# A Robust and Energy-Efficient Weighted Clustering Algorithm on Mobile Ad Hoc Sensor Networks +
## 1 Introduction  
A collection of mobile nodes can make up mobile Ad hoc sensor networks, which are not intervened on by any centralized access point [1; 2]. In order to assist other nodes in the network to build information links, nodes can be used as router or terminal or both of them [3; 4]. Mobile Ad hoc sensor network can be utilized in these scenarios, such as military and habitat monitoring [5; 6], target tracking network [7; 8]. For example, in the animal tracking system, sensor nodes are loaded on the body of animals in order to observing animal behavior. Generally, the animals (such as zebras, elephants etc.) have the low group mobility. Additionally, the sensor nodes cannot be charged in this situation. Hence, the energy consumption is a vital problem for the limitation of the energy. Moreover, since the animals live in a relatively bad environment, the fault node will be a necessary part needed to be considered. Therefore, our proposed protocol is motivated by this kind of applications. It has been proved that clustering in hierarchical structure is an effective scheme to improve the network survivability [9; 10]. In [9], it is introduced that the clustering method of fuzzy logic theory in the ECPF protocol. At the same time, in order to solve the problem of clustering non-uniformity,LEACH-C algorithm is proposed in [10] and the residual energy and location of the cluster node are decided by the base station. However, how to elect the optimal cluster heads (CHs) and how can the optimal number of nodes be assigned become the bottleneck [11; 12; 13]. The structure of cluster is especially more significant in large scale network. Instead of using gateways to exchange data packet, nodes in the network are distributed and confined within each cluster. The cluster members only need to collect data and transmit packet to CHs. Though the process of clustering will consume a little of energy, the overhead of routing control can be reduced a lot. Apart from above, the measurement will cause some difficulties due to the high mobility of nodes. In this paper, a high density network is considered, so we adopt the specific group mobility model [14; 15; 16]. In order to reduce the re-clustering times and save more energy, the novel mobility measurement is adopted. Nodes with similar motion pattern will form into a group or a cluster. The linear displacement of nodes is based on the record of history movement. The displacement index of each node will be calculated only when their displacement goes beyond the cluster range. Consequently, robustness of network is becoming a hotspot because the network has characteristics of dynamic topology, limited energy and mobility. Currently, a number of researches on robustness have been done in the mobile Ad hoc network. Reasonable fault management framework can enhance work efficiency of nodes, which can improve the robustness [17; 18]. A strong robust network will be utilized in different scenarios. Currently, the proposed algorithms have taken fault tolerance and energy-efficiency into consideration and make some progress on fault detection and _CH_ election. However, to some degree, only consideration of fault detection and energy-efficiency is unilateral to network, which neglected the mobility of nodes. Therefore, in order to render the energy consumption more homogenized, a robust and energy-efficient weighted clustering algorithm is adopted, which considers the group mobility and the residual energy. Meanwhile, for the purpose of enhancing the robustness of the network, a topology maintenance algorithm is proposed to control when the topology need be maintained. Our algorithm, A Robust, Energy-efficient Weighted Clustering Algorithm (RE\({}^{2}\)WCA), achieves the tradeoff of energy-efficiency and robustness and the following goals of our algorithm is demonstrated as below:  
1. For purpose of achieving load balance of cluster head, the clustering algorithm we proposed takes group mobility and residual energy into account to adapt to the change of network.