Secure Cluster based Routing Using Multiobjective Trust Centric Reptile Search Algorithm for WSN

Abstract

Wireless sensor networks (WSN) is self-organizing network that has numerous tiny sensor nodes used to track and monitor applications in an extensive range. However, security and energy consumption are considered two important issues, because of the open medium and restricted energy resources. In this paper, the multiobjective-trust centric reptile search algorithm (M-TCRSA) is proposed to perform the secure cluster based routing for WSN. The M-TCRSA is used to ensure the secure cluster head (SCH) and secure route discovery to achieve reliable communication over the WSN. Hence, the developed M-TCRSA method provides improved security against malicious attacks while enhancing energy efficiency. The main objective of the M-TCRSA is to achieve secure data transmission while increasing the life expectancy of the WSN. The performance of M-TCRSA is analyzed by means of packet delivery ratio (PDR), throughput, end to end delay (EED), jitter and life expectancy. The existing research such as trust-based routing using adaptive genetic algorithm (TAGA), trusted cluster based energy and lifetime aware routing (TCELR), secure clustering and routing using IMFO (SCRIMFO) and cost centric cuckoo search algorithm (CCCSA) are compared with the M-TCRSA. The PDR of the M-TCRSA is 99.27% for 400 nodes which is high when compared to the TAGA, TCELR, SCRIMFO and CCCSA.

TCRP: Trust-aware Clustering and Routing Protocol Based on Atom Search Optimization for WSNs

“…Seresane Venkata Krishna Reddy and Jayanthi Keshava Murthy [24] have introduced the multiobjective-trust centric reptile search algorithm (M-TCRSA) to perform secured cluster based routing in WSN. The M-TCRSA utilized in selecting the secured cluster heads and secure path to provide reliable transmission in WSN.…”

“…The TCRP's performance is measured using energy consumption, throughput, and packet delivery ratio. The performance of the proposed TCRP is evaluated with existing approaches such as SQEER [16], PFCS-ARP-HC [18], TEDG [23] and M-TCRSA [24]. The existing methodologies such as TEDG and M-TCRSA are implemented with the same simulation parameter in table 1 to evaluate the efficiency of TCRP.…”

“…This section provides a comparative examination of the TCRP with prior studies. The previous study SQEER [16], PFCS-ARP-HC [18], TEDG [23] and M-TCRSA [24] are utilized to assess the TCRP's efficiency. Table 2 shows a comparison of the SQEER [16], PFCS-ARP-HC [18], TEDG [23] and M-TCRSA [24].…”

“…The previous study SQEER [16], PFCS-ARP-HC [18], TEDG [23] and M-TCRSA [24] are utilized to assess the TCRP's efficiency. Table 2 shows a comparison of the SQEER [16], PFCS-ARP-HC [18], TEDG [23] and M-TCRSA [24]. According to Table 2, the TCRP outperforms the existing approaches due to its effective balance between the exploration and exploitation phases.…”