Academic literature on the topic 'Independent sensor networks'

Wireless Sensor Networks (WSNs) is a distributed wireless network consists of large amount of sensor nodes which gather useful information from a variety of environment and these sensor nodes communicate with each other in a multi-hop radio networks, with the end goal of handing their processed data to the data collector or access point (AP) [1,2]. WSNs have many issues such as self-configuration, fault-tolerance, adaptation, flexibility, energy efficiency, security, scalability, interference, architectural issues, mobility and delay tolerance [3]. Amongthese issues the most critical issue is to save energy and interference. The aim of this study is to construct the network graph which is conflict free and has minimum interference and minimum energy consumption. We have MAC Access protocols but TDMA protocol is more efficient than other protocols because TDMA can eliminate collisions and remove the need for a back-off [4]. A TDMA scheduling algorithm is constructed for the wireless sensor network, which is based on the creation of separate independent sets of the representing network graph. Independent sets are employed to minimize the time slots needed for the complete transmission of data packets in the network. An algorithm has been developed to implement it and there are three different steps in the implementation of this algorithm. In first phase, the minimum independent sets of the network are constructed. In second phase, the conflict graph of given network graph has been created. In third phase, time slots are assigned to all the transmissions according to the independent sets which were created in first phase, so that all the data packets are transmitted to the access point (AP) or data collector. The simulation results indicate that the TDMA scheduling algorithm reduce the interference and energy consumption in the network graph.

A wireless sensor network comprises of distributed independent devices, called sensors that monitor the physical conditions of the environment for various applications, such as tracking and observing environmental changes. Sensors have the ability to detect information, process it, and forward it to neighboring sensor nodes. Wireless sensor networks are facing many issues in terms of scalability, which necessitates numerous nodes and network range. The route chosen between the source node and the destination node with the shortest distance determines how well the network performs. In this paper, evolutionary algorithm based shortest path selection provides high end accessibility of path nodes for data transmission among source and destination. It employs the best fitness function methodology, which involves the replication of input, mutation, crossover, and mutation methods, to produce efficient outcomes that align with the best fitness function, thereby determining the shortest path. This is a probabilistic technique that receives input from learning models and provides the best results. The execution results are presented well compared with earlier methodologies in terms of path cost, function values, throughput, packet delivery ratio, and computation time.

Near real-time continuous monitoring systems have been proposed as a promising approach for enhancing drinking water utilities detect and respond efficiently to threats on water distribution systems. Water quality sensors are aimed at revealing contamination intrusions, while hydraulic pressure and flow sensors are utilized for estimating the hydraulic system state. To date optimization models for placing sensors in water distribution systems are targeting separately water quality and hydraulic sensor network goals. Deploying two independent sensor networks within one distribution system is expensive to install and maintain. It might thus be beneficial to consider mutual sensor locations having dual hydraulic and water quality monitoring capabilities (i.e. sensor nodes which collect both hydraulic and water quality data at the same locations). In this study a multi-objective sensor network placement model for conjunctive monitoring of hydraulic and water quality data is developed and demonstrated using the multi-objective non-dominated sorted genetic algorithm NSGA II methodology. Two water distribution systems of increasing complexity are explored showing tradeoffs between hydraulic and water quality sensor location objectives. The proposed method provides a new tool for sensor placements.

A passive wireless impedance-loaded orthogonal frequency-coded (OFC) surface acoustic wave (SAW) sensor for wireless sensor networks was proposed in this paper. One of the chips on OFC SAW tag is connected to an external sensor, which could cause a phase shift in the time response of the corresponding part on the SAW device. The phase shift corresponds to the sensed quantity, which could be temperature, strain, vibration, pressure, etc. The OFC SAW tag is isolated by a proper package from the direct effect of the measurand on the device’s response which could avoid the multiple measurands coupling. The simultaneous work of multiple sensors is guaranteed by orthogonal frequency coding. By processing the response based on an extended matched filter algorithm, sensing information of the specific coded OFC device can be extracted from the superimposed response of multiple independent encoded sensors. Compared to previous methods, the proposed method can produce a more flexible passive (battery-free) wireless sensor suitable for large-scale wireless sensor networks. Simulation and experimental results demonstrate the effectiveness of the sensor.