http://romisatriawahono.net/lecture/rm/survey/machine%20learning/Afsar%20-%20Clustering%20in%20Sensor%20Networks%20-%202014.pdf

Clustering in sensor networks

Due to the nonuniform node distribution, the energy consumption among nodes are more imbalanced in cluster-based wireless sensor networks. Based on this problem, in this paper, a cluster-based routing protocol for wireless sensor networks with nonuniform node distribution is proposed, which includes an energy-aware clustering algorithm EADC and a cluster-based routing algorithm. EADC uses competition range to construct clusters of even sizes. At the same time, the routing algorithm increases forwarding tasks of the nodes in scarcely covered areas by forcing cluster heads to choose nodes with higher energy and fewer member nodes as their next hops, and finally, achieves load balance among cluster heads. Theoretical analysis and simulation results show that our protocol can balance the energy consumption among nodes and increase the network lifetime significantly.

A cluster-based routing protocol for wireless sensor networks with nonuniform node distribution

Wireless sensor network (WSN) systems are typically composed of thousands of sensors that are powered by limited energy resources. To extend the networks longevity, clustering techniques have been introduced to enhance energy efficiency. This paper presents a survey on clustering over the last two decades. Existing protocols are analyzed from a quality of service (QoS) perspective including three common objectives, those of energy efficiency, reliable communication and latency awareness. This review reveals that QoS aware clustering demands more attention. Furthermore, there is a need to clarify how to improve quality of user experience (QoE) through clustering. Understanding the users’ requirements is critical in intelligent systems for the purpose of enabling the ability of supporting diverse scenarios. User awareness or user oriented design is one remaining challenging problem in clustering. In additional, this paper discusses the potential challenges of implementing clustering schemes to Internet of Things (IoT) systems in 5G networks. We indicate that clustering techniques enhanced with smart network selection solutions could highly benefit the QoS and QoE in IoT. As the current studies for WSNs are conducted either in homogeneous or low level heterogeneous networks, they are not ideal or even not able to function in highly dynamic IoT systems with a large range of user scenarios. Moreover, when 5G is finally realized, the problem will become more complex than that in traditional simplified WSNs. Several challenges related to applying clustering techniques to IoT in 5G environment are presented and discussed.

A Survey of Clustering Techniques in WSNs and Consideration of the Challenges of Applying Such to 5G IoT Scenarios

Energy-aware routing algorithm for wireless sensor networks

A survey on unequal clustering protocols in Wireless Sensor Networks

Due to the imbalance of energy consumption of nodes in wireless sensor networks (WSNs), some local nodes die prematurely, which causes the network partitions and then shortens the lifetime of the network. The phenomenon is called “hot spot” or “energy hole” problem. For this problem, an energy-aware distributed unequal clustering protocol (EADUC) in multihop heterogeneous WSNs is proposed. Compared with the previous protocols, the cluster heads obtained by EADUC can achieve balanced energy, good distribution, and seamless coverage for all the nodes. Moreover, the complexity of time and control message is low. Simulation experiments show that EADUC can prolong the lifetime of the network significantly.

An Energy-Aware Distributed Unequal Clustering Protocol for Wireless Sensor Networks

Due to the limitation of energy resources, energy efficiency is a key issue in wireless sensor networks (WSNs). Clustering is proved to be an important way to realize hierarchical topology control, which can improve the scalability and prolong the lifetime of wireless sensor networks. In this paper, an energy-driven unequal clustering protocol (EDUC) for heterogeneous wireless sensor networks is proposed. EDUC includes an unequal clustering algorithm and an energy-driven adaptive cluster head rotation method. The unequal size of clusters can balance the energy consumption among clusters, and the energy-driven cluster head rotation method can achieve the balance of energy consumption among nodes within a cluster, which reduces the waste of energy. Simulation experiments show that EDUC balances the energy consumption well among the cluster heads and prolongs the network lifetime.

Yingying Qi

Papers

A cluster-based routing protocol for wireless sensor networks with nonuniform node distribution

An Energy-Aware Distributed Unequal Clustering Protocol for Wireless Sensor Networks

An energy-driven unequal clustering protocol for heterogeneous wireless sensor networks