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.

An electronic nose is an instrument intended to mimic the human sense of smell. Electronic noses (e-nose) employ an array of chemical gas sensors, a sample handling system and a pattern recognition system. Pattern recognition provides a higher degree of selectivity and reversibility to the system leading to an extensive range of applications. These ranges from the food and medical industries to environmental monitoring and process control. Many other types of different gas sensors available. These include conducting polymers (CP), metal oxide semiconductors (MOS), piezoelectric, optical fluorescence, quartz crystal microbalance (QCM) and Amperometric gas sensors. The ideal gas sensor would exhibit reliability, robustness, sensitivity, selectivity and reversibility. High selectivity with high reversibility is difficult to attain. After signal processing and feature extraction the output of the sensors provide a unique "smellprint" for that substances which can be used to classify, measure concentration, or verify quality. The present paper illustrates the function of electronic nose, its application and investigates the effective use of e-nose in detecting gases that have some smell developed by the volatile organic compounds (VOC) like ethanol, acetone and benzene at different concentrations. The response and characteristics prove that the Electronic nose is a reliable instrument which can be used for environment control (air quality, pollutants, and gas emission levels), medical science (urine, skin and breath odour etc.), food industry (coffee, milk, soft drink fish, meat etc.), pharmaceutics, chemical industry, Defence and security industries (detecting humanitarian land mines etc.) and semiconductor industrial processes.

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.

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.

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