ble) networks. Computer Communications, 2015.

[6]MCollotta and G Pau. Bluetooth for internet of things: A fuzzy approach to improve power management in smart homes. Computers & Electrical Engineering, 2015.

[7]Mario Collotta, Giovanni Pau, and Gianfranco Scat`a. Deadline-aware scheduling perspectives in industrial
wireless networks: A comparison between ieee 802.15. 4 and bluetooth. International Journal of Distributed Sensor Networks, 2013.

[8]David Contreras and Mario Castro. Adaptive polling enhances quality and energy saving for multimedia over bluetooth. Communications Letters, IEEE, 15(5):521–523, 2011.

[9]Artem Dementyev, Steve Hodges, Stephen Taylor, and Johan Smith. Power consumption analysis of bluetooth low energy, zigbee and ant sensor nodes in a cyclic sleep scenario. In Proceedings of Wireless Symposium (IWS), 2013 IEEE International, pages 1–4. IEEE, 2013.

[10]Messaoud Doudou,Mohammad Alaei, Djamel Djenouri, JoseMBarcelo-Ordinas, and Nesrine Badache.
Duo-mac: Energy and time constrained data delivery mac protocol in wireless sensor networks. In Proceedings of Wireless Communications and Mobile Computing Conference (IWCMC), 2013 9th International, pages 424–430. IEEE, 2013.

[11]Abbas El Gamal, Chandra Nair, Balaji Prabhakar, Elif Uysal-Biyikoglu, and Sina Zahedi. Energy-efficient scheduling of packet transmissions over wireless networks. In Proceedings of INFOCOM 2002. Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.
IEEE, volume 3, pages 1773–1782. IEEE, 2002.

[12]Sinem Coleri Ergen and Pravin Varaiya. Tdma scheduling algorithms for wireless sensor networks.
Wireless Networks, 16(4):985–997, 2010.

[13]Duarte Fernandes, Andre Ferreira, Jose Mendes, and Jorge Cabral. A wireless body sensor network based on dynamic power control and opportunistic packet scheduling mechanisms. In Proceedings of Industrial Technology (ICIT), 2015 IEEE International Conference on, pages 2160–2165. IEEE, 2015.

[14]D Giovanelli, B Milosevic, and E Farella. Bluetooth low energy for data streaming: Application-level analysis and recommendation. In Proceedings of Advances in Sensors and Interfaces (IWASI), 2015 6th IEEE International Workshop on, pages 216–221. IEEE, 2015.

[15]Carles Gomez, Ilker Demirkol, and Josep Paradells. Modeling the maximum throughput of bluetooth low energy in an error-prone link. Communications Letters, IEEE, 15(11):1187–1189, 2011.

[16]F Hoflinger, Gerd Ulrich Gamm, Joan Albesa, and Leonhard M Reindl. Smartphone remote control for home automation applications based on acoustic wake-up receivers. In Proceedings of Instrumentation and Measurement Technology Conference (I2MTC), 2014 IEEE International, pages 1580–1583. IEEE, 2014.

[17]Texas Instruments. Texas Instruments CC2540/41 BluetoothR Low Energy Software Developers Guide v1.3.2, 2013.

[18]Anil K Jacob and Lillykutty Jacob. Energy efficient mac for qos traffic in wireless body area network.
International Journal of Distributed Sensor Networks, 2015, 2015.

[19]Beakcheol Jang, Jun Bum Lim, and Mihail L Sichitiu. An asynchronous scheduled mac protocol for wireless sensor networks. Computer Networks, 57(1):85–98, 2013.

[20]Philipp Kindt, Daniel Yunge, Mathias Gopp, and Samarjit Chakraborty. Adaptive online powermanagement for bluetooth low energy. In Proceedings of Computer Communications (INFOCOM), 2015 IEEE Conference on, pages 2695–2703. IEEE, 2015.

[21]KonstantinMikhaylov. Accelerated connection establishment (ace) mechanismfor bluetooth low energy.
In Proceedings of Personal, Indoor, and Mobile Radio Communication (PIMRC), 2014 IEEE 25th Annual International Symposium on, pages 1264–1268. IEEE, 2014.

[22]Per Magnus Østhus. Concurrent operation of bluetooth low energy and ant wireless protocols with an embedded controller. Master’s thesis, Norwegian University of Science and Technology Department of Electronics and Telecommunications, June 2011.

[23]Anjaly Paul and Robin Cyriac. A review of packet scheduling schemes in wireless sensor networks. International Journal of Advanced Research in Computer and Communication Engineering, pages 5283–5286, 2014.

[24]Mark Perillo and Wendi B Heinzelman. Asp: An adaptive energy-efficient polling algorithm for bluetooth piconets. In System Sciences, 2003. Proceedings of the 36th Annual Hawaii International Conference on, pages 10–pp. IEEE, 2003.

[25]Nguyen Minh Proceedings of Phuong, Manuel Schappacher, A Sikora, Z Ahmad, and A Muhammad.
Real-time water level monitoring using low-power wireless sensor network. In Embedded World Conference, 2015.

[26]Yalcin Sadi and Sinem Coleri Ergen. Optimal power control, rate adaptation, and scheduling for uwbbased intravehicular wireless sensor networks. Vehicular Technology, IEEE Transactions on, 62(1): 219–234, 2013.

[27]Joakim Lindh Sandeep Kamath. Measuring Bluetooth Low Energy Power Consumption. TEXAS INSTRUMENTS, 2012. AN092.

[28]Feng Shan, Junzhou Luo, and Xiaojun Shen. Optimal energy efficient packet scheduling with arbitrary individual deadline guarantee. Computer Networks, 75:351–366, 2014.

[29]Lin Tang, Quansheng Guan, Shengming Jiang, and Bingyi Guo. A deadline-aware and distance-aware packet scheduling algorithm for wireless multimedia sensor networks. International Journal of Distributed Sensor Networks, 2015.

[30]Lu Kai Tang Hong-wei, Sun Cai-xia and Liu Yong-peng. Mpt-mac: A multiple packets transmission mac protocol for wireless sensor networks. In Proceedings of SENSORCOMM 2011 : The Fifth International Conference on Sensor Technologies and Applications, pages 58–66, 2011.

[31]Farid Touati, Rohan Tabish, and Adel Ben Mnaouer. A real-time ble enabled ecg system for remote monitoring. APCBEE Procedia, 7:124–131, 2013.

[32]Elif Uysal-Biyikoglu, Balaji Prabhakar, and Abbas El Gamal. Energy-efficient packet transmission over a wireless link. IEEE/ACM Transactions on Networking (TON), 10(4):487–499, 2002.

[33]Chonggang Wang, Bo Li, Kazem Sohraby, Mahmoud Daneshmand, and Yueming Hu. Upstream congestion control in wireless sensor networks through cross-layer optimization. Selected Areas in Communications, IEEE Journal on, 25(4):786–795, 2007.

[34]Yanting Wu, Rajgopal Kannan, and Bhaskar Krishnamachari. Efficient scheduling for energy-delay tradeoff on a time-slotted channel. Master’s thesis, University of Southern California, Los Angeles, California, April 2015.

[35]Jing Yang and Sennur Ulukus. Optimal packet scheduling in an energy harvesting communication system. Communications, IEEE Transactions on, 60(1):220–230, 2012.

[36]Xiuming Zhu, Song Han, Pei-Chi Huang, Aloysius K Mok, and Deji Chen. Mbstar: A real-time communication protocol for wireless body area networks. In Proceedings of Real-Time Systems (ECRTS), 2011 23rd Euromicro Conference on, pages 57–66. IEEE, 2011.

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