在行動無線感測網路中具太陽能考量之目標物監控技術

近年來，隨著無線感測網路興起，Target Coverage的議題已引起學者們的重視，主要應用於環境中特定位置的監控。由於，監控區域中的每個目標物(POI)重要性等級可能有所不同，監控區域中POIs監控品質(QoM)的維持便成為重要探討的議題之一。除此之外，由於覆蓋於POI上的感測器，電力皆以電池作為電量的提供來源，在無任何充電機制的配合之下，感測器的電量有限，無法長時間的在監控區域中進行監控，造成網路生命週期受到限制。為了延長監控區網路的生命時間，並維持監控區域中每個POI其監控品質，在本論文中，我們擬探討太陽能充電之資料收集暨充電排程技術，利用太陽能即時充電的特性，使得感測器能有充沛的電量來源，並且為了減少硬體成本的花費，將使用具移動能力的Data Mule進行感測。其中，行動感測器雖然可透過太陽能充電，但電池充電的速度較感測或移動所消耗的速度慢，且行動感測器在充電或是移動時沒辦法監控目標物，勢必需要額外的DM代替其執行資料收集或POI監控的任務在考慮充放電速率的條件下，如何以最少數量之DM進行資料收集與POI的監控任務，以及在兼顧資料收集與網路監控的目的下，使此資料收集與監控網路可永續經營。因此，本論文擬在行動無線感測網路中，提出具太陽能考量之目標物監控技術，不僅期望達到永續監控區域的網路生命，也希望有效滿足每個POIs的QoM需求和降低應低硬體成本花費。

關鍵字

目標物覆蓋；行動無線感測網路；監控品質；太陽能充電

並列摘要

Target coverage problem has received plenty of attention in the past few years. In target coverage problem, a set of given Points of Interest (POIs) in the monitoring area need to be covered by sensor nodes. A common challenge of developing algorithms for target coverage in static sensor network is the high hardware cost, caused by deployment of sensors especially for connectivity purpose. Recent researches developed algorithms that use the mobility of mobile sensors for connectivity purpose, resulting in lower hardware cost. However, the network lifetime is very limited because mobile sensors are battery-powered and their constant movement requires plenty of energy. In this paper, we study how to make the network lifetime in target coverage unlimited, by using the mobility of a minimal number of mobile sensors to harvest solar energy. The major contribution of this paper is that we consider the scenarios in which POIs have different importance, referred as quality of monitoring (QoM). The POIs with higher QoM need to be covered by more mobile sensors. Additionally, the application of mobility of mobile sensor for better harvesting opportunity within the monitoring area makes the overall ratio of energy harvested relatively high and the cost of network cheaper.

並列關鍵字

Target Coverage ； Mobile Wireless Sensor Networks ； Quality of Monitoring ； Solar-based Energy Harvesting

參考文獻

[1] C. Liu, K. Wu, Y. Xiao, and B. Sun, “Random Coverage with Guaranteed Connectivity: Joint Scheduling for Wireless Sensor Networks,” IEEE Transactions on Parallel and Distributed Systems, vol. 17, no. 6, June 2006, pp. 562–575.

[2] Z. Yun, X. Bai, D. Xuan, T. H. Lai, and W. Jia, “Optimal Deployment Patterns for Full Coverage and k-Connectivity (k ≤ 6) Wireless Sensor Networks,” IEEE/ACM Transactions on Networking, vol. 18, no. 3, June 2010, pp. 934–947.

[4] A. Chen, T. H. Lai, and D. Xuan, “Measuring and Guaranteeing Quality of Barrier-Coverage in Wireless Sensor Networks,” ACM International Symposium on Mobile Ad Hoc Networking and Computing (ACM MobiHoc), Hong Kong, May 2008.

[5] K. Chakrabarty, S. Iyengar, H. Qi, and E. Cho, “Grid Coverage for Surveillance and Target Location in Distributed Sensor Networks,” IEEE Transactions on Computers, vol. 51, no. 12, Dec. 2002, pp. 1448–1453.

[6] W. Wang, V. Srinivasan, B. Wang, and K. C. Chua, “Coverage for Target Localization in Wireless Sensor Networks,” IEEE Transactions on Wireless Communications, vol. 7, no. 2, Feb. 2008, pp. 667–676.

國際替代計量

在行動無線感測網路中具太陽能考量之目標物監控技術

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