This report proposes two topology control schemes, namely SmartBone and HCR separately, in wireless sensor networks. The first proposed scheme in the report, SmartBone, selects proper backbone nodes in wireless sensor networks.
Flow-Bottleneck preprocessing is adopted to obtain critical-aware nodes, and Dynamic Density Cutback is adopted to reduce the number of redundant nodes efficiently. A significant result of this section is that the proposed algorithm can achieve a 50% smaller backbone than previous algorithms, and improves the energy saving ratio from 25% using traditional methods to 40% using SmartBone. Moreover, SmartBone improves packet delivery ratio from 40% using traditional methods to 90% when the density of sensor networks become sparse due to the node failure.
The second proposed scheme in the report has modeled and analyzed the performance of HCR in wireless sensor networks. The objective of the HCR is to choose the appropriate nodes for the next hop and to perform path aggregation. The end-to-end transmission delay of HCR is as short as brute-force method, and the power consumption of HCR is efficient comparing with other methods. The impact of failed nodes was studied, and Lazy Grouping was proposed to improve the robustness of HCR. In addition to providing the maintenance algorithm, the proposed algorithm performs restricted flooding to handle the effects caused by the fault nodes. A major result of HCR is that only about 15% of nodes out of 400 are NTR. Furthermore, in LG-HCR algorithm, only about 7% of nodes out of 400 are NTR. The flooding scopes of the two methods are similar. About 5% of 400 nodes are needed to be updated with correct HCVs. The performance of restricted flooding is compared with using full-scale flooding. HCR is a complete solution comprising routing, grouping and maintenance. HCR performs significantly better than other algorithms, since it simultaneously considers energy cost and transmission delay.
Our study results have been accepted in four international conferences and four domestic conferences. The achievement has brought about accomplishment of eight master theses. By executing this project, we expect to bring the most advanced research in the world to Taiwan, and potentially will become the performance benchmark for the energy efficient design for next generation mobile devices such as wireless sensor nodes.
Appendix:
[Lemma 1] Node-X is assumed to have one neighbor node-Y, and the HCVs of the two nodes are (X1,X2,X3,...,Xn) and (Y1,Y2,Y3,...,Yn) separately. It exists the formula that
|Xk-Yk||≤ 1, for any k in the range [1 to n], and if node-X and node-Y are neighbor nodes.
[Proof] Without loss of generality, supposes two nodes, node-A and node-B like Fig.
45 shows, are neighbor nodes. The HCV of node-A is equal to n, and the undecided HCV of node-B is equal to n+k (k>1) which obtained through path 1. However, according to the assumption, node-A and node-B are neighbor nodes, it exists a path which costs 1-hop to achieve another node like path 2. Therefore, the undecided HCV of node-B is equal to n+1. Since n+1 is less than n+k (k>1), the HCV of node-B is equal to n+1 based on the definition of HCV. Hence, the difference in HCV between node-A and node-B is not more than one. Scilicet, the property of |Xk-Yk||≤ 1 is guaranteed for any k in the range [1 to n].
Fig. 45. The mathematical proof of lemma 1
[Lemma 2] Assumes that node-X exists in the network topology, according to HCR algorithm, messages could achieve each sinks from node-X. This property guarantees HCR works.
[Proof] We would prove that two propositions subsist. The first proposition is that there exists certainly routing paths to achieve each sinks. The second proposition is that HCR could find routing paths to achieve each sinks. According to lemma 1, the first proposition is straightforward. For each sink-k, we could individually find a neighbor of node-X which is more close to the sink-k. The rest may be deduced by
analogy. Finally, we could get the destination. The following is the proof of the second proposition:
Assumes that node-X is in the network topology and the HCV of node-X is (X1,X2,X3,...,Xn). According to lemma 1, we could find n nodes, namely node-N1, node-N2, …, and node-Nn, which are more close to sinks than node-X. The HCV of Nk
is (Nk,1, Nk,2, Nk,3, ..., Nk,k, ..., Nk,n) and Nk,k < Xk which k is in the range [1 to n]. Based on Set Cover algorithm, without loss of generality, we have j nodes which are I1,k1, I2,k2, I3,k3, ..., Ij,kj and satisfies that:
node-N1 = node-N2 = …= node-Nk1 = I1,k1 ; node-Nk1+1 = node-Nk1+2 = …= node-Nk2 = I2,k2 ;
…
node-Nkj-1+1 = node-Nkj-1+2 = …= node-Nkj = Ij,kj = Ij,n ;
These intermediate nodes, namely I1,k1, I2,k2, I3,k3, ..., Ij,kj are more close to sinks than node-X. Tautologically, for each intermediate node-I, there exists certainly routing paths to achieve the restricted part of sinks based on the first proposition. Therefore, we could find routing paths to achieve each sinks from node-X using HCR algorithm.
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