Energy Efficient Strategy for WSN Technology Using Modified HGAF Technique

Abstract

<p class="0affiliation">Due to the rapid growth in technologies has led to the development of sensor nodes. As we know that wireless sensor network is collection of small and large number of sensor node. These sensor nodes are used for different domain like environmental research, health care, monitor, military, and record the physical activity. These nodes communicate with each other and forward the message to base station. For communication of these node different algorithms used Geographical adaptive fidelity (GAF) is one of them. Dropping energy utilization in wireless sensor network directly affects the network lifetime. HGAF is one of the important multiple location based on routing system algorithm. The main function of HGAF technique is to turn-off the unnecessary nodes in the network without interrupting the other connected node. In this paper we proposed a technique known as modified HGAF and it design as a power saving method. In the proposed technique the size of cell structure in grid changed and communication method improve due to those changes. Based on the result the proposed technique increase 25% in dead node ratio and also increase the network.</p>

Enhanced GAF protocol based on graph theory to optimize energy efficiency and lifetime in WSN technology

“…In fact, many sensors network protocols have been developed in recent years. Previous work in the areas of data collection (Qi and Qiu, 2009; Grover et al , 2014b; Kaur and Gujral, 2016; Aznaoui et al , 2021a, b) encourages us to develop an effective approach for large-scale sensor networks. Based on the minimum routing cost trees regenerated by our E-GAF version based on graph theory, the optimal message transmission path was selected, which reflects the significant importance of this step in optimizing the consumption of energy in a WSN (Aznaoui et al , 2019).…”

“…Moreover, it is very conservative because it guesses its connectivity instead of measuring it directly, which results in less energy savings (Roychowdhury and Patra, 2010). To this end, some versions seem to exceed these limits such as the diagonal GAF (DGAF) protocol which allows direct communication between two diagonal grids (Shang and Liu, 2012), two-level GAF (TGAF) that overcome the problem of communication between only neighboring grids (Vaibhav and Dheeresh, 2015), optimized GAF that improve transitions between node states (Grover et al , 2014b), dislocated grid GAF (GAFDG) that help overcome the problem of limited energy (Zu-jue et al , 2012), hierarchical GAF (HGAF) which also improve energy efficiency by increasing cell size, and using a layered structure in each cell to select active nodes (Inagaki and Ishihara, 2009; Aznaoui et al , 2021a), cooperative agents GAF (CAGAF) that improve routing path to reduce energy consumed (Aznaoui et al , 2019), etc. Given the limitations of GAF protocol and its many improved versions to overcome the problems encountered in the wireless communication sector, we propose an enhanced version of GAF based on the theory of graphs, linear mathematical programming and data aggregation to save and reduce energy consumption and extend the network lifetime.…”

A secure routing protocol for wireless sensor network

“…However, the original routing protocols generally lack security considerations at the beginning of design and are very susceptible to various network attacks. Therefore, considering the energy efficiency and security of the network comprehensively, designing a suitable key distribution scheme and a lowenergy secure routing protocol for wireless sensor networks has high application value [3][4][5].…”