Lifetime prolongation of a wireless charging sensor network using a mobile robot via linear Diophantine fuzzy graph environment

Abstract Edge networking plays a major part in issues with computer networks and the path. In this article, linear Diophantine fuzzy (LDF) graphs, we present special forms of bridges, cut-vertices, cycles, trees, forests, introduce some their characteristics. Also, one most researched sets (LDFS) systems is minimum spanning tree (MST) problem, where arc costs have values. work, focus on an MST issue graph (LDFG), each length allocated number (LDFG) rather than real number. The LDFN can reflect uncertainty LDFG’s costs. Two critical must be addressed problem LDFG. One determining how to compare LDFNs, i.e., cost edges. other question calculate edge addition determine LDF-MST. To overcome these difficulties, score function representation LDFNs utilized Prim’s method well-known approach for solving minimal which ignored, precise values lengths are supplied. This technique works by providing more energy nodes dependent position tree. addition, illustrated example provided explain suggested approach. By considering mobile charger vehicle that travels across sensor network regular basis, charging batteries node.