An Improved Gossip based Ad-hoc On-Demand Distance Vector Protocol for Efficient Neighbour Node Discovery

被引：2

作者：

Bethi S. ^{[1
]}

Moparthi N.R. ^{[1
]}

机构：

[1] Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Andhra Pradesh, Vaddeswaram

来源：

J. Inst. Eng. Ser. B | 2022年 / 2卷 / 351-360期

关键词：

Ad hoc on-demand distance vector; Gossip protocol; Neighbor discovery; Node localization; Wireless sensor network;

D O I：

10.1007/s40031-021-00654-x

中图分类号：

学科分类号：

摘要：

Recently, mobile low duty cycle wireless sensor network (MLDC-WSN) is being widely used in many areas, due to the rapid development in the fields of wireless communication and microelectronics. In MLDC-WSN, node localization is important in many applications such as underwater sensor networks, monitoring of objects in outdoor and indoor environments. The major requirement in node localization is to allocate a location to every sensor node since multiple nodes in MLDC-WSN ares utilized for retrieving sensitive information. The main aim of this research study is to address the localization issues using improved gossip-ad hoc on-demand distance vector protocol for an efficient neighbor node discovery. The improved gossip protocol enhances the neighbor node detection by eliminating redundant information, and the ad hoc on-demand distance vector (AODV) routing protocol is used to effectively transmit the information from a source node to the base station. In addition to this, the improved gossip-AODV protocol significantly prevents the issues created by the clock drift of the nodes. Though delay during the data transmission is reduced by avoiding the clock drift issue. The improved gossip-AODV has reduced discovery delay of 0.05, energy consumption, and wake-up time better as compared to the existing selective proactive wake-up fast neighbor discovery (SPND) method. © 2021, The Institution of Engineers (India).

引用

页码：351 / 360

页数：9

共 36 条

[1]

Rao P.S., Jana P.K., Banka H., A particle swarm optimization based energy efficient cluster head selection algorithm for wireless sensor network, Wirel. Netw., 23, 7, pp. 2005-2020, (2017)

[2]

Wang Z.X., Zhang M., Gao X., Wang W., Li X., A clustering WSN routing protocol based on node energy and multipath, Clust. Comput., 22, 3, pp. 5811-5823, (2019)

[3]

Zhu H., Luo M., Hybrid robust sequential fusion estimation for wsns-assisted moving targets localization with sensor node position uncertainty, IEEE Trans. Instrum. Meas., (2020)

[4]

Phoemphon S., So-In C., Leelathakul N., Fuzzy weighted centroid localization with virtual node approximation in wireless sensor networks, IEEE Internet Things J., 5, 6, pp. 4728-4752, (2018)

[5]

Xiao K., Chen Z., Yang C., Estimate information fusion weight of wsns nodes based on truth discovery optimization method among conflicting sources of data, IEEE Access, 7, pp. 35606-35618, (2019)

[6]

Cheng L., Hang J., Wang Y., Bi Y., A fuzzy C-means and hierarchical voting based RSSI quantify localization method for wireless sensor network, IEEE Access, 7, pp. 47411-47422, (2019)

[7]

Dutta S., Obaidat M.S., Dahal K., Giri D., Neogy S., M-MEMHS: modified minimization of error in multihop system for localization of unknown sensor nodes, IEEE Syst. J., 139, 1, pp. 215-225, (2018)

[8]

Shao H.J., Zhang X.P., Wang Z., Efficient closed-form algorithms for AOA based self-localization of sensor nodes using auxiliary variables, IEEE Trans. Sig. Process., 62, 10, pp. 2580-2594, (2014)

[9]

Singh P., Mittal N., An efficient localization approach for WSNs using hybrid DA-FA algorithm, IET Commun., (2020)

[10]

Zhang Y., Wu Y.I., Multiple sources localization by the WSN using the direction-of-arrivals classified by the genetic algorithm, IEEE Access, 7, pp. 173626-173635, (2019)

← 1 2 3 4 →