Energy balanced optimum path determination based on graph theory for wireless sensor network

2015 ◽  
Vol 5 (6) ◽  
pp. 290-298 ◽  
Author(s):  
Shilpa Mahajan ◽  
Jyoteesh Malhotra ◽  
Sandeep Sharma
2021 ◽  
Author(s):  
Abdul Muneera ◽  
T. Nageswara Rao ◽  
R. V. N. Srinivasa ◽  
J. Venkateswara Rao

Abstract The intend of the paper is to grant the centrality of fuzzy graph (f-graph) hypothetical ideas and the uses of dominations in fuzzy graphs to different genuine circumstances in the territories of science and designing. It is seen an eminent development because of various applications in PC and correspondence, biomedical, atomic material science and science, interpersonal organizations, natural sciences and in different various regions. Interpersonal organizations are the zones where countless individuals are associated. A wireless sensor Network (WSN) remote system which comprises of spatially circulated independent sensors to screen the physical or ecological conditions, for example, pressure, temperature, sound and so forth and to communicate their data through the remote system to a fundamental area. This paper gives an audit of the employments of Fuzzy Graph theory in different sorts of fields.


2020 ◽  
Vol 11 (2) ◽  
pp. 107-114
Author(s):  
Ahmed S. Al-Zuhairi ◽  
Alaa H. Altimimy ◽  
Ali T. Al-Aqbi ◽  
Hazim M. Al-Kargole

AbstractGrowing ramification in WSN contemplations are not restricted to routing, construction of protocols, dynamic of mobile nodes and infrastructure of the network. Although transcended to geometric level demonstrated as computational and dynamical geometries in spite of graph theory. In this paper we present step forward recognition features of a network devoted to solve the problem of reconstructing the disconnected network by connecting any disconnected chains. It considers geometrical properties of random depletion nodes deviated from unit grid. Number of chains and number of nodes in each chain are calculated with the average number of connections to a total nodes and longest chain. Histogram represented number of chains and numbers of nodes for each chain are used to show fragmentation of the network. Algorithm included a method to translate adjacent matrix to chain matrix and vice versa to check the agreement of initial case with the results. The amount of chain deviation and average connections per node for longest connected chain and for the total network are drawn as bar charts and conduct interpretations.


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