## 3 Cluster Formation
### Failure Management
#### 3.3.1 Permanent-Fault Management  
In [90], Zone-based Fault-Tolerant Management Architecture (ZFTMA) is proposed to improve the network efficiency and reliability by adding fault detection and recovery functions as an integral part of the network management systems of the cluster-based algorithms. To minimize resource utilization, the network is divided into four zones; each zone is supervised by Zone Manager node (ZM), which performs as the task manager of the zone in setup phase and is a gateway for forwarding the aggregated data of CHs in steady data transmission state. The CH selection and formation stages of the algorithm are the same as LEACH. However, ZFTMA performs four levels of fault-management, including self-managed CH rotation, sensor node fault-detection, CH node fault detection and CH fault recovery. At the First level, each CH continuously monitors its level of remaining energy. When it drops below a predefined threshold value, the CH selects the highest energized node among its cluster members and announces it as new CH. Sensor node fault-detection level is performed by CHs. The nodes, not sending any packets in a round, are first flagged as suspicious nodes, and after a specific time interval of not hearing from a node, CH announces the node as faulty to the rest of the network. The same procedure is done for CH fault detection level, with a subtle difference that in this level, ZM performs CH fault detection inside its supervised zone and initiates CH fault recovery. At the recovery stage, the algorithm exploits the ZMs' complete view of their zones obtained during data transmission stage by generating lists of all CHs and their cluster members. Having a complete view of the zone topology, ZM selects the new CH among the cluster members of faulty cluster, based on the merit of residual energy. ZFTMA properly addresses node failure at all cluster levels (except ZM) and provides a fault-management platform. However, one drawback of the algorithm is maintaining and transmitting lists of cluster members to ZMs, which imposes extra memory usage and energy expenditure, especially in large-scale networks. Furthermore, the algorithm does not provide any failure recovery strategy for faulty ZMs, thus a faulty ZM may be a bottleneck for the performance of the scheme. [PERSON] _et al._[91; 92] proposed an energy-efficient distributed cluster-based failure management approach to detect failing nodes and recover the connectivity of network. The main objective of the algorithm is to achieve fast failure recovery with the least overhead, while it only addresses the permanent event failures due to energy exhaustion. The applicability the algorithm is dependent on the special clustering protocol presented by the same author in [96]. According to this clustering scheme, clusters are formed using an expanding ring-search technique. In this technique, CH selects its one-hop neighbouring nodes and each node follows the same procedure for a maximum of \(D\) number of nodes, until the number of cluster members reaches a predefined maximum number. Based on this technique of clustering and for improving the scalability and manageability of failure detection and recovery, the nodes in clusters are classified into four types: boundary node (has no children), pre-boundary node (whose children are all boundary nodes), internal nodes (has at least one pre-boundary or internal node as a child) and CH node. The failure detection scheme is the same for all four types of nodes through receiving a failure report message generated by a node whose energy level fails below a threshold value, while the threshold value is defined as the energy required for transmission of \(D\) number of _l-bit_messages across a distance equal to the node's transmission range. However, the failure recovery algorithm is slightly different for each type of node as follows:  
1. _Boundary Node Failure Recovery Algorithm_: since the boundary nodes are in fact the leaf nodes, their failure does not affect the connectivity of the network.