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研究生:黃宏宗
研究生(外文):Hung-tsung Huang
論文名稱:耐延遲網路下以動態叢集感知建構之訊息傳遞機制
論文名稱(外文):Message Forwarding with Dynamic Cluster Awareness in Delay-Tolerant Networks
指導教授:胡誌麟
學位類別:碩士
校院名稱:國立中央大學
系所名稱:通訊工程學系
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:2014
畢業學年度:102
語文別:英文
論文頁數:85
中文關鍵詞:訊息傳遞機制奈延遲網路動態的叢集
外文關鍵詞:message forwardingdynamic clusteringdelay-tolerant networks
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由於節點之間的連線在耐延遲網路(DTNs)下存在間歇性連線的問題,因此在這樣的環境下設計訊息傳遞機制極具挑戰性。間歇性的連線使得節點很難找到一條來源端到目的端的點對點傳送路徑。因此,在DTNs的環境中,訊息的傳遞必須透過儲存、攜帶與轉送的方式。
在真實情況下,人類的移動行為並非隨機的。相反的其受節點之間的社群關係所影響。然而因為網路拓譜的動態變化,使得要建立能廣泛適用的節點社群關係較為困難。由於上述動機,本論文藉由節點之間的社群關係所造成的節點群聚現象,設計一套新穎的動態叢集感知建構之訊息傳遞機制,簡稱MDCA。其是基於節點的社群關係使節點在網路中所造成的群聚現象。如果訊息可以被傳送到各個叢集,則訊息傳達率將可以被改善
為了達到此目的,MDCA被細分為七個程序: (1) 面積估測 (2) 叢集決策 (3) Quality 值更新 (4) 訊息密度決策 (5) 根據節點的數個度量將節點排名 (6) 節點進入/離開叢集決策 (7) 訊息傳遞。主要做法如下。首先,在程序(1)節點會計算叢集節點密度的期望值。接著在程序(2)節點會判斷是否正位於叢集內。最後透過程序(5)和(6),節點篩選出適合的中繼節點將訊息留在叢集內或散播到各個叢集。此外,MDCA透過訊息密度決策來控制訊息的副本數量,也就是程序(4)。最後,本論文在不同的移動模型上進行大量模擬,包含Random Waypoint (RWP)、Time-Variant Community Mobility model (TVCM)以及真實軌跡檔Infocm06。模擬結果顯示,MDCA在具有人類移動行為的移動模型上有較好的訊息傳達率。

Designing a message forwarding scheme in delay-tolerant networks (DTNs) is a challenging problem due to intermittent connectivity between nodes. The problem of intermittent connectivity makes a node difficult to find an end-to-end path for any source-destination pair in a network. Therefore, the store-carry-and-forward messaging method is used in DTNs.
Movement behavior of humans in real life is not random. A societal relationship exists among nodes. However, dynamic changes of network topology make it difficult to define the general relationship between nodes in a network. This problem motivates the study of this thesis to design a novel message forwarding scheme with dynamic cluster awareness (MDCA), which exploits the nodes’ aggregation phenomenon caused by an implicit relationship among nodes in a network. Because the aggregation phenomenon of nodes will create some clusters in a network, the delivery probability can be improved if messages can be distributed to each cluster.
To achieve this goal, the MDCA design includes seven functional processes: (1) area estimation, (2) cluster decision, (3) quality value update, (4) determining message density, (5) ranking nodes’ metrics, (6) nodes moving in/out of a cluster, and (7) message transmission. Thus, the main idea of MDCA is as follows. First, the node calculates the expected density of nodes in process 1. Secondly, the node determines whether it is in a cluster or not in process 2. Lastly, the node chooses the appropriate relay nodes to carry messages in a cluster through processes 5 and 6. In addition, the MDCA controls the quantity of message copies by determining the message density, i.e., process 4. Furthermore, this study conducts many simulations with various mobility models, including random waypoint (RWP), time-variant community mobility model (TVCM) as well as real trace Infocm06. Performance results show that the MDCA has better delivery probability in the mobility models related to human behavior.

1 Introduction 1
2 Related Work 5
2.1 General Message Forwarding Schemes 5
2.2 Cluster-Related Research 7
2.3 Schemes associate with cluster 8
3 System Model 10
3.1 System model 10
3.2 Forwarding Architecture 11
4 Communication Area Estimation 15
4.1 Single one-hop node 18
4.2 Multiple one-hop nodes 19
4.2.1 In-contact case 20
4.2.2 Non-contact case 25
5 Message forwarding with Dynamic Cluster 32
5.1 Cluster Decision 32
5.2 Message density decision 33
5.3 Quality Value 37
5.4 Leaving on nodes in/out a cluster 39
6 Simulations 40
6.1 Performance Metrics 40
i
6.2 Steps in simulation 41
6.3 Mobility Model Setting 42
7 Experimental Results 46
8 Discussion 64
9 Conclusions and Future Work 66
Bibliography 68
[1] Y. Cao and Z. Sun, “Routing in Delay/Disruption Tolerant Networks: A Taxonomy,
Survey and Challenges,” IEEE Communications Surveys Tutorials, vol. 15, no. 2, pp.
654–677, Feb. 2013.
[2] K. Fall, “A Delay-tolerant Network Architecture for Challenged Internets,” in Pro-
ceedings of the Conference on Applications, Technologies, Architectures, and Proto-
cols for Computer Communications, ser. SIGCOMM ’03. ACM, 2003, pp. 27–34.
[3] Z. Zhang, “Routing in intermittently connected mobile ad hoc networks and delay
tolerant networks: overview and challenges,” Communications Surveys Tutorials,
IEEE, vol. 8, no. 1, pp. 24–37, Jan. 2006.
[4] E. Bulut and B. K. Szymanski, “Exploiting Friendship Relations for Efficient Routing
in Mobile Social Networks,” IEEE Transactions on Parallel and Distributed Systems,
vol. 23, no. 12, pp. 2254–2265, Dec. 2012.
[5] Y. Chen, W. Zhao, M. Ammar, and E. Zegura, “Hybrid Routing in Clustered DTNs
with Message Ferrying,” in Proceedings of the 1st International MobiSys Workshop
on Mobile Opportunistic Networking, ser. MobiOpp ’07. ACM, 2007, pp. 75–82.
[6] H. Dang and H. Wu, “Clustering and cluster-based routing protocol for delay-tolerant
mobile networks,” IEEE Transactions on Wireless Communications, vol. 9, no. 6, pp.
1874–1881, Jun. 2010.
[7] C.-L. Hu and B.-J. Hsieh, “A Density-aware Routing Scheme in Delay Tolerant Net-
works,” in Proceedings of the 27th Annual ACM Symposium on Applied Computing,
ser. SAC ’12. ACM, 2012, pp. 563–568.
[8] A. Lindgren, A. Doria, and O. Schel´en, “Probabilistic routing in intermittently con-
nected networks,” in Proceedings of the 1st International Workshop on Service As-
surance with Partial and Intermittent Resources, Aug. 2004, pp. 239–254.
[9] T. Phe-Neau, M. de Amorim, M. E. M. Campista, and V. Conan, “Examining Vicin-
ity Dynamics in Opportunistic Networks,” in Proceedings of the 8th Annual ACM
Workshop on Performance Monitoring and Measurement of Heterogeneous Wireless
and Wired Networks, ser. PM2HW2N ’13. ACM, 2013, pp. 153–160.
[10] T. Phe-Neau, M. de Amorim, and V. Conan, “Vicinity-based DTN Characteriza-
tion,” in Proceedings of the 3rd Annual ACM International Workshop on Mobile
Opportunistic Networks, ser. MobiOpp ’12. ACM, 2012, pp. 37–44.
[11] T. Spyropoulos, K. Psounis, and C. S. Raghavendra, “Spray and Focus: Efficient
Mobility-Assisted Routing for Heterogeneous and Correlated Mobility,” in Proceed-
ings of the 5th Annual IEEE International Workshop on Pervasive Computing and
Communications, 2007, pp. 79–85.
[12] ——, “Spray and Wait: An Efficient Routing Scheme for Intermittently Connected
Mobile Networks,” in Proceedings of ACM SIGCOMM Workshop on Delay-tolerant
Networking, ser. WDTN ’05. ACM, 2005, pp. 252–259.
[13] A. Vahdat and D. Becker, “Epidemic Routing for Partially Connected Ad Hoc Net-
works,” Tech. Rep., 2000.
[14] Q. Yuan, I. Cardei, and J. Wu, “An Efficient Prediction-Based Routing in Disruption-
Tolerant Networks,” IEEE Transactions on Parallel and Distributed Systems, vol. 23,
no. 1, pp. 19–31, Jan. 2012.
[15] ——, “Predict and Relay: An Efficient Routing in Disruption-tolerant Networks,”
in Proceedings of the 10th Annual ACM International Symposium on Mobile Ad Hoc
Networking and Computing, ser. MobiHoc ’09. ACM, 2009, pp. 95–104.
[16] S. Ahmed and S. S. Kanhere, “Characterization of a large-scale Delay Tolerant Net-
work,” in Proceedings of the 35th Annual IEEE Conference on Local Computer Net-
works (LCN), Oct. 2010, pp. 56–63.
[17] C. Xia, D. Liang, H. Wang, M. Luo, and W. Lv, “Characterization and modeling
in large-scale urban DTNs,” in Proceedings of the 37th Annual IEEE Conference on
Local Computer Networks (LCN), 2012, pp. 352–359.
[18] P. Tournoux, J. Leguay, F. Benbadis, V. Conan, M. de Amorim, and J. Whit-
beck, “The Accordion Phenomenon: Analysis, Characterization, and Impact on DTN
Routing,” in Proceedings of IEEE INFOCOM, Apr. 2009, pp. 1116–1124.
[19] P. Tournoux, J. Leguay, F. Benbadis, J. Whitbeck, V. Conan, and M. de Amorim,
“Density-Aware Routing in Highly Dynamic DTNs: The RollerNet Case,” IEEE
Transactions on Mobile Computing, vol. 10, no. 12, pp. 1755–1768, Dec. 2011.
[20] D. B. Johnson and D. A. Maltz, “Dynamic source routing in ad hoc wireless net-
works,” in Mobile Computing. Kluwer Academic Publishers, 1996, pp. 153–181.
[21] W.-J. Hsu, T. Spyropoulos, K. Psounis, and A. Helmy, “Modeling Spatial and Tem-
poral Dependencies of User Mobility in Wireless Mobile Networks,” IEEE/ACM
Transactions on Networking, vol. 17, no. 5, pp. 1564–1577, Oct. 2009.
[22] J. Scott, R. Gass, J. Crowcroft, P. Hui, C. Diot, and A. Chaintreau,
“{CRAWDAD} data set cambridge/haggle (v. 2006-01-31),” Downloaded from
http://crawdad.org/cambridge/haggle/, 2006.
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