Heinzelman et al. [3] have presented the Low Energy Adaptive Clustering Hierarchy-LEACH protocol. In LEACH, the cluster heads are chosen arbitrarily and this function of cluster head is transferred among the nodes to ensure uniform utilization of energy in the network. It recuperates energy by turning off receivers of sensor nodes and accomplishes somewhat load compensation also.
Manjeshwar E. and Agrawal D.P [4] introduced Threshold sensitive Energy Efficient sensor Network (TEEN). In TEEN, the surroundings are examined by the nodes frequently and energy consumption is very less as compared to that in dedicated networks, as data is transmitted less frequently.
Younis O. and Fahmy S. [5] introduced Hybrid Energy-Efficient Distributed clustering (HEED). The choice of cluster heads is done systematically on account of remaining energy and the price of communion of the nodes within the cluster. Selected cluster heads have comparatively larger mean residual energy than the member nodes. HEED inculcates even Cluster Head dispersal all over the network and attains some load compensation also.
G. Smaragdakis et al. projected SEP (Stable Election Protocol) protocol [6]. This protocol is a supplementary remodeling of the LEACH protocol. It is a heterogeneity acquainted protocol, wherein according to the energy and weighted probabilities of selection of the nodes, the nodes are involved to be the cluster leader. This technique assures that the cluster head is expeditiously and arbitrarily selected and dispersed on account of fragment of energy of each and every node assuring that there is a homogeneous utilization of energy of the nodes.
Energy Efficacious clustering technique called EECS was proposed by Ye et al. [7]. In this the node which is having greater remaining energy is selected to be the cluster head. There is a fixed number off clusters across the network and direct communication between the cluster leader and terminal station is utilized. In this scheme, the consumption of energy is uniform in the network. Congestion happens because of universal information required for communication. The drawback is that much energy is exhausted because of one hop communication.
Qing et al. [8] have suggested a Distributed Energy-Efficacious clustering technique (DEEC). The proportion of left over energy of each node and the mean value of network energy is used to determine the possibility for appointing the cluster leaders. DEEC works well in case of multiple level heterogeneous wireless sensor networks. It can be observed from the simulation results that DEEC performs well in comparison to the above mentioned protocols. However through comprehensive investigations it has been found that that there is a scope of further enhancement in the lifetime, packet transmission ability and throughput of the network.
Maraiya et al. [9] recommended effective technique for selecting cluster head for the purpose of accumulating data in wireless sensor networks. J. S. Lee and T. Y. Kao [10] suggested an improved three-layer low-energy adaptive Clustering hierarchy for wireless sensor networks. L. Xu et al.[11] conducted a review of clustering approaches in WSNs.
V. K. Kumar and A. Khunteta [12] suggested Energy Efficient PEGASIS Routing Protocol for Wireless Sensor Networks. In this protocol the sensor nodes are linked with the subsequent nearby nodes and the pioneer node is elected for communicating the data to the base terminal station but this creates problem when sensor nodes and base station have larger distance between them resulting in greater delay in transmission and selection of pioneer node, as well as uneven consumption of energy.
A. Shahraki et al.[13] discussed clustering objectives in wireless sensor networks. M. Gheisari et al.[14] also conducted an analysis on clustering algorithms in wireless sensor networks. An analysis on clustering schemes for wireless sensor networks was conducted by Loganathan et al. [15].
Khuspare, M.N., & Khobragade, A.S.[16] carried out a review on various clustering algorithms in WSN for optimal energy utilization in which a survey on energy efficacious clustering calculations used in WSNs has been demonstrated and the advantages of data aggregation have been presented. The fundamental traits affecting the aggregation implementation have also been investigated.
A.Lv et al. [17] performed the investigation on routing algorithm for WSN on the basis of Hierarchical Clustering. Chang et al. [18] recommended an augmented clustering protocol which is based on the density of the nodes for WSN.
It can be observed from the simulation results that DEEC performs well in comparison to the other protocols mentioned above. Also, it has been found through extensive investigations and analysis that the lifetime, packet transference ability, throughput and energy-efficiency of the network as provided by DEEC protocol has the scope of further enhancement, so, in this paper, we have recommended a novel protocol SDEEC (Supplemented Distributed energy efficient clustering) which performs even better than pre-existing protocol DEEC in terms of the aforesaid parameters.