Adaptive Distributed Topology Control for Wireless Ad-Hoc Sensor Networks Kai-Ting Chu ∗ , Chih-Yu Wen ∗ , Yen-Chieh Ouyang ∗ , and William A. Sethares † Abstract— This paper presents a decentralized clustering and gateway selection algorithm for wireless ad-hoc sensor networks. Each sensor uses a random waiting timer and local criteria to determine whether to form a new cluster or to join a current cluster and utilizes the messages transmitted during hierarchical clustering to choose distributed gateways such that communication for adjacent clusters and adaptive distributed topology control can be achieved. The algorithm operates without a centralized controller, it operates asynchronously, and does not require that the location of the sensors be known a priori. A performance analysis of the topology management and the energy requirements of the algorithm are used to study the behaviors of the proposed algorithm. The performance of the algorithm is described analytically and via simulation. I. I NTRODUCTION Without a robust infrastructure, sensors in an ad-hoc net- work may be required to self-organize. Such sensor networks are self-configuring distributed systems and, for reliability, should also operate without centralized control. In addition, because of the limited energy source, energy-efficiency is a critical consideration. There has been extensive research on the design and devel- opment of energy efficient networking techniques. In [1], the Low-Energy Adaptive Clustering Hierarchy (LEACH) utilizes a randomized periodical rotation of clusterheads to balance the energy load among the sensors. LEACH-C (Centralized) [2] uses a centralized controller to select clusterheads. The main drawbacks of this algorithm are nonautomatic clusterhead selection and the requirement that the position of all sensors must be known. LEACH’s stochastic algorithm is extended in [3] with a deterministic clusterhead selection. Simulation results demonstrate that an increase of network lifetime can be achieved compared with the original LEACH protocol. The Ad hoc Network Design Algorithm (ANDA) [4] maximizes the network lifetime by determining the optimal cluster size and the optimal assignment of sensors to clusterheads but requires a priori knowledge of the number of clusterheads, number of sensors in the network, and the location of all sensors. The Weighted Clustering Algorithm (WCA) [5] considers the number of neighbors, transmission power, mobility, and bat- tery usage in choosing clusters. It limits the number of sensors in a cluster so that clusterheads can handle the load without degradation in performance. These clustering methods rely on * The Department of Electrical Engineering, Graduate Institute of Commu- nication Engineering, National Chung Hsing University, Tai-Chung, Taiwan. (email:cwen@dragon.nchu.edu.tw) † The Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA (email:sethares@ece.wisc.edu) synchronous clocking for the exchange of information among sensors which typically limits these algorithms to smaller networks [6]. In [7], the distributed topology control using the cooperative communication (DTCC) algorithm is proposed to provide a connected network topology with minimal total energy consumption. In order to provide reliable communication in wireless ad- hoc networks, maintaining network connectivity is crucial [8]- [15]. An implementation of the linked cluster architecture may consider the following tasks: cluster formation, cluster connectivity, and cluster reorganization. In order not to rely on a central controller, clustering is carried out by adaptive distributed control techniques via random waiting timers. To this end, the Adaptive Distributed Topology Control Algo- rithm (ADTCA) forms clusters and links in three phases: (I) clusterhead selection; (II) gateway selection, and (III) cluster reformation. In Phase I, clusterheads are selected and cluster members are assigned. A decentralized algorithm [8] is used to organize the network into clusters. Each sensor operates independently, monitoring communication among its neigh- bors. Based on the number of neighbors and a randomized timer, each sensor either joins a nearby cluster, or else forms a new cluster with itself as clusterhead. In Phase II, based on bidirectional message exchanges and the cluster architecture, sensors are selected as gateways in a fully distributed way. Once the network topology is specified (as a hierarchical collection of clusters and distributed gateways), maintenance of the linked cluster architecture becomes an issue. In Phase III, localized criterions governing cluster reformation are de- scribed and illustrated via simulations. This proposed self-configuration protocol is energy efficient, scalable, and may extend the lifetime of the network. Several aspects of this cluster-based topology control (such as the time synchronization problem and efficient network routing) are studied. A performance analysis and simplified models of the algorithm are derived, and the results are compared to the behavior of the algorithm in a number of settings. II. THE ADAPTIVE DISTRIBUTED TOPOLOGY CONTROL ALGORITHM (ADTCA) This section describes a randomized distributed algorithm that forms clusters and reselects clusterheads efficiently. The network setup is performed in three phases: “clustering,” “selecting gateways,” and “restructuring the clusters.” The main assumptions on the network are that (a) the sensors are in fixed but unknown locations, (b) all links between sensors are bidirectional, and (c) all sensors have the same transmitting