Balanced Energy Efficient Grid Based Clustering Protocol for
Wireless Sensor Networks

Amer, Asmaa

doi:10.12785/ijcds/060101

Cited by 4 publications

(2 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this section, the proposed method evaluated in five different scenarios. And it compared with recent algorithms, such as NR_LEACH [15], BEEG (GRID) [24], Adaptive MCFL [28] and FPA [31]. NR LEACH is a hierarchical protocol, BEEG is chosen from network-based protocols, MCFL comes from fuzzy-based protocols, and FPA is a metaheuristic protocol.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

An Intelligent SDN-Based Clustering Approach for Optimizing IoT Power Consumption in Smart Homes

Nazari

Tavassolian

Abbasi

et al. 2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

As a novel technology, the Internet of Things (IoT) has many applications in diverse fields, especially in smart homes. IoT includes a variety of communication networks and technologies which facilitate communication between heterogeneous devices. One of the primary challenges of IoT is energy consumption. This paper introduces a new Software Defined Network-based (SDN-based) clustering approach using intelligent algorithms for energy conservation in IoT. The proposed method uses an evolutionary algorithm to identify the required number of clusters and ensures their distribution in the environment. A virtual network is also employed to ensure network coverage and the formation of balanced clusters. Clustering, steady, and routing are the main steps of the proposed method that the clustering step is done in SDN. By expanding the steady phase and leveraging energy-based greedy routing, the network’s lifetime increases. After simulation in MATLAB, the proposed method is tested then the results are compared with other well-known algorithms. The evaluation results indicate that the proposed method has improved in terms of metrics such as energy consumption and network lifetime. The proposed approach improves energy consumption by 31%, 28%, 8% and 21% than FPA, MCFL, BEEG and NodeRanked respectively. The lifetime has been improved by 34% and 71% than BEEG and NodeRanked, respectively, and more than 100% for MCFL and FPA.

show abstract

Section: Resultsmentioning

confidence: 99%

“…The other nodes will locate the sink's last position by sending a message to the closest crossover node. The key emphasis of BEEG [24] is on getting the cluster size. The optimum size causes reduced transmission and energy consumption.…”

Section: Related Workmentioning

confidence: 99%