Wireless Sensor Networks (WSNs) based on the IEEE 802.15.4 MAC and PHY layer standards is a recent trend in the market. It has gained tremendous attention due to its low energy consumption characteristics and low data rates. However, for larger networks minimizing energy consumption is still an issue because of the dissemination of large overheads throughout the network. This consumption of energy can be reduced by incorporating a novel cooperative caching scheme to minimize overheads and to serve data with minimal latency and thereby reduce the energy consumption. This paper explores the possibilities to enhance the energy efficiency by incorporating a cooperative caching strategy.

Over the past years, wireless sensor systems have picked up a global consideration from both the researchers and the genuine clients. It includes a large number of sensing devices, some computing techniques and communication with limited power supplies and processing abilities which collectively work to fulfill a large sensing task. IEEE 802.15.4/ZigBee based Wireless Sensor Networks raise a few issues like Energy Scavenging for the limited power supply. Accordingly good functioning of such system relies upon energies of the wireless motes. This paper presents two analytical models which demonstrate and predict the QoS in terms of throughput, jitter, average end-to-end delay and energy consumption. These two distinct network models based on IEEE 802.15.4 are cluster-based and grid-based, and are simulated using QualNet v 6.1 Simulator.

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Considering Wireless Sensor Networks (WSNs) in today's scenario, sending and receiving uninterrupted sensory data remains a challenge to achieve with minimal latency and energy consumption as low as possible. Energy consumption is exponentially growing in computing devices such as computers, embedded systems, portable devices, and wireless sensor networks. Extensive research has been in practice recently to minimize energy consumption without compromising the Quality of Service (QoS) that is to provide data to the requester node with minimum Delay and high Reliability. In this paper, a cooperative caching algorithm is used with the proposed Distributed Energy Aware Routing (DEAR) protocol that attempts to minimize energy consumption by reducing the packet overhead in the network and also providing the data to the requester with minimum delay by retrieving requested datum from the nearby caching node available in the vicinity of the requester or sink node. The simulation results clearly show that the energy consumption is less when the grid-based analytical model is used against the star/cluster based model while keeping the same necessary attributes.

This paper demonstrates the investigation of the acquired outcomes from consistent information observing a 467.2 kWp solar photovoltaic (SPV) framework commissioned on the roofs of three separate high-rise buildings, which are located at the location of 26.9585° N and 80.9992° E. Onside real-time performance for this system was investigated for three years, 2018–2020; this system contains 1460 SPV panels of 320 Wp each, having 20 PV panels per string, 09 DC/AC power conditioning units (PCU), and a SCADA (supervisory control and data acquisition) system for monitoring the other necessary parts of a grid-interactive SPV system. The outcomes of the different buildings are compared with each other to analyze the power output at the same input conditions. Hardware components of the plants with approximately the same ratings (P2 ~ 108.8 kWp + P3 ~ 128 kWp) are compared (with P1 ~ 230.4 kWp). Simulation modeling of the year 2020 in PVsyst tool for generated energy, Performance Ratio (PR), and Capacity Utilization Factor (CUF) are carried out additionally and compared with the installed rooftop grid-interactive SPV system of 467.2 kWp (~P1 + P2 + P3) at the site. Numerous performance parameters such as array efficiency, inverter efficiency, system efficiency, Performance Ratio (PR), and Capacity Utilization Factor (CUF) of the plant are evaluated and compared with already installed systems in different regions of the world. These points demonstrate great feedback to framework architects, workers, designers, and energy suppliers regarding the genuine limit and plausibility of the framework they can offer to clients. Moreover, one of the environmental benefits of the SPV plant is that the 467.2 kWp PV framework reduces the tremendous measure of CO2, SO2, and NOX that is discharged into the air.