Zinon Zinonos

The GINSENG system for wireless monitoring and control: Design and deployment experiences

Todays industrial facilities, such as oil refineries, chemical plants, and factories, rely on wired sensor systems to monitor and control the production processes. The deployment and maintenance of such cabled systems is expensive and inflexible. It is, therefore, desirable to replace or augment these systems using wireless technology, which requires us to overcome significant technical challenges. Process automation and control applications are mission-critical and require timely and reliable data delivery, which is difficult to provide in industrial environments with harsh radio environments. In this article, we present the GINSENG system which implements performance control to allow us to use wireless sensor networks for mission-critical applications in industrial environments. GINSENG is a complete system solution that comprises on-node system software, network protocols, and back-end systems with sophisticated data processing capability. GINSENG assumes that a deployment can be carefully planned. A TDMA-based MAC protocol, tailored to the deployment environment, is employed to provide reliable and timely data delivery. Performance debugging components are used to unintrusively monitor the system performance and identify problems as they occur. The article reports on a real-world deployment of GINSENG in an especially challenging environment of an operational oil refinery in Sines, Portugal. We provide experimental results from this deployment and share the experiences gained. These results demonstate the use of GINSENG for sensing and actuation and allow an assessment of its ability to operate within the required performance bounds. We also identify shortcomings that manifested during the evaluation phase, thus giving a useful perspective on the challenges that have to be overcome in these harsh application settings.

Mobility in WSNs for critical applications

Recent critical application sectors of sensor networks like military, health care, and industry require the use of mobile sensor nodes, something that poses unique challenges in aspects like handoff delay, packet loss, and reliability. In this paper we propose a novel mobility model that handles those challenges effectively by providing on-time mobility detection and handoff triggering. In that way soft handoffs and controlled disconnections are assured. The proposed solution uses cross-layer information from the MAC and Network layers. Our solution was implemented and evaluated in an experimental testbed, in the context of the European FP7 GINSENG project.

Inter-mobility support in controlled 6LoWPAN networks

The research and industrial community started to think of more complex application scenarios for wireless sensor networks, where the use of mobile sensor nodes is essential. The support of mobile sensor nodes in such applications requires the existence of a suitable mobility management protocol. However, existing mobility protocols, like MIPv6, can not be directly applied on mobile sensor nodes, since they are inefficient in terms of energy, communication, and computation cost, and fail to meet the stringent operational requirements of a mobile sensor node. In this paper we propose a new mobility management protocol for 6LoWPAN which uses the technology of Proxy Agents and aims to enhance the handoff time by predicting or rapidly responding to a handover event. The proposed protocol lessens the involvement of the mobile node in mobility-related message exchange.

Mobility solutions for wireless sensor and actuator networks with performance guarantees

Wireless sensor and actuator networks (WSANs) have been studied for about ten years now. However, a gap between research and real applications and implementations remains. The lack of an integrated solution, capable of providing the reliability levels of monitoring and actuation required by critical applications, have postponed the replacement and extension of the existing inflexible and expensive wired solutions with the low-cost, easy-to-deploy, and portable wireless options. In order to assist this transition this paper presents a new method for supporting mobility in WSANs specifically designed for time-critical scenarios. The method is being targeted for a critical application located in a real oil refinery, in which a WSAN has been implemented in the scope of a European research project.

Dynamic Topology Control for WSNs in Critical Environments

Plant automation and control are mission-critical applications and require timely and reliable data delivery, which is difficult to provide using a wireless technology. This is especially more difficult in industrial environments with harsh radio conditions. In this paper we present a dynamic and distributed topology control algorithm for Wireless Sensor Networks for use in performance critical environments. This topology control algorithm assumes a small number of sensor nodes connected to a single sink and communicating using a TDMA-based MAC protocol designed with the application requirements in mind. Our solution was implemented and evaluated in real testbed inside an oil refinery. Evaluation results demonstrating the self-organizing properties of the proposed mechanism, as well as its operational performance are included. The results show that the system reliability is high and that data are delivered on time to the control center.

S-GinMob: Soft-handoff solution for mobile users in industrial environments

In current research studies and testbed deployments of sensor networks, individual sensor nodes are usually assumed to be static. However, recent applications require mobile sensor nodes, something that poses unique challenges in aspects like resource management, topology control, and performance. In this paper we propose a novel soft-handoff mobility protocol that provides zero handoff time and zero packet losses. The proposed solution uses cross-layer information from the MAC layer, the Topology Control, and the Performance Debugging modules of the employed architecture. Our solution was implemented and evaluated in a critical scenario inside an oil refinery.

WSN evaluation in industrial environments first results and lessons learned

The GINSENG project develops performance-controlled wireless sensor networks that can be used for time-critical applications in hostile environments such as industrial plant automation and control. GINSENG aims at integrating wireless sensor networks with existing enterprise resource management solutions using a middleware. A cornerstone is the evaluation in a challenging industrial environment — an oil refinery in Portugal. In this paper we first present our testbed. Then we introduce our solution to access, debug and flash the sensor nodes remotely from an operations room in the plant or from any location with internet access. We further present our experimental methodology and show some exemplary results from the refinery testbed.

Radio propagation in industrial wireless sensor network environments: from testbed to simulation evaluation

In recent years, sensor networks characteristics have led to incremental utilization in different types of applications. Several techniques have been proposed to evaluate the performance of WSNs; the two most popular being mathematical analysis and simulations. An important drawback of these techniques is that they provide evaluation results that usually are not similar to those of real deployments. One reason for this is the fact that both techniques introduce physical layer modeling assumptions, which do not usually corresponded to real-life environments. In this paper, we used measurements from an industrial environment to develop a new radio propagation model for use in simulators and mathematical tools. The proposed radio model was implemented in the COOJA simulator and validated against real-life results obtained from a testbed inside a running oil refinery, which were found not to conform to any legacy radio propagation model. The proposed model has been shown to successfully match the refinery testbed behavior.

Handoff triggering for wireless sensor networks with performance needs

In this paper, we deal with mobility management for wireless sensor networks and we focus on the first phase of a handoff procedure which is concerned with the mechanics of measuring important parameters and initiating (triggering) the handoff decision process. We introduce a range of metrics that could potentially be used in triggering a handoff and we focus on two easy-to-find local values, namely the Received Signal Strength Indicator (RSSI) and the Local Link Loss. We investigate these metrics on their ability to provide correct triggers for the decision process, taking into account different threshold values, averaging methods, averaging windows, and hysteresis margins. We evaluate the performance of the different metrics and methods using not only the resulting end-to-end packet loss, the handoff triggers, the eventual handoffs performed, and the handoff success rate, but also using the new concept of on-time triggering. Our evaluation provides a unique insight into the mechanics of the handoff trigger and decision phases.

Controlling the Handoff Procedure in an Oil Refinery Environment Using Fuzzy Logic

Mobility is one of the most important challenges in a wireless sensor system. Usually, continuous connectivity of a Mobile Node (MN) is achieved by supporting handoff from one connection point to another. In order to guarantee reliability and seamless communications to a MN, it is important to avoid unnecessary handoffs occurring during a short period of time. In this paper, we present a mobility management solution that is applied to a network operating in an oil refinery environment. The proposed mobility solution is supported by fuzzy logic techniques in order to keep the number of handoff triggers to low values and at the same time to provide high reliability. The performance evaluation of the proposed fuzzy-based solution and the conventional Received Signal Strength Indicator (RSSI) based method shows that the proposed solution manages to increase the reliability of the system and at the same time reduce the handoff overhead.