ODCHM: Optimal Dynamic Convex Hull Computation Model for Efficient Data Delivery in Uncertain Wireless Sensor Networks

Uncertain Wireless Sensor Network (WSN) conditions create a continuous burden for ensuring feasible data communication. Particularly, the characteristics such as movement of sensor nodes, frequent link breaks, unexpected node failures, channel distortions and energy conservation limits of WSN make the data sessions at uncertain state. Under these conditions, the deployment of an optimal WSN model is a challenging task on the field. The existing solutions use various node management, clustering procedures and link management techniques against the uncertain issues of WSN fields. Yet the successful and stable data transmission is unpredictable in complex WSN environment. On the constraint, the proposed Optimal Dynamic Convex Hull Computation Model (ODCHM) is developed to initiate more sophisticated clustering principles to achieve better data delivery rate in WSNs. Under this model, the novel phases such as uncertain (reactive) quick hull principles, secure trust evaluation schemes, network dynamic monitoring principles, modified routing protocol (Hybrid and Clustered Multi-Path Routing Protocol, HCRP) and network regeneration procedures. According to this proposed model, reactive quick hull principles are creating and managing network boundaries against uncertain conditions of WSNs. In the next phase, secure trust evaluation procedures are executed to compute the trust cost functions, hash validations, event log validations and malicious event identification. Third phase of proposed model gives the technical benefits of creating random convex hull-based clusters on demand basis under uncertain WSN changes with the help of modified HCRP rules. The integrated technical solutions of proposed ODCHM are providing the better data delivery rate than existing techniques by 12% to 15%. The implementation details and results are given in appropriate section.