Staff Members - Benha University
The Novel Stick Clustering Algorithm and its Applications for Ad-hoc Networks
International Journal of Intelligent Engineering and Systems • 2020
Publication Information
Authors
Abdulrahman Sabra, Mohamed Taha, and Dina S. M. Hassan
Keywords
: Flying ad-hoc networks, Vehicular ad-hoc networks, Mobile ad-hoc networks, Connected dominating set,
Balanced energy efficient virtual backbone construction algorithm
Journal
International Journal of Intelligent Engineering and Systems
Publisher
Not Available
Volume
13
Issue
3
Pages
177-188
publication.type
International
Paper Link
Open Link
Supplementary Materials
Not Available
Abstract
Clustering is considered a critical process to make a fast and reliable connection establishment of ad-hoc
networks. In this paper, a new clustering algorithm is proposed, namely Stick Clustering Algorithm (SCA). The
proposed SCA is used to overcome the low connectivity, low energy and delay to enhance the performance of largescale ad-hoc networks. The simulation results showed the efficiency and the reliability of the proposed clustering
algorithm against many greatest challenges such as high intensity of nodes under small network area. Also, the
results demonstrated that the proposed SCA is very competitive algorithm compared with RCA, CDS, Z-Degree and
ZID. The proposed SCA obtained 3.4306 approximation ratio. Also, the efficiency of the SCA is of O(n) for both
message complexities and time.
networks. In this paper, a new clustering algorithm is proposed, namely Stick Clustering Algorithm (SCA). The
proposed SCA is used to overcome the low connectivity, low energy and delay to enhance the performance of largescale ad-hoc networks. The simulation results showed the efficiency and the reliability of the proposed clustering
algorithm against many greatest challenges such as high intensity of nodes under small network area. Also, the
results demonstrated that the proposed SCA is very competitive algorithm compared with RCA, CDS, Z-Degree and
ZID. The proposed SCA obtained 3.4306 approximation ratio. Also, the efficiency of the SCA is of O(n) for both
message complexities and time.