# ERCP: Energy-Efficient and Reliable-Aware Clustering Protocol for Wireless Sensor Networks
## 1 Introduction  
A Wireless Sensor Network (WSN) refers to an infrastructure-less system of numerous tiny devices called sensor nodes. Such nodes are responsible for monitoring the area of interest and communicating with each other via wireless links to send their collected information to the sink node. However, the WSN is known to be a highly resource-constrained network, in which the energy constraint is always the main issue that affects the network operation. This results in researchers' primary concerns in this field being energy conservation and the network's lifetime [1, 2, 3]. Indeed, communication is the major source of energy consumption in WSNs. For this reason, numerous research publications have examined the energy-aware routing problem in WSNs [4, 5]. Among massive energy-aware routing techniques, cluster-based routing is one of the most effective solutions that can conserve sensor nodes' energy and thus increase the network's lifetime. In the clustering process, the network is divided into groups. Each group has a head or leader. Such cluster heads collect sensor nodes' local data, aggregate it, and transfer it to the sink node directly or via other cluster heads [6]. However, thecluster heads may lose their energy faster than the conventional sensor nodes due to the extra load of receiving, aggregating, and transferring data to the sink node. Hence, the cluster heads should be energy-efficient nodes because of their transmission and reception responsibilities. The death of such nodes in an area would cause network partitioning, and, thus, important data may be lost. Therefore, the proper selection of cluster heads plays a vital role in conserving sensor nodes' energy and enhancing the network's lifetime. In this context, in many existing clustering techniques, the cluster head assignment depends on the average cluster distance to maximize cluster heads' lifetimes. Therefore, the cluster heads are placed near their member nodes. Certainly, if a cluster head dies, the network may suffer from severe energy unbalance. Consequently, designing an energy-balanced clustering strategy is highly needed to optimize the network's lifetime [7; 8]. In view of the above advantages of the clustering techniques, numerous cluster head election strategies have been suggested in the literature for energy consumption conservation and network lifetime enhancement. Most of them tried optimizing energy efficiency by employing nodes' energy in the cluster head decision to address the energy unbalance problem [3; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24]. However, from our point of view, in addition to energy, reliability is another factor that needs careful consideration when designing any clustering algorithm. The quality of wireless links enables sensor nodes to communicate with each other; thus, reliable wireless links would be required to successfully deliver data packets from the member nodes to their cluster heads. However, due to wireless communication's inherent nature in WSNs, packet losses are quite inevitable. Wireless connections are prone to network disturbances due to several environmental parameters such as interference and fading. This increases the retransmission possibility of lost packets and thus causes more energy consumption and more delivery delay. This eventually affects the network's throughput and lifetime [25; 26; 27; 28]. To address the problems mentioned above, the work in this paper involves two phases. In the first phase, a cluster head is chosen, while the second phase proposes an inter-cluster routing algorithm. The proposed framework considers energy efficiency and network reliability to optimize the network's lifetime and throughput. The major contributions are as follows:  
1. Propose a novel energy-efficient and reliable clustering algorithm considering nodes' residual energy, quality of wireless links, cluster head load, and distance representing the average intra-cluster distance and distance to sink node. 2.