@conference { ISI:000385280000027,
	title = {Multi-hop Clustering Algorithm Based on Spectral Classification for Wireless Sensor Network},
	booktitle = {PROCEEDINGS OF THE MEDITERRANEAN CONFERENCE ON INFORMATION \& COMMUNICATION TECHNOLOGIES 2015 (MEDCT 2015), VOL 2},
	series = {Lecture Notes in Electrical Engineering},
	volume = {381},
	year = {2016},
	note = {Mediterranean Conference on Information and Communication Technologies (MedCT), Saidia, MOROCCO, MAY 07-09, 2015},
	pages = {255-264},
	abstract = {A Wireless Sensor Network (WSN) is composed of a large number of autonomous and compact devices called sensor nodes. This network can be an effective tool for gathering data in a variety of environments. However, these sensor nodes have some constraints due to their limited energy, storage capacity and computing power. Clustering is a kind of a technique which is used to reduce energy consumption and to extend network lifetime. Hence, multi-hop communication is often required when the communication range of the sensor nodes is limited or the number of sensor nodes is very large in a network. In this paper, we propose a multi-hop spectral clustering algorithm to organize the sensor nodes in a WSN into clusters. Simulation results show that the proposed algorithm performs better in reducing the energy consumption of sensors and effectively improves the WSN lifetime.},
	isbn = {978-3-319-30298-0; 978-3-319-30296-6},
	issn = {1876-1100},
	doi = {10.1007/978-3-319-30298-0\_27},
	author = {Jorio, Ali and El Fkihi, Sanaa and Elbhiri, Brahim and Aboutajdine, Driss},
	editor = {ElOualkadi, A and Choubani, F and ElMoussati, A}
}
@article {10906318420150210,
	title = {An Energy-Efficient Clustering Routing Algorithm Based on Geographic Position and Residual Energy for Wireless Sensor Network.},
	journal = {Journal of Computer Networks \& Communications},
	volume = {2015},
	year = {2015},
	pages = {1 - 11},
	abstract = {Recently wireless sensor network (WSN) has become one of the most interesting networking technologies, since it can be deployed without communication infrastructures. A sensor network is composed of a large number of sensor nodes; these nodes are responsible for supervision of the physical phenomenon and transmission of the periodical results to the base station. Therefore, improving the energy efficiency and maximizing the networking lifetime are the major challenges in this kind of networks. To deal with this, a hierarchical clustering scheme, called Location-Energy Spectral Cluster Algorithm (LESCA), is proposed in this paper. LESCA determines automatically the number of clusters in a network. It is based on spectral classification and considers both the residual energy and some properties of nodes. In fact, our approach uses the K-ways algorithm and proposes new features of the network nodes such as average energy, distance to BS, and distance to clusters centers in order to deter},
	keywords = {Data transmission systems, Energy consumption, Routing algorithms, Wireless sensor networks, Wireless sensor nodes},
	issn = {20907141},
	url = {http://search.ebscohost.com/login.aspx?direct=true\&db=iih\&AN=109063184\&site=ehost-live},
	author = {Jorio, Ali and El Fkihi, Sanaa and Elbhiri, Brahim and Aboutajdine, Driss}
}
@article { ISI:000362266900001,
	title = {An Energy-Efficient Clustering Routing Algorithm Based on Geographic Position and Residual Energy for Wireless Sensor Network},
	journal = {JOURNAL OF COMPUTER NETWORKS AND COMMUNICATIONS},
	year = {2015},
	abstract = {Recently wireless sensor network (WSN) has become one of the most interesting networking technologies, since it can be deployed without communication infrastructures. A sensor network is composed of a large number of sensor nodes; these nodes are responsible for supervision of the physical phenomenon and transmission of the periodical results to the base station. Therefore, improving the energy efficiency and maximizing the networking lifetime are the major challenges in this kind of networks. To deal with this, a hierarchical clustering scheme, called Location-Energy Spectral Cluster Algorithm (LESCA), is proposed in this paper. LESCA determines automatically the number of clusters in a network. It is based on spectral classification and considers both the residual energy and some properties of nodes. In fact, our approach uses the K-ways algorithm and proposes new features of the network nodes such as average energy, distance to BS, and distance to clusters centers in order to determine the clusters and to elect the cluster{\textquoteright}s heads of a WSN. The simulation results show that if the clusters are not constructed in an optimal way and/or the number of the clusters is greater or less than the optimal number of clusters, the total consumed energy of the sensor network per round is increased exponentially.},
	issn = {2090-7141},
	doi = {10.1155/2015/170138},
	author = {Jorio, Ali and El Fkihi, Sanaa and Elbhiri, Brahim and Aboutajdine, Driss}
}
@conference { ISI:000366999600151,
	title = {A Hierarchical Clustering Algorithm based on Spectral Classification for Wireless Sensor Networks},
	booktitle = {2014 INTERNATIONAL CONFERENCE ON MULTIMEDIA COMPUTING AND SYSTEMS (ICMCS)},
	year = {2014},
	note = {International Conference on Multimedia Computing and Systems (ICMCS), Marrakech, MOROCCO, APR 14-16, 2014},
	pages = {861-866},
	abstract = {A Wireless Sensor Network (WSN) is composed of a large number of autonomous and compact devices called sensor nodes. This network can be an effective tool for gathering data in a variety of enviornments. However, These sensor nodes have some constraints due to their limited energy, storage capacity and computing power. Therefor, saving energy and, thus extending the WSN lifetime entails great challenges. In order to prolong the lifetime of WSN, this study presents a hierarchical clustering algorithm based on spectral classification (HCA-SC). First, to overcome the ideal distribution of clusters, HCA-SC partition the network by spectral classification algorithm. Second, for each cluster, HCA-SC selects a node as a cluster head with regard residual energy and distance from base station. Simulation results showed that our algorithm performs better in reducing the energy consumption of sensor nodes and effectively improves the lifetime of wireless sensor networks.},
	isbn = {978-1-4799-3824-7},
	author = {Jorio, Ali and El Fkihi, Sanaa and Elbhiri, Brahim and Aboutajdine, Driss}
}
