第五章 模擬實驗
5.5 充電效能對生命週期的影響
在這裡從表 4 中可以看出模擬參數是多少，區域大小 640×640 以計算模型來做基 準，長 320 分成 8 層，依能源耗損計算後，為了正方形切割考量，充電機設定為 16 台，實驗得到圖 33 結果。
表 4. 改變充電效能模擬參數
參數 值
區域大小(m2) 640×640 感測點(Sensor Node)數量 1000 感測點能量全滿(nJ) 15000 能量標準值(Threshold) 7500 移動載具速度(hop/sec) 1
充電速度比率(nJ/min) 100、213
移動式載具數量 16
圖 33. 改變充電效能生存時間
圖 33 中，當充電效能提升可以使充電時間減短，進而節省時間，較迅速維護區 塊中的感測器，生存時間可以得到較長。
第6章 結論與未來展望
本篇論文的主要動機是要設計出最佳充電分割演算法以分配移動式充電載具。先 前的研究沒有考慮完善的切割分配，因此在這方面我們設計經由計算感測器的耗能，
計算每一層所產生的能源消耗，透過均勻耗能的區塊分配，使區塊中的感測器達到永 續生存的結果，計算需要分配理想的充電機數量，經由結果可達成一個永不缺電之無 線感測網路。
在現實生活中，充電機在充電的過程要達到沒有損耗是不可能的，充電機的電量 也是應該會耗損，由於我們假設無線充電作動是百分之百為理想沒有耗損，移動充電 機在移動也沒有能源損耗，在現實的生活環境下，要達成這種效果需要等待突破物理 特性，速率和距離的關係，在各自區塊中皆能迅速到達區塊中需要充電感測器。未來 將考慮更多現實情況能源耗損所面臨問題設計，如充電機的移動能源損耗，充電時所 損耗遺失的能源，現實中物理特性產生遇到的情況，都將做為思考，充電機充電速度 和充電機移動速度，對於維護充電上他們之間的關係。實驗模型中，覆蓋是以 r 當作 基準，有論文探討過最佳覆蓋是 r
2
3 ，探討研究是否有更佳效果。對於最佳充電機充 電效能設定值，還有充電機對感測器充電的充電範圍設定，最適當的值，未來是可以 思考。
使用 Kruskal 演算法所形成的展開樹(Spanning Tree)，建立資料轉傳路徑。考量 方便建立路徑，不過未必是最好的傳送資料演算法，這未來可以考量研究。
參考文獻
[1] Muhammd Imran Afzal, Waqar Mahmood, Ali Hammad Akbar, "A Battery Recharge Model for WSNs using FreeSpace Optics (FSO)", IEEE, 2008 International Multitopic Conference, pp. 272-277.
[2] Mohamed K.Watfa, Haitham Al-Hassanieh,Samir Salmen, "The Road to Immortal Sensor Nodes", IEEE, 2008 Intelligent Sensors, Sensor Networks and Information Processing, pp. 523–528 .
[3] Matthew D’Souza, Konstanty Bialkowski, Montserrat Ros, "A Wireless Sensor Node Architecture Using Remote Power Charging, for Interaction Applications", IEEE, 2007 Digital System Design Architectures, Methods and Tools, pp. 485-494 . [4] Wen Yao, Minglu Li, Min-You Wu , "Inductive Charging with Multiple Charger
Nodes in Wireless Sensor Networks", LNCS 3842(2006), pp. 262-270.
[5] Ian F. Akyildiz, Weilian Su, Yogesh Sankarasubramaniam, and Erdal Cayirci, “A Survey on Sensor Networks,” IEEE Communications Magazine, vol. 40, pp. 102 – 114, 2002,
[6] Ian F. Akyildiz, Weilian Su, Yogesh Sankarasubramaniam, and Erdal Cayirci,
“Wireless sensor networks: a survey,” Computer Networks, vol. 38, pp. 393-422, 2002.
[7] Curt Schurgers and Mani B. Srivastava “Energy Efficient Routing in Wireless Sensor Networks,” IEEE Military Communications Conference, 2001, pp.
357–361.
[8] Mohamed Younis, Moustafa Youssef, and Khaled Arisha “Energy Aware Routing in Cluster-Based Sensor Networks,” 10th IEEE International Symposium on
[9] C.-F. Huang and Y.-C. Tseng, "The Coverage Problem in a Wireless Sensor Network," ACM Mobile Networks and Applications (MONET), special issue on Wireless Sensor Networks (to appear).
[10] S.Adlakha and M. Srivastava,” Critical density thresholds for coverage in wireless sensor networks” IEEE WCNC, 2003, pp. 1615–1620.
[11] Zack Butler and Daniela Rus “Controlling Mobile Sensors for Monitoring Events with Coverage Constraints,” IEEE International Conference on Robotics and Automation, 2004, vol. 2, pp. 1568–1573.
[12] P. Berman, G. Calinescu, C. Shah, and A. Zelikovsky, “Power Efficient Monitoring Management in Sensor Networks,” IEEE WCNC, 2004, vol. 4, pp. 2329–2334.
[13] Guiling Wang, Guohong Cao, and T.La Porta, “Movement-assisted sensor deployment” IEEE INFOCOM, 2004, vol. 4, pp. 2469–2479.
[14] Shu Zhou, Min-You Wu, and Wei Shu “Finding Optimal Placements for Mobile Sensors: Wireless Sensor Network Topology Adjustment,” IEEE 6th Circuits and Systems Symposium on Emerging Technologies: Mobile and Wireless Communication, 2004, vol. 2, pp. 529–532.
[15] Jindong Tan and Ning Xi, “Integration of sensing, computation, communication and cooperation for distributed mobile sensor networks” IEEE International Conference on Robotics, Intelligent Systems and Signal Processing, 2003, vol. 1, pp. 54–59.
[16] Guiling Wang, Guohong Cao, and T. LaPorta, “A bidding protocol for deploying mobile sensors” IEEE International Conference on Network Protocols, 2003, pp.
315–324.
[17] Z. Butler and D. Rus, ”Event-based motion control for mobile-sensor networks”
IEEE Pervasive Computing, 2003, pp. 34–42.
[18] P. Ogren, E. Fiorelli, and N.E. Leonard “Cooperative control of mobile sensor networks: Adaptive gradient climbing in a distributed environment” IEEE Transactions on Automatic Control, 2004, vol. 49, pp. 1292–1302.
[19] Kian Hsiang Low, Wee Kheng Leow, and Jr. M.H Ang., ”Reactive, distributed layered architecture for resource-bounded multi-robot cooperation: application to mobile sensor network coverage” IEEE International Conference on Robotics and Automation, 2004, vol. 4, pp. 3747–3752.
[20] Nojeong Heo and P.K. Varshney, ”An intelligent deployment and clustering algorithm for a distributed mobile sensor network” IEEE International Conference on Systems, Man and Cybernetics, 2003, vol. 5, pp. 4576–4581.
[21] Yihan Li, S.S.Panwar, and S. Burugupalli, ”A Mobile Sensor Network Using Autonomously Controlled Animals” First International Conference on Broadband Networks, 2004, pp. 742–744.
[22] V. Zadorozhny, P.K. Chrysanthis, and A. Labrinidis, ”Algebraic optimization of data delivery patterns in mobile sensor networks” 15th International Workshop on Database and Expert Systems Applications, 2004, pp. 668–672.
[23] Joengmin Hwang, D.H.C. Du, and E. Kusmierek, “Energy efficient organization of mobile sensor networks,” ICPP, 2004, pp. 84–91.
[24] S. Poduri and G.S. Sukhatme, “Constrained coverage for mobile sensor networks,”
IEEE International Conference on Robotics and Automation, 2004, vol. 1, pp.
165–171.
[25] M. Rahimi, H. Shah, G.S.Sukhatme, J. Heideman, and D.Estrin, ”Studying the feasibility of energy harvesting in a mobile sensor network” IEEE International Conference on Robotics and Automation, 2003, vol. 1, pp. 19–24.