José Cecílio

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.

Architecture for Uniform (Re)Configuration and Processing Over Embedded Sensor and Actuator Networks

Deployment of embedded systems in industrial environments requires preconfiguration for operation, and, in some contexts, easy reconfiguration capabilities are also desirable. It is therefore useful to define a mechanism for embedded devices that will operate in sensor and actuator networks to be remotely (re)configured and to have flexible computation capabilities. We propose such a configuration, reconfiguration, and processing mechanism in the form of a software architecture. A node component should be deployed in any embedded device and implements application programming interface (API), configuration, processing, and communication. The resulting system provides remote configuration and processing of data in any node in a most flexible way, since every node has the same uniform API, processing, and access functionalities. The experimental section shows a working deployment of this concept in an industrial refinery setting, as part of the EU FP7 project Ginseng.

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.

ONE: a predictable and scalable DW model

The star schema model has been widely used as the facto DW storage organization on relational database management systems (RDBMS). The physical division in normalized fact tables (with metrics) and denormalized dimension tables allows a trade-off between performance and storage space while, at the same time offering a simple business understanding of the overall model as a set of metrics (facts) and attributes for business analysis (dimensions). However, the underlying premises of such trade-off between performance and storage have changed. Nowadays, storage capacity increased significantly at affordable prices (below 50

BlindeDroid: An Information Tracking System for Real-time Guiding of Blind People

/terabyte) with improved transfer rates, and faster random access times particularly with modern SSD disks. In this paper we evaluate if the underlying premises of the star schema model storage organization still upholds. We propose an alternative storage organization (called ONE) that physically stores the whole star schema into a single relation, providing a predictable and scalable alternative to the star schema model. We use the TPC-H benchmark to evaluate ONE and the star schema model, assessing both the required storage size and query execution time.

Wireless Sensors in Heterogeneous Networked Systems

Abstract Among the activities affected by visual impairment, navigation plays a fundamental role, since it enables the person to independently move in safety. The heterogeneous environment, easily perceived by visually enabled people, is hardly known by partially sighted people. A challenging task for these people is independent navigation in new spaces/buildings/environments. The environment is usually signaled and labeled with visual marks and signs which are not appropriate for blind persons. With the purpose of balancing the access to services and spaces among all persons, this work proposes an innovative navigation and information system to help the navigation of blind people within new environments (e.g. shopping center, public office building). Based on smartphones and wireless sensors deployed in the environment, we propose an information tracking system for realtime guide blind people (BlindeDroid). It offers guided navigation, answering questions, and providing objective information about places, products and services that are available surrounding the user.

Survey on Data Routing in Wireless Sensor Networks

Regions Group based, multi-hop non-connected Node centric Imperative Data sharing TinyDB Global view System centric Declarative Database oriented Flask Routing dependent Node centric Functional Message passing Table 7.2 Architectural characteristics Language Reach Stack penetration SO/SR Interaction pattern Time nesC, Contiki-C Vertical solution Active messages SO M-to-M Periodic + event driven Pleiades Appl level No SO M-to-M Periodic ATaG Application level No SR M-to-M Periodic SINA Application level No SO Many to one Periodic Cougar Application level No SO Many to one Periodic Hood Vertical solution On-demand bdcast SO M-to-M Periodic Regiment Application level No SO Many to one Event driven Abstract Regions Application level Tuning interface SO Depends on region Periodic + event drivenRegions Application level Tuning interface SO Depends on region Periodic + event driven TinyDB Application level No SO Many to one Periodic Flask Vertical solution No SO Many to many Periodic + event driven 7.3 Language and Architectural Features

Distributed configuration and processing for industrial sensor networks

Routing in sensor networks is very challenging, due to several characteristics that distinguish them from contemporary communication and wireless ad-hoc networks. Many new goal and data-oriented algorithms have been proposed for the problem of routing data in sensor networks. Most routing protocols can be classified as data-centric, hierarchical, location-based or QoS-aware. Data-centric protocols are query-based and depend on the naming of desired data. Hierarchical protocols aim at clustering the nodes so that cluster heads can do some aggregation and reduction of data in order to save energy. Location-based protocols utilize the position information to relay the data to the desired regions. The QoS-aware are based on general network-flow modeling for meeting some QoS requirements. In this chapter, we will explore goal and data-oriented routing mechanisms for sensor networks developed in recent years. Our aim is to help better understanding current routing protocols for wireless sensor networks and point out open issues that should be subject to further research.

Existing Middleware Solutions for Wireless Sensor Networks

Sensor and Actuator Networks (SAN) are distributed systems deployed to sense, monitor and act on the environment. They may include any of the following: sensors, wiring, embedded system components, wireless communication and backbone servers. Given current technological advances, costs and flexibility advantages of wireless sensor networks technology, wireless SAN (WSAN) deployments are being considered in such environments. WSAN nodes are small embedded devices that provide sensing, acting and (limited) in-network processing capabilities. A significant research challenge is how to provide an interface that allows configuration and operation of any computation-capable node or group of nodes in an industrial setting, as opposed to hand-coding every component of the system for every minor or major configuration change and/or having multiple configuration systems. In this paper we propose a configuration approach over industrial WSAN networks. Our approach was successfully tested in an industrial refinery setting, allowing deployers to configure and re-configure the system to meet specific needs.

Overcoming the scalability limitations of parallel star schema data warehouses

Nowadays, heterogeneous sensor networks can be found in application contexts such as environment monitoring, agriculture, warehouse tracking, transport logistics, surveillance and health care, as discussed in Chap. 3. In this chapter we discuss current middleware architectures for distributed sensor systems, where wireless sensor networks are part of the architecture. These middleware architectures refer to software and tools that hide the complexity and heterogeneity of hardware and network platforms. We present an extensive review of existing middleware solutions for wireless sensor networks. This review includes the definition of a taxonomy of operating software for wireless sensor data and a review of several important subjects: remote (re)configuration approaches, middleware architectures inside the WSN, Internet-based integration of sensor data and finally IP-based homogeneous middleware solutions. After reading this chapter, the reader will know precisely what solutions have been investigated and what different paradigms and systems exist concerning middleware software for wireless and hybrid sensor networks.