Rotation Scheme Based Power Consumption Analysis for Wireless Sensor Network

Wireless sensor node is an autonomous and compact device that has capability to monitor a variety of real-world phenomena. It is designed composed of sensing device, embedded processor, communication module, and power equipment. Wireless sensor node is part of wireless sensor network where hundred or thousand sensor node can be deployed. Over the past decade Wireless Sensor Networks (WSNs) have emerged as one of the computing platforms of note within the electronics community. In prediction, there will be more than 127 million wireless sensor nodes deployed worldwide by 2014. We have surveyed 100 currently available wireless sensor network node platforms have been developed and produced not only by the research institutions, the universities but also some companies in last ten years. In this paper, we present a review of 27 different wireless sensor node platforms. We review these devices under a number of different parameters, and we highlight the key advantages of each node platform according to dimension and power consumption. We also discuss the characteristics and trend of development and deployment a wireless sensor node technology.

Wireless sensor networking is a rapidly merging research area. There are many areas where Wireless Sensor Network (WSN) applications are very important such as military, healthcare, agricultural and transportation. In WSN applications, power consumption is foremost crucial. Therefore reducing power consumption is a focal concern when developing WSN applications. Majority of power in WSN environment is used for communication purpose. As such the facility to acquire data based on location only from sensor node at required location would save power consumption. However this type of data acquisition has not been possible due to the unavailability of spatial queries. The acquisitional queries should be enhanced with the location aspect and moreover each sensor node should also be made aware of its location. This will enable user to specify queries based on the location and only the corresponding nodes respond by acquiring data. Thus main objective of this research is to come up with this enhancement. We have purposed spatial query syntaxes which have similar features as in Relational database spatial queries and main target of that approach is to increase the user friendliness. Other than that sensor nodes in the sensor network are capable to identify its location based on the GPS value. We evaluate these issues in the context of TikiriDB, a distributed, shared WSN, query processor for smart sensor devices, and show how acquisitional data based on location can provide significant reductions in power consumption on our sensor devices.

Wireless sensor networks (WSNs) of spatially distributed autonomous sensors are used to monitor physical or environmental conditions such as temperature, sound, pressure, etc. They are also used to cooperatively pass the collected data through the network to a main location. Due to the application of wireless sensor networks as a monitoring device in the real world, the physical time of the occurrence of events is important. Since WSNs have particular constraints and limitations, synchronizing the physical times for these networks is considered to be a complex task. Although many algorithms have been proposed for synchronizing time in the network, there are two main error factors in all the proposed algorithms. The first factor is the clock drift which might be caused by the influence of different environmental factors such as temperature, ambient temperature, humidity, it might be generated on crystal oscillator which is inevitable The second error factor is indeterminacy which is attributed to the existence of non-deterministic delays in sending and receiving messages between sensor nodes. These two factors together reduce the precision of synchronization algorithms. In this paper, the researchers proposed a new approach for dealing with the above-mentioned two problems and achieving better synchronization. The proposed approach is a combination of flooding time synchronization protocol (FTSP) and reference broadcast synchronization (RBS).This approach is intended to increase synchronization accuracy and network lifetime by reducing the number of synchronization messages sent between nodes and eliminating the most of non-deterministic errors in sending messages. The results of simulations conducted in the study indicated that the proposed approach is significantly more efficient than the FTSP and RBS methods in terms of parameters such as accurate synchronization, amount of sent packets and power consumption.

A scheme for WSNs (wireless sensor networks) security is given by dividing sensing tetrahedron into clusters and using the symmetric polynomials in this paper.The sensing tetrahedron is divided into a number of small grids.All those sensor nodes, both ordinary sensor nodes and heterogeneous sensor nodes are distributed in the sensing tetrahedron.In a grid, all ordinary sensor nodes and heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.All the heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.At last, all sensor nodes establish their keys directly or indirectly in the whole sensing tetrahedron.Analysis and comparison demonstrate this scheme enhances the WSN security, has good network connectivity, saves node storage, reduces network computing load, and extends the network lifetime.

With the advent of ubiquitous computing society, many advanced technologies have enabled wireless sensor networks which consist of small sensor nodes. However, the sensor nodes have limited computing resources such as small size memory, low battery life, short transmission range, and low computational capabilities. Thus, decreasing energy consumption is one of the most significant issues in wireless sensor networks. In addition, numerous applications for wireless sensor networks are recently spreading to various fields (health-care, surveillance, location tracking, unmanned monitoring, nuclear reactor control, crop harvesting control, u-city, building automation etc.). For many of them, supporting security functionalities is an indispensable feature. Especially in case wireless sensor networks should provide a sufficient variety of security functions, sensor nodes are required to have more powerful performance and more energy demanding features. In other words, simultaneously providing security features and saving energy faces a trade-off problem. This paper presents a novel energy-efficient security architecture in an IEEE 802.15.4-based wireless sensor network called the Hybrid Adaptive Security (HAS) framework in order to resolve the trade off issue between security and energy. Moreover, we present a performance analysis based on the experimental results and a real implementation model in order to verify the proposed approach.

Smart sensor network technology integrates sensors, embedded computing, modern networks, wireless communication and distributed information processing technologies, and is currently a frontier hot research field in the world. The application of wireless sensor network to the greenhouse environment monitoring system to realize self-organizing network, wireless data transmission and intelligent control is also of great significance to the realization of agricultural modernization. The purpose of this paper is to study the monitoring of macadamia nut planting environment based on smart sensor technology. Since the greenhouse environment monitoring system has very high requirements for power consumption, cost and stability, this article selects ZigBee wireless sensor network technology with low power consumption, low cost, high stability, etc. to build a set of monitoring temperature and humidity Greenhouse wireless smart sensor network model. According to the actual requirements of greenhouse environment monitoring, this article proposes a new type of ZigBee technology-based greenhouse macadamia nut planting environment monitoring system solution, and gives the overall structure of the system. Considering many aspects such as cost and power consumption, this article stores, displays, analyzes and processes the acquired data. The functions of the system meet the design requirements. The system realizes the collection of greenhouse parameters and the data display and processing functions, and realizes the video monitoring of the greenhouse. Experimental studies have shown that in the actual greenhouse environment, due to a large number of crops blocking, it is bound to produce certain obstacles to signal transmission, but because of the large number of nodes, the distance between the node and its parent node will not exceed 25m, which also ensures The data collected by sensor nodes can be safely and error-freely transmitted to the coordinator node in a multi-hop manner.

Data gathering is a major function of many applications in wireless sensor networks. The most important issue in designing a data gathering algorithm is how to save energy of sensor nodes while meeting the requirements of special applications or users. Wireless sensor networks are characterized by centralized data gathering, multi-hop communication and many to one traffic pattern. These three characteristics can lead to severe packet collision, network congestion and packet loss, and even result in hot-spots of energy consumption thus causing premature death of sensor nodes and entire network. In this paper, we propose a load balance data gathering algorithm that classifies sensor nodes into different layers according to their distance to sink node and furthermore, divides the sense zone into several clusters. Routing trees are established between sensor node and sink depending on the energy metric and communication cost. For saving energy consumption, the target of data aggregation scheme is adopted as well. Analysis and simulation results show that the algorithm we proposed provides more uniform energy consumption among sensor nodes and can prolong the lifetime of sensor networks.

The rapid advancement of programmable logic devices (PLDs) and field-programmable gate arrays (FPGAs) has enabled the development of adaptive VLSI architectures optimized for next-generation wireless communication systems. This research focuses on RFID and Wireless Sensor Network (WSN) applications, integrating AI-driven optimization techniques to enhance power efficiency, processing speed, and system adaptability. A hybrid AI-based hardware optimization technique, combining Reinforcement Learning (RL) and Genetic Algorithm (GA), is introduced to improve resource utilization and reduce latency. Additionally, an AI-Optimized Dynamic Frequency Scaling (DFS) technique is implemented to adjust FPGA operating frequencies in real-time, achieving a power reduction of 27.6% while maintaining high computational efficiency. Processor implementation for RFID-based power-saving appliances, reducing power consumption by 32.5% compared to conventional approaches. Hardware realization of an optimized anti-collision algorithm for RFID, achieving a 24.8% increase in tag identification speed. FPGA-based security architecture integrating lightweight cryptographic techniques, enhancing data security with a 96.2% encryption success rate and 25% lower hard-ware resource usage. Power-efficient WSN node implementation using an adaptive localization algorithm, reducing localization errors by 18.4% and extending node lifespan by 29.3%. Low-power CORDIC algorithm-based DPSK modem implementation with 32.1% lower latency in real-time signal processing applications. AI-Optimized DFS technique, reducing dynamic power consumption by 27.6% and improving computational throughput by 22.7%, making FPGA implementations more energy-efficient. The designs were developed using VHDL-based high-level hardware description, simulated in Xilinx ISE 14.3, and implemented on Virtex-5, Spartan-6, and Kintex-7 FPGA platforms. Performance evaluations and comparative studies with existing models confirm significant improvements in power efficiency, processing speed, and adaptability. The findings contribute to the development of high-performance, power-efficient, and scalable VLSI architectures for RFID and WSN applications, paving the way for next-generation secure and intelligent wireless communication systems.

For most wireless sensor network (WSN) applications, the positions of the sensor nodes need to be known. Global positioning systems have not fitted into WSNs very well owing to their price, power consumption, accuracy and limitations in their operating environment. Hence, the last decade has brought about a large number of proposed methods for WSN node localization. They show tremendous variation in the physical phenomena they use, the signal properties they measure, the resources they consume, as well as in their accuracy, range, advantages and limitations. This paper provides a high-level, comprehensive overview of this very active research area.

ABSTRACTLocation information of sensor nodes is of vital importance for most applications in wireless sensor networks (WSNs). This paper proposes a new range-free localisation algorithm using support vector machine (SVM) and polar coordinate system (PCS), LSVM-PCS. In LSVM-PCS, two sets of classes are first constructed based on sensor nodes’ polar coordinates. Using the boundaries of the defined classes, the operation region of WSN field is partitioned into a finite number of polar grids. Each sensor node can be localised into one of the polar grids by executing two localisation algorithms that are developed on the basis of SVM classification. The centre of the resident polar grid is then estimated as the location of the sensor node. In addition, a two-hop mass-spring optimisation (THMSO) is also proposed to further improve the localisation accuracy of LSVM-PCS. In THMSO, both neighbourhood information and non-neighbourhood information are used to refine the sensor node location. The results obtained verify that the proposed algorithm provides a significant improvement over existing localisation methods.

With the advent of technology MEMS came surpassing and led to the design of very small sensor nodes. This led to the creation of wireless sensor nodes. Background: Wireless Sensor Networks are entrancing to researchers due to their wide range of ever-growing application potential in every area and have been adapted in order to implement many applications such as habitat monitoring, military surveillance, precision agriculture. One of the major design challenges in Wireless Sensor Networks is power consumption. Analysis: It is crucial in various functions to position sensor nodes in an efficient way in order to monitor the event squarely and deliver the data to sink node. Uneven power consumption by nodes leads to the creation of energy holes, which means that data can never be delivered to the sink on that path. Findings: The sensor nodes located near to the sink node as the precedence, as there are the first ones to get effected due to this power consumption patterns and in 99 percent of the cases the first and the second rings are the places where an energy hole is first created. The main aim of this paper is to develop an algorithm using hashing technique which reduces the power consumption and energy harvesting is done optimally by avoiding duplication of packets in static network. Improvements: The power consumption improvement ratio and the life elongation of the network were simulated using Network simulator tool using the hashing technique and avoiding duplication of packets.

Wireless sensor networks consist of a large number of low-cost, low-power, and multifunctional sensor nodes that communicate over short distances through wireless links. Such sensor networks are ideal candidates for a wide range of applications such as monitoring of critical infrastructures, data acquisition in hazardous environments, industry control systems, vehicular networks, and military operations. Wireless sensor networks introduce new security challenges due to their dynamic topology, severe resource constraints, and absence of a trusted infrastructure. The purpose of this special issue is to publish high-quality research papers as well as review articles addressing recent advances of wireless sensor network security. In this special issue, we will explore the topic of security challenges and solutions for the wide application of wireless sensor networks in different areas, such as RFID and smart grid. RFID has been widely used in logistics and internet of things. Smart grid leverages sensor networks to better balance the load of the power grid. Both of them have great impact on the daily life and areweak points of thewhole economy,which attract the attention of terrorists. The feasible attacks and defense solutions are still not clear.The papers in this volume also cover several important foundational security services for wireless sensor networks, such as key management, key distribution, secure cluster formation, secure architecture for multihop communication, intrusion prediction, and secure localization. All these foundational security services are critical bases for application of wireless sensor networks. We hope that the papers in this volume engender further thinking about new security challenges for wireless sensor networks and even further “out-of-the-box” ideas about how to solve new security problems for wireless sensor networks.

A Wireless sensor network (WSN) comprises several sensor nodes such as magnetic, thermal, and infrared, and the radar is set up in a particular geographical area. The primary aim of sensor network is to transmit reliable, secure data from one node to another node, node to base station and vice versa and from base station to all nodes in a network and to conserve the energy of sensor nodes. On the other hand, there are several restrictions such as large energy consumption, limited storage/memory and processing ability, higher latency, and insufficient resources. The related security issues in wireless sensor network are authenticity, confidentiality, robustness, integrity, and data freshness. The sensor nodes are susceptible to several attacks such as DOS, Sybil, flood, black hole, selective forwarding which results in the leakage of sensitive and valuable information. It is therefore necessary to provide security against these critical attacks in the network. Wireless sensor network were earlier used for military applications with the objective of monitoring friendly and opposing forces, battlefield surveillance, detection of attacks, but today Wireless Networking have a huge number of applications-environmental, healthcare, home, industrial, commercial and are still counting. This paper is an extensive review of the security requirements, attacks that are to be avoided and resolved for achieving a secure network connection. This paper also emphasizes various limitations and defense strategies to prevent threats and attacks. The issues of applications of wireless sensor network for smooth and reliable transmissions are also discussed. The sensor networks are popular for mission-critical-tasks and security is immensely required for such hostile environment employed networks.

In some applications of wireless sensor networks (WSN), sensor nodes are mobile while the sinks are static. In such dynamic environment, situations may arise where many sensor nodes are forwarding data through the same sink node resulting in sink overloading. One of the obvious effects of sink overloading is packet loss. It also indirectly affects the network lifetime in loss-sensitive WSN applications. Therefore, proper placement of sinks in such dynamic environment has a great impact on the performance of WSN applications. Multiple sink placement may not also work in some situations as node density may not be uniform. This paper introduces a sink placement scheme that aims at gathering experiences about sensor node density in a region at different times and based on these observations, the scheme proposes candidate sink locations in order to reduce sink overloading. Next, based upon current sensor node density pattern, sinks at these locations are scheduled to active mode, while sinks at remaining candidate locations are scheduled to sleep mode. The second phase is repeated periodically. The scheme is implemented in a simulation environment and compared with another well-known strategy, namely Geographic Sink Placement (GSP). It has been observed that the proposed scheme exhibits better performance with respect to sink overloading and packet loss in comparison with GSP.

The range of applications of Wireless Sensor Networks (WSNs) is increasing continuously despite of their serious constraints of the sensor nodes’ resources such as storage, processing capacity, communication range and energy. The main issues in WSN are the energy consumption and the delay in relaying data to the Sink node. This becomes extremely important when deploying a big number of nodes, like the case of industry pollution monitoring. We propose an artificial neural network based energy-efficient and robust routing scheme for WSNs called ELDC. In this technique, the network is trained on huge data set containing almost all scenarios to make the network more reliable and adaptive to the environment. Additionally, it uses group based methodology to increase the life-span of the overall network, where groups may have different sizes. An artificial neural network provides an efficient threshold values for the selection of a group's CN and a cluster head based on back propagation technique and allows intelligent, efficient, and robust group organization. Thus, our proposed technique is highly energy-efficient capable to increase sensor nodes’ lifetime. Simulation results show that it outperforms LEACH protocol by 42 percent, and other state-of-the-art protocols by more than 30 percent.