Frequency converter integration to wireless sensor network

Wireless sensor and actuator networks (WSANs) are heterogeneous networks composed of many different nodes that can cooperatively sense the environment, determine an appropriate action to take, then change the environment’s state after acting on it. As a natural extension of wireless sensor networks (WSNs), WSANs inherit from them a variety of research challenges and bring forth many new ones. These challenges are related to dealing with imprecise and vague information, solving complicated optimization problems or collecting and processing data from multiple sources. Computational intelligence (CI) is an overarching term denoting a conglomerate of biologically and linguistically inspired techniques that provide robust solutions to NP-hard problems, reason in imprecise terms and yield high-quality yet computationally tractable approximate solutions to real-world problems. Many researchers have consequently turned to CI in hope of finding answers to a plethora of WSAN-related challenges. This paper reviews the application of several methodologies under the CI umbrella to the WSAN field. We describe and categorize existing works leaning on fuzzy systems , neural networks , evolutionary computation , swarm intelligence , learning systems , and their hybridizations to well-known or emerging WSAN problems along five major axes: 1) actuation; 2) communication; 3) sink mobility; 4) topology control; and 5) localization. The survey offers informative discussions to help reason through all the studies under consideration. Finally, we point to future research avenues by: 1) suggesting suitable CI techniques to specific problems; 2) borrowing concepts from WSNs that have yet to be applied to WSANs; or 3) describing the shortcomings of current methods in order to spark interest on the development of more refined models.

The conventional setup of a wireless sensor network is composed of several sensor nodes and one or more sinks. The network topology and data collection techniques are then optimized towards efficient collection of the sensed data at the sink(s). In this paper, we present a novel network coding technique based on Compressed Sensing that allows each node to operate as a sink. Our network coding technique efficiently disseminates a number of linear combinations of the sensed data. After the dissemination phase, the entire sensed data is available by querying any node of the network. This is especially useful for distributed control using a wireless sensor and actuator network or in scenarios where the end user needs to access the global state of the environment from any node in its vicinity; e.g., when the end user is mobile.

A large number of potential applications for Wireless Sensor and Actuator Networks (WSAN) have yet to be embraced by industry despite high interest amongst academic researchers. This is due to various factors such as unpredictable costs related to development, deployment and maintenance of WSAN, especially when integration with existing IT infrastructure and legacy systems is needed. Service-Oriented Architecture (SOA) is seen as a promising technique to bridge the gap between sensor nodes and enterprise applications such as factory monitoring, control, and tracking systems where sensor data is used. To date, research efforts have focused on middleware software systems located in gateway devices that implement standard service technology, such as Devices Profile for Web Services (DPWS), for interacting with the sensor network. This paper takes a different approach-deploying interoperable Simple Object Access Protocol (SOAP)-based web services directly on the nodes and not using gateways. This strategy provides for easy integration with legacy IT systems and supports heterogeneity at the lowest level. Twofold analysis of the related overhead, which is the main challenge of this solution, is performed; Quantification of resource consumption as well as techniques to mitigate it are presented, along with latency measurements showing the impact of different parts of the system on system performance. A proof-of-concept application using Mulle-a resource-constrained sensor platform-is also presented.

The number of devices connected to the Internet is experiencing an explosive growth. The interconnection of smart objects embedded with sensors enables them to interact with the environment and among themselves, forming a Wireless Sensor Network (WSN). These network nodes perform acquisition, collection and analysis of data, such as temperature and soil moisture. Such data can be employed to automate the irrigation process in agriculture while decreasing water consumption, resulting in monetary and environmental benefits. The high storage and processing capabilities, the rapid elasticity and payper-use characteristics makes Cloud Computing an attractive solution to the large amount of data generated by the WSN. This paper proposes and evaluates on a real deployment a cloud-based Wireless Sensor and Actuator Network (WSAN) communication system. This solution monitors and controls a set of sensors and actuators, respectively, to assess plants water needs.

An energy efficient and QoS aware routing protocol for wireless sensor and actuator networks

Reliable real-time sensing plays a vital role in ensuring the reliability and safety of industrial cyber-physical systems (CPSs) such as wireless sensor and actuator networks. For many reasons, such as harsh industrial environments, fault-prone sensors, or malicious attacks, sensor readings may be abnormal or faulty. This could lead to serious system performance degradation or even catastrophic failure. Current anomaly detection approaches are either centralized and complicated or restricted due to strict assumptions, which are not suitable for practical large-scale networked industrial sensing systems (NISSs), where sensing devices are connected via digital communications, such as wireless sensor networks or smart grid systems. In this paper, we introduce a fully distributed general anomaly detection (GAD) scheme, which uses graph theory and exploits spatiotemporal correlations of physical processes to carry out real-time anomaly detection for general large-scale NISSs. We formally prove the scalability of our GAD approach and evaluate the performance of GAD for two industrial applications: building structure monitoring and smart grids. Extensive trace-driven simulations validate our theoretical analysis and demonstrate that our approach can significantly outperform state-of-the-art approaches in terms of detection accuracy and efficiency.

The use of wireless multimedia sensor networks (WMSNs) for surveillance applications has attracted the interest of many researchers. As with traditional sensor networks, it is easy to deploy and operate WMSNs. With inclusion of multimedia devices in wireless sensor networks, it is possible to provide data to users that is more meaningful than that provided by scalar sensor-based systems alone; however, producing, storing, processing, analyzing, and transmitting multimedia data in sensor networks requires consideration of additional constraints, including energy, processing power, storage capacity, and communication. Furthermore, as multimedia sensors produce much more data than scalar sensors, more manpower is required to analyze multimedia data. To overcome these constraints and challenges, this paper aimed to propose a system architecture and a set of procedures for WMSNs that facilitate automatic classification of moving objects using scalar and multimedia sensors. Methods and standards for detecting and classifying a moving object, as well as transmission of the results, are described in detail. The hardware for each sensor node includes a built-in camera, a passive infrared motion sensor, a vibration sensor, and an acoustic sensor. An application using our proposed methods was developed and embedded in the multimedia sensor node. In addition, a sink station was set up and the data produced by the sensor network was collected by this server. The classification performance of the application was tested using video recorded by the sensor node. The effect of the proposed methods on power consumption was also tested and measured. The experimental results show that the proposed approach is sufficiently lightweight to be used for real-world surveillance applications.

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.

Pattern transformation-invariant schemes for wireless sensor networks based on an edge detection gradient-based mechanism

Using wireless sensor networks (WSNs) in delay and reliability critical environments is highly desired due to their unique advantages such as low cost, ease of deployment, and redundancy. However, successful deployment of resource-limited WSNs in such applications requires strict quality-of-service (QoS) provisioning techniques to meet the desired latency and reliability targets of those applications. Implementation of QoS techniques in WSNs is significantly challenging since WSNs have been initially devised for low-data-rate non-real-time applications. Therefore, WSN designers and developers resort to different cross-layer interaction and optimization techniques to provision QoS in WSNs. In this paper, we present a survey on the state of the art of cross-layer QoS approaches in wireless terrestrial sensor networks to achieve delay and reliability bounds in critical applications. Our paper provides a unique classification of cross-layer QoS approaches in WSNs that allows surveying a large amount of studies with utmost clarity. Furthermore, we highlight the main challenges of implementing QoS protocols in WSNs and present an overview of QoS-aware WSN applications.

The deployment of the nodes in a Wireless Sensors and Actuators Network (WSAN) is typically restricted by the sensing and acting coverage. This implies that the locations of the nodes may be, and usually are, not optimal from the point of view of the radio communication. And also when the transmission power is tuned for those locations, there are other unpredictable factors that can cause connectivity failures, like interferences, signal fading due to passing objects, and of course, radio irregularities. A control based self-adaptive system is a typical solution to improve the energy consumption while keeping a good connectivity. In this paper, we explore how the communication range for each node evolves along the iterations of an energy saving self-adaptive transmission power controller when using different parameter sets in an outdoor scenario, providing a WSAN that automatically adapts to surrounding changes keeping a good connectivity. The results obtained in this paper show how the parameters with the best performance keep a k-connected network, where k is in the range of the desired node degree plus or minus a specified tolerance value. In addition, the worst performance shows how a bad parameters choice can create isolated islands, groups of nodes disconnected from the rest of the network.

The heterogeneity characterizing the Internet of Things (IoT) landscape can be addressed by leveraging network operating systems (NOS)s. Current NOS solutions have been developed for traditional infrastructured networks: they do not take the specific features of fundamental IoT components such as wireless sensor and actuator networks into account. Accordingly, in this paper an innovative integrated network operating system for the IoT which is obtained as the evolution of the Open Network Operating System (ONOS) is proposed. This has been appropriately extended to enhance the recently proposed SDN-WISE platform for supporting SDN in wireless sensor networks and let it interact with standard OpenFlow (OF) switches. The proposed integrated system has been prototyped.

Wireless sensor and actuator networks (WSANs) are emerging as a new generation of wireless sensor networks. Due to the coupling between the sensing areas of the sensors and the action areas of the actuators, the efficient coordination among the nodes is a great challenge. In this paper, we address the problem of distributed node coordination in WSANs aiming at meeting the user's requirements on the states of the points of interest (POIs) in a real-time and energy-efficient manner. The node coordination problem is formulated as a nonlinear program. To solve it efficiently, the problem is divided into two correlated subproblems: 1) the sensor-actuator (S-A) coordination and 2) the actuator-actuator (A-A) coordination. In the S-A coordination, a distributed federated Kalman filter-based estimation approach is applied for the actuators to collaborate with their ambient sensors to estimate the states of the POIs. In the A-A coordination, a distributed Lagrange-based control method is designed for the actuators to optimally adjust their outputs, based on the estimated results from the S-A coordination. The convergence of the proposed method is proved rigorously. As the proposed node coordination scheme is distributed, we find the optimal solution while avoiding high computational complexity. The simulation results also show that the proposed distributed approach is an efficient and practically applicable method with reasonable complexity.

A collaborative light control system considering uniformity and illuminance in WSAN

Wireless Sensor Network is greatly evolved in recent years. Technological advancements in wireless networks are intended to develop various fields especially in medical domain. Nowadays, remote health monitoring is possible by the enormous growth of wireless body area sensor networks. The Wireless Body Area Sensor Network monitors the human health by using wearable body sensors, and sends the status of the human health to the medical experts. Body nodes will be placed on, in and around the human body. The major key issue in Wireless Body Area Sensor Network is power management. Since batteries used in sensors are very tiny, it tends to have a minimal lifetime. In order to increase the lifetime of the sensor node, the energy needs to be utilized in an efficient manner. In this paper we have proposed conditional re-transmission technique to minimize the energy consumption. So the sensor nodes lifetime will get increased and in turn Wireless Body Area Sensor Networks lifetime will also be increased. By increasing the lifetime of the sensor nodes, the batteries or sensor nodes need not to be replaced frequently.