Abstract — This paper presents a mobility-based d-hop clustering algorithm (MobDHop), which forms variable-diameter clusters based on node mobility pattern in MANETs. We introduce a new metric to measure the variation of distance between nodes over time in order to estimate the relative mobility of two nodes. We also estimate the stability of clusters based on relative mobility of cluster members. Unlike other clustering algorithms, the diameter of clusters is not restricted to two hops. Instead, the diameter of clusters is flexible and determined by the stability of clusters. Nodes which have similar moving pattern are grouped into one cluster. The simulation results show that MobDHop has stable performance in randomly generated scenarios. It forms lesser clusters than Lowest-ID and MOBIC algorithm in the same scenario. In conclusion, MobDHop can be used to provide an underlying hierarchical routing structure to address the scalability of routing protocol in large MANETs.

The spread of wireless portable devices is pushing towards service provisioning over dense Mobile Ad-hoc NETworks (MANETs), i.e., limited spatial regions, such as shopping malls and airports, where a high number of mobile peers can autonomously cooperate without a statically deployed network infrastructure. The paper proposes the REDMAN middleware to manage, retrieve, and disseminate replicas of data/service components to cooperating nodes in a dense MANET. The guideline is to exploit high node population to enable optimistic lightweight resource replication capable of tolerating node exits/failures. REDMAN adopts original approximated solutions, specifically designed for dense MANET, that have demonstrated good scalability and limited overhead for dense MANET configuration (node identification and manager election), for replica distribution/retrieval, and for lazily-consistent replica degree maintenance.

In wireless ad hoc networks, clustering is one of the most important approaches for many applications. A connected k-hop clustering network is formed by electing clusterheads in k-hop neighborhoods and finding gateway nodes to connect clusterheads. Therefore, the number of nodes to be flooded in broadcast related applications could be reduced. In this paper, we study the localized solution for the connectivity issue of clusterheads with less gateway nodes. We develop the adjacency-based neighbor clusterhead selection rule (A-NCR) by extending the “2.5 ” hops coverage theorem [17] and generalizing it to k-hop clustering. We then design the local minimum spanning tree [9] based gateway algorithm (LMSTGA), which could be applied on the adjacent clusterheads selected by A-NCR to further reduce gateway nodes. In the simulation, we study the performance of the proposed approaches, using different values for parameter k. The results show that the proposed approaches generate a connected k-hop clustering network, and reduce the number of gateway nodes effectively. 1.

Network clustering is an important technique widely used in efficient MANETs network management, hierarchical routing protocol design, network modeling, Quality of Service, etc. Recently many researchers are focusing on clustering which is one of the fundamental problems in mobile ad hoc networks. This article presents the descriptions of recently proposed clustering algorithms and is categorized into different approaches that support similar features. Based on the comparison of different performance metrics of different clustering algorithms, the most suitable one is recommended that adapt it to various application scenarios. This study provides adequate information for the researchers that facilitate to analyze many avenues and to offer more effective and efficient clustering protocols for MANETs.

Clustering Approach (DECA) for mobility-resistant and energy-efficient clustering in multi-hop wireless networks. The clusterheads cover the whole network and each node in the network can exclusively determine the single cluster it belongs. DECA is fully distributed, each node transmits only one message during clustering operation, and the algorithm terminates in deterministic time without iterations. Theoretical results show the correctness of DECA, and extensive simulation results demonstrate that DECA is energy-efficient and robust against node mobility. Index Terms—clustering, ad hoc networks, wireless sensor networks, mobility, performance evaluation I.

Abstract—In the context of mobile ad hoc networks (MANETs) routing, we propose a clustering algorithm called Connectivity, Energy and Mobility driven Clustering Algorithm (CEMCA). The aim of CEMCA consists in appropriately choosing the cluster head to reduce routing overhead. In order to reduce traffic and energy consumption, the control messages are sent only when needed, according to the speed of the node. Each node has a quality that indicates its suitability as a cluster head. This quality takes into account the node connectivity, battery energy and mobility. These parameters are very important for the stability of the cluster. Simulation experiments are carried out to validate our algorithm in terms of stability of the clusters and their members and the quality of the connectivity. The results are compared to a previous approach called Weight Clustering Algorithm (WCA) and they show that CEMCA is performing better. I.

Abstract. Clustering in mobile ad hoc networks (MANETs) and wireless sensor networks (WSNs) is an important method to ease topology management and routing in such networks. Once the clusters are formed, the leaders (coordinators) of the clusters may be used to form a backbone for efficient routing and communication purposes. A set of clusters may also provide the underlying physical structure for multicast communication for a higher level group communication module which may effectively be used for fault tolerance and key management for security purposes. We survey graph theoretic approaches for clustering in MANETs and WSNs and show that although there is a wide range of such algorithms, each may be suitable for a different cross-layer design objective.

Radio transmission and reception consumes a lot of energy in a wireless sensor network (WSN), which are made of low-cost, low-power, small in size, and multifunctional sensor nodes. Thus, one of the important issues in wireless sensor network is the inherent limited battery power within the sensor nodes. Therefore, battery power is crucial parameter in the algorithm design in maximizing the lifespan of sensor nodes. It is also 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 in the area of low power routing protocol, but, there are still many design options open for improvement, and for further research targeted to the specific applications, need to be done. In this paper, we propose a new approach of an energy-efficient homogeneous clustering algorithm for wireless sensor networks in which the lifespan of the network is increased by ensuring a homogeneous distribution of nodes in the clusters. In this clustering algorithm, energy efficiency is distributed and network performance is improved by selecting cluster heads on the basis of (i) the residual energy of existing cluster heads, (ii) holdback value, and (iii) nearest hop distance of the node. In the proposed clustering algorithm, the cluster members are uniformly distributed and the life of the network is further extended.

Abstract. Node clustering and data aggregation are popular techniques to reduce energy consumption in large WSNs and a large body of literature has emerged describing various clustering protocols. Unfortunately, for practitioners wishing to exploit clustering in deployments, there is little help when trying to identify a protocol that meets their needs. This paper takes a step back from specific protocols to consider the fundamental question: what is the optimal cluster size in terms of the resulting communication generated to collect data. Our experimental analysis considers a wide range of parameters that characterize the WSN, and shows that in the most common cases, clusters in which all nodes can communicate in one hop to the cluster head are optimal. 1

Wireless sensor networks (WSNs), consist of small nodes with sensing, computation, and wireless communications capabilities, are now widely used in many applications, including environment and habitat monitoring, traffic control, and etc. Routing in WSNs is very challenging due to the inherent characteristics that distinguish these networks from other wireless networks like mobile ad hoc networks or cellular networks. Hierarchical or cluster-based methods, originally proposed in wireline networks, are well-known techniques with special advantages related to scalability and efficient communication. As such, the concept of hierarchical routing is also utilized to perform energy-efficient routing in WSNs. Using a virtual backbone infrastructure which is one kind of hierarchical methods has received more attention. Thus, a Connected Dominating Set (CDS) has been recommended to serve as a virtual backbone for a WSN to reduce routing overhead. Having such a CDS simplifies routing by restricting the main routing tasks to the dominators only. Fault tolerance and routing flexibility are necessary for routing since nodes in WSNs are prone to failures and nodes may have mobility and turn on and off frequently. Thus, it is important to maintain a certain degree of redundancy in a CDS. Unfortunately, a CDS only preserves 1-connectivity and it is therefore very vulnerable. Therefore, the concept of k-connected m-dominating sets (kmCDS) are used to provide these redundancy. In this chapter, we first survey some existing cluster-based algorithms. After that, we focus on connected dominating set algorithms, including both centralized and distributed, for how to construct CDS. Theoretical analysis are also presented. Furthermore, some algorithms for kmCDS are described in detail. 1