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研究生:邱炫又
研究生(外文):Chiou, Shiuan - You
論文名稱:在固定封包速率下並基於頻寬分配之事件觸發式無線感測器網路多路徑壅塞控制
論文名稱(外文):A Rate-allocation Based Multi-path Congestion Control Scheme for Event-Driven Wireless Sensor Networks on Constant Event Packet Rates
指導教授:呂芳懌呂芳懌引用關係
指導教授(外文):Leu, Fang - Yie
口試委員:連志誠段裘慶黃其泮楊朝棟
口試日期:2011/07/14
學位類別:碩士
校院名稱:東海大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2011
畢業學年度:99
語文別:英文
論文頁數:64
中文關鍵詞:事件觸發多路徑壅塞控制公平傳輸無線感測器網路速率控制頻寬調整
外文關鍵詞:Event-driven systemsMulti-path congestion controlTransmission fairnessWireless sensor networksRate controlBandwidth adjustment
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在本論文中,我們提出一在事件觸發式無線感測器網路(Wireless Sensor Network, WSN)下,基於速率分配及使用高可用性封包傳遞路徑之多路徑壅塞控制方式(multi-path congestion control approach)。本方式包含兩部分,第一部分為建立一以基地台(sink)為根節點,連接WSN中各感測器之生成樹,並以其為初始路由路徑。第二部分為藉由使用多路徑及速率分配,來建立一公平之封包傳遞環境。一般來說,新事件的發生會增加網路中的流量,將會使新建立的路由路徑上之節點產生雍塞,尤其是在基地台附近之節點,因而破壞原先流量之平衡並導致封包之丟棄。事實上,若干事件之訊息無法即時地傳遞到sink,可能會造成決策者因資訊不足而做出錯誤的決策。而在事件結束時,因停止傳送封包,亦將破壞路由上之中間節點的流量平衡。因此,我們動態地調整頻寬以維持各流量間之公平性和善加利用現有資源。實驗結果顯示本方法可有效的改善無線感測器網路的吞吐量、封包延遲及封包遺失率。
In this paper, we proposed a rate-allocation based multi-path congestion control approach, called multi-path-congestion control method (MUCON for short), which enforcing high path availability of packet delivery for event-driven Wireless Sensor Networks (WSNs) consists of two parts. The first is constructing a spanning tree to connect all sensor nodes of a WSN to the sink for initial routing. The second is establishing a fair packet forwarding environment by employing multi-path and rate control to deliver packets through routing paths with a balanced manner. Generally, the occurrence of an event will increase net flow, which may congest the nodes on the newly established routing path if the nodes are currently shared by several routing paths, particularly for those nodes near the sink, consequently ruining originally balanced traffic on paths and forcing some event packets to be dropped. In fact, without the information conveyed on the lost packets, users may make an inaccurate decision and react improperly for events. When an event disappears, the surrounding sensor(s) stops transmitting packets. This will again destroy the fairness and unbalance net flows flowing through the co-node routing paths. Thus, to maintain the fairness and balance net flows for a WSN, a downstream node needs to dynamically adjust bandwidths for all its upstream nodes. Experimental results show that this method can effectively improve a WSN’ throughputs, shorter end-to-end delays and reduce packet loss rates.
摘要
Abstract
致謝
List of Contents
List of Figures
List of Tables
I. Introduction
II. Related Work
III. The Proposed Scheme
3.1. System phases
3.2. The link establishment phase and configuration table
3.3. The rate allocation and adjustment phase
3.4. Multipath congestion alleviation phase
3.5. Algorithms
IV. Simulation Results and Discussion
4.1. Different Data Rates
4.2. Different Packet Sizes
4.3. Different Number of Events
4.4. Different Event-lasting Times
4.5. Different Node Densities
V. Conclusions and Future Work
References
Appendix

[1]J.P Sheu, L.J. Chang and W.K. Hu, “Hybrid congestion control protocol in wireless sensor networks,” Journal of Information Science and Engineering, vol. 25, 2009, pp. 1103-1119.
[2]F.B. Hussain, G. Seckin and Y. Cebi, “Many-to-one congestion control scheme for densely populated WSNs,” IEEE/IFIP International Conference in Central Asia, 2007, pp. 1-6.
[3]C. Wang, B. Li, K. Sohraby, M. Daneshmand and Y. Hu, “Upstream congestion control in wireless sensor networks through cross-layer optimization,” IEEE Journal on Selected Areas in Communications, vol. 25, 2007, pp. 786-795.
[4]V.P. Munishwar, S.S. Tilak and N.B. Abu-Ghazaleh, Congestion and Flow Control in Wireless Sensor Networks, Guide to Wireless Sensor Networks, Springer London, 2009.
[5]X. Yin, X. Zhou, R. Huang, Y, Fang and S. Li, “A fairness-aware congestion control scheme in wireless sensor networks,”, IEEE Transactions on Vehicular Technology, vol. 58, issue.9, 2009, pp. 5225-5234.
[6]M.M. Monowar, M.O. Rahman and C.S Hong, “Multipath congestion control for heterogeneous traffic in wireless sensor network,” International Conference on Advanced Communication Technology, 2008. pp. 1711-1715.
[7]H. Morino, H. Kawamura, M. Inoue and T. Sanefuji, “Load-balanced multipath routing for wireless mesh networks: A step by step rate control approach,” International Symposium on Autonomous Decentralized Systems, 2009. pp. 1-6.
[8]H.W. Oh, J.H. Jang, K.D. Moon, S.C. Park, E.S. Lee, and S.H. Kim, “An explicit disjoint multipath algorithm for Cost efficiency in wireless sensor networks,” IEEE International Symposium on Personal Indoor and Mobile Radio Communications, 2010, pp. 1899-1904.
[9]N. Stephan, S. Varakliotis, and P. Kirstein, “Transport layer multipath on wireless sensor network backhaul links,” International Conference on Sensor Technologies and Applications, 2009, pp. 469-472.
[10]W.J. Lou, “An efficient N-to-1 multipath routing protocol in wireless sensor networks,” International Conference on Mobile Adhoc and Sensor Systems, 2005, pp. 665-672.
[11]H. Fariborzi and M. Moghavvemi, “EAMTR: energy aware multi-tree routing for wireless sensor networks,” IET Communications, vol. 3, no. 5, 2009, pp. 733-739.
[12]Y. Sankarasubramaniam, Ö.B. Akan and I.F. Akyildiz, “ESRT: event-to-sink reliable transport in wireless sensor networks,” the ACM international symposium on Mobile ad hoc networking & computing, 2003, pp. 177-188.
[13]C.Y. Wan, S.B. Eisenman and A.T. Campbell, “CODA: congestion detection and avoidance in sensor networks,” the international conference on Embedded Networked Sensor Systems, 2003, pp. 266-279.
[14]Y. Xiao, “Concatenation and piggyback mechanisms for the IEEE 802.11 MAC,” Wireless Communications and Networking Conference, 2004, pp. 1642-1647.
[15]B.H. Walke, S. Mangold and L. Berlemann, IEEE 802 Wireless Systems: Protocols, Multi-Hop Mesh/Relaying, Performance and Spectrum Coexistence. Wiley, 2007.
[16] ns-2, http://www.isi.edu/nsnam/ns/

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