A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

Experiences and issues for environmental engineering sensor network deployments

Sensor network research is a large and growing area of academic effort, examining technological and deployment issues in the area of environmental monitoring. These technologies are used by environmental engineers and scientists to monitor a multiplicity of environments and services, and, specific to this paper, energy and water supplied to the built environment. Although the technology is developed by Computer Science specialists, the use and deployment is traditionally performed by environmental engineers. This paper examines deployment from the perspectives of environmental engineers and scientists and asks what computer scientists can do to improve the process. The paper uses a case study to demonstrate the agile operation of WSNs within the Cloud Computing infrastructure, and thus the demand-driven, collaboration-intense paradigm of Digital Ecosystems in Complex Environments

Automatic application object migration in sensor networks

Object migration in wireless sensor networks has the potential to reduce energy consumption for a wireless sensor network mesh. Automated migration reduces the need for the programmer to perform manual static analysis to find an efficient layout solution. Instead, the system can self-optimise and adjust to changing conditions. This paper describes an automated, transparent object migration system for wireless sensor networks, implemented on a micro Java virtual machine. The migration system moves objects at runtime around the sensor mesh to reduce communication overheads. The movement of objects is transparent to the application developer. Automated transparent object migration is a core component of Hydra, a distributed operating system for wireless sensor networks that is currently under development. Performance of the system under a complex performance test scenario using a real-world dataset of seismic events is described. The results show that under both simple and complex conditions the migration technique can result in lower data traffic and consequently lower overall energy cost

Clustering objectives in wireless sensor networks: A survey and research direction analysis

Wireless Sensor Networks (WSNs) typically include thousands of resource-constrained sensors to monitor their surroundings, collect data, and transfer it to remote servers for further processing. Although WSNs are considered highly flexible ad-hoc networks, network management has been a fundamental challenge in these types of net- works given the deployment size and the associated quality concerns such as resource management, scalability, and reliability. Topology management is considered a viable technique to address these concerns. Clustering is the most well-known topology management method in WSNs, grouping nodes to manage them and/or executing various tasks in a distributed manner, such as resource management. Although clustering techniques are mainly known to improve energy consumption, there are various quality-driven objectives that can be realized through clustering. In this paper, we review comprehensively existing WSN clustering techniques, their objectives and the network properties supported by those techniques. After refining more than 500 clustering techniques, we extract about 215 of them as the most important ones, which we further review, catergorize and classify based on clustering objectives and also the network properties such as mobility and heterogeneity. In addition, statistics are provided based on the chosen metrics, providing highly useful insights into the design of clustering techniques in WSNs.publishedVersio

Data sharing in secure multimedia wireless sensor networks

© 2016 IEEE. The use of Multimedia Wireless Sensor Networks (MWSNs) is becoming common nowadays with a rapid growth in communication facilities. Similar to any other WSNs, these networks face various challenges while providing security, trust and privacy for user data. Provisioning of the aforementioned services become an uphill task especially while dealing with real-time streaming data. These networks operates with resource-constrained sensor nodes for days, months and even years depending on the nature of an application. The resource-constrained nature of these networks makes it difficult for the nodes to tackle real-time data in mission-critical applications such as military surveillance, forest fire monitoring, health-care and industrial automation. For a secured MWSN, the transmission and processing of streaming data needs to be explored deeply. The conventional data authentication schemes are not suitable for MWSNs due to the limitations imposed on sensor nodes in terms of battery power, computation, available bandwidth and storage. In this paper, we propose a novel quality-driven clustering-based technique for authenticating streaming data in MWSNs. Nodes with maximum energy are selected as Cluster Heads (CHs). The CHs collect data from member nodes and forward it to the Base Station (BS), thus preventing member nodes with low energy from dying soon and increasing life span of the underlying network. The proposed approach not only authenticates the streaming data but also maintains the quality of transmitted data. The proposed data authentication scheme coupled with an Error Concealment technique provides an energy-efficient and distortion-free real-time data streaming. The proposed scheme is compared with an unsupervised resources scenario. The simulation results demonstrate better network lifetime along with 21.34 dB gain in Peak Signal-to-Noise Ratio (PSNR) of received video data streams

A novel cooperative opportunistic routing scheme for underwater sensor networks

Increasing attention has recently been devoted to underwater sensor networks (UWSNs) because of their capabilities in the ocean monitoring and resource discovery. UWSNs are faced with different challenges, the most notable of which is perhaps how to efficiently deliver packets taking into account all of the constraints of the available acoustic communication channel. The opportunistic routing provides a reliable solution with the aid of intermediate nodes’ collaboration to relay a packet toward the destination. In this paper, we propose a new routing protocol, called opportunistic void avoidance routing (OVAR), to address the void problem and also the energy-reliability trade-off in the forwarding set selection. OVAR takes advantage of distributed beaconing, constructs the adjacency graph at each hop and selects a forwarding set that holds the best trade-off between reliability and energy efficiency. The unique features of OVAR in selecting the candidate nodes in the vicinity of each other leads to the resolution of the hidden node problem. OVAR is also able to select the forwarding set in any direction from the sender, which increases its flexibility to bypass any kind of void area with the minimum deviation from the optimal path. The results of our extensive simulation study show that OVAR outperforms other protocols in terms of the packet delivery ratio, energy consumption, end-to-end delay, hop count and traversed distance

Autonomous monitoring framework for resource-constrained environments

Acknowledgments The research described here is supported by the award made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub, reference: EP/G066051/1. URL: http://www.dotrural.ac.uk/RemoteStream/Peer reviewedPublisher PD

Extending sensor networks into the cloud using Amazon web services

Sensor networks provide a method of collecting environmental data for use in a variety of distributed applications. However, to date, limited support has been provided for the development of integrated environmental monitoring and modeling applications. Specifically, environmental dynamism makes it difficult to provide computational resources that are sufficient to deal with changing environmental conditions. This paper argues that the Cloud Computing model is a good fit with the dynamic computational requirements of environmental monitoring and modeling. We demonstrate that Amazon EC2 can meet the dynamic computational needs of environmental applications. We also demonstrate that EC2 can be integrated with existing sensor network technologies to offer an end-to-end environmental monitoring and modeling solution

A Survey on Mobile Charging Techniques in Wireless Rechargeable Sensor Networks

The recent breakthrough in wireless power transfer (WPT) technology has empowered wireless rechargeable sensor networks (WRSNs) by facilitating stable and continuous energy supply to sensors through mobile chargers (MCs). A plethora of studies have been carried out over the last decade in this regard. However, no comprehensive survey exists to compile the state-of-the-art literature and provide insight into future research directions. To fill this gap, we put forward a detailed survey on mobile charging techniques (MCTs) in WRSNs. In particular, we first describe the network model, various WPT techniques with empirical models, system design issues and performance metrics concerning the MCTs. Next, we introduce an exhaustive taxonomy of the MCTs based on various design attributes and then review the literature by categorizing it into periodic and on-demand charging techniques. In addition, we compare the state-of-the-art MCTs in terms of objectives, constraints, solution approaches, charging options, design issues, performance metrics, evaluation methods, and limitations. Finally, we highlight some potential directions for future research

Performance analysis of self-organized Ad-Hoc sensor networks

This project deals with a Distributed Sensor Network (DSN). The main focus of this thesis is to deliver an OPNET simulation model for working DSN model. After building a model, various performance analysis techniques in terms of different parameters were used to verify the working model. Query Dominant Sets (QDS) are the main idea behind this thesis. The QDS node is in charge of the nodes for a specific region and its job is to assign the query tasks that it gets to the nodes in that region to help maximize the life of the network. If no user queries are being sent, the QDS nodes themselves go to sleep to conserve energy and just listen for special incoming control signals. QDS management (including the selection of QDS and the interaction of QDS nodes and other common nodes) is a challenging issue in DSN platforms. Our algorithm for QDS management attempts to limit the dead spots in the network that tend to disrupt the communication of the whole network. It has two phases and the first phase is the election phase. The second stage is the previously elected QDS nodes distribute the tasks to the other nodes. This algorithm turns out to be distributed which is good for sensor networks. There is no use of any global communication or long-range, high energy data communication, but just local communications. This also helps to save power and energy for long life of the sensors. This algorithm is also very scalable and fault tolerant. We have done significant simulations to verify our QDS concepts. There are some metrics that are used to evaluate our schemes such as the average energy values of all the nodes in the network, minimum energy of all the nodes in the network, total energy consumed in the awake, transmit, and receive states, maximum time spent by any node in electing a new QDS, number of elected QDSs, and so on. Our simulations have shown satisfactory energy-efficiency of our algorithms