Acumen : an open-source testbed for cyber-physical systems research

Developing Cyber-Physical Systems requires methods and tools to support simulation and verification of hybrid (both continuous and discrete) models. The Acumen modeling and simulation language is an open source testbed for exploring the design space of what rigorousbut- practical next-generation tools can deliver to developers of Cyber- Physical Systems. Like verification tools, a design goal for Acumen is to provide rigorous results. Like simulation tools, it aims to be intuitive, practical, and scalable. However, it is far from evident whether these two goals can be achieved simultaneously. This paper explains the primary design goals for Acumen, the core challenges that must be addressed in order to achieve these goals, the “agile research method” taken by the project, the steps taken to realize these goals, the key lessons learned, and the emerging language design.

URIs and Intertextuality: Incumbent Philosophical Commitments in the Development of the Semantic Web

Examines two commitments inherent in Resource Description Framework (RDF): intertextuality and rationalism. After introducing how rationalism has been studied in knowledge organization, this paper then introduces the concept of bracketed-rationalism. This paper closes with a discussion of ramifications of intertextuality and bracketed rationalism on evaluation of RDF.

Ontologies and the Semantic Web: Problems and Perspectives for LIS Professionals

Many years have passed since Berners-Lee envi- sioned the Web as it should be (1999), but still many information professionals do not know their precise role in its development, especially con- cerning ontologies –considered one of its main elements. Why? May it still be a lack of under- standing between the different academic commu- nities involved (namely, Computer Science, Lin- guistics and Library and Information Science), as reported by Soergel (1999)? The idea behind the Semantic Web is that of several technologies working together to get optimum information re- trieval performance, which is based on proper resource description in a machine-understandable way, by means of metadata and vocabularies (Greenberg, Sutton and Campbell, 2003). This is obviously something that Library and Information Science professionals can do very well, but, are we doing enough? When computer scientists put on stage the ontology paradigm they were asking for semantically richer vocabularies that could support logical inferences in artificial intelligence as a way to improve information retrieval systems. Which direction should vocabulary development take to contribute better to that common goal? The main objective of this paper is twofold: 1) to identify main trends, issues and problems con- cerning ontology research and 2) to identify pos- sible contributions from the Library and Information Science area to the development of ontologies for the semantic web. To do so, our paper has been structured in the following manner. First, the methodology followed in the paper is reported, which is based on a thorough literature review, where main contributions are analysed. Then, the paper presents a discussion of the main trends, issues and problems concerning ontology re- search identified in the literature review. Recom- mendations of possible contributions from the Library and Information Science area to the devel- opment of ontologies for the semantic web are finally presented.

Scheme Versioning in the Semantic Web

This paper describes a conceptual framework and meth- odology for managing scheme versioning for the Semantic Web. The first part of the paper introduces the concept of vocabulary encoding schemes, distinguished from metadata schemas, and discusses the characteristics of changes in schemes. The paper then presents a proposal to use a value record–similar to a term record in thesaurus management techniques–to manage scheme versioning challenges for the Semantic Web. The con-clusion identifies future research directions.

Directly training spiking neural networks for cyber-physical systems: from supervised to reinforcement learning

Spiking Neural Networks (SNNs) are bio-inspired Artificial Neural Networks (ANNs) utilizing discrete spiking signals, akin to neuron communication in the brain, making them ideal for real-time and energy-efficient Cyber-Physical Systems (CPSs). This thesis explores their potential in Structural Health Monitoring (SHM), leveraging low-cost MEMS accelerometers for early damage detection in motorway bridges. The study focuses on Long Short-Term SNNs (LSNNs), although their complex learning processes pose challenges. Comparing LSNNs with other ANN models and training algorithms for SHM, findings indicate LSNNs' effectiveness in damage identification, comparable to ANNs trained using traditional methods. Additionally, an optimized embedded LSNN implementation demonstrates a 54% reduction in execution time, but with longer pre-processing due to spike-based encoding. Furthermore, SNNs are applied in UAV obstacle avoidance, trained directly using a Reinforcement Learning (RL) algorithm with event-based input from a Dynamic Vision Sensor (DVS). Performance evaluation against Convolutional Neural Networks (CNNs) highlights SNNs' superior energy efficiency, showing a 6x decrease in energy consumption. The study also investigates embedded SNN implementations' latency and throughput in real-world deployments, emphasizing their potential for energy-efficient monitoring systems. This research contributes to advancing SHM and UAV obstacle avoidance through SNNs' efficient information processing and decision-making capabilities within CPS domains.

Networked embedded systems for active flow control in aircraft

Aerodynamic drag is known to be one of the factors contributing more to increased aircraft fuel consumption. The primary source of skin friction drag during flight is the boundary layer separation. This is the layer of air moving smoothly in the immediate vicinity of the aircraft. In this paper we discuss a cyber-physical system approach able of performing an efficient suppression of the turbulent flow by using a dense sensing deployment to detect the low pressure region and a similarly dense deployment of actuators to manage the turbulent flow. With this concept, only the actuators in the vicinity of a separation layer are activated, minimizing power consumption and also the induced drag.

Building a microscope for the data center

Managing the physical and compute infrastructure of a large data center is an embodiment of a Cyber-Physical System (CPS). The physical parameters of the data center (such as power, temperature, pressure, humidity) are tightly coupled with computations, even more so in upcoming data centers, where the location of workloads can vary substantially due, for example, to workloads being moved in a cloud infrastructure hosted in the data center. In this paper, we describe a data collection and distribution architecture that enables gathering physical parameters of a large data center at a very high temporal and spatial resolutionof the sensor measurements. We think this is an important characteristic to enable more accurate heat-flow models of the data center andwith them, _and opportunities to optimize energy consumption. Havinga high resolution picture of the data center conditions, also enables minimizing local hotspots, perform more accurate predictive maintenance (pending failures in cooling and other infrastructure equipment can be more promptly detected) and more accurate billing. We detail this architecture and define the structure of the underlying messaging system that is used to collect and distribute the data. Finally, we show the results of a preliminary study of a typical data center radio environment.

An Approach To Publish a Data Warehouse Content as Linked Data

Mestrado em Engenharia Informática - Área de Especialização em Tecnologias do Conhecimento e Decisão

A microscope for the data center

Nowadays, data centers are large energy consumers and the trend for next years is expected to increase further, considering the growth in the order of cloud services. A large portion of this power consumption is due to the control of physical parameters of the data center (such as temperature and humidity). However, these physical parameters are tightly coupled with computations, and even more so in upcoming data centers, where the location of workloads can vary substantially due, for example, to workloads being moved in the cloud infrastructure hosted in the data center. Therefore, managing the physical and compute infrastructure of a large data center is an embodiment of a Cyber-Physical System (CPS). In this paper, we describe a data collection and distribution architecture that enables gathering physical parameters of a large data center at a very high temporal and spatial resolution of the sensor measurements. We think this is an important characteristic to enable more accurate heat-flow models of the data center and with them, find opportunities to optimize energy consumptions. Having a high-resolution picture of the data center conditions, also enables minimizing local hot-spots, perform more accurate predictive maintenance (failures in all infrastructure equipments can be more promptly detected) and more accurate billing. We detail this architecture and define the structure of the underlying messaging system that is used to collect and distribute the data. Finally, we show the results of a preliminary study of a typical data center radio environment.

jxSensor: a sensor network integration layer for JXTA

Nowadays, Wireless Sensor Networks (WSN) arealready a very important data source to obtain data about the environment. Thus, they are key to the creation of Cyber-Physical Systems (CPS). Given the popularity of P2P middlewares as ameans to efficiently process information and distribute services, being able to integrate them to WSN¿s is an interesting proposal. JXTA is a widely used P2P middleware that allows peers to easily exchange information, heavily relying on its main architectural highlight, the capability to organize peers with common interests into peer groups. However, right now, approaches to integrate WSNs to a JXTA network seldom take advantage of peer groups. For this reason, in this paper we present jxSensor, an integrationlayer for sensor motes which facilitates the deployment of CPS¿s under this architecture. This integration has been done taking into account JXTA¿s idiosyncrasies and proposing novel ideas,such as the Virtual Peer, a group of sensors that acts as a single entity within the peer group context.

Development of hardware in the loop real-time control techniques for hybrid power systems involving distributed demands and sustainable energy sources

The future power grid will effectively utilize renewable energy resources and distributed generation to respond to energy demand while incorporating information technology and communication infrastructure for their optimum operation. This dissertation contributes to the development of real-time techniques, for wide-area monitoring and secure real-time control and operation of hybrid power systems. ^ To handle the increased level of real-time data exchange, this dissertation develops a supervisory control and data acquisition (SCADA) system that is equipped with a state estimation scheme from the real-time data. This system is verified on a specially developed laboratory-based test bed facility, as a hardware and software platform, to emulate the actual scenarios of a real hybrid power system with the highest level of similarities and capabilities to practical utility systems. It includes phasor measurements at hundreds of measurement points on the system. These measurements were obtained from especially developed laboratory based Phasor Measurement Unit (PMU) that is utilized in addition to existing commercially based PMU’s. The developed PMU was used in conjunction with the interconnected system along with the commercial PMU’s. The tested studies included a new technique for detecting the partially islanded micro grids in addition to several real-time techniques for synchronization and parameter identifications of hybrid systems. ^ Moreover, due to numerous integration of renewable energy resources through DC microgrids, this dissertation performs several practical cases for improvement of interoperability of such systems. Moreover, increased number of small and dispersed generating stations and their need to connect fast and properly into the AC grids, urged this work to explore the challenges that arise in synchronization of generators to the grid and through introduction of a Dynamic Brake system to improve the process of connecting distributed generators to the power grid.^ Real time operation and control requires data communication security. A research effort in this dissertation was developed based on Trusted Sensing Base (TSB) process for data communication security. The innovative TSB approach improves the security aspect of the power grid as a cyber-physical system. It is based on available GPS synchronization technology and provides protection against confidentiality attacks in critical power system infrastructures. ^

Top-K Query Processing in Edge-Labeled Graph Data

Edge-labeled graphs have proliferated rapidly over the last decade due to the increased popularity of social networks and the Semantic Web. In social networks, relationships between people are represented by edges and each edge is labeled with a semantic annotation. Hence, a huge single graph can express many different relationships between entities. The Semantic Web represents each single fragment of knowledge as a triple (subject, predicate, object), which is conceptually identical to an edge from subject to object labeled with predicates. A set of triples constitutes an edge-labeled graph on which knowledge inference is performed. Subgraph matching has been extensively used as a query language for patterns in the context of edge-labeled graphs. For example, in social networks, users can specify a subgraph matching query to find all people that have certain neighborhood relationships. Heavily used fragments of the SPARQL query language for the Semantic Web and graph queries of other graph DBMS can also be viewed as subgraph matching over large graphs. Though subgraph matching has been extensively studied as a query paradigm in the Semantic Web and in social networks, a user can get a large number of answers in response to a query. These answers can be shown to the user in accordance with an importance ranking. In this thesis proposal, we present four different scoring models along with scalable algorithms to find the top-k answers via a suite of intelligent pruning techniques. The suggested models consist of a practically important subset of the SPARQL query language augmented with some additional useful features. The first model called Substitution Importance Query (SIQ) identifies the top-k answers whose scores are calculated from matched vertices' properties in each answer in accordance with a user-specified notion of importance. The second model called Vertex Importance Query (VIQ) identifies important vertices in accordance with a user-defined scoring method that builds on top of various subgraphs articulated by the user. Approximate Importance Query (AIQ), our third model, allows partial and inexact matchings and returns top-k of them with a user-specified approximation terms and scoring functions. In the fourth model called Probabilistic Importance Query (PIQ), a query consists of several sub-blocks: one mandatory block that must be mapped and other blocks that can be opportunistically mapped. The probability is calculated from various aspects of answers such as the number of mapped blocks, vertices' properties in each block and so on and the most top-k probable answers are returned. An important distinguishing feature of our work is that we allow the user a huge amount of freedom in specifying: (i) what pattern and approximation he considers important, (ii) how to score answers - irrespective of whether they are vertices or substitution, and (iii) how to combine and aggregate scores generated by multiple patterns and/or multiple substitutions. Because so much power is given to the user, indexing is more challenging than in situations where additional restrictions are imposed on the queries the user can ask. The proposed algorithms for the first model can also be used for answering SPARQL queries with ORDER BY and LIMIT, and the method for the second model also works for SPARQL queries with GROUP BY, ORDER BY and LIMIT. We test our algorithms on multiple real-world graph databases, showing that our algorithms are far more efficient than popular triple stores.

Minimalist Hardware Architectures for Agent Tracking and Guidance

The philosophy of minimalism in robotics promotes gaining an understanding of sensing and computational requirements for solving a task. This minimalist approach lies in contrast to the common practice of first taking an existing sensory motor system, and only afterwards determining how to apply the robotic system to the task. While it may seem convenient to simply apply existing hardware systems to the task at hand, this design philosophy often proves to be wasteful in terms of energy consumption and cost, along with unnecessary complexity and decreased reliability. While impressive in terms of their versatility, complex robots such as the PR2 (which cost hundreds of thousands of dollars) are impractical for many common applications. Instead, if a specific task is required, sensing and computational requirements can be determined specific to that task, and a clever hardware implementation can be built to accomplish the task. Since this minimalist hardware would be designed around accomplishing the specified task, significant reductions in hardware complexity can be obtained. This can lead to huge advantages in battery life, cost, and reliability. Even if cost is of no concern, battery life is often a limiting factor in many applications. Thus, a minimalist hardware system is critical in achieving the system requirements. In this thesis, we will discuss an implementation of a counting, tracking, and actuation system as it relates to ergodic bodies to illustrate a minimalist design methodology.

Infomobility for “Car-Driver” Systems: Reference Model and Case Study

Part 21: Mobility and Logistics

Bidding and Optimization Strategies for Wind-PV Systems in Electricity Markets Assisted by CPS

The variability in non-dispatchable power generation raises important challenges to the integration of renewable energy sources into the electricity power grid. This paper provides the coordinated trading of wind and photovoltaic energy assisted by a cyber-physical system for supporting management decisions to mitigate risks due to the wind and solar power variability, electricity prices, and financial penalties arising out the generation shortfall and surplus. The problem of wind-photovoltaic coordinated trading is formulated as a stochastic linear programming problem. The goal is to obtain the optimal bidding strategy that maximizes the total profit. The wind-photovoltaic coordinated operation is modelled and compared with the uncoordinated operation. A comparison of the models and relevant conclusions are drawn from an illustrative case study of the Iberian day-ahead electricity market.