Reconfigurable Wireless Sensor Networks Research Articles

Reinforcement Learning-Enabled Resampling Particle Swarm Optimization for Sensor Relocation in Reconfigurable WSNs

Aiming to maximize coverage performance and reduce the number of sensors deployed in the reconfigurable wireless sensor networks (RWSNs), in this paper, we first formulate a new cooperative sensing coverage control problem based on the confident information coverage model. Then, inspired by the reinforcement learning and resampling technology, a novel learning automata-based resampling particle swarm optimization (RPSOLA) algorithm is proposed to solve complex multi-peak optimization problem and optimize the cooperative sensing coverage control problem of RWSNs. Experimental results demonstrate that the RPSOLA considerably outperforms other three peer schemes, the RPSO, BASPSO and PSO, in terms of the convergence, coverage rate and sensor redundancy.

A model based process for reconfigurable wireless sensor network development

A model based process for reconfigurable wireless sensor network development

An Extended Object Constraint Language for Adaptive Discrete Event Systems With Application to Reconfigurable Wireless Sensor Networks

This paper deals with software validation of flexible discrete-event systems. A reconfiguration scenario is any run-time adaptation of the software execution according to user requirements. Nevertheless, since several behaviors can be redundant from an execution to another, using the object constraint language (OCL) is not useful to specify all constraints that should be satisfied by a system. We propose an extension of OCL named reconfigurable OCL for improving the specification and validation of constraints related to different execution scenarios of a system. An ROCL metamodel is proposed with formal syntax and semantics. This solution gains in terms of validation time and quick expressions of constraints. We apply the proposed extended language to reconfigurable wireless sensor networks to highlight the benefits of this contribution.

Toward Efficient Data Trading in AI Enabled Reconfigurable Wireless Sensor Network Using Contract and Game Theories

Reconfigurable Wireless Sensor Network (RWSN) schedules a set of devices with reconfigurable wireless interface to accomplish different data collection plans in a cost-effective way. AI technologies are applied to optimize decision making for high-level network reconfiguration. Besides, AI based data mining tools are exploited by third parities to extract useful information underlying raw data. This leads to the emergence of AI enabled RWSN. We further study a data trading market to provide the data-centric environment for large-scale applications of AI enabled RWSN. A network operator employs the devices to gather environmental data, and sells the collected data to interested third parities as data consumers. After that, two-level optimizations are performed to ensure efficient data trading. In data collection, a contract based incentive mechanism is presented for the network operator to stimulate the devices and simultaneously achieve the contractor's goal subject to feasible constraints. In data selling, a non-cooperative game is formulated among multiple data consumers. They balance the data demand since the final data price is correlated with the total data demand. Nash equilibrium is analyzed and solved under different conditions. Finally, numerical results are provided to demonstrate the effectiveness of our scheme.

Novel framework of retaining maximum data quality and energy efficiency in reconfigurable wireless sensor network

Novel framework of retaining maximum data quality and energy efficiency in reconfigurable wireless sensor network

A Remotely Reconfigurable IoT System using Wiki Software

Herein, an Internet of Things (IoT) system with remotely reconfigurable gateways and wireless sensor network (WSN) nodes is presented and its applications are discussed. This IoT system consists of wiki pages, bots, (defined as remotely controlled devices), and remotely reconfigurable WSN Nodes. Each bot can be used as the gateway of the WSN if the bot was connected with it. The bots/gateways and WSN nodes of the IoT system are controlled by scripts written on wiki pages that are read by the bot/gateways, which then forward the commands contained in the scripts to the WSN nodes. Each WSN node then executes the commands, obtains the resulting sensor values, and then returns those values to the bot/gateways. The bot/gateways relay the values and write them onto the wiki page. Each bot and WSN node is flexible and reconfigurable because its behavior can be changed by the script commands written onto the wiki page. Using this IoT system, we created a measurement system to evaluate activity levels of group work in a classroom. After developing the measurement system, we found it was possible to adjust the sampling rate for obtaining sensor values simply by rewriting the script on the wiki page without directly manipulating the WSN.

New Power-Oriented Methodology for Dynamic Resizing and Mobility of Reconfigurable Wireless Sensor Networks

This paper deals with reconfigurable wireless sensor networks (RWSNs) that should be adapted to their environment in order to minimize the energy consumption during the communication among nodes and consequently to maximize the lifetime of the network as much as possible. An RWSN is assumed to be composed of a set of nodes located in distributed zones such that each node executes reconfigurable software tasks to control local sensors. We propose in a previous work a zone-based multiagent architecture for an RWSN where a communication protocol is well-defined to optimize distributed reconfigurations. This architecture combines all possible reconfiguration forms of the network to be adapted to its environment under energy constraints. With the multiagent architecture we gain in term of energy to be consumed by each node in the network. After applying a set of reconfiguration scenarios, the total charge of the network decreases. In order to preserve this charge as much as possible before the next recharging operation, in this particular study, we tend to resize geographically the zones in an RWSN. We propose also to move the mobile nodes in order to increase the network lifetime. A new run-time power oriented methodology is reported, which manages the zones and their mobile nodes in order to control the energy consumption. Two dynamic solutions are applied: 1) the resizing of zones and 2) the mobility of nodes. For the new proposed methodology, we present a set of equation systems to model the resizing of zones and the mobility of nodes. The solution of these systems allows us to conclude that we can conserve more energy during the communication among network elements (nodes, stations, and agents). The contributions are applied to a case study that we simulate with the reconfigurable wireless network environment 1 to analyze the research originality. 1 http://lisi-lab.wix.com/rwinproject

RWiN: New Methodology for the Development of Reconfigurable WSN

This paper presents new challenges for the development of reconfigurable wireless sensor networks (RWSNs) that adapt dynamically their behaviors to their environment under different properties. An RWSN is a set of networked nodes that execute reconfigurable software tasks for the control of local sensors. We propose a new design methodology named RWiN of an RWSN using unified modeling language (UML) to analyze, construct, develop, and verify easily RWSN architectures. For that, we formulate a metamodel of RWSN based on UML to describe a zone-based architecture that uses a communication protocol for the optimization of distributed reconfigurations. To control the design complexity, we model each agent of this architecture by nested state machines. To verify the temporal constraints by communicating agents, each one is modeled by a timed automaton. The paper's contribution is applied to a case study, which is simulated with TRMSim-WSN and UPPAAL environment to expose the originality of this new architecture.

Distributed algorithms for a robust topology using reconfigurable radios wireless sensor networks

Distributed algorithms for a robust topology using reconfigurable radios wireless sensor networks

Demand-Addressable Sensor Network: Toward Large-Scale Active Information Acquisition

A new type of sensor network called the demand-addressable sensor network (DASN) is proposed in this paper. The DASN actively acquires the desired information by addressing user demands and delivers the information to appropriate destinations. This is in contrast to the conventional sensor networks that simply send sensed data to users. The DASN is useful for finding the desired information in a short duration of time from a large amount of sensed data generated by a large-scale sensor network. The DASN is constructed with a demand-addressable network that integrates many on-demand reconfigurable wireless sensor networks (ODRWSN) and other existing information and communications technology systems or services, such as Google Maps and Twitter. In addition to the demand-addressing mechanism, the demand-addressable network has an in-network data combining or mashup mechanism. The mashed up data are displayed on the user terminal using an ordinary Web browser without any requirement to install a dedicated application program. The functions of the ODRWSN can be dynamically customized by injecting roles specified by the user. Thus, the user can actively get the desired information by customizing the sensor network function. The main application of the DASN is wide-area disaster site monitoring, for which the DASN features outlined above are suitable. In this paper, the concept underlying the DASN, its architecture and implementation, and experimental results are presented.

Detection and self-healing of cluster breakages in mines and tunnels: an empirical investigation

Purpose – The study aims at providing a reliable system of real-time monitoring for underground mine and tunnels which detects any structural change in the network and reconfigures it for resuming the data delivery process. In high stress environments, e.g. underground mines and tunnels, real-time activity monitoring is an emerging issue. Wireless sensor networks (WSNs) play a key role in ensuring the safety of people working in underground mines and tunnels. WSN not only provide real-time monitoring of underground environment but also detects any structural change in the network itself. Design/methodology/approach – In this paper, results of empirical implementation of a re-configurable WSN, capable of self-healing approach, reconfigure the network connectivity upon failure or addition of nodes in the system. An open-source radio-frequency identification standard for WSN, named as DASH7, is used for practical implementation. The proposed system is capable of determining cluster breakage by sudden disruptions caused by roof falls, explosions and node failures, sensor coverage hole, node re-addition to the network and distress priority signal generation by the miner. Findings – The proposed platform contributes to re-attain network state for establishing a communication link with fusion center in terms of: instant and accurate detection of collapse holes, acceptable error rate, time to re-attain network state, rapid distress signal propagation and low deployment cost. This platform is deployed in four different environments of anechoic chamber, hallway, outdoor and underground mine environment, to test the aforementioned scenarios using DASH7-compatible Bitsense Sensor Motes operating at 433 MHz. The effectiveness of the proposed approach has been experimentally validated for the single and multiple adjacent and disjoint node failures in all the four environments. Originality/value – The number of monitoring systems was implemented for safety assurance in high stress environments before, but the novelty of our platform is long range, cost effectiveness, quick response to any structural change in the network, rapid and accurate data delivery using WSN operated on DASH7 protocol stack.

Dynamically Reconfigurable WSN Node Based on ISO/IEC/IEEE 21451 TEDS

Ubiquitous and plug-and-play are fundamental characteristics for the development of wireless sensor networks (WSNs). The ISO/IEC/IEEE 21451 family of standards has recently awakened its interest in this development, making easier the introduction of both characteristics in the design of wireless sensor nodes. Dynamic reconfigurability is also an exciting topic that is gathering interest for the development of embedded systems and smart sensor nodes in the last few years. The use of dynamic reconfiguration increases the scalability and heterogeneity capabilities of the sensor network. However, the ISO/IEC/IEEE 21451 standards do not handle dynamically reconfigurable nodes and previously proposed frameworks do not include this capability into novel wireless sensor nodes. In this paper, an ISO/IEC/IEEE 21451 transducer electronic data sheet (TEDS) architecture for the management of reconfigurable WSNs nodes is proposed. To test the node architecture and validate its capability, the proposed TEDS was implemented for an environmental sensor network.

Hardware reconfigurable wireless sensor network node with power and area efficiency

For wireless sensor networks (WSNs), it is constantly demanded to process information more rapidly with less energy and area cost. Currently, processor based solutions have difficult to achieve high processing speed with low-power consumption. A novel partial dynamic reconfiguration-based WSN node is proposed in this study. First, a node architecture is described, which contains a processor and reconfigurable hardware (HW). The reconfigurable area can be dynamically and remotely reconfigured. Then the associated design and work flow are presented. As the compiled configuration file is pre-stored in the node. For a new configuration, only the related signal is transmitted to initiate the reconfiguration. To demonstrate the benefits of our approach, four typical test cases are selected and used to evaluate our reconfigurable HW. Compared with the software approach, apart from the performance improvement, power and area saving are also demonstrated in this study. Furthermore, each node can be maintained during its lifetime.

An Open and Reconfigurable Wireless Sensor Network for Pervasive Health Monitoring

Sensor networks constitute the backbone for the construction of personalized monitoring systems. Up to now, several sensor networks have been proposed for diverse pervasive healthcare applications, which are however characterized by a significant lack of open architectures, resulting in closed, non-interoperable and difficult to extend solutions. In this context, we propose an open and reconfigurable wireless sensor network (WSN) for pervasive health monitoring, with particular emphasis in its easy extension with additional sensors and functionality by incorporating embedded intelligence mechanisms. We consider a generic WSN architecture comprised of diverse sensor nodes (with communication and processing capabilities) and a mobile base unit (MBU) operating as the gateway between the sensors and the medical personnel, formulating this way a body area network (BAN). The primary focus of this work is on the intra-BAN data communication issues, adopting SensorML as the data representation mean, including the encoding of the monitoring patterns and the functionality of the sensor network. In our prototype implementation two sensor nodes are emulated; one for heart rate monitoring and the other for blood glucose observations, while the MBU corresponds to a personal digital assistant (PDA) device. Java 2 Micro Edition (J2ME) is used to implement both the sensor nodes and the MBU components. Intra-BAN wireless communication relies on the Blue-tooth protocol. Via an adaptive user interface in the MBU, health professionals may specify the monitoring parameters of the WSN and define the monitoring patterns of interest in terms of rules. This work constitutes an essential step towards the construction of open, extensible, inter-operable and intelligent WSNs for pervasive health monitoring.