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Wireless networking covers a variety of topics involving many
challenges. The main concern of clustering approaches for mobile
wireless sensor networks (WSNs) is to prolong the battery life of
the individual sensors and the network lifetime. For a successful
clustering approach, the need of a powerful mechanism to safely
elect a cluster head remains a challenging task in many research
works that take into account the mobility of the network. In
Mobile, Wireless and Sensor Networks: A Clustering Algorithm for
Energy Efficiency and Safety, the authors use an approach based on
computing of the weight of each node in the network as the proposed
technique to deal with this problem. They present a virtual
laboratory platform (VLP) of baptized mercury, allowing students
and researchers to make practical work (PW) on different aspects of
mobile wireless sensor networks. The authors' choice of WSNs is
motivated mainly by the use of real experiments needed in most
college courses on WSNs. These usual experiments, however, require
an expensive investment and many nodes in the classroom. The
platform presented here aims at showing the feasibility, the
flexibility, and the reduced cost using the authors' approach. The
authors demonstrate the performance of the proposed algorithms that
contribute to the familiarization of the learners in the field of
WSNs. The book will be a valuable resource for students in
networking studies as well as for faculty and researchers in this
area.
Wireless networking covers a variety of topics involving many
challenges. The main concern of clustering approaches for mobile
wireless sensor networks (WSNs) is to prolong the battery life of
the individual sensors and the network lifetime. For a successful
clustering approach, the need of a powerful mechanism to safely
elect a cluster head remains a challenging task in many research
works that take into account the mobility of the network. In
Mobile, Wireless and Sensor Networks: A Clustering Algorithm for
Energy Efficiency and Safety, the authors use an approach based on
computing of the weight of each node in the network as the proposed
technique to deal with this problem. They present a virtual
laboratory platform (VLP) of baptized mercury, allowing students
and researchers to make practical work (PW) on different aspects of
mobile wireless sensor networks. The authors' choice of WSNs is
motivated mainly by the use of real experiments needed in most
college courses on WSNs. These usual experiments, however, require
an expensive investment and many nodes in the classroom. The
platform presented here aims at showing the feasibility, the
flexibility, and the reduced cost using the authors' approach. The
authors demonstrate the performance of the proposed algorithms that
contribute to the familiarization of the learners in the field of
WSNs. The book will be a valuable resource for students in
networking studies as well as for faculty and researchers in this
area.
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