ECRP: an energy-aware cluster-based routing protocol for wireless sensor networks

Moussa, Noureddine; Hamidi‐Alaoui, Zakaria; Alaoui, Abdelbaki El Belrhiti El

doi:10.1007/s11276-019-02247-5

Cited by 68 publications

(54 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It also evaluates energy consumption, delay, jitter, throughput, and the number of clusters formed as the number of sensor nodes increases. The Energy-aware Cluster-based Routing Protocol (ECRP) proposed by N o u r e d d i n e M o u s s a, H a m i d i-A l a o u i and E l B e l r h t i E l A l a o u i [36] demonstrate that cluster configuration is done only once during the network's lifetime. It chooses CHs based on residual energy in each round and uses multiple parameters to find the best solution.…”

Section: Clustering and Routing Protocolsmentioning

confidence: 99%

Role of Clustering, Routing Protocols, MAC protocols and Load Balancing in Wireless Sensor Networks: An Energy-Efficiency Perspective

Munusamy¹,

Vijayan²,

Ezhilarasi³

2021

Cybernetics and Information Technologies

View full text Add to dashboard Cite

Wireless networks play an important role in science, including medicine, agriculture, the military, geography, and so on. The main issue with a network of wireless sensors is how to manage resource utilization to extend its lifetime. This paper investigates the various aspects of increased energy usage that may improve network life. Variables related to energy consumption and various performance metrics are investigated in terms of energy efficiency. To investigate how the network’s energy usage can be managed, a quick overview of clustering protocols, routing protocols, MAC protocols, and load balancing protocols is conducted. This paper can provide researchers with an idea of the various parameters that influence energy consumption and what methodologies could be adapted by each parameter to conserve energy, thereby extending the network’s lifetime.

show abstract

Section: Clustering and Routing Protocolsmentioning

confidence: 99%

Role of Clustering, Routing Protocols, MAC protocols and Load Balancing in Wireless Sensor Networks: An Energy-Efficiency Perspective

Munusamy¹,

Vijayan²,

Ezhilarasi³

2021

Cybernetics and Information Technologies

View full text Add to dashboard Cite

show abstract

“…This method offers the aggregation facility in the cluster, which reduces the duplicate data from the CM and only the aggregated data are passed to the BS. In a clustering protocol, the essential processes are cluster creation, cluster head (CH) selection, and route establishment between nodes and BS [19][20][21][22][23][24][25][26][27]. The CH selection plays a crucial role in increasing the network lifetime.…”

Section: Introductionmentioning

confidence: 99%

T2FL-PSO: Type-2 Fuzzy Logic-Based Particle Swarm Optimization Algorithm Used to Maximize the Lifetime of Internet of Things

Sankar¹,

Ramasubbareddy

Balasubramaniyam³

et al. 2021

IEEE Access

View full text Add to dashboard Cite

In recent years, the Internet of Things (IoT) has evolved as a research field that transforms human lifestyle from traditional to sophisticated. In IoT, the network plays a crucial role in collecting data from sensors and moving to the sink. Increasing the network lifetime is a challenging task in IoT, which is connected to devices that are limited by resource. Clustering is one of the effective methods of increasing the network lifetime. However, improper cluster head (CH) selection easily drains the energy early in network nodes. With the aim to overcome the issue, this paper proposes the Type-2 Fuzzy Logic-based Particle Swarm Optimization (T2FL-PSO) algorithm to select the optimal CH to extend the network lifetime. The T2FL is highly useful in providing the accurate solution in uncertain network environments. Hence, T2FL is applied on the network parameters, residual energy, and the distance between sensor node and base station to determine the fitness value. Later, virtual clusters are formed on the basis of distance between sensor node and CH and between node and base station. To validate the performance of the proposed T2FL-PSO algorithm, extensive simulations are carried out using MATLAB 2019a. Furthermore, the proposed T2FL-PSO algorithm is compared with Particle Swarm Optimization Clustering (PSO-C) and Particle Swarm Optimization Wang Zhang (PSO-WZ). The result confirms that the proposed T2FL-PSO increases the network lifetime by 10%-15% and the packet transmission ratio by 10%. Compared with similar algorithms, the proposed T2FL-PSO also causes a higher increase of network lifetime.

show abstract

“…Also, the nodes for heterogeneous networks have different capabilities for choosing the high energy nodes, high data refining, and computational power as the CH which are classified as dynamic cluster head and static cluster head [10]. e cluster head selection processes in WSNs help manage the lifespan of the network where the CH conducts the data aggregation from various cluster members to be transferred to the database station (BS) for analysis [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

A Hyper-Heuristic Heterogeneous Multisensor Node Scheme for Energy Efficiency in Larger Wireless Sensor Networks Using DEEC-Gaussian Algorithm

Aroba

Naicker

Adeliyi

2021

Mobile Information Systems

View full text Add to dashboard Cite

A wireless sensor network (WSN) is an intellect-sustainable network that comprises multiple spatially distributed sensor nodes and several sink nodes that collect data from sensors. WSNs remain an active research area in the literature due to challenging factors such as the selection of sensor location according to a given premise, finding optimal routing algorithm, and ensuring energy efficiency and consumption. Minimizing energy and prolonging the network lifetime in the WSNs are the focus of this research work. In the literature, a clustering approach is used in grouping sensor nodes into clusters and is seen as an effective technique used in optimizing energy consumption in WSNs. Hence, in this paper, we put forward a novel clustering-based approach by amalgamating the Gaussian elimination method with the Distributed Energy-Efficient Clustering to produce DEEC_Gaussian (DEEC_Gaus) to stabilize energy efficiency optimization in WSNs. We took the advantages of DEEC and Gaussian elimination algorithms to resolve energy efficiency problems in WSNs. DEEC presents attributes such as increased heterogeneity performance level, clustering stability in operation, and energy efficiency which helps to prolong network lifetime while the Gaussian elimination algorithm added an additional advantage to improve and optimize energy efficiency, to aggregate packets of operations performed in the network lifestyle of energy efficiency in WSNs. The simulations were carried out using MATLAB software with 1000 to 1500 nodes. The performance of the proposed work was compared with state-of-the-art algorithms such as DEEC, DDEEC, and EDEEC_E. The simulated results presented show that the proposed DEEC-Gauss outperformed the three other conventional algorithms in terms of network lifetime, first node dead, tenth node dead, alive nodes, and the overall timing of the packets received at the base station. The results showed that the proposed hyper-heuristic heterogeneous multisensor DEEC-Gauss algorithm presented an average percentage of 3.0% improvement for the tenth node dead (TND) and further improvement of 4.8% for the first node dead (FND). When the performance was compared to the state-of-the-art algorithms in larger networks, the overall delivery was greatly improved and optimized.

show abstract

ECRP: an energy-aware cluster-based routing protocol for wireless sensor networks

Cited by 68 publications

References 19 publications

Role of Clustering, Routing Protocols, MAC protocols and Load Balancing in Wireless Sensor Networks: An Energy-Efficiency Perspective

Role of Clustering, Routing Protocols, MAC protocols and Load Balancing in Wireless Sensor Networks: An Energy-Efficiency Perspective

T2FL-PSO: Type-2 Fuzzy Logic-Based Particle Swarm Optimization Algorithm Used to Maximize the Lifetime of Internet of Things

A Hyper-Heuristic Heterogeneous Multisensor Node Scheme for Energy Efficiency in Larger Wireless Sensor Networks Using DEEC-Gaussian Algorithm

Contact Info

Product

Resources

About