Analysis of single-hop routing protocol evaluation models in wireless sensor networks

This paper aims to introduce some key parameters for the tracking application in wireless sensor networks. In this work the Single-hop protocol with J-Sim simulation tool has been implemented, and consequently some useful trade-off analysis results among the density, coverage, reliability and lifetime have been obtained. Based on these results, two intelligent evaluation models are proposed in this paper.

Wireless network of wearable biomedical sensors by human body shows great potential to enhance the biometrics performance significantly. Meanwhile, it poses prominent characteristics and challenges to physicians and engineers for its particular medical application as compared to other application of wireless sensor networks (WSN). Mobility pattern plays an important role in designing the wireless body sensor networks (WBSN) and will also affect the accuracy of modeling WBSN in health care application. Much of the mobility scenarios generated in current work of wireless body sensor networks has used fairly simple models to generate the mobile topological graph, which bear little resemblance to the actual mobility patterns. This paper is the first attempt to investigate the mobility model in WBSN based on the existing mobility models in wireless data networks and ad hoc networks. We first briefly review the existing mobility models in related research areas such as wireless ad hoc network and cellular networks. Further on, we propose a dedicated and more realistic mobility model named BAMM (Body Area Mobility Model) for wireless body sensor networks by concentrating on the unique characteristics of WBSN and finally study the effects of mobility on the performance of WBSN by simulation experiments.

Resource Management Approach to an Efficient Wireless Sensor Network

The main study of traditional probability coverage problem in wireless sensor networks (WSNs) is aiming at two-dimensional space, however, most practical applications of wireless sensor network is placed in a three-dimensional sensor networks. Therefore, probability model is introduced for three-dimensional WSNs. This paper presents a method that using Voronoi divide to control the Scheduling of the probability model nodes in the target area. Also, a coverage control algorithm based on probability model (PMCCA) is proposed. We verify the effectiveness and the practice of PMCCA algorithm by comparing PMCCA algorithm to another algorithm in simulation experiment.

Developing Wireless Sensor Networks (WSN) applications is not an easy task, since it demands different expertise and knowledge. To address this problem, we propose a model-driven approach to build WSN applications. It promotes the separation of concerns between two levels of requirements involved: (i) domain experts, with no knowledge on WSN platforms, contribute to the development of applications, (ii) network experts, with no knowledge on the application domain, program nodes to meet application requirements. Our approach also promotes the reuse of software artifacts: an application model can be reused on different sensor platforms and a platform model can be reused for different WSN applications.

Wireless industrial sensor networks are wireless sensor networks which have been adapted to industrial applications. Most techniques for wireless sensor networks can be applied to wireless industrial sensor networks. However, for industrial applications of wireless industrial sensor networks, new requirements such as real-time, reliable delivery need to be considered. In this paper, we propose EARQ, which is a novel routing protocol for wireless industrial sensor networks. It provides real-time, reliable delivery of a packet, while considering energy awareness. In EARQ, a node estimates the energy cost, delay and reliability of a path to the sink node, based only on information from neighboring nodes. Then, it calculates the probability of selecting a path, using the estimates. When packet forwarding is required, it randomly selects the next node. A path with lower energy cost is likely to be selected, because the probability is inversely proportional to the energy cost to the sink node. To achieve real-time delivery, only paths that may deliver a packet in time are selected. To achieve reliability, it may send a redundant packet via an alternate path, but only if it is a source of a packet. Experimental results show that EARQ is suitable for industrial applications, due to its capability for energy efficient, real-time, reliable communications.

WITHDRAWN: Developing a software reliability evaluation model for wireless sensor networks based on analysis of software fault growth

The area of Ambient Intelligence recently seems to be matured enough and widely accepted as one of the basic supporting technologies and approaches for human living environment enhancement. There are many interesting applications of wireless sensor networks coupled with ambient intelligence applications, mainly for the creation of indoor intelligent spaces. However, there are just a few of them aiming at the enhancement of outdoor environments in order to support human activities typical for wide-area spaces in open natural environments. There are also a number of useful applications of wireless sensor networks aiming at environmental monitoring, however, just a few of them, if any, are taking advantage of recent achievements of Ambient Intelligence. In our paper, we intend to go further with the ideas of how the Ambient Intelligence used in a wide manner in connection with wireless sensor networks throughout the open natural environment could be beneficial not only for early warning in case of possible disasters, but also as an important supporting tool for people located in outdoor areas due to various reasons, e.g. hitchhikers, hikers on difficult mountains tracks, or even workers in exacting outdoor workplaces (i.e., a coal mine). An idea of a large-scale Ambient Intelligence system based on a wide area wireless sensor network is presented, where the system should be able to monitor the environment, evaluate the collected data and, if necessary, inform the workers in the environment about possible threats and also give some hints for their rescue, using various communication devices.

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.

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.

The study introduced foreign and domestic situation of wireless sensor network technology in precision agriculture in detail. Applications of wireless sensor network are universal in foreign precision agriculture, however in its beginning stage in domestic agriculture. The function of domestic system based on wireless sensor network is usually positioning measurement and processing of agriculture elements, which does not meet final requirement of precision agriculture. The study designed a universal wireless sensor network for M2M combined intelligent communication technology and big agriculture machinery. The key technologies of wireless sensor network for M2M include development plan of ISA SP100.11a, spectrum technology based on DSSS, network technology based on net routing and low power radio frequency design, which can meet the real-time character, reliability, robustness and low energy consumption requirement of wireless communication in precision fruits. Moreover, the study presented several typical applications in precision fruits (including farming machine, water-saving irrigation machine and picking machine). With development of precision fruits in breadth and depth, integration application of wireless sensor network would have a widen prospect in the future.

The wireless sensor network is an emerging technology, which is used to sense and monitor the environment. As the nodes are deployed in an open environment, the security is one of the essential factors. The cryptography techniques can ensure confidentiality, integrity and authentication. However, wireless sensor network also needs to deal with inside and outside attackers. To deal with outside attackers, attacks by compromised or malicious nodes, trust management system is suggested by many researchers in the area of wireless sensor network. Trust management system can be implemented in various applications for security management such as secure data aggregation, secure cluster head selection, trusted routing, access control, etc. Many researchers provide different kind of solutions for these secure applications based on trust management. However, to incorporate, all such applications on a single sensor node in the network, it is essential to design and develop a trust management system, which considers various aspects and applications of wireless sensor network. As a result, in this paper, we would like to propose a parameter and trust factor based secure communication framework and design a trust management system for wireless sensor networks. Our main contribution is to identify various parameters and trust factors which influences on trust in wireless sensor network and developing a framework for a trust management system based on various parameters and trust factors. The working of the proposed model is shown by simulation experiments conducted in MATLAB for the application of secure communication, data aggregation and intrusion detection in wireless sensor networks.

Wireless Sensor Network (WSN) technology has the potential to have impact on many aspects of Precision Agriculture (PA). However, current WSN applications in Precision Agriculture all adopt the traditional client/sever model, data are sent from the source to the destination, because of hugeous data, high concurrency and strong signal interference in Precision Agriculture and the extremely limited sensor network resources, such client/sever model hampers WSN applications in Precision Agriculture.[ This paper presents a mobile-based agent of wireless sensor network model MAPA, MAPA avoids the large agricultural intermediate data transmission through migrating the computing to the resource source, and consequently it prolongs the sensor network lifetime and promotes the WSN applications in Precision Agriculture.

Internet of Things (IOT) is experiencing a super-fast growing phase. Wireless Sensor Networks (WSN), as the “five sense organs” and teleneuron of IOT, is developing fast along. Owing to the application-oriented characteristics of WSN, WSN applications may differ enormously in implementation methods. The WSN developers may have to rewrite the code for each and every application. Along with the increasing demand to WSN applications, WSN developers may have heavier tasks of programming for these applications. Thanks to TinyOS and NesC, an operating system and programming language designed especially for WSN, raises the WSN application's programming to a higher level. Large number of supported sensor hardware plus system provided and user-de-fined libraries eases WSN application programmers' jobs. How-ever, the massive amount of nodes' communication and networking, and security protection slows down the development pace. A unified and empirical WSN application implementation platform is one of the available solutions to the problem. This paper introduces an empirical WSN application implementation platform, which avails the WSN developers build an application with unified code template and network packet generation and processing strategies.

Error control coding improves reliability and efficiency of wireless communication systems. This research delves into the latest advancements in error control coding schemes for wireless communication systems, with a specific focus on their application within the domain of Low Power Wide Area Networks (LPWANs) such as Narrowband Internet of Things (NB-IoT) systems, LoRa energy-efficient hardware design, random access control systems, and wireless sensor networks. In the context of LPWANs, particularly NB-IoT systems, we investigate the adaptive coding and modulation (ACM) in NB-IoT systems, which adapts coding rates and modulation techniques to changing channel circumstances. Comprehensive analysis of the literature review shows that the proposed approaches are more energy efficient and less error-prone than fixed coding and modulation schemes. Using Cell Design Methodology (CDM), Single Error Correction (SEC) codes are optimized for energy efficiency. Power and energy efficiency have improved in standard CMOS and CDM logic systems. This impacts IoT devices, memory storage, and security systems. Next, Forward Error Correction (FEC) is examined for ALOHA-based random-access control systems wherein packet loss rate and spectral efficiency metrics are mathematically calculated. FEC is beneficial, especially when time and frequency synchronization diverge. Monte Carlo simulations studied in the literature shows that FEC improves satellite communication systems. This review establishes benefits of FEC, notably in satellite communications systems. In addition, Wireless Sensor Networks (WSNs) error control techniques and network reliability and performance are examined along with Convolutional, Turbo, Low density parity check codes(LDPC), and Polar error correction coding (ECC) methods. We learn about their benefits, drawbacks, and implementation challenges by assessing their efficacy, efficiency, and applicability in wireless sensor networks (WSN) applications. This study further highlights advancements of energy-efficient error control coding when, integrated into network designs alongwith the trade-offs between efficacy and intricacy to help improve wireless communication networks. Finally, this study summarizes current error control coding approaches for wireless communication systems. We provide insights into improving reliability, energy conservation, and efficacy by examining ACM, CDM, FEC, and error correction coding (ECC) across varied domains including LPWAN and IoT technologies with earnest hope to facilitate researchers, engineers, and professionals working in the field of error control coding in wireless communication.