Statistical Approach Based Cluster Head Selection in Heterogeneous Networks for IoT Applications

Abstract This paper provides an effective Wireless Sensor Network(WSN) routing solution for Internet of Things(IoT) applications cognizant of congestion, security, and interference. Because several sources try to deliver their packets to a destination simultaneously, which is a common case in IoT applications. The proposed congestion and interference aware safe routing protocol is claimed to work in networks with high traffic. The signal to interference ratio (SINR), congestion level, and survival factor is used in our suggested procedure to estimate the cluster head selection factor first. The adaptive fuzzy c-means clustering method clusters the network nodes based on the cluster head selection factor. After that, data packets are encrypted using Adaptive Quantum Logic-based packet coding. Finally, the Adaptive Krill Herd (AKH) optimization method identifies the least congested corridor, resulting in optimal data transmission routing. The exploratory findings show that the provided strategy outperforms previous methodologies in network performance, end-to-end delay, packet delivery ratio, and node remaining energy level.

Download Full-text

Efficient Cluster Head Selection in IEEE 802.11ahfor IoT Applications

International Journal of Advanced Trends in Computer Science and Engineering ◽

10.30534/ijatcse/2021/291012021 ◽

2021 ◽

Vol 10 (1) ◽

pp. 208-213

Keyword(s):

Wireless Lan ◽

Control Mechanism ◽

Cluster Head ◽

Cost Effective ◽

Access Point ◽

Cluster Head Selection ◽

Iot Applications ◽

Ieee 802.11Ah ◽

Simulation Results ◽

Long Range Communication

EEE 802.11ah is a wireless LAN standard in the sub-1-GHz license-exempt bands for cost-effective and long-range communication. The most challenging issue in IEEE 802.11ah is to ensure that thousands of stations associate efficiently with a single access point. When several thousand stations try to associate with the access point during network initialization, it causes channel contention and long association delay. IEEE 802.11ah has introduced an authentication control mechanism (ACM) that divides the stations into groups allowing fewest stations to access the medium. In this paper, we propose to automate the cluster head selection using LEACH. Simulation results reveal that our proposed method is efficient in terms of association delay.

Download Full-text

Developing Multi-Tier Network Design for Effective Energy Consumption of Cluster Head Selection in WSN

Scientific Research Journal ◽

10.24191/srj.v13i1.9386 ◽

2016 ◽

Vol 13 (1) ◽

pp. 116

Author(s):

Wan Isni Sofiah Wan Din ◽

Saadiah Yahya ◽

Mohd Nasir Taib ◽

Ahmad Ihsan Mohd Yassin ◽

Razulaimi Razali

Keyword(s):

Sensor Network ◽

Clustering Algorithm ◽

Cluster Head ◽

Residual Energy ◽

Sensor Nodes ◽

Cluster Head Selection ◽

Energy Usage ◽

Network Cluster ◽

Fuzzy Logic Approach ◽

The Stability

Clustering in Wireless Sensor Network (WSN) is one of the methods to minimize the energy usage of sensor network. The design of sensor network itself can prolong the lifetime of network. Cluster head in each cluster is an important part in clustering to ensure the lifetime of each sensor node can be preserved as it acts as an intermediary node between the other sensors. Sensor nodes have the limitation of its battery where the battery is impossible to be replaced once it has been deployed. Thus, this paper presents an improvement of clustering algorithm for two-tier network as we named it as Multi-Tier Algorithm (MAP). For the cluster head selection, fuzzy logic approach has been used which it can minimize the energy usage of sensor nodes hence maximize the network lifetime. MAP clustering approach used in this paper covers the average of 100Mx100M network and involves three parameters that worked together in order to select the cluster head which are residual energy, communication cost and centrality. It is concluded that, MAP dominant the lifetime of WSN compared to LEACH and SEP protocols. For the future work, the stability of this algorithm can be verified in detailed via different data and energy.

Download Full-text