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Core Network and Operational Support System
Published in Saad Z. Asif, 5G Mobile Communications Concepts and Technologies, 2018
CDN improves the performance of networks by moving content closer to the end user. Some cases where CDN can make a difference are as follows [34]: As an Application Optimization Engine, CDN can optimize the amount of data being sent while increasing the utilization of available user bandwidth. Moreover, as CDNs connect the user to the geographically closest server, the net effect is in latency reduction introduced by the network. Such engines handle optimization at various networking levels to speed up the delivery of content to all types of users.As a file replicator, particularly when large data files are required at multiple geographies, CDNs can replicate data from a corporate headquarters in one region to one or more regional headquarters in a timely manner.As an ultimate bandwidth source, CDNs can be used to mitigate the effect of high volume, bursty, and ill-defined traffic growth, and keep the application performance at an acceptable level.
Operations on the Move: Vehicle Movement and Soldier Performance
Published in Pamela Savage-Knepshield, John Martin, John Lockett, Laurel Allender, Designing Soldier Systems, 2018
Latency is a measure of time between when a signal is sent and when the system responds. In normal driving, this could be illustrated as the time between a driver seeing an obstacle in the street and the driver engaging the brakes causing the vehicle to finally stop, which can more generically be described as the sensory, perception, and response components of latency. In teleoperation, sensory latency is increased by the delay during which the camera signal is processed, the image is transmitted to the operator, and the signal is reprocessed and seen on the display. Response latency is increased after the operator activates a control by the information processing and transmission time required to send instructions to the teleoperated vehicle. Latencies below 10 ms are generally below human perception and are acceptable in most applications (Mansfield 1973). However, in a study supported by ARL as part of the Future Combat System program, it was shown that latencies of 250 ms during teleoperated driving could be overcome with effort, but latencies longer than 250 ms made driving much slower with more collisions (Bolling and Reudin 2009). This study was done with the operator at a stationary workstation. Currently, the combined effects of latency and uncoupled movement have not been well defined.
5G Connectivity in the Transport Sector
Published in Zoran S. Bojkovic, Dragorad A. Milovanovic, Tulsi Pawan Fowdur, 5G Multimedia Communication, 2020
V. Bassoo, V. Hurbungs, Tulsi Pawan Fowdur, Y. Beeharry
Low latency. Another key specification of 5G networks is low latency down to 1 ms, and in order to achieve this specification, research work is being carried out in designing novel network topologies free of hardware components. Concepts such as SDN, network virtualized function, edge computing and caching are being utilized to lower latency [33]. Low latency is crucial for the safe operation of drones as it helps to provide improved control. It is even more important in scenarios where multidrones are deployed and coordination, collision avoidance and quick adaptability are essential [34,35]. Moreover, low latency can enhance “real-time” transmission of high-definition photos and videos.
Perceived potential for value creation from cloud computing: a study of the Australian regional government sector
Published in Behaviour & Information Technology, 2018
Omar Ali, Jeffrey Soar, Anup Shrestha
In technological context, the research also found that latency issues that were not discussed in the original research model were highlighted as a key challenge. Latency challenges relate to the network connection speed which is a crucial factor for the adoption of cloud computing. Having a fast and reliable network connection also translates to higher costs to acquire such connections. This research found that latency is one of the most significant challenges for regional Governments to adopt cloud computing, unlike other studies that prioritise security concerns as the most challenging factor (Buyya, Yeo, and Venugopala 2008; Catteddu and Hogben 2009).
Integrated application model for visual detection of welding quality based on visual neuron under edge-end collaboration
Published in International Journal of Computer Integrated Manufacturing, 2023
Liangrui Zhang, Xi Zhang, Jing Hu, Mingzhou Liu, Lin Ling
Therefore, the huge visual technology demand for quality detection in the welding process, especially in the face of the complexity of the vehicle welding process, must consider the integration of visual applications to achieve efficient and economic application deployment. In Industry 4.0, the three major integration and collaboration issues (Wang et al. 2016) have been a hot research topic in the field of smart manufacturing. Edge computing (EC) in smart manufacturing systems provides a theoretical basis for machine-vision integration applications. The flow of intelligence and computation close to the end devices is known as edge computing by the research community. Smart edge devices can pre-process, aggregate, and analyze sensory data closer to the data-generating sources (Nain, Pattanaik, and Sharma 2022). It is envisioned to address the issue of higher latency in delay-sensitive tasks and applications that are inadequately handled within the cloud platform (Premsankar, Di Francesco, and Taleb 2018). It is important to apply edge computing to process high real-time tasks and cloud computing to undertake high computing-needs tasks such that the edge and cloud fully utilize their computing resources (Shi et al. 2016). Consequently, a collaborative cloud-edge computing architecture is used for target defect detection to achieve model inference at the edge (Zhao et al. 2020; Shunjie et al. 2021). A cloud-edge collaborative DNN inference architecture, AppealNet, has been proposed to optimize the trade-off between accuracy and computational communication costs for cloud-edge collaborative architectures (Min et al. 2021). Adopting a 5 G deployment approach, EdgePlus, an industrial intelligence edge computing system, has been proposed to achieve data collection, analysis, and processing for industrial intelligence manufacturing (Ding et al. 2021).
Addressing some of bill of lading issues using the Internet of Things and blockchain technologies: a digitalized conceptual framework
Published in Maritime Policy & Management, 2023
Elnaz Irannezhad, Hamed Faroqi
Performance of the architecture can be identified with three measures of throughput, latency, and security level. Throughput is defined as the number of requests that can be processed within a time period and depends on the type of platform and block configuration. Latency is defined as the speed that the system responds to a request that could be read or write request.