PYTHAGOREAN EQUATION BASED SIMPLE PAIRING IN THE WIRELESS SENSOR NETWORK FOR SLEEP SCHEDULING

: The node pairing is the mechanism to pair the nodes on the basis of their behavior, distance or other parameters in order to serve the various purposes in the case of wireless networks. The simplest node pairing can be accomplished on the basis of node distance, which must be equal to or lesser than the maximum transmission distance decided according to the wireless standard or node’s capability. The node pairing has been tested up to various extents in this paper, while using the simplest node pairing. The network performance is thoroughly analyzed on the basis of various performance parameters, where the primary performance indicators are throughput and transmission delay. The proposed model is observed as a scalable and balanced solution for the wireless networks, which has been clearly observed from the results.


INTRODUCTION
Other than amplifying the network lifetime of network nodes, it is desirable over disperse the vitality scattered all through the remote sensor network with the specific goal for limit upkeeping and augment general framework execution. Any correspondence protocol that includes synchronization between peer hubs causes some overhead for the incorporating of correspondet nodes. WSN routing or grouping protocols decide if the advantages of more mind boggling routing calculations eclipse the additional control messages every hub needs to impart. Every hub could settle on the most educated choice in regards to its correspondence choices in the event that they had finish information of the whole network topology and power levels of the considerable density of the wireless sensor nodes in the given network. This undoubtedly demonstrates to yield the best execution if the synchronization messages are not considered. Notwithstanding, since each of the sensor nodule would dependably need worldwide information, the cost of the synchronization messages would at last be exceptionally costly. For both the dispersion and bunching calculations, we will dissect both practical and ideal plans with the detailed aim for acquisition for understanding in the properties of both methodologies.

LITERATURE REVIEW
Chen, Manju [1] et. al. has built up a novel threedimensional restriction calculation in view of DV-HOP. Its situating deviation is too substantial to discover the obscure hubs, and the extent of scope is too little to discover each of the sensor nodes. Gayan Samiru et. al. [2] has worked on the enhancement of DV-Hop counting or evaluation mechanisms, which are specifically designed for the estimation of node and setting up their particular positioning in the given topology. The node positioning is quite important for the node pairing during the sleep scheduling applications, hence the node positioning accuracy has been further improved in this model to create the highly compatible pairs. Bal Mert et. al. [4] has developed a testbed environment for the testing of the sleep scheduling based simulations in the multi-parameter based performance. This test-bed has been specifically constructed to offer the efficient network localization practices along with the node status and node health monitoring in the WSNs. Shekofteh, S. Kazem [5] et. al. has built up a limitation calculation for wireless sensor networks utilizing the Tabu and Series based network route inquiry and recreated tempering. This paper proposes a strategy in which the restriction is done through two stages. Pei, Zhongmin et. al. [6] have built up a grapple free limitation technique for versatile focuses in coal mine wireless sensor networks. Kumar, Anil, Arun Khosla [7] and others have chipped away at Meta-heuristic range based hub limitation calculation for WSNs. Tan Liping et. al. [8] has carried out his work towards the improvement in the localization of the WSNs, which has been primarily accounted around the moving anchor or beacon nodes in the given simulation. The primary improvement is primarily made to the WSN in coordination with with higher order of innovation among the WSNs, which coordinate information obtaining, preparing and transmission, correspondence, cause the consideration of individuals.

EXPERIMENTAL DESIGN
The proposed model is based upon the simplest distance based pairing mechanism, which is used to create the lower level connectivity to segment the network in the different active zones with time synchronization. In this paper, the primary focus lies upon the neighbor formation with the non-paired devices, where all of the paired nodes are labeled with different labels, such as 0 for first node in each pair and 1 for the second node in the given pair. The pairing has been tested in the 2-D plane using the 2-D (x,y) coordinates. The pairing method is designed according to the following algorithmic workflow:    In figure 1.2, the performance of this proposed optimized sleep scheduling oriented duty cycling model has been evaluated over the given set of nodes in the experimental simulation. The transmission delay in the simulation is recorded up to 0.14 seconds, which is considerably and significantly lower in relation to general requirements for data delivery services. Also the non-zero value for transmission delay are recorded between 0.02 and 0.04 seconds on nearly all of the events, excluding the peak between 1 st and 2 nd seconds, which could be caused by the higher volumes of data received during this time event.
Overall result of this model indicates the significant and stable performance in this scheme under the sleep scheduling paradigm.

CONCLUSION
This proposed model is based upon the 1-hop and 2-hop neighbor formation for the implementation of this model smart pairing model over the 802.11 standard. The proposed scheme's performance is analyzed with various performance parameters of throughput and transmission delay. The throughput readings has been observed for the complete simulation of nearly 10 seconds, where the minimum nonzero value has been recorded at 0.0506 KBps and maximum value of 15.6 KBps during the wireless network setup phase. The proposed model has been recorded at 0.025 as the minimum non-zero value, whereas the maximum value of 0.35 seconds is observed from the simulation model, which can be easily considered as the efficient value for the transmission delay across the wireless network.