Proceedings ArticleDOI
Supporting Internet-of-Things Analytics in a Fog Computing Platform
Hua-Jun Hong,Pei-Hsuan Tsai,An-Chieh Cheng,Yusuf Sarwar Uddin,Nalini Venkatasubramanian,Cheng-Hsin Hsu +5 more
- pp 138-145
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TLDR
A fog computing platform that runs analytics in a distributed way on multiple devices, including IoT devices, edge servers, and data-center servers, is designed and implemented and 100% of the deployed IoT analytics satisfy the QoS targets.Abstract:
Modern IoT analytics are computational and data intensive. Existing analytics are mostly hosted in cloud data centers, and may suffer from high latency, network congestion, and privacy issues. In this paper, we design, implement, and evaluate a fog computing platform that runs analytics in a distributed way on multiple devices, including IoT devices, edge servers, and data-center servers. We focus on the core optimization problem: making deployment decisions to maximize the number of satisfied IoT analytics. We carefully formulate the deployment problem and design an efficient algorithm, named SSE, to solve it. Moreover, we conduct a detailed measurement study to derive system models of the IoT analytics based on diverse QoS levels and heterogeneous devices to facilitate the optimal deployment decisions. We implement a testbed to conduct experiments, which show that the system models achieve reasonably good accuracy. More importantly, 100% of the deployed IoT analytics satisfy the QoS targets. We also conduct extensive simulations for larger-scale scenarios. The simulation results reveal that our SSE algorithm outperforms a state-of-the-art algorithm by up to 89.4% and 168.3% in terms of the number of satisfied IoT analytics and active devices. In addition, our SSE algorithm reduces CPU, RAM, and network resource consumptions by 18.4%, 12.7%, and 898.3%, respectively, and terminates in polynomial time.read more
Citations
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Journal ArticleDOI
All one needs to know about fog computing and related edge computing paradigms: A complete survey
Ashkan Yousefpour,Caleb Fung,Tam T. Nguyen,Krishna P. Kadiyala,Fatemeh Jalali,Amirreza Niakanlahiji,Jian Kong,Jason P. Jue +7 more
TL;DR: This paper provides a tutorial on fog computing and its related computing paradigms, including their similarities and differences, and provides a taxonomy of research topics in fog computing.
Journal ArticleDOI
All One Needs to Know about Fog Computing and Related Edge Computing Paradigms: A Complete Survey
Ashkan Yousefpour,Caleb Fung,Tam T. Nguyen,Krishna P. Kadiyala,Fatemeh Jalali,Amirreza Niakanlahiji,Jian Kong,Jason P. Jue +7 more
TL;DR: In this paper, the authors provide a tutorial on fog computing and its related computing paradigms, including their similarities and differences, and provide a taxonomy of research topics in fog computing.
Journal ArticleDOI
IoT big data analytics for smart homes with fog and cloud computing
TL;DR: A new platform that enables innovative analytics on IoT captured data from smart homes and the use of fog nodes and cloud system to allow data-driven services and address the challenges of complexities and resource demands for online and offline data processing, storage, and classification analysis is presented.
Journal ArticleDOI
An Overview of Service Placement Problem in Fog and Edge Computing
TL;DR: A survey of current research conducted on Service Placement Problem (SPP) in the Fog/Edge Computing is presented and a categorization of current proposals is given and identified issues and challenges are discussed.
Journal ArticleDOI
Internet of things (IoT); internet of everything (IoE); tactile internet; 5G – A (not so evanescent) unifying vision empowered by EH-MEMS (energy harvesting MEMS) and RF-MEMS (radio frequency MEMS)
TL;DR: The frame of reference depicted in this work outlines a relevant potential borne by EH-Mems and RF-MEMS solutions within the unified scenario of IoT, IoE, Tactile Internet and 5G, making the forecast of future relentless growth of MEMS-based devices, more plausible and likely to take place.
References
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Proceedings ArticleDOI
Fog computing and its role in the internet of things
TL;DR: This paper argues that the above characteristics make the Fog the appropriate platform for a number of critical Internet of Things services and applications, namely, Connected Vehicle, Smart Grid, Smart Cities, and, in general, Wireless Sensors and Actuators Networks (WSANs).
Proceedings ArticleDOI
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TL;DR: A model for processing large graphs that has been designed for efficient, scalable and fault-tolerant implementation on clusters of thousands of commodity computers, and its implied synchronicity makes reasoning about programs easier.
Book ChapterDOI
Fog Computing and Its Role in the Internet of Things
TL;DR: This chapter argues that the above characteristics make the Fog the appropriate platform for a number of critical internet of things services and applications, namely connected vehicle, smart grid, smart cities, and in general, wireless sensors and actuators networks (WSANs).
Proceedings ArticleDOI
GPS: a graph processing system
Semih Salihoglu,Jennifer Widom +1 more
TL;DR: This paper describes the implementation of GPS and its novel features, and presents experimental results on the performance effects of both static and dynamic graph partitioning schemes, and describes the compilation of a high-level domain-specific programming language to GPS, enabling easy expression of complex algorithms.
Proceedings ArticleDOI
Network-Aware Operator Placement for Stream-Processing Systems
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