In WSN-assisted IoT environment, the sensors are resource constrained. The energy, computing and storage resources of deployed sensors in the sensing area are limited. Clustering is the key method for saving energy in wireless sensor networks. A hybrid protocol named as an Energy Efficient Centroid-based Ant colony Optimization (EECAO) protocol is proposed in this paper to improve the performance of the sensor network in WSN-assisted IoT environments. The protocol uses the concept of centroid based clustering to gather the information of local clusters and ant colony optimization to relay that information to the base station. proposed hybrid protocol includes multiple clustering factors such as energy cost, channel consistency and cognitive sensor throughput to select cluster heads and a new distributed cluster formation for self-organizing deployed sensors. Selection of the super cluster head among the cluster heads is based on the energy centroid position for a defined coverage area. In EECAO protocol, the energy level of cognitive sensors is the key parameter for defining the position of centroid. To reduce the long-distance communication, path optimization between the super cluster heads and the base station is carried out using an ant routing model. Our simulation results indicate that EECAO protocol performs better when benchmarked against existing ETSP and EECRP protocols. The proposed hybrid protocol EECAO is well-suited for networks that requires long lifetime when the base station is placed at either center, border or outside the network.

Wireless sensor network is highly resource constrained, where energy efficiency and network lifetime plays a major role for its sustenance. As the sensor nodes are battery operated and deployed in hostile environments, either recharging or replacement of batteries in sensor nodes is not possible after its deployment in inaccessible areas. In such condition, energy is the vital factor for the survival of sensor node in the sensing field. In order to increase the network lifetime and balance the energy consumption, robust routing protocols are required. The proposed network routing has three phases: 1. Network initiation phase to create a zone which enables the communication among local nodes 2. Zone coordinator selection phase algorithm to form zone cluster and its re-election procedure and 3. Zone head selection with its replacement phase based on energy centroid positional information and distance to the basestation to distribute load equally among zone coordinators , local sensor nodes. The data path between zone heads and basestation is distance centric and is optimized at one hop and dual hop levels to avoid data packet loss at zoneheads. Each zone is designed to own atmost ¼ rth of deployed sensor node count through uniform random deployment. Simulations results when basestation is placed inside sensing field indicates that the proposed network algorithm outperforms when benchmarked against similar protocols like conventional LEACH, Traditional PEGASIS, existing PRRP, ES3 protocols in terms of performance metrics like Network energy consumption, Average energy consumed by sensor node, Packet delivery ratio, Packet loss percentage and Network throughput.

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