Research Article

Modified Floyd–Warshall’s Algorithm for Maximum Connectivity in Wireless Sensor Networks under Uncertainty

Table 2

Significance influence of the different authors towards WSNs.

ReferencesYearSignificance influence

Dijkstra [17]1959A note on two problems in connexion with graphs
Feeney [18]2001An energy-consumption model for routing protocol performance analysis in mobile ad hoc networks
Mainwaring et al. [10]2002WSNs for habitat monitoring
Intanagonwiwat et al. [19]2003WSN directed diffusion
Akyildiz et al. [11]2007A survey of wireless multimedia sensor networks
Farahani [6]2008ZigBee wireless networks and transceivers
Champ and Saad [20]2008Geographic routing with location errors in WSNs: an energy-efficient approach
Flammini et al. [13]2009Sensor networks, both wired and wireless, for industrial applications
Attarde et al. [21]2010A WSN with an improved spanning-tree topology
Doohan et al. [22]2011The shortest path routing protocol (SPRP) for highly data-centric WSNs
Musznicki et al. [23]2012WSN routing algorithm in an interference environment
Salvatore and Yang [24]2012Localized multicast routing based on Dijkstra in WSNs
Ramson and Moni [25]2017WSN applications
Praveen Kumar et al. [14]2019An overview of machine learning algorithms for wireless sensor networks
Xu et al. [26]2020CUF-based FEM analysis of thin-wall structures with Lagrange polynomial expansion
Raman et al. [27]2020An overview of the WSN routing techniques
Yu et al. [28]2020WSN secure directed diffusion routing protocol based on trust
Daanoune et al. [29]2021LEACH-based clustering routing protocols in WSNs
Ullah [30]2021Energy-efficient clustering protocols based on hybrid, energy-efficient, and distributed (HEED) technology for WSNs
Sah et al. [16]2021EDGF: empirical dataset generation framework for wireless network networks
Praveen Kumar et al. [15]2021An extended ACO-based mobile sink path determination in wireless sensor networks