A Heuristic Angular Clustering Framework for Secured Statistical Data Aggregation in Sensor Networks  
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1 Department of IT, Kongu Engineering College, Tamil Nadu- 638060, India; [EMAIL_ADDRESS]  
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2 School of Computing Science & Engineering, Galogtias University, Uttar Pradesh 203201, India; [EMAIL_ADDRESS]  
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2 School of Information Technology and Engineering, VIT-Wellore, Tamil Nadu 632014, India; [EMAIL_ADDRESS]  
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3 School of Information Technology and Engineering, VIT-Wellore, Tamil Nadu 632014, India; [EMAIL_ADDRESS]  
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4 Advanced Manufacturing Institute, King Saud University, Riyadh 11421, Saudi Arabia 4  
converts them to a single tiny packet, and sends it to the sink node. Implementing the clustering technique reduces the network load and conserves energy, and makes the nodes live.  
Clustering, based on the size and shape of the deployment area, is a method adopted commonly to collect and transmit data to reduce energy consumption considerably. In previous research that has been studied, various clustering techniques have been identified to improve energy efficiency in a network of sensor nodes. However, most of the deployment structures adopted are either square or rectangular in shape. The square or rectangular-shaped structures might produce satisfactory results during simulation, but they are not suitable for all geographical regions for real-time deployment.  
In real-time applications, square-shaped sensors are not often deployed. For example, in airports, sensors are deployed in the passenger lobbies and runway paths, which are often irregular in shape. In weather stations also, sensors are deployed randomly in specific areas that are irregular in shape, based on the transmission range. Therefore, there is a need for an algorithm capable of adapting to any geographic region with different deployment structures.  
The security of sensor nodes and the data collected from the sensors that has to be transmitted securely to the sink or another network is another challenging issue, in addition to the deployment structure and cluster optimization. The intruders play a major role for spoofing the data in the middle. Many research algorithms and techniques were implemented to address the security issues like artificial intelligence mechanisms, multiagent schemes and artificial intelligent bots, etc. [8].  
Although attention has been given to the deployment structure, energy optimization in sensor nodes poses a significant challenge in WSNs. In recent years, several clustering approaches have been aimed at addressing the efficient energy consumption issues in WSNs [4; 5; 9; 10; 11; 12]. In most of the existing works, including LEACH [9], HEED [10], PEGASIS [13], enhanced LEACH and GBCR [14], and SPIN [15], the CH is selected based on the highest residual energy and the CH to CH data transmission is based on the coverage range and energy level. The selection and data transmission between CHs are based only on the energy levels and it could increase the number of hops from a CH to the sink node. The CH located closest to the mid area and angular-based routing can minimize the number of hops from the CH to the sink node.  
The major contributions of this work are:  
* to determine the shape of the deployment area and the coverage range based on the network area to ensure that no node is left unattended and
* to select the CH with energy optimization to achieve a balanced WSN with minimal energy requirements.