Edge Cloud

2019 ◽  
pp. 107-131
Author(s):  
Lucia Agnes Beena Thomas
Keyword(s):  
Cloud Computing ◽  
Virtual Reality ◽  
Cost Saving ◽  
New Technologies ◽  
Smart Cities ◽  
Low Latency ◽  
Battery Life ◽  
Real Time Processing ◽  
Time Processing ◽  
Autonomous Cars

With the proliferation of new technologies such as augmented and virtual reality, autonomous cars, 5G networks, drones, and IOT with smart cities, consumers of cloud computing are becoming the producers of data. Large volume of data is being produced at the edge of the network. This scenario insists the need for efficient real-time processing and communication at the network edge. Cloud capabilities must be distributed across the network to form an edge cloud, which places computing resources where the traffic is at the edge of the network. Edge cloud along with 5G services could also glint the next generation of robotic manufacturing. The anticipated low latency requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy are also inscribed by edge cloud. A number of giants like Nokia, AT&T, and Microsoft have emerged in the market to support edge cloud. This chapter wraps the features of edge cloud, the driving industries that are providing solutions, the use cases, benefits, and the challenges of edge cloud.

scholarly journals Integration and Exploitation of Sensor Data in Smart Cities through Event-Driven Applications

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1372 ◽  
Author(s):  
Manuel Garcia Alvarez ◽  
Javier Morales ◽  
Menno-Jan Kraak
Keyword(s):  
Real Time ◽  
Spatial Data ◽  
Spatial Information ◽  
Smart Cities ◽  
Spatial Data Analysis ◽  
Sensor Data ◽  
Reference Architecture ◽  
Real Time Processing ◽  
Time Processing ◽  
Event Driven

Smart cities are urban environments where Internet of Things (IoT) devices provide a continuous source of data about urban phenomena such as traffic and air pollution. The exploitation of the spatial properties of data enables situation and context awareness. However, the integration and analysis of data from IoT sensing devices remain a crucial challenge for the development of IoT applications in smart cities. Existing approaches provide no or limited ability to perform spatial data analysis, even when spatial information plays a significant role in decision making across many disciplines. This work proposes a generic approach to enabling spatiotemporal capabilities in information services for smart cities. We adopted a multidisciplinary approach to achieving data integration and real-time processing, and developed a reference architecture for the development of event-driven applications. This type of applications seamlessly integrates IoT sensing devices, complex event processing, and spatiotemporal analytics through a processing workflow for the detection of geographic events. Through the implementation and testing of a system prototype, built upon an existing sensor network, we demonstrated the feasibility, performance, and scalability of event-driven applications to achieve real-time processing capabilities and detect geographic events.

New Perspectives of Pattern Recognition for Automatic Credit Card Fraud Detection

2018 ◽  
pp. 4937-4950 ◽  
Author(s):  
Addisson Salazar ◽  
Gonzalo Safont ◽  
Alberto Rodriguez ◽  
Luis Vergara
Keyword(s):  
Pattern Recognition ◽  
False Alarm ◽  
Credit Card ◽  
New Technologies ◽  
Fraud Detection ◽  
Surrogate Data ◽  
Decision Fusion ◽  
Credit Card Fraud ◽  
Real Time Processing ◽  
Time Processing

Automatic credit card fraud detection (ACCFD) is a challenge issue that has been increasingly studied considering expanded potential of new technologies to emulate legitimate operations. Solution has to handle with fraud behavior changing in time; detection in data with very small fraud/legitimate operations ratio; and accomplish operation requirements of very low false alarm in real-time processing. In this chapter, main issues related with the problem of ACCFD and proposed solutions are discussed from theoretical and practical standpoints. The perspective of detection analyses from receiving operating characteristic curves and business key performance indicators are jointly analyzed. A new conceptual framework for ACCFD considering decision fusion and surrogate data is outlined including a case of study with different proportions of real and surrogate data. In addition, the sensitivity of the methods to different proportions of fraud/legitimate ratios is tested. Finally, theoretical and practical conclusions are provided as well as several open lines of research are proposed.

New Perspectives of Pattern Recognition for Automatic Credit Card Fraud Detection

2019 ◽  
pp. 268-283
Author(s):  
Addisson Salazar ◽  
Gonzalo Safont ◽  
Alberto Rodriguez ◽  
Luis Vergara
Keyword(s):  
Pattern Recognition ◽  
Credit Card ◽  
New Technologies ◽  
Fraud Detection ◽  
Surrogate Data ◽  
Decision Fusion ◽  
Credit Card Fraud ◽  
Real Time Processing ◽  
Time Processing ◽  
Behavior Detection

Automatic credit card fraud detection (ACCFD) is a challenge issue that has been increasingly studied considering the expanded potential of new technologies to emulate legitimate operations. Solution has to handle changing fraud behavior, detection in data with very small fraud/legitimate operations ratio, and accomplish operation requirements of very low false alarm in real-time processing. In this chapter, main issues related with the problem of ACCFD and proposed solutions are discussed from theoretical and practical standpoints. The perspective of detection analyses from receiving operating characteristic curves and business key performance indicators are jointly analyzed. A new conceptual framework for ACCFD considering decision fusion and surrogate data is outlined including a case of study with different proportions of real and surrogate data. In addition, the sensitivity of the methods to different proportions of fraud/legitimate ratios is tested. Finally, theoretical and practical conclusions are provided, and several open lines of research are proposed.

scholarly journals A Multidomain Standards-Based Fog Computing Architecture for Smart Cities

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Víctor Rampérez ◽  
Javier Soriano ◽  
David Lizcano
Keyword(s):  
Cloud Computing ◽  
Smart Cities ◽  
Fog Computing ◽  
Cost Savings ◽  
Low Latency ◽  
Location Awareness ◽  
Rapid Urbanization ◽  
Computing Architecture ◽  
Computing Paradigm ◽  
Urban Population Growth

Many of the problems arising from rapid urbanization and urban population growth can be solved by making cities “smart”. These smart cities are supported by large networks of interconnected and widely geo-distributed devices, known as Internet of Things or IoT, that generate large volumes of data. Traditionally, cloud computing has been the technology used to support this infrastructure; however, some of the essential requirements of smart cities such as low-latency, mobility support, location-awareness, bandwidth cost savings, and geo-distributed nature of such IoT systems cannot be met. To solve these problems, the fog computing paradigm proposes extending cloud computing models to the edge of the network. However, most of the proposed architectures and frameworks are based on their own private data models and interfaces, which severely reduce the openness and interoperability of these solutions. To address this problem, we propose a standard-based fog computing architecture to enable it to be an open and interoperable solution. The proposed architecture moves the stream processing tasks to the edge of the network through the use of lightweight context brokers and Complex Event Processing (CEP) to reduce latency. Moreover, to communicate the different smart cities domains we propose a Context Broker based on a publish/subscribe middleware specially designed to be elastic and low-latency and exploit the context information of these environments. Additionally, we validate our architecture through a real smart city use case, showing how the proposed architecture can successfully meet the smart cities requirements by taking advantage of the fog computing approach. Finally, we also analyze the performance of the proposed Context Broker based on microbenchmarking results for latency, throughput, and scalability.

Post Pandemic World and Challenges for E-Governance Framework

2021 ◽  
Vol 10 (3) ◽  
pp. 2630-2636
Keyword(s):  
Cloud Computing ◽  
Smart Cities ◽  
Rapid Development ◽  
Smart Devices ◽  
Economic Modelling ◽  
Intelligent Robots ◽  
Autonomous Cars ◽  
Autonomous Machines ◽  
Almost All ◽  
Digital Or

Emergence of cloud computing and rapid development of automation in terms of Internet of Things (IoT), it was evident in the wake of 2019 that world is gradually moving towards a complete digital system from individual to business and ultimately government level. Technology advancements start expanding from smart devices to smart cities, autonomous machines to autonomous cars and expert systems to intelligent robots. These advancements are supported by the swiftly growing communication and networking domain where 5G is introducing new range of expansion and more freedom to creativity and novelty. This new regime of advanced technologies has made the foundation on live digital or internet based structures that transformed into cloud computing with swiftly growing facilities and innovative competitors. Cloud computing penetrates in almost all digital domains from individuals to corporates and to governments as well due to its versatile services, economic modelling and ease of accessibility.

An Efficient Implementation of Low-Latency Two-Dimensional Gaussian Smoothing Filter using Approximate Carry-Save Adder

2020 ◽  
pp. 2150021
Author(s):  
Hadise Ramezani ◽  
Majid Mohammadi ◽  
Amir Sabbagh Molahoseini
Keyword(s):  
Real Time ◽  
Filter Design ◽  
Low Latency ◽  
Gaussian Filter ◽  
Two Dimensional ◽  
Gaussian Smoothing ◽  
Real Time Processing ◽  
Time Processing ◽  
Smoothing Filter ◽  
Gaussian Filters

The two-dimensional Gaussian smoothing filter (2D-GSF) is one of the most useful techniques in image processing. Since the 2D-GSF requires high computational resources, its efficient design and implementation are critical in real-time processing purposes. Approximate computing is a new method that can be used to increase the performance of 2D Gaussian filter design with low computing overhead on field-programmable gate arrays (FPGAs). This study aims to provide a low-latency Gaussian filter architecture on FPGA such that it can be used in real-time processing applications. In this regard, accurate and approximate carry-save adders (CSAs) have been used in adder tree-based Gaussian filters. In our proposed method, we use two approximation steps: in the first step, we use an approximation structure named Speed–Power–Area–Accuracy for Gaussian filter design and in the second stage, we use approximate CSAs to convert adder-tree structures that are used in Gaussian filter, and as a result, we have significantly reduced the delay. The results of simulation and implementation show that the latency has reduced in a 3[Formula: see text] 3 2D-GSF architecture up to 22% using proposed accurate CSAs and 45% using proposed approximate CSAs, compared to existing Gaussian filters with an adder tree structure.

scholarly journals Extended VEOT Framework – Implemented in a Smart Boutique

2019 ◽  
Vol 8 (9S3) ◽  
pp. 762-767
Keyword(s):  
Cloud Computing ◽  
Virtual Reality ◽  
Augmented Reality ◽  
Virtual Environment ◽  
Real World ◽  
New Technologies ◽  
Smart Homes ◽  
Touch Screen ◽  
Edge Computing ◽  
Base Paper

With advent of new technologies in communication and security in IoT and advantages of Cloud computing, have multiplied, the opportunities in Smart homes, Offices and Equipments. Augmented Reality (AR) adds another dimension to the experience. The proposed system makes use of all these concepts including Edge computing to design a Smart Boutique. A boutique is a unique store that sells stylish, luxury and fashion clothing, jewelry, or other exquisite goods. Considering the richness to be experienced by the Customers, the usage of these techniques would amply complement their senses. VEoT or Virtual Environment of Things is a framework for combining all these technologies to mix both real world objects and Virtual Reality. It is very important to cater to the needs of customer in a unique way, giving personal touch to the business. This would create repeat orders and would attract more customer footfalls. The base paper gives a concrete architecture for combining IoT and AR with the help of Edge server. We have tried to make the system robust, including a kiosk touch screen to enable the customer to have more information on Boutique and its articles. The goal of the system is to produce renewed customer experience and create a Smart Boutique with technology.

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