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User-centric Composable Services: A New Generation of Personal Data Analytics [article]

Jianxin Zhao, Richard Mortier, Jon Crowcroft, Liang Wang
2017 arXiv   pre-print
Many existing research and product begin to move computation towards edge devices.  ...  Machine Learning (ML) techniques, such as Neural Network, are widely used in today's applications. However, there is still a big gap between the current ML systems and users' requirements.  ...  One crucial aspect of existing solutions is to move ML computation towards local devices.  ... 
arXiv:1710.09027v3 fatcat:ygkafsajpvc77j4vbltdxpqq4q

Introducing a New Scalable Data-as-a-Service Cloud Platform for Enriching Traditional Text Mining Techniques by Integrating Ontology Modelling and Natural Language Processing [chapter]

Alexey Cheptsov, Axel Tenschert, Paul Schmidt, Birte Glimm, Mauricio Matthesius, Thorsten Liebig
2014 Lecture Notes in Computer Science  
The technique is inherently designed with parallelism in mind, which allows for high performance on large-scale Cloud computing infrastructures.  ...  User-centric software The use of the cloud platform by the users is facilitated by user-centric software, which includes interfaces to submit and control experiments, analyse results, etc.  ...  Following subsections discuss some distinctive features of the suggested data-centric cloud architecture design with regard to the analysis platform, infrastructure, and user-centric services.  ... 
doi:10.1007/978-3-642-54370-8_6 fatcat:qoxc6xntnbczlp247iak3fb7dm

MEDAL: An AI-driven Data Fabric Concept for Elastic Cloud-to-Edge Intelligence [article]

Vasileios Theodorou, Ilias Gerostathopoulos, Iyad Alshabani, Alberto Abello, David Breitgand
2021 arXiv   pre-print
Current Cloud solutions for Edge Computing are inefficient for data-centric applications, as they focus on the IaaS/PaaS level and they miss the data modeling and operations perspective.  ...  We describe the MEDAL Platform as a usable tool for Data Scientists and Engineers, encompassing our concept and we illustrate its application though a connected cars use case.  ...  the data application layer, formed by the federation of semantically enabled, cloud-native data-centric constructs acting as building blocks • Offering a platform for AI-driven Cloud-to-Edge DataOps that  ... 
arXiv:2102.13125v1 fatcat:m5dzoeutjrh65ftymi5fkxreae

How could 6G Transform Engineering Platforms Towards Ecosystemic Business Models?

Seppo Yrjola, Marja Matinmikko-Blue, Petri Ahokangas
2020 2020 2nd 6G Wireless Summit (6G SUMMIT)  
The research extends the product platform and service modularity concepts beyond connectivity innovations towards multisided transactional ecosystem platforms.  ...  This development will change the traditional business models and ecosystem roles, as well as open the market for new stakeholders like micro-operators, cloud operators and resource brokers.  ...  based towards novel transaction platform based ecosystemic model in 6G?  ... 
doi:10.1109/6gsummit49458.2020.9083737 dblp:conf/6gsummit/YrjolaMA20 fatcat:5mlmsn7jkzh7jkspycddyjpl34

STRATUS: Towards Returning Data Control to Cloud Users [chapter]

Ryan K. L. Ko, Giovanni Russello, Richard Nelson, Shaoning Pang, Aloysius Cheang, Gill Dobbie, Abdolhossein Sarrafzadeh, Sivadon Chaisiri, Muhammad Rizwan Asghar, Geoffrey Holmes
2015 Lecture Notes in Computer Science  
Services in the Cloud) research project.  ...  Exposing the data at some point in the cloud to a few privileged users is undoubtedly a vendorcentric approach, and hinges on the trust relationships data owners have with their cloud service providers  ...  Acknowledgements This research is supported by STRATUS (Security Technologies Returning Accountability, Trust and User-Centric Services in the Cloud) (https://stratus.org.nz), a science investment project  ... 
doi:10.1007/978-3-319-27161-3_6 fatcat:mberng3n2zhslmosqcqf3nraau

A Survey on Information-Centric Networking with Cloud Internet of Things and Artificial Intelligence

Farhan Ahmed Karim, Azana Hafizah Mohd Aman, Rosilah Hassan, Kashif Nisar, A.H. Alamoodi
2022 Wireless Communications and Mobile Computing  
We then present the most recent research on ICN-CIoT-AI and provide a comprehensive analysis of this domain in terms of technology, AI/ML domain, IoT, and cloud technology.  ...  An information-centric network (ICN) uses this idea and makes data, instead of host addresses, an integral component.  ...  Processing (NLP) and ML 2021 [25] Yes Cloud ML 2021 [29] Yes Cloud Neural network/ML 2021 [22] Yes Cloud/edge ML Table 2 : 2 Detailed AI/ML technique analysis.  ... 
doi:10.1155/2022/7818712 fatcat:yhxonbgcezbnjmfjufz6g64oiq

What can Data-Centric AI Learn from Data and ML Engineering? [article]

Neoklis Polyzotis, Matei Zaharia
2021 arXiv   pre-print
In this paper, we discuss several lessons from data and ML engineering that could be interesting to apply in data-centric AI, based on our experience building data and ML platforms that serve thousands  ...  Data-centric AI is a new and exciting research topic in the AI community, but many organizations already build and maintain various "data-centric" applications whose goal is to produce high quality data  ...  “Towards ML Engineering: A Brief History Of TensorFlow Extended (TFX)”. In: CoRR abs/2010.02013 (2020). arXiv: 2010 . 02013.  ... 
arXiv:2112.06439v1 fatcat:jsgkbhobsfennkubpmcjksdi6m

Technology Antecedents of the Platform-Based Ecosystemic Business Models beyond 5G

Seppo Yrjola
2020 2020 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)  
network-ofservices model builds on platform with data and algorithms.  ...  on the topic in the recent literature and the results of the future-oriented workshop held in 6G Summit 2019, study showed that the transformation from current network-for-connectivity business models towards  ...  Furthermore, in addition to telco centric and device-centric model aggregator and service centric model were envisioned [73] - [75] .  ... 
doi:10.1109/wcncw48565.2020.9124823 dblp:conf/wcnc/Yrjola20 fatcat:vjgyl7kfurei5m4racleefprmy

Table of Contents

2021 2021 IEEE 46th Conference on Local Computer Networks (LCN)  
for Special Education 573 DRo: A Data-Scarce Mechanism to Revolutionize the Performance of DL-Based Security Systems 581 CLEDGE: A Hybrid Cloud-Edge Computing Framework over Information Centric Networking  ...  Infrastructures 495 On the Analysis of Adaptive-Rate Applications in Data-Centric Wireless Ad-Hoc Networks 503 Hop-By-Hop: Advancing Cooperative Congestion Control for Cyber-Physical Systems 511 Toward  ... 
doi:10.1109/lcn52139.2021.9524933 fatcat:bopsc4l2qrc7bobzfyb6343iou

Big Data and Fog Computing [chapter]

Yogesh Simmhan
2018 Encyclopedia of Big Data Technologies  
Fog computing serves as a computing layer that sits between the edge devices and the cloud in the network topology.  ...  They have more compute capacity than the edge but much less so than cloud data centers. They typically have high uptime and always-on Internet connectivity.  ...  Clouds also offer these platforms as a service.  ... 
doi:10.1007/978-3-319-63962-8_41-1 fatcat:zs7bkyqsbnd2bgqzbo36ozoi24

Towards a Quality-centric Big Data Architecture for Federated Sensor Services

Lakshmish Ramaswamy, Victor Lawson, Siva Venkat Gogineni
2013 2013 IEEE International Congress on Big Data  
The paper explores the advantages and limitations of current big data technologies in building various components of the platform. We also outline our initial ideas towards addressing the limitations.  ...  In this paper, we present our vision for data quality (DQ)centric big data infrastructure for federated sensor service clouds. We first motivate our work by providing real-world examples.  ...  None, to the best of our knowledge, has comprehensively investigated mechanisms to apply data quality toward clouds for sensor service platforms.  ... 
doi:10.1109/bigdata.congress.2013.21 dblp:conf/bigdata/RamaswamyLG13 fatcat:vhuqmdxpd5eejpi7umtwjwpgzu

A MOBILE EDGE COMPUTING SERVICES WITH QoS SUPPORT MODEL FOR NEXT GENERATION MOBILE NETWORKS

Tomislav Šuminoski, Bojana Veličkovska, Toni Janevski
2022 Journal of Electrical Engineering and Information Technologies  
The purpose of the ML algorithm is to understand the traffic activity and determine how the traffic schedule should be made.  ...  Also, the improved advanced QoS model including Machine Learning (ML) algorithm within for next generation of mobile networks and services are proposed.  ...  Recent years there is an increased interest in transferring computing from Clouds towards the network edges or Mobile Edge Computing (MEC).  ... 
doi:10.51466/jeeit2271188023sh fatcat:4vdo26dncndifbfnl6yyruqai4

Platforms for Smart Environments and Future Internet Design: A Survey

Antonio M. Alberti, Mateus A. S. Santos, Ricardo Souza, Hirley Dayan L. Silva, Jorge R. Carneiro, Vitor C. Figueiredo, Joel J. P. C. Rodrigues
2019 IEEE Access  
INDEX TERMS Internet of Things, middleware, platform virtualization, wireless sensor networks, clouds, information-centric networking.  ...  This paper provides a review of platforms, middleware, and frameworks that can help in this big challenge, discussing their architectures, service life-cycling, digital twins, cloud-based operation, virtualization  ...  This approach also offers to end-users the possibility of creating their own cloud services once the platform is user-centric. 1) ARCHITECTURE AND CLOUD COMPUTING ClouT is based on three main layers:  ... 
doi:10.1109/access.2019.2950656 fatcat:kxspcj4rjjaulctzqtankmlpjq

Data lifecycle and technology-based opportunities in new Product Service System offering towards a multidimensional framework

Michela Zambetti, Roberto Pinto, Giuditta Pezzotta
2019 Procedia CIRP  
In today's business environment, the trend towards more product variety and customization is unbroken.  ...  An enormous amount of data is generated from connected products and gathered from sensors; data is sent to the cloud via wireless networks and stored, and the possibility to distribute new cloud-based  ...  [4] Cloud platform can provide an excellent environment for large-scale data analysis processing.  ... 
doi:10.1016/j.procir.2019.02.135 fatcat:talfaaot3ja4zcqcq2spopjt54

ACE: Towards Application-Centric Edge-Cloud Collaborative Intelligence [article]

Luhui Wang, Cong Zhao, Shusen Yang, Xinyu Yang, Julie McCann
2022 arXiv   pre-print
In this article, we systematically design and construct the first unified platform, ACE, that handles ever-increasing edge and cloud resources, user-transparent services, and proliferating intelligence  ...  Yet current implementations running in the Cloud are unable to satisfy all these constraints.  ...  APPLICATION-CENTRIC ECCI PLATFORM Driven by all principles above, the explicit design of our Application-Centric ECCI (ACE) platform is as follows.  ... 
arXiv:2203.13061v1 fatcat:qg7oiikfwnd6zfvkawjhih7cem
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