Survey: Graph clustering

Clustering is an important research topic for mobile ad hoc networks (MANETs) because clustering makes it possible to guarantee basic levels of system performance, such as throughput and delay, in the presence of both mobility and a large number of mobile terminals. A large variety of approaches for ad hoc clustering have been presented, whereby different approaches typically focus on different performance metrics. This article presents a comprehensive survey of recently proposed clustering algorithms, which we classify based on their objectives. This survey provides descriptions of the mechanisms, evaluations of their performance and cost, and discussions of advantages and disadvantages of each clustering scheme. With this article, readers can have a more thorough and delicate understanding of ad hoc clustering and the research trends in this area.

A survey of clustering schemes for mobile ad hoc networks

In this paper we describe several new clustering algorithms for nodes in a mobile ad hoc network. We propose to combine two known approaches into a single clustering algorithm which considers connectivity as a primary criterion and lower ID as secondary criterion for selecting cluster heads. The goal is to minimize the number of clusters, which results in dominating sets of smaller sizes (this is important for applications in broadcasting and Bluetooth formation). We also describe algorithms for modifying cluster structure in the presence of topological changes. Next, we generalize the cluster definition so that a cluster contains all nodes that are at a distance of at most k hops from the cluster head. The efficiency of four clustering algorithms (k-lowestID and k-CONID, k=1 and k=2) is tested by measuring the average number of created clusters, the number of border nodes, and the cluster size in random unit graphs. The most interesting experimental result is stability of the ratio of the sum of CHs and border nodes in the set. It was constantly 60-70% for 1-lowestID and 46-56% for 1-ConID, for any value of n (number of nodes) and d (average node degree). Similar conclusions and similar number were obtained for k=2. We also proposed a unified framework for most existing and new clustering algorithms where a properly defined weight at each node is the only difference in the algorithm. Finally, we propose a framework for generating random unit graphs with obstacles.

/pdf/connectivity-based-k-hop-clustering-in-wireless-networks-21rocaf20o.pdf

Connectivity based k-hop clustering in wireless networks

In this paper we describe several new clustering algorithms for nodes in a mobile ad hoc network. The main contribution is to generalize the cluster definition and formation algorithm so that a cluster contains all nodes that are at distance at most k hops from the clusterhead. We also describe algorithms for modifying cluster structure in the presence of topological changes. We also proposed an unified framework for most existing and new clustering algorithm where a properly defined weight at each node is the only difference in otherwise the same algorithm. This paper studied node connectivity and node ID as two particular weights, for k=1 and k=2. Finally, we propose a framework for generating random unit graphs with obstacles.

Connectivity Based k-Hop Clustering in Wireless Networks

------------------------------------------------------------------------------------------------------------------------------------Recent technological advances in communications and computation have enabled the development of low-cost, low-power, small in size, and multifunctional sensor nodes in a wireless sensor network. Since the radio transmission and reception consumes a lot of energy, one of the important issues in wireless sensor network is the inherent limited battery power within network sensor nodes. Therefore, battery power is crucial parameter in the algorithm design to increase lifespan of nodes in the network. In addition to maximizing the lifespan of sensor nodes, it is preferable to distribute the energy dissipated throughout the wireless sensor network in order to maximize overall network performance. Much research has been done in recent years, investigating different aspects like, low power protocols, network establishments, routing protocol, and coverage problems of wireless sensor networks. There are various routing protocols like location-aided, multi-path, datacentric, mobility-based, QoS based, heterogeneity-based, hierarchical routing, hybrid routing, etc., in which optimal routing can be achieved in the context of energy. In this paper, the focus is mainly driven over the survey of the energy-efficient hierarchical cluster-based available routings for Wireless Sensor Network.

/pdf/a-survey-of-energy-efficient-hierarchical-cluster-based-9gu59nl9me.pdf

A Survey of Energy-Efficient Hierarchical Cluster-Based Routing in Wireless Sensor

The ad hoc network is a temporary wireless system without a fixed (wired or wireless) infrastructure. Many clustering algorithms have been proposed to partition mobile users into clusters to support routing and network management. Most previous studies, however, focus on algorithm design, lacking an overall evaluation of clustering overheads. We design a multiple access scheme for the broadcast of control messages, and propose a new access-based clustering protocol (ABCP) whose cluster formation is heavily influenced by the outcome of the multiple access. By taking into account many delicate aspects in the clustering process, the ABCP provides a generic, flexible, rapidly deployed and stable cluster architecture for the upper layer protocols. Simulation is used to compare ABCP with the other clustering strategy in terms of cluster stability and overheads. Since ABCP makes clustering decision directly based on the result of channel access, it requires fewer control overheads and has shorter convergence time than the other clustering criteria. We also demonstrate that the resulting cluster structure by ABCP behaves stable in face of topology changes.

A access-based clustering protocol for multihop wireless ad hoc networks

In order to ensure an efficient network control for mobile ad hoc networks, nodes are usually aggregated into clusters to provide a convenient framework. However, an important issue on how to properly assign channels over a multi-cluster structure has not been studied in depth. In this paper, we first propose a new clustering algorithm to facilitate subsequent channel assignment. Each cluster has one clusterhead. Between clusterheads, there are gateways that relay control information and help eliminate the hidden terminal problem. Then two dynamic channel assignment (DCA) strategies are designed to make the best use of available channels by taking advantage of the spatial reuse concept. One strategy tries approaching a compact-channel pattern so that the channel reuse efficiency can be enhanced. On the other hand, the other strategy tries reducing the control overhead on the channel assignment so that the users can have a lower power consumption. We evaluate our cluster structure via simulation in terms of cluster stability and overheads. Furthermore, the two DCA strategies are compared to provide a guideline on how to trade off between the channel reuse efficiency and the control overhead.

Tzu-Jane Tsai

Papers

A access-based clustering protocol for multihop wireless ad hoc networks

On the cluster based dynamic channel assignment for multihop ad hoc networks

Distributed Clustering for Multimedia Support in Mobile Multihop Ad Hoc Networks