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Register a new userEvaluation of Time-Critical Communications for IEC 61850-Substation Network Architecture
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Added by
Ahmed Altaher
Publication date
2015
fields
Informatics Engineering
and research's language is
English
Authors
Ahmed Altaher
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Present-day developments, in electrical power transmission and distribution, require considerations of the status quo. In other meaning, international regulations enforce increasing of reliability and reducing of environment impact, correspondingly they motivate developing of dependable systems. Power grids especially intelligent (smart grids) ones become industrial solutions that follow standardized development. The International standardization, in the field of power transmission and distribution, improve technology influences. The rise of dedicated standards for SAS (Substation Automation Systems) communications, such as the leading International Electro-technical Commission standard IEC 61850, enforces modern technological trends in this field. Within this standard, a constraint of low ETE (End-to-End) latency should be respected, and time-critical status transmission must be achieved. This experimental study emphasis on IEC 61850 SAS communication standard, e.g. IEC 61850 GOOSE (Generic Object Oriented Substation Events), to implement an investigational method to determine the protection communication delay. This method observes GOOSE behaviour by adopting monitoring and analysis capabilities. It is observed by using network test equipment, i.e. SPAN (Switch Port Analyser) and TAP (Test Access Point) devices, with on-the-shelf available hardware and software solutions.
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Ultra-low latency supported by the fifth generation (5G) give impetus to the prosperity of many wireless network applications, such as autonomous driving, robotics, telepresence, virtual reality and so on. Ultra-low latency is not achieved in a moment, but requires long-term evolution of network structure and key enabling communication technologies. In this paper, we provide an evolutionary overview of low latency in mobile communication systems, including two different evolutionary perspectives: 1) network architecture; 2) physical layer air interface technologies. We firstly describe in detail the evolution of communication network architecture from the second generation (2G) to 5G, highlighting the key points reducing latency. Moreover, we review the evolution of key enabling technologies in the physical layer from 2G to 5G, which is also aimed at reducing latency. We also discussed the challenges and future research directions for low latency in network architecture and physical layer.
This paper has been withdrawn by the authors.
The growing use of aerial user equipments (UEs) in various applications requires ubiquitous and reliable connectivity for safe control and data exchange between these devices and ground stations. Key questions that need to be addressed when planning the deployment of aerial UEs are whether the cellular network is a suitable candidate for enabling such connectivity, and how the inclusion of aerial UEs might impact the overall network efficiency. This paper provides an in-depth analysis of user and network level performance of a cellular network that serves both unmanned aerial vehicles (UAVs) and ground users in the downlink. Our results show that the favorable propagation conditions that UAVs enjoy due to their height often backfire on them, as the increased co-channel interference received from neighboring ground BSs is not compensated by the improved signal strength. When compared with a ground user in an urban area, our analysis shows that a UAV flying at 100 meters can experience a throughput decrease of a factor 10 and a coverage drop from 76% to 30%. Motivated by these findings, we develop UAV and network based solutions to enable an adequate integration of UAVs into cellular networks. In particular, we show that an optimal tilting of the UAV antenna can increase their coverage and throughput from 23% to 89% and from 3.5 b/s/Hz to 5.8 b/s/Hz, respectively, outperforming ground UEs. Furthermore, our findings reveal that depending on UAV altitude, the aerial user performance can scale with respect to the network density better than that of a ground user. Finally, our results show that network densification and the use of micro cells limit UAV performance. While UAV usage has the potential to increase area spectral efficiency (ASE) of cellular networks with moderate number of cells, they might hamper the development of future ultra dense networks.
Industry 4.0 applications foster new business opportunities but they also pose new and challenging requirements, such as low latency communications and highly reliable systems. They enable to exploit novel wireless technologies (5G), but it would also be crucial to rely on architectures that appropriately support them. Thus, the combination of fog and cloud computing is emerging as one potential solution. It can dynamically allocate the workload depending on the specific needs of each application. Our main goal is to provide a highly reliable and dynamic architecture, which minimizes the time that an end node or user, for instance a car in a smart mobility application, spends in downloading the required data. In order to achieve this, we have developed an optimal distribution algorithm that decides, based on multiple parameters of the proposed system model, the amount of information that should be stored at, or retrieved from, each node to minimize the data download time. Our scheme exploits Network Coding (NC) as a tool for data distribution, as a key enabler of the proposed solution. We compare the performance of our proposed scheme with other alternative solutions, and the results show that there is a clear gain in terms of the download time.
Measuring and evaluating network resilience has become an important aspect since the network is vulnerable to both uncertain disturbances and malicious attacks. Networked systems are often composed of many dynamic components and change over time, which makes it difficult for existing methods to access the changeable situation of network resilience. This paper establishes a novel quantitative framework for evaluating network resilience using the Dynamic Bayesian Network. The proposed framework can be used to evaluate the networks multi-stage resilience processes when suffering various attacks and recoveries. First, we define the dynamic capacities of network components and establish the networks five core resilience capabilities to describe the resilient networking stages including preparation, resistance, adaptation, recovery, and evolution; the five core resilience capabilities consist of rapid response capability, sustained resistance capability, continuous running capability, rapid convergence capability, and dynamic evolution capability. Then, we employ a two-time slices approach based on the Dynamic Bayesian Network to quantify five crucial performances of network resilience based on core capabilities proposed above. The proposed approach can ensure the time continuity of resilience evaluation in time-varying networks. Finally, our proposed evaluation framework is applied to different attacks and recovery conditions in typical simulations and real-world network topology. Results and comparisons with extant studies indicate that the proposed method can achieve a more accurate and comprehensive evaluation and can be applied to network scenarios under various attack and recovery intensities.
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