Clustering in wireless sensor network

The notion behind the clustering technique is to group the nodes in several overlapping clusters. Clustering enables the aggregation of the routing information, and hence, supports the scalability of routing algorithms. Cluster based routing tackles the problem of node heterogeneity, and routing overhead. In particular, the clustering enables the process of hierarchical routing in which routes are recorded between clusters resulting in increased route lifetime and decreased control overhead. Cluster head co-ordinates the cluster members and their activities. The cluster bottleneck problem arises as the cluster concentrates more on the traffic of its cluster and this can be avoided by adopting a fully distributed clustering approach. The communications in cluster can be inter-cluster or intra-cluster. The inter-cluster communication represents the communication of nodes within the cluster while the intra-cluster communication represents the communication between the clusters through the gateway nodes.


 Indeed, the lifetime is regarded as a fundamental factor in the context of avail- ability in the WSN. This parameter posses energy, safeguarding problems, particularly if the application must work a long time. In fact, it is impossible to reload or replace nodes’ batteries after they are exhausted.


Low Energy Adaptive Clustering Hierarchy (LEACH)

 LEACH is the most popular algorithm. It is chosen by chance the clustered for one time, according to a policy called “Round Robin”. The communication intra-cluster as well as the communication between the cluster heads and the base station is carried out in 1-hop. LEACH is a clustering-based protocol that utilizes a randomized rotation of local cluster base stations (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. The principal goal of LEACH is the balance of energy dissipation between sensors.

Mobility-Energy-Degree-Distance to the Base Station (MED-BS)

MED-BS Clustering algorithm elects the sensor having high connectivity, low mobility, closer to the destination and reduced power consumption sensor as a clustered (CH). Through the election of high connectivity CH, the number of hops involved between sensor and clusterhead is reduced thereby reducing the energy. Through the election low mobility CH, frequent changing of CH is avoided under the condition of movement of current CH. Through the election of reduced energy consumption CH, effective utilization of sensor’s resources is achieved. Through the election of CH closer to destination, number of hops in the data transmission is reduced. When the current CH runs out of energy, re-election of CH is conducted to facilitate the balanced energy consumption among the sensors in the network. Under the condition of mobility procedure of joining the new cluster is included.

Solution in NS2

  • Adaptive and efficient MED-BS clustering algorithm is applied over the wireless sensor network and is evaluated for the various network configurations.

  • MED-BS approach produces the efficient result in terms of network life, packet delivery ratio, and control overhead by selecting the energy, connectivity, mobility and distance efficient sensor as cluster head.

  • The reelection of cluster head and adjusting the transmission range under the reduced energy condition, improves the effective energy utilization of the sensor network.

Related Titles

  • “MED-BS Clustering Algorithm for the Small-Scale Wireless Sensor Networks” Awatef Ben Fradj Guiloufi, Nejah Nasri, Mohamed Alamine Ben Farah, AbdennaceurKachouri.

  • M. J. Handy, M. Haase and D. Timmermann, “Low Energy Adaptive Clustering Hierarchy with Deterministic Cluster-Head Selection,” Proceedings of the IEEE 4th International Workshop Mobile and Wireless Communi cation Network, Germany, 2002, pp. 368-372.