The detection points are the detection points in the space of network. The properties of detection points include cost effective materials and longer battery capacity. WSN can span variety of applications like sensing of data related to environment entities, detection of enemy vehicles. Lifetime ratio defines the efficiency of the WSN network operation. There are multiple techniques which can help in improvement of Network Lifetime (NL) spanning from transmission nature, data connections, formation of System and time scheduling. This paper provides the analysis of how energy consumption happens and its effect on lifetime ratio. LEACH and CHEF algorithms responsible for hierarchical kind of routing are discussed in detail with simulation results. The parameters used for comparison includes delay, hops, consumption of energy. Non-Hole detection points, Hole detection points, Non-Hole to Hole Ratio, residual energy, routing overhead and throughput.

WSN consist of set of Sensing points which are responsible for collecting the detected information and then send the packets towards control centre which is responsible for processing of data. The applications of WSN include environmental data analysis, defence data collection and information. The survey of algorithms is done for the improvement of lifetime ratio. Four different algorithms namely Random, Random-CGT, EGT-Random and GTEB algorithms. The four algorithms are compared and then it is proved GTEB exhibits best behaviour with respect to energy consumed, number of non-holes, number of holes, Non-Hole to Hole ratio, residual energy, overhead and throughput.

The current Wireless Sensor Network (WSN) lacks the desired power owning to the non-availability of the power source. The challenge posed in the current scenario is conserving power for effective data transfer, which is seldom achieved. Added to the owes is the evolving technological innovations where the physical size of the Packet Forwarding Nodes (PFNs) is also reduced along with its power source, thereby reducing the power available to the system and making it inefficient. The existing methodology employed in monitoring the parameters used in Epidemic Algorithm (EA) and Incentive Compatible Routing Protocol (ICRP) protocols which are power guzzlers, the power available for data transfer is greatly reduced making the entire system inefficient. This paper attempts to mitigate the challenges posed by the EA & ICRP, the proposed protocol, “Incentive Routing Protocol with Virtual Projection (IRPVP)”, employs a Relay Sensing Node (RSN) which is designed to be distributed in a square cross-sectional area where each node acts as a unique Sensing Point (SP) monitoring each of the essential parameters like energy consumption, vibrant & non-vibrant SPN count, residual energy and routing overhead while still retaining power for data transfer since the RSN is connected to a dedicated power source. In IRPVP protocol, each packet of a node is subdivided into fragments that are designed to have fixed or variable lengths depending upon the application. Each of these packets is sent over multiple Packet Forwarding Nodes (PFNs) towards the data center. The selection of PFNs in the path is based on their trust levels like meeting probability, computation of residual energy, data weight, and security value. Special PFNs are placed in the network and are entrusted to deliver the packets to the data center without data loss during transmission. The result of the IRPVP protocol Vis-à-Vis the EA & ICRP protocol, backed by the simulation results proves that the IRPVP protocol is better in data handling and is more efficient.

No abstract