Autonomous pipeline monitoring and maintenance system: a RFID-based approach

Pipeline networks are one of the key infrastructures of our modern life. Proactive monitoring and frequent inspection of pipeline networks are very important for sustaining their safe and efficient functionalities. Existing monitoring and maintenance approaches are costly and inefficient because pipelines can be installed in large scale and in an inaccessible and hazardous environment. To overcome these challenges, we propose a novel Radio Frequency IDentification (RFID)-based Autonomous Maintenance system for Pipelines, called RAMP, which combines robotic, sensing, and RFID technologies for efficient and accurate inspection, corrective reparation, and precise geo-location information. RAMP can provide not only economical and scalable remedy but also safe and customizable solution. RAMP also allows proactive and corrective monitoring and maintenance of pipelines. One prominent advantage of RAMP is that it can be applied to a large variety of pipeline systems including water, sewer, and gas pipelines. Simulation results demonstrate the feasibility and superior performance of RAMP in comparison to the existing pipeline monitoring systems

Energy-aware distributed routing algorithm to tolerate network failure in wireless sensor networks

Wireless Sensor Networks are prone to link/node failures due to various environmental hazards such as interference and internal faults in deployed sensor nodes. Such failures can result in a disconnection in part of the network and the sensed data being unable to obtain a route to the sink(s), i.e. a network failure. Network failures potentially degrade the Quality of Service (QoS) of Wireless Sensor Networks (WSNs). It is very difficult to monitor network failures using a manual operator in a harsh or hostile environment. In such environments, communication links can easy fail because of node unequal energy depletion and hardware failure or invasion. Thus it is desirable that deployed sensor nodes are capable of overcoming network failures. In this paper, we consider the problem of tolerating network failures seen by deployed sensor nodes in a WSN. We first propose a novel clustering algorithm for WSNs, termed Distributed Energy Efficient Heterogeneous Clustering (DEEHC) that selects cluster heads according to the residual energy of deployed sensor nodes with the aid of a secondary timer. During the clustering phase, each sensor node finds k-vertex disjoint paths to cluster heads depending on the energy level of its neighbor sensor nodes. We then present a k-Vertex Disjoint Path Routing (kVDPR) algorithm where each cluster head finds k-vertex disjoint paths to the base station and relays their aggregate data to the base station. Furthermore, we also propose a novel Route Maintenance Mechanism (RMM) that can repair k-vertex disjoint paths throughout the monitoring session. The resulting WSNs become tolerant to k-1 failures in the worst case. The proposed scheme has been extensively tested using various network scenarios and compared to the existing state of the art approaches to show the effectiveness of the proposed scheme

Fault-tolerant wireless sensor networks using evolutionary games

This dissertation proposes an approach to creating robust communication systems in wireless sensor networks, inspired by biological and ecological systems, particularly by evolutionary game theory. In this approach, a virtual community of agents live inside the network nodes and carry out network functions. The agents use different strategies to execute their functions, and these strategies are tested and selected by playing evolutionary games. Over time, agents with the best strategies survive, while others die. The strategies and the game rules provide the network with an adaptive behavior that allows it to react to changes in environmental conditions by adapting and improving network behavior. To evaluate the viability of this approach, this dissertation also describes a micro-component framework for implementing agent-based wireless sensor network services, an evolutionary data collection protocol built using this framework, ECP, and experiments evaluating the performance of this protocol in a faulty environment. The framework addresses many of the programming challenges in writing network software for wireless sensor networks, while the protocol built using the framework provides a means of evaluating the general viability of the agent-based approach. The results of this evaluation show that an evolutionary approach to designing wireless sensor networks can improve the performance of wireless sensor network protocols in the presence of node failures. In particular, we compared the performance of ECP with a non-evolutionary rule-based variant of ECP. While the purely-evolutionary version of ECP has more routing timeouts than the rule-based approach in failure-free networks, it sends significantly fewer beacon packets and incurs statistically fewer routing timeouts in both simple fault and periodic fault scenarios

Continuous maintenance and the future – Foundations and technological challenges

High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security

The State of the Art of Information Integration in Space Applications

This paper aims to present a comprehensive survey on information integration (II) in space informatics. With an ever-increasing scale and dynamics of complex space systems, II has become essential in dealing with the complexity, changes, dynamics, and uncertainties of space systems. The applications of space II (SII) require addressing some distinctive functional requirements (FRs) of heterogeneity, networking, communication, security, latency, and resilience; while limited works are available to examine recent advances of SII thoroughly. This survey helps to gain the understanding of the state of the art of SII in sense that (1) technical drivers for SII are discussed and classified; (2) existing works in space system development are analyzed in terms of their contributions to space economy, divisions, activities, and missions; (3) enabling space information technologies are explored at aspects of sensing, communication, networking, data analysis, and system integration; (4) the importance of first-time right (FTR) for implementation of a space system is emphasized, the limitations of digital twin (DT-I) as technological enablers are discussed, and a concept digital-triad (DT-II) is introduced as an information platform to overcome these limitations with a list of fundamental design principles; (5) the research challenges and opportunities are discussed to promote SII and advance space informatics in future

Practical Aggregation in the Edge

Due to the increasing amounts of data produced by applications and devices, cloud infrastructures are becoming unable to timely process and provide answers back to users. This has led to the emergence of the edge computing paradigm that aims at moving computations closer to end user devices. Edge computing can be defined as performing computations outside the boundaries of cloud data centres. This however, can be materialised across very different scenarios considering the broad spectrum of devices that can be leveraged to perform computations in the edge. In this thesis, we focus on a concrete scenario of edge computing, that of multiple devices with wireless capabilities that collectively form a wireless ad hoc network to perform distributed computations. We aim at devising practical solutions for these scenarios however, there is a lack of tools to help us in achieving such goal. To address this first limitation we propose a novel framework, called Yggdrasil, that is specifically tailored to develop and execute distributed protocols over wireless ad hoc networks on commodity devices. As to enable distributed computations in such networks, we focus on the particular case of distributed data aggregation. In particular, we address a harder variant of this problem, that we dub distributed continuous aggregation, where input values used for the computation of the aggregation function may change over time, and propose a novel distributed continuous aggregation protocol, called MiRAge. We have implemented and validated both Yggdrasil and MiRAge through an extensive experimental evaluation using a test-bed composed of 24 Raspberry Pi’s. Our results show that Yggdrasil provides adequate abstractions and tools to implement and execute distributed protocols in wireless ad hoc settings. Our evaluation is also composed of a practical comparative study on distributed continuous aggregation protocols, that shows that MiRAge is more robust and achieves more precise aggregation results than competing state-of-the-art alternatives

Recent Advances in Internet of Things Solutions for Early Warning Systems: A Review

none5noNatural disasters cause enormous damage and losses every year, both economic and in terms of human lives. It is essential to develop systems to predict disasters and to generate and disseminate timely warnings. Recently, technologies such as the Internet of Things solutions have been integrated into alert systems to provide an effective method to gather environmental data and produce alerts. This work reviews the literature regarding Internet of Things solutions in the field of Early Warning for different natural disasters: floods, earthquakes, tsunamis, and landslides. The aim of the paper is to describe the adopted IoT architectures, define the constraints and the requirements of an Early Warning system, and systematically determine which are the most used solutions in the four use cases examined. This review also highlights the main gaps in literature and provides suggestions to satisfy the requirements for each use case based on the articles and solutions reviewed, particularly stressing the advantages of integrating a Fog/Edge layer in the developed IoT architectures.openEsposito M.; Palma L.; Belli A.; Sabbatini L.; Pierleoni P.Esposito, M.; Palma, L.; Belli, A.; Sabbatini, L.; Pierleoni, P

Survivability modeling for cyber-physical systems subject to data corruption

Cyber-physical critical infrastructures are created when traditional physical infrastructure is supplemented with advanced monitoring, control, computing, and communication capability. More intelligent decision support and improved efficacy, dependability, and security are expected. Quantitative models and evaluation methods are required for determining the extent to which a cyber-physical infrastructure improves on its physical predecessors. It is essential that these models reflect both cyber and physical aspects of operation and failure. In this dissertation, we propose quantitative models for dependability attributes, in particular, survivability, of cyber-physical systems. Any malfunction or security breach, whether cyber or physical, that causes the system operation to depart from specifications will affect these dependability attributes. Our focus is on data corruption, which compromises decision support -- the fundamental role played by cyber infrastructure. The first research contribution of this work is a Petri net model for information exchange in cyber-physical systems, which facilitates i) evaluation of the extent of data corruption at a given time, and ii) illuminates the service degradation caused by propagation of corrupt data through the cyber infrastructure. In the second research contribution, we propose metrics and an evaluation method for survivability, which captures the extent of functionality retained by a system after a disruptive event. We illustrate the application of our methods through case studies on smart grids, intelligent water distribution networks, and intelligent transportation systems. Data, cyber infrastructure, and intelligent control are part and parcel of nearly every critical infrastructure that underpins daily life in developed countries. Our work provides means for quantifying and predicting the service degradation caused when cyber infrastructure fails to serve its intended purpose. It can also serve as the foundation for efforts to fortify critical systems and mitigate inevitable failures --Abstract, page iii