A Survey on Mobility Driven Clustering Techniques for Wireless Sensor Networks
07 Aug 2018-pp 1521-1528
TL;DR: This paper is a study about constraints of WSN and clustering techniques used for forming the network are presented and the proposed protocols to make the efficient use of available energy in the nodes and to acquire complete operability are presented.
Abstract: In recent years Mobile Wireless Sensor Networks have observed a substantial increase in the use of specific applications like surveillance, military applications, disaster management, wildlife monitoring, etc. The wireless nodes are small electronic devices embedded with various sensors to perform the given tasks. These sensor nodes are provided with a limited battery power which is a big constraint for the performance of the network in unattended environments. Also, mobility affects the battery life of the nodes to a great extent. Thus, it is necessary to design protocols to make the efficient use of available energy in the nodes and to acquire complete operability. This problem can be solved to some extent by clustering of the sensor nodes. This paper is a study about constraints of WSN and clustering techniques used for forming the network are presented.
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11 Mar 2015TL;DR: This paper examines various distributed and hybrid clustering algorithm as on date reported by different authors actively working in this area and briefly discusses the operations of these algorithms.
Abstract: Wireless sensor networks (WSNs) have many applications in military services, health centers, industries as well as home surveillances. In such networks energy efficiency of nodes and life time of network are main concerns. Different clustering approaches are used to efficiently optimize the energy of sensor nodes. Clustering also improves the scalability of sensor nodes. We reviewed different approaches of clustering which are centralized, distributed and hybrid used in Sensor Networks. Recently there have been many researches on developing algorithms using equal and unequal clustering techniques. These techniques use residual energy of nodes and distance to base station as parameters for selecting cluster heads. This paper aims to examine various distributed and hybrid clustering algorithm as on date reported by different authors actively working in this area. We also briefly discuss the operations of these algorithms, as well as compare on the basis of various clustering attributes.
30 citations
01 Dec 2014
TL;DR: This paper has presented a virtual grid-based distributed clustering (VGDC) solution for MWSN that gives data reliability up to 30% more than existing solutions at the cluster-heads and reduces energy consumption resulting in increased lifetime of the network.
Abstract: Wireless Sensor Network (WSN) applications require reliable data communication and maximized network lifetime. Both requirements are more demanding in Mobile Wireless Sensor Networks (MWSN) as compared to static WSN. In cluster-based MWSN it is a challenge is to receive data reliably at the cluster-head. This can be achieved by conserving network energy and maintaining reliable connectivity between the cluster-head(s) and the sensor nodes. Most of the cluster-based MWSN protocols can acquire data with some reliability but at the cost of heavy power consumption, thus they limit the network lifetime. In this paper we have presented a virtual grid-based distributed clustering (VGDC) solution for MWSN that gives data reliability up to 30% more than existing solutions at the cluster-heads. Our proposed VGDC scheme also reduces energy consumption resulting in increased lifetime of the network.
12 citations
25 Apr 2011
TL;DR: A group mobility adaptive clustering scheme (GMAC) for mobile WSN based on a new group mobility metric Mobility Group, which use network topology information and a position predictor to determine if nodes move together or separately is proposed.
Abstract: Recently, with the emergence of MWSNs utilization in different applications, some real-world situations, such as large-scale military networks and search-and-rescue operations, consider that sensor nodes move together in groups. To approximate the simulation of such applications to the reality, group mobility models are required. In this paper, we propose a group mobility adaptive clustering scheme (GMAC) for mobile WSN based on a new group mobility metric Mobility Group, which use network topology information and a position predictor to determine if nodes move together or separately. In GMAC, the area of interest is divided in equal zones, and each sensor calculates its weight based on Mobility Group and residual energy. The sensor node with the greatest weight in its zone will become the cluster-head. Using RPGM mobility model we have performed simulations to illustrate the benefits of our proposal comparing to ACE-L and LEACH. Obtained results show that GMAC outperforms ACE-L and LEACH in terms of energy consumption and the amount of data packets received at the sink.
12 citations
11 Dec 2015
TL;DR: This work proposes a new cluster-based protocol, Dynamic Load-balancing Cluster Based Protocol (DLCP), which introduces a new inter-cluster approach to increase the network lifetime, rotates continuously the election of the Cluster Head (CH) in each cluster, and selects the node with the highest residual energy in each round.
Abstract: In Wireless Sensor Networks (WSNs), clustering techniques are among the effective solutions to reduce energy consumption and prolong the network lifetime. During the iterative re-clustering process, extra energy and time are consumed especially at the setup phase of every round. To address these issues, we propose a new cluster-based protocol namely, Dynamic Load-balancing Cluster Based Protocol (DLCP). Our protocol introduces a new inter-cluster approach to increase the network lifetime, rotates continuously the election of the Cluster Head (CH) in each cluster, and selects the node with the highest residual energy in each round. When the energy of CHs falls below a fixed threshold (TCH), a new clustering process is created. Extensive simulation experiments show that our proposed approach balances effectively the energy consumption among all sensor nodes and increases the network lifetime compared to other clustering protocols.
10 citations
01 Jul 2015
TL;DR: The Distributed Clustering Algorithm the mechanism to elect the head of the cluster and the mechanism for engagement a non-cluster head nodes to a specific cluster provides a significant increase in the network life-time, availability, stability period of wireless sensor networks and reduction of packet loss in the cluster formed by a simple point predictor for combined criterion prediction and stability value.
Abstract: In this study, the authors propose a mobility adaptive clustering algorithm for wireless sensor networks with mobile nodes. In the proposed algorithm, a sensor node selects itself as a cluster head based on a Single Point Predictor for the combined criterion prediction. Here, as a combined criterion predicting proposed comprising parameters as connectivity, coverage, mobility and residual energy consumption of all the nodes (Distributed Clustering Algorithm). A non-cluster-head nodes declare themselves as members of the cluster based on a new value, that value is related to each cluster head, which is used to indicate its suitability for connecting this cluster head or other (Mobility-Based Clustering protocol). We found in the Distributed Clustering Algorithm the Mechanism to elect the head of the cluster and in the Mobility-Based Clustering protocol the mechanism for engagement a non-cluster head nodes to a specific cluster. Thus, the combination of them together provides a significant increase in the network life-time, availability, stability period of wireless sensor networks and reduction of packet loss in the cluster formed by a simple point predictor for combined criterion prediction and stability value.
10 citations