Topology control in a sensor network balances load on sensor nodes and increases network scalability and lifetime. Clustering sensor nodes is an effective topology control approach. We propose a novel distributed clustering approach for long-lived ad hoc sensor networks. Our proposed approach does not make any assumptions about the presence of infrastructure or about node capabilities, other than the availability of multiple power levels in sensor nodes. We present a protocol, HEED (Hybrid Energy-Efficient Distributed clustering), that periodically selects cluster heads according to a hybrid of the node residual energy and a secondary parameter, such as node proximity to its neighbors or node degree. HEED terminates in O(1) iterations, incurs low message overhead, and achieves fairly uniform cluster head distribution across the network. We prove that, with appropriate bounds on node density and intracluster and intercluster transmission ranges, HEED can asymptotically almost surely guarantee connectivity of clustered networks. Simulation results demonstrate that our proposed approach is effective in prolonging the network lifetime and supporting scalable data aggregation.

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HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks

Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks

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

Typically, a wireless sensor network contains an important number of inexpensive power constrained sensors, which collect data from the environment and transmit them towards the base station in a cooperative way. Saving energy and therefore, extending the wireless sensor networks lifetime, imposes a great challenge. Clustering techniques are largely used for these purposes. In this paper, we propose and evaluate a clustering technique called a Developed Distributed Energy-Efficient Clustering scheme for heterogeneous wireless sensor networks. This technique is based on changing dynamically and with more efficiency the cluster head election probability. Simulation results show that our protocol performs better than the Stable Election Protocol (SEP) by about 30% and than the Distributed Energy-Efficient Clustering (DEEC) by about 15% in terms of network lifetime and first node dies.

Developed Distributed Energy-Efficient Clustering (DDEEC) for heterogeneous wireless sensor networks

EDDEEC: Enhanced Developed Distributed Energy-efficient Clustering for Heterogeneous Wireless Sensor Networks

Routing in ad-hoc networks is a difficult challenge that involves a tradeoff between efficiency and responsiveness. An ad-hoc network routing algorithm must adapt rapidly enough to topology changes to meet the performance demands of users, without over-utilizing network resources. This paper presents the (/spl alpha/,t) cluster framework which utilizes a distributed dynamic clustering strategy to organize nodes into clusters in which the probability of path failure due to node movement can be bounded over time. The objective of the clustering strategy is to achieve scalability and support robust, efficient routing subject to a wide range of mobility rates. Based on the (/spl alpha/,t) cluster scheme, routes within clusters are maintained on a proactive basis, whereas hierarchical routing between clusters is managed on a demand-basis. Simulation results show that the cluster organization can be effectively adapted to node mobility and that routing is both more robust and efficient than routing in fully proactive, reactive or fixed-hybrid schemes.

A.B. McDonald

Papers

Design and performance of a distributed dynamic clustering algorithm for ad-hoc networks