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On the Cluster Based Dynamic Channel Assignment for Multihop Ad Hoc Networks

On the Cluster Based Dynamic Channel Assignment for Multihop Ad Hoc Networks. Advisor: Wen-Hsing Kuo Presenter:Che-Wei Chang. Ting-Chao Hou; Tzu-Jane Tsai; Journal of Communications and Networks Volume 4, no. 1, March 2002 Page(s):40-47. Abstract.

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On the Cluster Based Dynamic Channel Assignment for Multihop Ad Hoc Networks

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  1. On the Cluster Based Dynamic Channel Assignment for Multihop Ad Hoc Networks Advisor: Wen-Hsing Kuo Presenter:Che-Wei Chang Ting-Chao Hou; Tzu-Jane Tsai; Journal of Communications and Networks Volume 4, no. 1, March 2002 Page(s):40-47

  2. Abstract • Wefirst propose a new clustering algorithm to facilitate subsequent channel assignment. • Then two dynamic channel assignment (DCA)strategies are designed to make the best use of available channels by taking advantage of the spatial reuse concept. • Onestrategy tries approaching a compact-channel pattern so thatthe channel reuse efficiency can be enhanced. • On the otherhand, the other strategy tries reducing the control overheadon the channel assignment so that the users can have a lowerpower consumption.

  3. Content • Introduction • Cluster Architecture and Algorithm • Cluster Structure • Color-Based Clustering Algorithm(CBCA) • Hidden Terminal Problem in CBCA • Dynamic Channel Assignment • Greedy-Based DCA • Channel-Segregation DCA • Mobility Issue • Simulations • Cluster Stability and Overhead Evaluation • Performance on DCA • Conclusions

  4. Introduction(1/2) In general, to ensure efficient network control, nodes are aggregated into clusters to provide a convenient framework [1]-[4]. Most previous studies on DCA targeted at cellular systems [7]-[11]. Some [7], [8] were concerned about maximizing the channel spatial reuse and various compact pattern (CP) based channel assignment strategies were proposed. Forco-channels in term of C/I (Carrier/Interference) ratio, Fanget al. [9] proposed a Greedy-based DCA strategy that canbe applied to any irregular cell shape.

  5. Introduction(2/2) Instead of the above centralized operations, the authors in [10], [11] devised a fully-distributed channel allocation algorithm named ”Channel Segregation”. we first propose the color-based clustering algorithm (CBCA). Additionally, two DCA strategies, Greedy-based (GB-DCA) and Channel-Segregation (CS-DCA) algorithms,based on a CBCA cluster structure are designed. The clusterheads in GB-DCA have to record the usage status of allchannels by exchanging information continually. On the other hand, the clusterheads in CS-DCA keep trackof the channel status independently by themselves.

  6. Cluster Architecture and Algorithm(1/5) Fig. 1. An example of the cluster structure in ad hoc networks • Two assumptions are made in this paper. • One is that every node has a unique node ID. • The second is that the transmission ranges for all nodes are equal.

  7. Cluster Architecture and Algorithm(2/5) • The qualification for being a clusterhead may require the node with slow moving speed, morepowerful equipment, or a larger node-degree [15]. • A ”successor” or ”backup” to the clusterhead is needed to take overthe original cluster structure when the clusterhead ceasesto function. • When a node (say, node i) becomes active, it calculates its priority sum, , where mi, pi, diare the moving speed, battery power, and node-degree of node i, respectively.

  8. Cluster Architecture and Algorithm(3/5)

  9. Cluster Architecture and Algorithm(4/5)

  10. Cluster Architecture and Algorithm(5/5) • The hidden terminal problem has been shown to cause severe system performance degradation in wireless LAN and packet radio networks [16]-[19]. Fig. 4. Hidden Terminal Problem in a clustered ad hoc network. 1. 2. 3.

  11. Dynamic Channel Assignment(1/2) Fig. 5. Algorithm of GB-DCA.

  12. Dynamic Channel Assignment(2/2) Fig. 6. Flowchart of CS-DCA

  13. Simulations(1/7) This section shows the stability and overhead evaluation of CBCA in comparison with the clustering algorithms in [3]. In [3], two clustering algorithms are evaluated: one is ABCP (Access-Based Clustering Protocol) and the other is CM (Cluster Maintenance). In the following CBCA simulations, the three weighting factors (alpha, beta, gamma)are set as.

  14. Simulations(2/7) Fig. 7. Stability of the cluster structure versus speed.

  15. Simulations(3/7) Fig. 8. Overhead evaluation of cluster maintenance.

  16. Simulations(4/7) Fig. 9. Channel reuse efficiency vs. transmission range.

  17. Simulations(5/7) Fig. 10. Spatial reuse with different node density.

  18. Simulations(6/7) Fig. 11. Average number of used channels vs. transmission range.

  19. Simulations(7/7) Fig. 12. Overhead evaluation of channel update.

  20. Conclusions In this paper, we first propose a clustering algorithm, CBCA, to construct a multi-cluster structure. Additionally, we design two DCAstrategies, GB-DCA and CS-DCA, for the channel assignment among clusters. Simulation experiments show that the cluster structure by CBCA is morestable than other algorithms though it requires a few moreoverheads. The two DCA strategies are also evaluated interms of channel reuse efficiency and control overheads.

  21. Thanks for Your Attention!

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