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Page 41

beacon traffic interval
3 20 0.29
4 40 0.31
5 60 0.35
6 80 0.33

4.4 Enhanced composite approach with mobile beacon shortest path
Mobile beacon traverse the deployment area with the shortest path. Deployment
area is partitioned into hexagon cells as in cellular network. The mobile beacon
passes at the mid point of each hexagon cell to follow by any traveling
salesperson algorithm for shortest path. The main goal of this approach is to
reduce the power, required for computation and traversing. When mobile
beacon traverse the shortest path to cover the deployment region definitely it
saves the power. Further this method is cost saving as it required only one GPS
which is inbuilt or physically added in mobile beacon to cover the shortest path.
The deployment area is divided into hexagon cells and mobile beacon trajectory
follow the shortest path, moving center of each hexagon cells reduce the little
bit error in comparison of composite approach. Average traffic not affected by
mobile beacon shortest path so it almost equal to the previous composite
approach. So this method improves a little bit performance and efficiency. We
can see improved mobile beacon trajectory with shortest path in figure 2.3.

Table 4.4 Average position error and traffic of enhanced composite


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No. of

3 20 0.27
4 40 0.29
5 60 0.33
6 80 0.31

When we compare the result of average traffic and error intervals with other
approaches then we find the enhanced composite approach with mobile beacon
shortest path is a bit better then composite approach. But this approach will give
much better result in terms of power saving which reduces the cost also, as
compared the other approaches. When the deployment area is large then this
algorithm plays an important role as it consumes less power. So this algorithm
is good for battlefield surveillances, Industrial and large geographical

Chapter 5

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This proposed method provides high localization precisions, low payload of the
traffic and high self adaptability. However, the requirement of the beacon is
exigent and rigid. When the dimension of the wireless sensor network is very
big, energy depletion leads the infectivity of the mobile beacon. We have
developed an optimal movement schedule for mobile beacon that can achieve a
shortest path under expected localization accuracy using cellular hexagon cells.
Algorithms show that there are some merits and demerits of all the algorithms.
Some localization schemes have fewer merits and greater demerits and some of
them have less demerits and greater merits. These merits and demerits were the
main source for proposing the idea of a unique approach which is the enhanced
composite approach. The proposed algorithm may address those problems
which are faced by company in real time deployment. Definitely the results of
the approach show worth of the localization schemes. It shows the use of an
algorithm, and it is very important to know about the usage of an algorithm.
Localization problem is an open challenge in wireless sensor network. There
are many aspects where we need improvements such as how to define threshold
value in wireless sensor network. Security is another aspects, as the data is
transferred from mobile beacon node to blind node then any of mobile beacon
which is a virus or not secure acting as original mobile beacon transmit false
message, Due to that an error will occur which is harmful for our computation.
Environmental obstacles like indoors, walls, cage, mountains etc are some
issues which comes when we do measurements in real deployment area. So
localization system should be able to overcome these problems.
In future work, we would like to modify this approach to make the already
position aware static nodes to participate in localization. Also the consideration
of changing communication range for the mobile nodes is seen as a potential
area for future work in three dimensional.



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