Conference Paper

TSDDR: Threshold Sensitive Density Controlled Divide and Rule Routing Protocol for Wireless Sensor Networks

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Abstract

In Wireless Sensor Networks, efficient energy man-agement is of great importance. In this paper, we propose a novel routing protocol; Threshold Sensitive Density Controlled Divide and Rule (TSDDR) to prolong network lifetime and stability period. To achieve these targets, we utilize static clustering with threshold aware transmissions. Simulations are done in MATLAB and the results show that our protocol has 60% longer stability period than LEACH [1] and 36% longer stability period than DDR [2]. We also implemented the Uniform Random Model (URM) to find Packet Drop to make our scheme more practical.

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... To tackle this, many protocols recommended clustering of the network area, a pioneer contribution by W. B. Heinzelman [7]. Fundamentally, clustering divides the field into multiple smaller observation versions thereby making resource management a comparatively convenient task [8]- [11]. However, this requires free and fair election of cluster heads (CHs) in each cluster. ...
... To optimize resources, a sensible decision is to deploy an equal percentage of nodes over different regions to ensure minimization of coverage holes, and elongation of network lifetime. Therefore, in this scenario, we propose to deploy 20% of the nodes in region R 1 and the rest 80% of the nodes to be distributed evenly over R 2,3,..., 8,9 regions as shown in Fig. 3(a). This nodes' deployment always depend upon the network field area and number of nodes. ...
... Note that even though the CH of R 3 is receiving data from CHs of both R 7 and R 8 , this is blessing in disguise. This is because, as shown in the figure, the CHs of both R 7 and R 8 have not received data from all the nodes in its region, since some nodes find another nearest CH, so these CHs are aggregating ...
... To tackle the aforementioned problem, many protocols have exploited and voted for clustering of the network area, a pioneer contribution by W. B. Heinzelman [12], as one of the appreciated methods toward efficient resource utilization. Fundamentally, clustering aims to effectively divide the network field into multiple smaller observation versions thereby making resource management a comparatively convenient task [13]- [15]. However, this requires free and fair election of cluster heads (CHs) in each cluster. ...
... Without loss of generality, let ρ and δ be positive real numbers because for ρ < 0, P would be replaced by −P , and then we would write | ρ | instead of ρ. The commutative probability function can be written as: (13) where ϕ(.) represents the unit Gaussian density function. However, as the integrand (2π) −1 exp(−(p 2 + q 2 )/2) possesses circular symmetry, the numerical property of this in- tegral is a function of length of the origin from ρp + δq = z . ...
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... To achieve these targets, it utilized static clustering with threshold aware transmissions. Simulations were done in MATLAB and the results showed that the protocol has 60% longer stability period than LEACH and 36% longer stability period than DDR [1]. ...
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... We assume the commonly used simple first order radio model [24]. The radio parameters for our model are shown in table 1. ...
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