Thin films of CdS x Te 1-x were deposited by the pulse electrodeposition technique using cadmium sulfate, sodium thiosulfate, and tellurium dioxide on titanium and conducting glass substrates. Structural studies indicated the formation of polycrystalline films possessing hexagonal structure. The resistivity varies from 53 Ω cm to 8 Ω cm as the stochiometric coefficient "x" value decreases from 1 to 0. The carrier concentration increases with CdTe concentration. It is observed that as the post-heat treatment temperature increases, the photosensitivity also increases. It is observed that a post-heat treatment temperature of 550°C results in high photosensitivity as well as low light resistance. The optical constants, refractive index (n) and extinction coefficient (k) were evaluated from the transmission spectra of the films of different composition.

Wireless Sensor Networks (WSNs) are spatially distributed to independent sensor networks that can sense physical characteristics such as temperature, sound, pressure, energy, and so on. WSNs have secure link to physical environment and robustness. Data Aggregation (DA) plays a key role in WSN, and it helps to minimize the Energy Consumption (EC). In order to have trustworthy DA with a rate of high aggregation for WSNs, the existing research works have focused on Data Routing for In-Network Aggregation (DRINA). Yet, there is no accomplishment of an effective balance between overhead and routing. But EC required during DA remained unsolved. The detection of objects belonging to the same event into specific regions by the Bayes Node is distributed through the Sensor Nodes (SNs). Multi-Sensor Data Synchronization Scheduling (MSDSS) framework is proposed for efficient DA at the sink in a heterogeneous sensor network. Secure and Energy-Efficient based In-Network Aggregation Sensor Data Routing (SEE-INASDR) is developed based on the Dynamic Routing (DR) structure with reliable data transmission in WSNs. Theoretical analysis and experimental results showed that in WSN, the proposed Bayes Node Energy Polynomial Distribution (BNEPD) technique reduced Energy Drain Rate (EDR) by 39% and reduced 33% of Communication Overhead (CO) using poly distribution algorithm. Similarly, the proposed MSDSS framework increased the Network Lifetime (NL) by 15%. This framework also increased 10.5% of Data Aggregation Routing (DAR). Finally, the SEE-INASDR framework significantly reduced EC by 51% using a Secure and Energy-Efficient Routing Protocol (SEERP).

In this study, we can design data aggregation using the routing protocols, Data aggregation can reduce the cost of communication in the wireless sensor network. Heavy traffic occurs when the multiple sensor nodes has detect one or more events. To Save the energy, the network should notify the event properly, only when an event occurs. Overhead occurs in InFRA because its scalability is very low. In the proposed DRINA(Data Routing for In-Network Aggregation) algorithm reduces the communication cost and saves the energy consumption by building the routing tree, maximized the number of overlapping routes and eliminating the redundant data. The performance of the DRINA has compared to three other known protocols: the Information Fusion-based Role Assignment (InFRA), Shortest Path Tree (SPT) algorithms and Centered-At-Nearest-Source algorithm (CNS).

Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

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