可充電式行動感測網路下之節點自我組態與佈署救援演算法之研製

無線感測網路就是由許多微小的感測器組成一個系統網路，並佈署在難以深入前往的區域，經由感測器中的感測能力與無線網路技術回傳該地區之環境參數。每個感測器將監控到的資料立即回傳給收集端，此方法能夠立即獲取感測環境資訊，但若收集端是處於一個較遠距離的位置，對每個感測器在傳送資料所消耗的能源是相當龐大的，導致整體的感測時間縮減，欲繼續監控該區域，則必須前往更換電池或再佈下更多新的感測器。因此該如何佈署較少的感測器節點數與有效的使用能源策略兩個議題成為近來的主要研究。另外，近年來再生能源的議題熱絡，若將所佈署下的感測器加入轉換再生能源裝置進行自我能源回復，進而使感測網路的監控變得更加的持久。本篇研究在單一充電區與多個充電區能固定接收到太陽的照射等場景所設計之演算法，本篇論文對每個感測器中加入行動能力，在具備有充電的區域中，感測器能自我能量回復並進行資料收集，設計更有效率的救援方法讓感測節點能來回穿梭於充電區域，降低能源消耗與持久的環境監控。最後，行動感測器能自我組態前往做更換位置救援的動作，使得該區域中的感測生命週期延長甚至永久存在。由於過去並無相關文獻提出結合佈署演算法與移動節點的策略，因此在後面的模擬結果中，本篇論文將以過去的佈署演算法與本篇論文提出的佈署演算法，並結合本篇論文提出的兩種移動策略比較其整體生命週期、覆蓋率以及移動次數，另外，在不同場景下提出的移動策略在整體生命週期提升了10%，在多個充電區的場景中覆蓋率達到96%，在移動次數方面FED比MAX_COV_AVG多移動了200多次。

關鍵字

無線感測網路；覆蓋範圍；行動節點；充電能源策略

並列摘要

A wireless sensor network consists of many tiny devices. These devices are sensors deployed in the dangerous regions or the unreachable locations. Sensors collect the environmental information and transfer to the device called as sink via the wireless communication technology. When the sink locates far away from the interested area, sensors require spending much energy on delivering the collected data. This will shorten the operation time of sensors. To continue the monitoring operation, sensors need replacing the battery or more sensors should be deployed. Therefore, the research topic is how to cover the interested area with fewest numbers of sensors and how to minimize the energy consumption. In most of the current studies, sensors do not have the ability to recharge the energy. If the sensors can fulfill its power, the sensors must operate longer. Thus, this paper proposes two algorithms for energy rechargeable sensor networks. Sensors are moveable, and they will move back and forth between duty locations and the recharging areas. Single and multiple recharging areas are considered. The experimental results show that the operation duration in the multiple recharging areas improves 10% than in the single recharging area, and coverage area achieves 96%. The number of movements in the proposed two algorithms is 200 times between the MAX_COV_AVG and FED.

並列關鍵字

Wireless sensor networks ； Coverage ； Mobile nodes ； Charging energy

參考文獻

[1] O.D. Incel, A. Ghosh, B. Krishnamachari, K. Chintalapudi, “Fast Data Collection in Tree-Based Wireless Sensor Networks,” in proceedings of the IEEE Transactions on Mobile Computing, Jan. 2012, pp. 86 – 99.

[2] S.D. Muruganathan, D.C.F. Ma, R.I. Bhasin, A. Fapojuwo, “A centralized energy-efficient routing protocol for wireless sensor networks,” in proceedings of the IEEE Communications Magazine, March 2005, pp. S8 – 13.

[3] S. Lindsey, C.S. Raghavendra, “PEGASIS: Power-Efficient GAthering in Sensor Information Systems,” in proceedings of the IEEE Aerospace Conference, vol.3, 2002, pp. 3-1125 - 3-1130.

[4] W.B. Heinzelman, A.P. Chandrakasan, H. Balakrishnan, “An application-specific protocol architecture for wireless microsensor networks,” in proceedings of the IEEE Transactions on Wireless Communications, Oct 2002, pp. 660 – 670

[5] H. Luo, F. Ye, J. Cheng, S. Lu, L. Zhang, “TTDD: A Two-tier Data Dissemination Model for Large-scale Wireless Sensor Networks,” in proceedings of the ACM Journal of Mobile Networks and Applications (MONET), 2002, pp. 161-175.

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可充電式行動感測網路下之節點自我組態與佈署救援演算法之研製

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