## 1 Introduction  
Without a robust infrastructure, sensors in an ad-hoc network may be required to self-organize. Such sensor networks are self-configuring distributed systems and, for reliability, should also operate without centralized control. It has been shown that cluster architecture guarantees basic performance achievement in a mobile ad-hoc network [1; 2]. This effective topology control technique may be advantageous since it (1) conserves limited energy resources and improves energy efficiency, (2) facilitates the spatial reuse of resources to increase the system capacity [3], (3) can construct a virtual backbone for abstracting the characteristics of network topology [4, 5], and (4) makes an ad-hoc network more stable and further provides scalability and robustness for the network [6, 7]. In order to provide reliable communication in wireless ad-hoc networks, maintaining network connectivity is crucial. An implementation of the linked cluster architecture may consider the following tasks: cluster formation, cluster connectivity, and cluster reorganization. This paper presents an adaptive combined-metrics-based clustering scheme for mobile sensor networks, which manages the mobile sensors by utilizing the hierarchical network structure and allocates network resources efficiently. In order to not to rely on a central controller, clustering is carried out by adaptive distributed control techniques via random waiting timers, which takes a number of metrics into account for cluster configuration, including neighboring node properties, residual energy level, and node mobility. To this end, the _Self-Adaptive Mobile Clustering Algorithm_ (SAMCA) forms clusters and links in two phases: (I) cluster formation and (II) cluster maintenance. In Phase I, clusterheads are selected and cluster members are assigned. The proposed algorithm generalizes the previous work [8] to include the motion by using the velocities of the sensors and the characteristics of the network in the waiting timers such that the mobile sensors can be organized automatically in an ad-hoc network. Each sensor operates independently, monitoring communication among its neighbors. Based on the number of neighbors, the node mobility, and a randomized timer, each sensor either joins a nearby cluster, or else forms a new cluster with itself as clusterhead. Established upon bidirectional message exchanges and the cluster architecture, sensors are selected as gateways for adjacent clusters 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 order to govern the hierarchical structure and the topology change efficiently, in Phase II a cluster reformation scheme using localized criterions is applied, especially on merger and division of clusters and reselection of clusterhead and gateway. As we know, the clustering protocol is vital for a network to achieve scalability. However, a cluster-based network infrastructure requires extra cost for constructing and maintaining a cluster structure compared with a flat-based one. Therefore, the cost of clustering is a key issue to validate the effectiveness and scalability enhancement of a cluster structure. This paper explores the cost of the proposed scheme such as energy consumption for cluster formation and maintenance, communication complexity, and time complexity. By analyzing the proposed clustering scheme in different aspects qualitatively or quantitatively such as neighboring node properties, node density change, and simplified models for describing the process of cluster formation, its robustness and scalability can be clearly specified. The analytical results are compared to the behavior of the algorithm in a number of settings. The rest of the paper is organized as follows: Section 2. reviews the current literature on clustering techniques for mobile ad-hoc networks. Section 3. describes the procedures of the SAMCA method.