# A Robust and Energy-Efficient Weighted Clustering Algorithm on Mobile Ad Hoc Sensor Networks +
## 2 Related Work  
There are various clustering algorithms for mobile Ad hoc network. Among them, lowest relative mobility clustering algorithm (MOBIC) based on mobility is proposed [19]. The algorithm regards the relative mobility between nodes as the criterion of cluster header selection. WCA and DWCA are put forward in terms of weight clustering [20; 21]. Although both of them take the mobility, the limited energy and the degree of nodes into consideration, it is also not involved in how to enhance the robustness and anti-attacks ability. Based on energy-efficiency of network, HEED formsclusters through a distributed scheme to render the energy consumption of network communication minimized [22]. The algorithm elects the cluster heads based on the residual energy of nodes, which means that the nodes with high residual energy are more possible to be elected as cluster head than other nodes. Based on fuzzy c-means clustering, an energy efficient \(CH\) selection is put forward [22].  
The cluster structure is optimized to consume less energy. However, in order to make a right decision, the fuzzy c-means protocol has to collect more information, which actually needs more energy and shortens the lifespan of network. So, the performance of the algorithm is not better due to the optimized structure. In [23], based on residual energy and trust value, a cluster head selection is put forward. The trust value according to the interactive history and residual energy of each node are calculated to be used as the criterion of selecting cluster head.  
In [24], a distributed fault tolerant topology control scheme based on cooperative communication is proposed. In the literature, the author first defined the \(k\)-connectivity and constructed a \(t\)-spanner with \(k\)-connectivity of an arbitrary communication network. The scheme enhances the fault tolerance ability and also takes the advantages of the cooperative communication to reduce the power consumption. Other algorithms also have their concentration on how to construct redundant backbone and \(k\)-connected graph network [25; 26; 27]. In addition, in order to overcome the malicious attack, trust model through the weighted method with direct trust and recommendation trust is proposed [28]. In the literature, author builds a trust model to measure whether a node is a malicious node or not. However, since the multi-hop recommendation messages forwarding, each node consumed much energy although the security of the network and fault tolerance is enhanced. Especially when the route is long, the transmission delay and throughput of the whole network are seriously decreased.  
In the literature [29], the author adopts a voting scheme in sparse sensor network to obtain each statue of fault node. However, this scheme based on crowd-sourcing will increase the complexity of algorithm and decrease the network lifetime. Additionally, the algorithm is based on a flat structure and the routing overhead will be amplified. Besides many high complexity algorithms are presented to solve the problem of fault node with a flat structure instead of clustering [30; 31; 32], however, it also results in energy depletion of the sensors nodes. In [33], a full 2-connectivity restoration (F2 CRA) algorithm and partial 3-connectivity restoration algorithm (P3 CRA) algorithm for connectivity restoration are put forward. The topology quality and network coverage are taken into consideration when enhancing the fault tolerance and restoration. Unfortunately, the algorithm is executed in a flat structure so that when the network scale becomes large, the complexity of the calculation is increasing dramatically. Consequently, the P3 CRA algorithm is not suitable for the large scale wireless sensor networks. In summary, these above algorithms sacrifice the validity for the sake of reliability. Therefore, a method and protocol which does not increase the connectivity of the network but enhances the fault tolerance ability with a hierarchical structure are motivated.