An implementation of anonymous authentication system in wireless sensor network using vlr group signature

Nowadays, the efficiency of multiagent systems in wireless sensor networks prompts the researchers to use these emerging mobile software packets in different simulated approaches or real-world applications. Heterogeneous and distributed wireless sensor networks could be integrated with the multiagent systems to map the real-world challenges into the artificial intelligence world. The multiagent systems have been applied from simulated approaches like object detection/tracking, healthcare, control/assistant, and security systems to real-world applications, including medical/human-care systems and unmanned aerial vehicles. Furthermore, the integration of wireless sensor networks with multiagent systems have emerged novel application, which is known as mobile robots. However, the extensive use of mobile agents in wireless sensor networks has posed different challenges for researchers, including security, resource, and timing limitation. In this work, we review recent simulated approaches and real-world applications of multiagent systems in wireless sensor networks, in which a set of common factors about the things that have been studied are extracted and compared to analyze the performance of mobile agent–based systems in the wireless sensor networks, as well. This analysis provides new research directions about multiagent systems in wireless sensor networks for interested researchers. Finally, a novel framework for dealing with the challenges of multiagent-based applications in the wireless sensor networks which have been mentioned is suggested.

The outdoor ambient temperature variations impact the performance of devices in wireless sensor network (WSN) systems. This paper presents a WSN system for researching the impact of temperature changing on the signal intensity of the WSN system. The system consists of a PC, a getaway and a sensor node. A transmission power self-adjusting algorithm is proposed. The influence of temperature on the WSN system and the function of the transmission power self-adjusting algorithm are tested respectively. The experimental results show that the signal intensity of the WSN system decreases 3.5 dBm while ambient temperature increases from 20 °C to 50 °C. The results verify that the transmission power self-adjusting algorithm is effective for stable communication and energy saving.

For the past decade, wireless sensor networks have focused primarily on data collection. As a result the network topology for these systems was usually heavily centralized. However, for these networks to form a full system, the introduction of proper actuation units and decision-making intelligence is inevitable. Such a new wireless sensor and actuator network system enables new architectural research issues that have not been previously studied. In this work, we introduce the DWSAN system architecture, which effectively combines both sensor and actuation hardware devices to a single network and manages this network so that the actuation decisions are made in a distributed manner and the topology of the network maintains a multitier architecture. Our intensive set of evaluations reveal that, compared to the centralized approach that has been used in most wireless sensor network systems until now, when actuation units are introduced to the system, the DWSAN architecture reduces the transmission load of the network and the actuation decision-making latency by close to twofold and threefold, respectively. Furthermore, we show that this benefit naturally leads to better scalability of the system, making it suitable for various sensing applications in different environments.

Outliers can contaminate the communication and measurement processes of many wireless sensor networks (WSNs) systems, which may be induced by environmental disturbances, model uncertainties or mismatches, sensor faults or errors, subnetwork faults, or malicious cyberattacks. Once the distributed Kalman filter (DKF) is used in such WSN systems with outliers for distributed state estimation, the estimation performance can be seriously degraded in each sensor node. To address this problem, this article proposes mean-shift-based outliers screening and fuzzy-trust-based information fusion mechanisms to modify the DKF toward improving resilience and enhancing robustness against outliers. The proposed mechanism is capable of screening out the outliers-contaminated local measurements and estimates and adaptively narrowing the outliers-contaminated information pairs without modifying the original local state estimates to guarantee the fused estimation consistency and accuracy. This design leads to the development of mean-shift-based outliers-robust DKF (MSRDKF) for the state estimation over WSN systems in a distributed manner. It is proved that our proposed MSRDKF can generate mean-square-bounded-error estimation in each sensor node under bounded outlier disturbances, system collective observability, and network connectivity, and the upper bound of estimation error increases with the occurrence probability of outliers. Simulation and experimental results demonstrate the practical validity and superiority of the proposed MSRDKF in suppressing the effects of outliers, as evidenced by significantly lower root-mean-square-error (RMSE) and average-RMSE (ARMSE) compared to the DKF.

In the present world, wireless sensor network-enabled network control system is performing a significant role in science, technology, and our day-to-day life. The Network control system in wireless sensor network has a great contribution in modern technology-oriented lifestyle and is bringing control to engineers in communicating network system through various applications. Though network control system is facing different challenges like latency, security, and multiple accesses, it is widely accepted for the successful communication and effective data transmission process. In this research paper, we are trying to explain generally the research aspect, trends, and variation of research directions through comparative analysis of existing research work and scientometric analysis on network control systems in the wireless sensor networks. With the help of the Scopus database and Web of Science database separately, some assessments were performed to analyze research data. From different experiments, it is noticed that network control systems can be applied in different fields like environment, agriculture, home applications, traffic control, health, aircraft, and motor control system using a wireless sensor networks. Observing in the last twenty years of research works in this field, we have found that network control system in wireless sensor networks is increasingly become a talented topic in the communication and networking field.

Designing hardware for wireless sensor network (WSN) systems is a time consuming process. Quite often new systems are designed from scratch and there is lack of support for the design, prototyping and debugging beyond the CAD tools. Therefore, many WSN systems are based on available platforms such as MicaZ, TelosB, EPIC [1] [7] [4]. Although these platforms offer a degree of flexibility, the hardware setup is limited to the predesigned sensor or extension modules. However, many WSN applications have specific requirements regarding the sensing types and fidelity while are very sensitive to the current draw by these sensors and waste by the unused components. Therefore, we propose a WSN hardware prototyping test bench EdiMote developed with the flexibility of prototyping, performance monitoring and hardware and software debug assistance in mind (Figure 1).

This paper proposes a Multimodal User Authentication System for Wireless Sensor Networks (WSN). User Authentication is important for customized services and restricted access control in Wireless Sensor Networks. Considering the need, the proposed Enhanced Multimodal Biometric System shall combine two biometric traits to provide authentication for accessing the information from Sensor nodes. The user will be granted access by the Enhanced Authentication System to the user for accessing sensitive information from Wireless Sensor Networks.

Interoperable agro-meteorological observation and analysis platform for precision agriculture: A case study in citrus crop water requirement estimation

This article is concerned with the nonlinear state estimation for the multisenor networked system with uncertain bounded noise. Traditional distributed methods only pay attention to the information fusion of state estimations, but neglect the fusion of noise statistics. The difference of noise statistics among sensor nodes usually affects the precision of state estimation in wireless sensor networks, especially for the distributed state estimation. In this article, in order to improve the accuracy of noise statistic estimations, a distributed noise statistic estimator is derived based on covariance intersection criterion and modified Sage–Husa maximum posterior. Then, distributed adaptive cubature information filtering (DACIF) is founded based on weighted average consensus to obtain accurate state estimation. Two‐step information fusion, including the information fusion of state estimations and noise statistics, is derived to enhance the precision of state estimations. Meanwhile, a novel weighted rule is devised based on the state and measurement innovation vectors to improve the accuracy of distribution information fusion. Next, the estimation errors of DACIF are proved to be bounded in mean square. Simulations and semisimulation experiments are conducted to verify the effectiveness of the proposed algorithm.

Applications of wireless sensor network face many censorious issues, fault tolerance being a prominent one. The problem of missing communication link(s), sensor node(s) and data is unavoidable in such networks. Fault tolerance is important for reliable delivery of data in WSN applications. This ensures the system’s availability for use in case of any interruption or occurrence of fault, thus enhancing the availability and reliability. Current work introduces the fault-tolerance behavior of a dynamically generated system of wireless sensor network that comprises of super-nodes and sensor nodes having k - vertex disjoint paths. As the parameters involved in the process of determination of fault-tolerance of a network change, the capacity of the network to tolerate the fault changes accordingly. This paper proposes an algorithm that evaluates the fault tolerance of randomly generated networks based on k - vertex disjoint path connectivity and also evaluates the results.

Underground coal mines are susceptible to many kinds of hazards. Mine fire is one of the most vulnerable threats that leads to loss of human lives and other resources inside the mines. Hence, continuous monitoring of underground coal mines is very important for early detection of mine fire. Nowadays, wireless sensor networks are being widely used for monitoring underground coal mines. However, the collected data from sensor nodes are inaccurate in nature, and there is a need for analyzing such data for taking preventive measure. In this article, we propose an optimized fuzzy logic-based fire monitoring system for wireless underground sensor network, which strengthens reliability of making decision in preventing mine fire. However, storing of large fuzzy rule set in the memory constraint sensor nodes and their traversal for every sensor reading are very challenging. Therefore, we use the binary particle swarm optimization (BPSO) algorithm to optimize the proposed fuzzy system that eliminates redundant rules but preserves event detection accuracy of the monitoring system. The proposed system is simulated using BPSO algorithm and Fuzzy Logic Toolbox inbuilt in the MATLAB. The simulation results demonstrate that the proposed system outperforms the existing monitoring systems for underground coal mines.

Trust and reputation systems have been regarded as a powerful tool to defend against insider attacks caused by the captured nodes in wireless sensor networks (WSNs). However, trust systems are vulnerable to on-off attacks, in which malicious nodes can opportunistically behave good or bad, compromising the network with the hope that bad behavior will be undetected. Thus, malicious nodes can remain trusted while behaving badly. In this paper, we propose O2Trust, On-Off attack mitigation for Trust systems in wireless sensor networks. O2Trust adopts the penalty policy against the misbehavior history of each node in the network as a reliable factor that should influence on the calculation of the trust value. This punishment future helps to perceive malicious node that aim to launch intelligent attacks against trust-establishment and consequently on-off attack is mitigated efficiently.

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.

In this paper, we describe a reliability model which can be used to analyze the performance and power consumption in resource constrained, data rate scarce, mobile agent-based wireless sensor network (WSN) systems. The primary model is referred to as a generalize access structure congestion (GGC) system which is an extended model from a circular sequential k-out-of-n congestion (CSknC). There are many other reliability models which can be used to study WSN systems, but they are not suitable to analyze and address mobile agent-based multisensory WSN systems. These systems are not based on a centralized architecture because they use mobile agent technologies to distribute decision tasks at local nodes. By employing mobile agent technologies, the systems can make accurate decisions quickly and reduce data rate and data redundancy problems. An important research problem is to determine how to maintain efficient duty cycle by using multiple types of sensors without centralized architecture and with mobile agent technologies. From the GGC model, we can develop a method to determine an optimal power management scheme by computing an efficient duty cycle in mobile agent-based multisensory WSN systems.

Over the past decades, many WSN (Wireless Sensor Network) systems have emerged. Today, the WSN systems with different technologies have started to become parts of Internet of Things (IoT) and Cyber-Physical Systems(CPSs). This situation has also led to the emergence of heterogeneous and autonomous WSN structures. In these types of complex projects, involving different WSN systems, it is necessary to well define the structure of WSN heterogeneity in order to perform some important operations such as interoperability and resource-sharing. To this end, the paper presents a WSN heterogeneity classification model. In the classification, WSN heterogeneity is addressed from a general perspective. The classification considers not only the heterogeneity within a WSN but also the heterogeneity which can be occurred in the scope of IoT/CPS projects. As far as is known, this type of classification on WSN heterogeneity has been proposed for the first time in literature.