Abstract

Proceedings of the Academic Track at State of the Map 2020 - Online (originally planned in Cape Town, South Africa), July 4-6, 2020. Editors Marco Minghini – European Commission, Joint Research Centre (JRC), Ispra, Italy Serena Coetzee, Department of Geography, Geoinformatics and Meteorology, University of Pretoria Levente Juhász – GIS Center, Florida International University, Miami, FL, United States A. Yair Grinberger – Department of Geography, The Hebrew University of Jerusalem, Israel Peter Mooney – Department of Computer Science, Maynooth University, Maynooth, Ireland Godwin Yeboah – Institute for Global Sustainable Development, School of Cross-faculty Studies, University of Warwick, Coventry, United Kingdom

Abstract

With the purpose of automatic detection of crowd patterns including abrupt and abnormal changes, a novel approach for extracting motion “textures” from dynamic Spatio-Temporal Volume (STV) blocks formulated by live video streams has been proposed. This paper starts from introducing the common approach for STV construction and corresponding Spatio-Temporal Texture (STT) extraction techniques. Next the crowd motion information contained within the random STT slices are evaluated based on the information entropy theory to cull the static background and noises occupying most of the STV spaces. A preprocessing step using Gabor filtering for improving the STT sampling efficiency and motion fidelity has been devised and tested. The technique has been applied on benchmarking video databases for proof-of-concept and performance evaluation. Preliminary results have shown encouraging outcomes and promising potentials for its real-world crowd monitoring and control applications.

Abstract

Open Distributed Processing (ODP) is a framework for specifying open distributed systems, under development by the International Standards Organisation (ISO). It is based on the general idea of viewpoints - i.e. partial specifications of an overall system, from different perspectives - but assumes five specific, named viewpoints, which are described informally in the ODP Reference Model (RM-ODP). This paper summarises some observations regarding an attempt to use ODP to specify a complex air traffic control system. Some of the key issues that arise are discussed further in the context of the formal specification of a simpler, idealised model, involving two formalised viewpoints - the Information Viewpoint (a high-level, abstract specification, in Z), and the Computational Viewpoint (a specification of distributed components and objects, in Object-Z).

Abstract

© 2015 IEEE.In this paper, we study the problem of multi-resource fairness in multi-user sensor networks with heterogeneous and time-varying resources. Particularly we focus on data gathering applications run on Wireless Sensor Networks (WSNs) or Internet of Things (IoT) in which users require to run a serious of sensing operations with various resource requirements. We consider both the resource demands of sensing tasks, and data forwarding tasks needed to establish multi-hop relay communications. By exploiting graph theory, queueing theory and the notion of dominant resource shares, we develop Symbiot, a light-weight, distributed algorithm that ensures multi-resource fairness between these users. With Symbiot, nodes can independently schedule its resources while maintaining network-level resource fairness through observing traffic congestion levels. Large-scale simulations based Contiki OS and Cooja network emulator show the effectiveness of Symbiot in adaptively utilizing available resources and reducing average completion times.

Abstract

There are a large number of workflow systems designed to work in various scientific domains, including support for the Internet of Things (IoT). One such workflow system is Node-RED, which is designed to bring workflow-based programming to IoT. However, the majority of scientific workflow systems, and specifically systems like Node-RED, are designed to operate in a fixed networked environment, which rely on a central point of coordination in order to manage the workflow. The main focus of the work described in this paper is to investigate means whereby we can migrate Node-RED workflows into a decentralized execution environment, so that such workflows can run on Edge networks, where nodes are extremely transient in nature. In this work, we demonstrate the feasibility of such an approach by showing how we can migrate a Node-RED based traffic congestion detection workflow into a decentralized environment. The detection algorithm is implemented as a set of Web services within Node-RED and we have architected and implemented a system that proxies the centralized Node-RED services using cognitively-aware wrapper services, designed to operate in a decentralized environment. Our cognitive services use a Vector Symbolic Architecture to semantically represent service descriptions and workflows in a way that can be unraveled on the fly without any central point of control. The VSA-based system is capable of parsing Node-RED workflows and migrating them to a decentralized environment for execution; providing a way to use Node-RED as a front-end graphical composition tool for decentralized workflows.

Abstract

Resource sharing in the mapping of an algorithm to an architecture allows the same resource to be scheduled for different uses in different cycles, generally at the cost of increased schedule length. Multi-pumping is a method whereby a resource is clocked at a frequency that is a multiple of the surrounding circuit, thereby offering multiple executions per global clock, and therefore sharing in the same clock cycle. This concept maps well to FPGA architectures, where hard macro blocks are typically capable of running at higher frequencies than standard logic. While this technique has been demonstrated for multipliers, modern DSP blocks are more complex with multiple computational nodes. In this paper, we apply multi-pumping to minimise DSP block usage, while taking advantage of the multiple nodes they support. The proposed approach uses, on average, 39% fewer DSP blocks, at a cost of 19% more LUTs and 7% more registers.

Abstract

dvanced urban traffic control systems are often based on feed-back algorithms. For instance, current traffic control systems often operate on the basis of adaptive green phases and flexible co-ordination in road (sub) networks based on measured traffic conditions. However, these approaches are still not very efficient during unforeseen situations such as road incidents when changes in traffic are requested in a short time interval. Therefore, we need self-managing systems that can plan and act effectively in order to restore an unexpected road traffic situations into the normal order. A significant step towards this is exploiting Automated Planning techniques which can reason about unforeseen situations in the road network and come up with plans (sequences of actions) achieving a desired traffic situation. In this paper, we introduce the problem of self-management of a road traffic network as a temporal planning problem in order to effectively navigate cars throughout a road network. We demonstrate the feasibility of such a concept and discuss our preliminary evaluation in order to identify strengths and weaknesses of our approach and point to some promising directions of future research.

Abstract

This article presents a parallel evolutionary algorithm for public transport optimization by synchronizing traffic lights in the context of Bus Rapid Transit systems. The related optimization problem is NP-hard, so exact computational methods are not useful to solve real-world instances. Our research introduces a parallel evolutionary algorithm to efficiently configure and synchronize traffic lights and improve the average speed of buses and other vehicles. The Bus Rapid Transit on Garzón Avenue (Montevideo, Uruguay) is used as a case study. This is an interesting complex urban scenario due to the number of crossings, streets, and traffic lights in the zone. The experimental analysis compares the numerical results computed by the parallel evolutionary algorithm with a scenario that models the current reality. The results show that the proposed evolutionary algorithm achieves better quality of service when compared with the current reality, improving up to 15.3% the average bus speed and 24.8% the average speed of other vehicles. A multiobjective optimization analysis also demonstrates that additional improvements can be achieved by assigning different priorities to buses and other vehicles. In addition, further improvements can be achieved on a modified scenario simply by deleting a few bus stops and changing some traffic lights rules. The benefits of using a parallel solver are also highlighted, as the parallel version is able to accelerate the execution times up to 26.9× when compared with the sequential version. Keywords: Bus Rapid Transit, Traffic lights synchronization, Evolutionary algorithm Document type: Article