Wireless sensor network operating systems: a survey

This paper presents a survey on the current state-of-the-art in Wireless Sensor Network (WSN) Operating Systems (OSs). In recent years, WSNs have received tremendous attention in the research community, with applications in battlefields, industrial process monitoring, home automation, and environmental monitoring, to name but a few. A WSN is a highly dynamic network because nodes die due to severe environmental conditions and battery power depletion. Furthermore, a WSN is composed of miniaturized motes equipped with scarce resources e.g., limited memory and computational abilities. WSNs invariably operate in an unattended mode and in many scenarios it is impossible to replace sensor motes after deployment, therefore a fundamental objective is to optimize the sensor motes’ life time. These characteristics of WSNs impose additional challenges on OS design for WSN, and consequently, OS design for WSN deviates from traditional OS design. The purpose of this survey is to highlight major concerns pertaining to OS design in WSNs and to point out strengths and weaknesses of contemporary OSs for WSNs, keeping in mind the requirements of emerging WSN applications. The state-of-the-art in operating systems for WSNs has been examined in terms of the OS Architecture, Programming Model, Scheduling, Memory Management and Protection, Communication Protocols, Resource Sharing, Support for Real-Time Applications, and additional features. These features are surveyed for both real-time and non-real-time WSN operating systems.

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.

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).

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.

The ever-increasing application of wireless sensor networks in many different fields is causing a growing demand of low-cost energy-efficient sensors for monitoring physical variables such as temperature, pressure or gas concentration. This paper presents a conditioning system for low-cost non-dispersive infrared gas sensors used to measure the CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> concentration in an open air environment. It mainly consists of an amplification and filtering circuit that adapts the small and noisy signal provided by the sensor to a signal which can be easily read by a low-power microcontroller. The proposed interface presents a good tradeoff between energy consumption and accuracy, compatible with the energy requirements of wireless sensor network applications. Test performed connecting the system interface to a node sensor in a wireless sensor network using a simple communications protocol only causes a 5% reduction in the operating life of the node.

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.

Wireless Sensor Networks (WSNs) consist of small, multifunctional nodes distributed across various locations to monitor and record parameters. These nodes store data and transmit signals for further processing, forming a crucial topic of study. Monitoring the network's status in WSN applications using clustering systems is essential. Collaboration among sensors from various domains enhances the precision of localised information reporting. However, nodes closer to the data sink consume more energy, leading to hotspot challenges. To address these challenges, this research employs clustering and optimised routing techniques. The aggregation of information involves creating clusters, further divided into sub-clusters. Each cluster includes a Cluster Head (CH) or Sensor Nodes (SN) without a CH. Clustering inherently optimises CHs' capabilities, enhances network activity, and establishes a systematic network topology. This model accommodates both multi-hop and single-hop systems. This research focuses on selecting CHs using a Genetic Algorithm (GA), considering various factors. While GA possesses strong exploration capabilities, it requires effective management. This research uses Prairie Dog Optimization (PDO) to overcome this challenge. The proposed Hotspot Mitigated Prairie with Genetic Algorithm (HM-PGA) significantly improves WSN performance, particularly in hotspot avoidance. With HM-PGA, it achieves a network lifetime of 20913 milliseconds and 310 joules of remaining energy. Comparative analysis with existing techniques demonstrates the superiority of the proposed approach.

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.

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.

Disseminating sensory information from sensor nodes to the gateway node towards Data Center Server has to be guaranteed its fruitfulness. However, these important information commonly are transmitted over wireless connections whereas everyone including adversaries may join freely in the network. Hence, the correctness of received information should be emphasized. To do so, such information should be ascertained from the authenticated sensor nodes, kept its secrecy, prevented from the alteration, and guaranteed its integrity, respectively without revealing sensor nodes' identity. On the other hand, data sensors in the Data Center Server also should be kept secret and only be accessed by authenticated users over common public connection such as Internet without exposing the users' privacy. Therefore, an anonymous authentication system in collecting data sensors from sensor nodes to the Data Center Server and accessing them by everyone would be strongly desirable. In this paper, we propose an implementation of anonymous authentication system in the wireless sensor network using VLR group signature.

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

Precision agriculture and agricultural decision making assistance have attracted researchers of engineering and agronomy as well as industries as a promising application of wireless sensor network (WSN) technology. However, agriculture is an industry with severe cost-cutting pressure and there is little advance guarantee that the WSN increases profit of farmers. Compared with other applications of the WSN such as power grid, civil engineering, etc., investment to the WSN cannot be expected so much. Nevertheless, if the problem of the cost is resolved, the WSN can be used with wide variety in the farm. The ready-made system satisfying requirements and constraints fully and generally of different farmers increases size and complexity of the system and finally the required investment. On the other hand, the full custom-made system for the individual farmer is not practical. This paper presents a concept of generative WSN framework enabling generation of semi custom-made WSN systems that satisfies requirements and constraints of individual farmers within a prescribed scope and also its fundamental technologies. The framework introduces a paradigm of software product line and manages core assets which are basis of the WSN system to be generated. Two tiered feature modeling, variation point mechanisms for hardware, and integer programming based optimization of system configuration are additionally developed technologies to realize the generative WSN framework.

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.