Distributed Dynamic Cluster-Head Selection and Clustering for Massive IoT Access in 5G Networks

With the rapid growth of Internet-of-things (IoT) devices, IoT communication has become an increasingly crucial part of 5G wireless communication systems. The large-scale IoT devices access results in system overload and low utilization of energy efficiency under the existing network framework. In this paper, the cluster head uses the LTE-M protocol, and the intra-cluster uses the low-power wide-area network (LPWAN) self-networking protocol in the wireless sensor network. By a detailed analysis of the messages exchanged between the device and the base station, we describe the causes of overload and the steps of data aggregate combined with the physical channel. Then, we explore the cluster head quantity and the optimal scale in the intra-cluster under the traditional K-mean algorithm. When K is 30 under specific resources, the simulation results show that the system’s access success probability and resource utilization are optimal. Also, we propose a distributed dynamic cluster-head selection and clustering scheme based on an improved K-means algorithm. Simulation results show that the proposed scheme can reach 88.07% on the access success probability. The throughput and resource utilization are 3.5 times high than that of the optimal K-means.

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Research and Improvement about LEACH Routing Protocol for Wireless Sensor Networks

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.241-244.1028 ◽

2012 ◽

Vol 241-244 ◽

pp. 1028-1032

Author(s):

Li Wang ◽

Qi Lin Zhu

Keyword(s):

Routing Protocol ◽

Routing Algorithm ◽

Cluster Head ◽

Wireless Sensor ◽

Cluster Head Selection ◽

Selection Algorithm ◽

Energy Factor ◽

Random Cluster ◽

Simulation Results ◽

Node Energy

In recent years, as the development of wireless sensor network, people do some deep researches on cluster-based protocol, most around the prolongation of the lifetime of WSN and decline of energy consumed by the sensors. This paper analyses of classical clustering routing protocol based on LEACH, aiming at the node energy foot presents energy improved clustering routing algorithm, the random cluster head selection algorithm of threshold to be changed, lowering the threshold, in the original threshold increases the node's remaining energy factor, reduces the communication load of cluster nodes, and simulation. The simulation results show that the LEACH-E improved algorithm, energy saving, reducing balance node energy consumption, effectively prolongs the network lifetime.

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Implementation of LEACH Protocol for Cluster Head Selection in D2D Cooperative Communication Systems

10.1109/cosite52651.2021.9649556 ◽

2021 ◽

Author(s):

Isyatur Raziah ◽

Yunida Yunida ◽

Rusdha Muharar ◽

Yuwaldi Away ◽

Nasaruddin Nasaruddin

Keyword(s):

Cooperative Communication ◽

Communication Systems ◽

Cluster Head ◽

Cluster Head Selection ◽

Leach Protocol

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Optimization of Energy Efficient Advance Leach Protocol

International Journal on Recent and Innovation Trends in Computing and Communication ◽

10.17762/ijritcc.v9i5.5472 ◽

2021 ◽

Vol 9 (5) ◽

pp. 07-16

Author(s):

Sandeep Kaur ◽

Dr. Rajeev Bedi ◽

Mohit Marwaha

Keyword(s):

Wireless Sensor Networks ◽

Energy Conservation ◽

Network Lifetime ◽

Energy Efficient ◽

Sensor Node ◽

Cluster Head ◽

Base Station ◽

Wireless Sensor ◽

Cluster Head Selection ◽

Leach Protocol

In WSNs, the only source to save life for the node is the battery consumption. During communication with other area nodes or sensing activities consumes a lot of power energy in processing the data and transmitting the collected/selected data to the sink. In wireless sensor networks, energy conservation is directly to the network lifetime and energy plays an important role in the cluster head selection. A new threshold has been formulated for cluster head selection, which is based on remaining energy of the sensor node and the distance from the base station. Proposed approach selects the cluster head nearer to base station having maximum remaining energy than any other sensor node in multi-hop communication. The multi hop approach minimizing the inter cluster communication without effecting the data reliability.

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An energy optimized path selection and dynamic Cluster head selection for Wireless Mesh Network

2017 International Conference on Trends in Electronics and Informatics (ICEI) ◽

10.1109/icoei.2017.8300931 ◽

2017 ◽

Cited By ~ 1

Author(s):

Bhawna Gangwar ◽

J.D. Bhosale ◽

Neha Gangwar

Keyword(s):

Wireless Mesh Network ◽

Cluster Head ◽

Path Selection ◽

Mesh Network ◽

Cluster Head Selection ◽

Dynamic Cluster ◽

Wireless Mesh ◽

Selection For

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EEDCHS-PSO: Energy-Efficient Dynamic Cluster Head Selection with Differential Evolution and Particle Swarm Optimization for Wireless Sensor Networks (WSNS)

Evolution in Computational Intelligence - Advances in Intelligent Systems and Computing ◽

10.1007/978-981-15-5788-0_67 ◽

2020 ◽

pp. 715-726

Author(s):

T. Guhan ◽

N. Revathy ◽

K. Anuradha ◽

B. Sathyabama

Keyword(s):

Wireless Sensor Networks ◽

Particle Swarm Optimization ◽

Sensor Networks ◽

Differential Evolution ◽

Energy Efficient ◽

Cluster Head ◽

Wireless Sensor ◽

Cluster Head Selection ◽

Swarm Optimization ◽

Dynamic Cluster

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Congestion Avoidance and Delay Minimization in Energy Aware Routing of Dynamic ieee 802.11s WMN

International Journal of Embedded and Real-Time Communication Systems ◽

10.4018/ijertcs.2016010105 ◽

2016 ◽

Vol 7 (1) ◽

pp. 85-112 ◽

Cited By ~ 1

Author(s):

S.P. Shiva Prakash ◽

T.N. Nagabhushan ◽

Kirill Krinkin

Keyword(s):

Mesh Networks ◽

Cluster Head ◽

High Energy ◽

Base Station ◽

Base Stations ◽

Cluster Head Selection ◽

Slot Allocation ◽

Proposed Model ◽

Slot Scheduling ◽

Link Duration

Minimization of delay in collecting the data at any base stations is one of the major concerns in cluster based Wireless Mesh Networks. several researches have proposed algorithms to control congestion considering static nature of a node. Mobility of a node results in high congestion due to frequent link breakages and high energy consumption due to re-establishment of route during routing process. Hence, the authors consider dynamic nodes with single hop inside the static cluster. The proposed model includes four modules namely, Cluster head selection, slot allocation, slot scheduling and data collection process. the cluster head selection is based on the maximum energy, number of links and link duration. Slot allocation is based on the available energy () and the required energy (). Slot scheduling is carried out based on the link duration. Data at the base station will be collected as they are scheduled. Model is tested using Network Simulator-3 (NS3) and results indicate that the proposed model achieves least delay besides reducing the congestion compared to the existing methods.

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A Probability-Based Clustering Algorithm with CH Election for Expanding WSN Life Span

International Journal of Electronics, Communications, and Measurement Engineering ◽

10.4018/ijecme.2020010101 ◽

2020 ◽

Vol 9 (1) ◽

pp. 1-14

Author(s):

Dimitris N. Kanellopoulos ◽

Pratik Gite

Keyword(s):

Clustering Algorithm ◽

Cluster Head ◽

Residual Energy ◽

Base Station ◽

Wireless Sensor ◽

Signal Power ◽

Aggregated Data ◽

Simulation Results ◽

Buffer Length ◽

Energy Buffer

Clustering achieves energy efficiency and scalable performance in wireless sensor networks (WSNs). A cluster is formed by several sensors nodes, and one of them is elected as Cluster-head (CH). A CH collects information from the cluster members and sends aggregated data to the base station or another CH. This article proposes a new clustering algorithm (EMESISC) that is based on each node's probability of becoming a CH. This node's probability depends on its residual energy, buffer length, and received signal power. We compared EMESISC with LEACH algorithm. Simulation results showed that EMESISC is superior to LEACH.

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Energy Aware Cluster Head Selection for Maximizing Lifetime Improvement in Internet of Things

International Journal of Grid and High Performance Computing ◽

10.4018/ijghpc.2017100105 ◽

2017 ◽

Vol 9 (4) ◽

pp. 71-91 ◽

Cited By ~ 3

Author(s):

Praveen Kumar Reddy Maddikunta ◽

Rajasekhara Babu Madda

Keyword(s):

Energy Efficiency ◽

Internet Of Things ◽

Hybrid Algorithm ◽

Artificial Bee Colony ◽

Cluster Head ◽

High Energy ◽

Superior Performance ◽

Cluster Head Selection ◽

Bee Colony ◽

Iot Devices

Energy efficiency is a major concern in Internet of Things (IoT) networks as the IoT devices are battery operated devices. One of the traditional approaches to improve the energy efficiency is through clustering. The authors propose a hybrid method of Gravitational Search Algorithm (GSA) and Artificial Bee Colony (ABC) algorithm to accomplish the efficient cluster head selection. The performance of the hybrid algorithm is evaluated using energy, delay, load, distance, and temperature of the IoT devices. Performance of the proposed method is analyzed by comparing with the conventional methods like Artificial Bee Colony (ABC), Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and GSO algorithms. The performance of the hybrid algorithm is evaluated using of number of alive nodes, convergence estimation, normalized energy, load and temperature. The proposed algorithm exhibits high energy efficiency that improves the life time of IoT nodes. Analysis of the authors' implementation reveals the superior performance of the proposed method.

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