=Paper= {{Paper |id=Vol-3058/paper45 |storemode=property |title=Crow Search BEENISH Routing Protocol to Increase The Lifetime And Stability of Nodes In WSN |pdfUrl=https://ceur-ws.org/Vol-3058/Paper-072.pdf |volume=Vol-3058 |authors=Supriya Sharma,Gurpurneet Kaur,Harminder Kaur }} ==Crow Search BEENISH Routing Protocol to Increase The Lifetime And Stability of Nodes In WSN== https://ceur-ws.org/Vol-3058/Paper-072.pdf

Crow Search BEENISH Routing Protocol to Increase the Lifetime
and Stability of Nodes in WSN
Supriya Sharma1, Gurpurneet Kaur2 and Harminder Kaur3
1,2,3
Guru Nanak Dev Engineering College, Ludhiana, Punjab, 141006, India.

Abstract

Routing protocols are utmostneeded for communication between source nodes and sink node,
least disruptive & more efficient. The performance of the network and reliability is generally
determined by selecting appropriate routing protocol. Since energy consumption has become
crucial problem in WSNs, therefore Energy Efficient (EE) routing protocols have been
introduced such as balanced energy-efficient network-integrated super heterogeneous
(BEENISH), improved-BEENISH and enhanced-BEENISH. Optimization techniques are
mandatory for achieving desired goals, minimizing energy depletion and maximizing
network’s life. The aim of this article is to extend the network’s life and stability of sensing
nodes through the use of heterogeneity factors such as alive nodes, dead nodes, throughput
and average residual energy by using the cross-search based balanced energy efficiency
network integrated super heterogeneous(CR-BEENISH) optimization technique.

Keywords

Alive Nodes, Crow Search, Energy Efficiency, Residual Energy, Throughput, Wireless
Sensor Networks.

1. Introduction
Routing protocol is a device that sends the data packets towards sink from source are selected
accordingly. The path selection is based on type of network. Datadetected by nodes is usually
transmitted towards a sink-node, connecting sensor network to the other networks. The task of
developing the protocols for WSNs is very difficult due to several characteristics that make them
distinct from wireless infrastructure [1, 2].In WSN’s there are many major design challenges as
shortage of assets such as capacity, bandwidth and handling power [3] The basic elements
required for designing new routing protocols by a network engineer are as follows: [4].
• Scalability
• Energy Efficiency
• Complexity
• Delay
• Robustness

In WSNs, the energy consumption of nodes is very critical problem. In order to extend WSN’s
lifespan and tomaximizenode’s energy efficiency, a static clustering algorithm is used to
minimize head overhead by sending multi-hop data and splitting the area into multiple areas for
reduction of the energy consumption of cluster heads [5, 6, 7, 8].
Optimization is a method to construct an ideal, functionally suitable design. The optimal goals of
reducing energy efficiency and optimizing network life are assisted by network optimization. The
aims of the projected work are:

1) Performance analysis of Crow Search-based optimized EBEENISH routing protocol.
International Conference on Emerging Technologies: AI, IoT, and CPS for Science & Technology Applications, September 06–07, 2021,
NITTTR Chandigarh, India
EMAIL: sharmasupriya14@ymail.com (A. 1); gurpurneetkaur@gndec.ac.in (A. 2); harminderece@gndec.ac.in (A. 3)
ORCID: XXXX-XXXX-XXXX-XXXX (A. 1); XXXX-XXXX-XXXX-XXXX (A. 2); XXXX-XXXX-XXXX-XXXX (A. 3)
©2021 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0
International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
2) To compare the proposed (crow search) optimized E-BEENISH performance for number of alive
/dead nodes, network lifespan and throughput with the previous work.

2. Crow Search BEENISH to Increase the Lifetime of Nodes
A heterogeneous 4-level network conceptwith alive/dead nodes, advanced, super and ultra-super
nodes are used in the CR-BEENISH protocol. The following flowchart indicates the process of
choosing cluster head using crow search optimization technique:

Start

Selection of Cluster Heads

Calculate probability of nodes

Generate Random Number

Compare Random Number
with Threshold Value

If Random Number
< Threshold Value

Node becomes Head

Figure 1: Flowchart for the selection of cluster head (CH) in CR-BEENISH

If a node has determined which cluster it belongs to, the cluster head must notify its status as a
cluster node. Each node uses this information to be returned to the head cluster. For this, all CH
nodes must retain their recipients. The cluster head node mustmaintain the source to gather all
data from the cluster’s node set. When the cluster is set up, every round begins with a steady
state process where the information is transferred to the Base Station. Then, a heterogeneous four-
layered wireless network threshold is described as:
𝑃𝑖
1
T (si) = { 1−𝑃𝑖 (𝑟.𝑚𝑜𝑑
𝑃𝑖 𝑖𝑓 𝑠𝑖 ∈ {𝑆, 𝑆 ′ , 𝑆 ′′ , 𝑆′′′} (1)
0 𝑒𝑠𝑙𝑒
Firstly, when a cluster is formed, each node first determines if it is the head of the recent
round. The network's current CH percentage (prior determination) is based on this decision
and the total CHs assigned to a particular node. If threshold T(si) is more than the random
number, the node will becomethe cluster head (CH) of the present round.

The CH is chosen based on the amount of energy send by node to the sink as well as the
number of frames. The crow search optimization algorithm works with fusion factor (FF), as
depicted in equation 2 only in the current state.
𝑑0 𝑅𝑒𝑚𝑎𝑖𝑛𝑖𝑛𝑔 𝑒𝑛𝑒𝑟𝑔𝑦 𝑜𝑓 𝐶𝐻𝑠
FF = 𝛾 (𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒 𝑡𝑜 𝑏𝑎𝑠𝑒 𝑠𝑡𝑎𝑖𝑜𝑛) + ∅ ( 𝐼𝑛𝑖𝑡𝑖𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦
) (2)

3. Results and Discussions
The performance of CR-BEENISH protocol is evaluated in thissegment in MATLAB Software.
The sensor nodes are randomly deployed having 100m * 100m area (x and y-coordinates) and
Base Station (BS) at the center. The proposed CR-BEENISH protocol is compared to current E-
BEENISH protocol. The simulation results are given below:
area (in meters)

area (in meters)

Figure 2: Random Deployment of Nodes

The above figure represents that the sensing nodes are organized randomly in a 100m*100m area
including member nodes;cluster heads (CHs) and base station (BS) in the middle or center.

Figure 3:cAlive Nodes versus Number of Rounds

In figure 3, the Enhanced BEENISH protocol clearly shows better performance in the earlyphase,
but it decreases gradually as the number of rounds increases. Above simulations show that
the performance of proposed CR-BEENISH protocol increases with the given total rounds.
Figure 4: Dead Nodes versus No. of Rounds

From fig. 4, it has been clearly analyzed that the dead nodes have been decreased in CR- BEENISH
than the existing E-BEENISH. Hence, the lifetime of the network has been increased.

Figure 5: Throughput versus Number of Rounds

Figure 5 depicts the network's aggregate residual energy. The throughput increases as the number of
data transmissions decrease, where throughput is defined as thenumber of packets successfully
transmitted to the total packets transmitted.The more efficient the algorithm, the more
accurate it will be.

Figure 6: Residual Energy versus Number of Rounds

The results of the average left behind energy for the existing (E-BEENISH) and proposed (CR-
BEENISH) approaches are shown in figure6. This clearly shows that the existing technique
has steeper drops in average residual energy than the proposed algorithm, where steeper drops
indicate faster energy depletion.
4. Conclusion
The proposed CR-BEENISH uses multi-hop communication while the previous method (E-
BEENISH) uses single-hop communication. The numerical results indicate that the algorithm exceeds
the network lifetime,average residual energy and throughput. In addition, by selecting parameters
carefully, for the proposed protocol, the life cycle can be extended further. Finally, more improvement
in performance can enhance the CR-BEENISH adaptability.

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