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An optimization framework for cloud-sensor systems: 2014 6th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2014

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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An optimization framework for cloud-sensor systems: 2014 6th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2014. / Xu, Y.; Helal, Sumi.
Cloud Computing Technology and Science (CloudCom), 2014 IEEE 6th International Conference on. IEEE, 2015. p. 38-45.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Xu, Y & Helal, S 2015, An optimization framework for cloud-sensor systems: 2014 6th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2014. in Cloud Computing Technology and Science (CloudCom), 2014 IEEE 6th International Conference on. IEEE, pp. 38-45. https://doi.org/10.1109/CloudCom.2014.52

APA

Xu, Y., & Helal, S. (2015). An optimization framework for cloud-sensor systems: 2014 6th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2014. In Cloud Computing Technology and Science (CloudCom), 2014 IEEE 6th International Conference on (pp. 38-45). IEEE. https://doi.org/10.1109/CloudCom.2014.52

Vancouver

Xu Y, Helal S. An optimization framework for cloud-sensor systems: 2014 6th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2014. In Cloud Computing Technology and Science (CloudCom), 2014 IEEE 6th International Conference on. IEEE. 2015. p. 38-45 doi: 10.1109/CloudCom.2014.52

Author

Xu, Y. ; Helal, Sumi. / An optimization framework for cloud-sensor systems : 2014 6th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2014. Cloud Computing Technology and Science (CloudCom), 2014 IEEE 6th International Conference on. IEEE, 2015. pp. 38-45

Bibtex

@inproceedings{a9bc6ca79cd74cf5bd1dad2ca9607af2,
title = "An optimization framework for cloud-sensor systems: 2014 6th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2014",
abstract = "Imminent massive-scale IoT deployments require a Cloud-Sensor architecture to facilitate an ecosystem of friction-free integration and programmability. In addition to these two functional requirements, challenging performance and scalability requirements must be addressed by any such architecture. We have introduced the Cloud-Edge-Beneath (CEB) architecture which addresses scalability and performance through a built-in distributed optimization framework. In this paper, we focus on CEB's optimization framework which follows a bi-directional waterfall model in which not only sensor data can move upward to applications, but applications (fragments) can move downward to lower layers of CEB closer to data sources. The framework enables many optimization ideas and opportunities, including our own. We present the bi-directional waterfall framework along with a sketch of several of our optimization algorithms enabled by the framework. We also present an example of an experimental study to determine dominant resources in the cloud - a variable which as will be seen greatly affects the logic of some of the optimization algorithms. {\textcopyright} 2014 IEEE.",
keywords = "Application caching, Cloud computing, Cloud-sensor systems, Optimization, Performance, Scalability, Algorithms, Computation theory, Computer architecture, Application-caching, Distributed optimization, Functional requirement, Optimization algorithms, Performance and scalabilities, Scalability and performance, Sensor systems, Distributed computer systems",
author = "Y. Xu and Sumi Helal",
year = "2015",
doi = "10.1109/CloudCom.2014.52",
language = "English",
pages = "38--45",
booktitle = "Cloud Computing Technology and Science (CloudCom), 2014 IEEE 6th International Conference on",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - An optimization framework for cloud-sensor systems

T2 - 2014 6th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2014

AU - Xu, Y.

AU - Helal, Sumi

PY - 2015

Y1 - 2015

N2 - Imminent massive-scale IoT deployments require a Cloud-Sensor architecture to facilitate an ecosystem of friction-free integration and programmability. In addition to these two functional requirements, challenging performance and scalability requirements must be addressed by any such architecture. We have introduced the Cloud-Edge-Beneath (CEB) architecture which addresses scalability and performance through a built-in distributed optimization framework. In this paper, we focus on CEB's optimization framework which follows a bi-directional waterfall model in which not only sensor data can move upward to applications, but applications (fragments) can move downward to lower layers of CEB closer to data sources. The framework enables many optimization ideas and opportunities, including our own. We present the bi-directional waterfall framework along with a sketch of several of our optimization algorithms enabled by the framework. We also present an example of an experimental study to determine dominant resources in the cloud - a variable which as will be seen greatly affects the logic of some of the optimization algorithms. © 2014 IEEE.

AB - Imminent massive-scale IoT deployments require a Cloud-Sensor architecture to facilitate an ecosystem of friction-free integration and programmability. In addition to these two functional requirements, challenging performance and scalability requirements must be addressed by any such architecture. We have introduced the Cloud-Edge-Beneath (CEB) architecture which addresses scalability and performance through a built-in distributed optimization framework. In this paper, we focus on CEB's optimization framework which follows a bi-directional waterfall model in which not only sensor data can move upward to applications, but applications (fragments) can move downward to lower layers of CEB closer to data sources. The framework enables many optimization ideas and opportunities, including our own. We present the bi-directional waterfall framework along with a sketch of several of our optimization algorithms enabled by the framework. We also present an example of an experimental study to determine dominant resources in the cloud - a variable which as will be seen greatly affects the logic of some of the optimization algorithms. © 2014 IEEE.

KW - Application caching

KW - Cloud computing

KW - Cloud-sensor systems

KW - Optimization

KW - Performance

KW - Scalability

KW - Algorithms

KW - Computation theory

KW - Computer architecture

KW - Application-caching

KW - Distributed optimization

KW - Functional requirement

KW - Optimization algorithms

KW - Performance and scalabilities

KW - Scalability and performance

KW - Sensor systems

KW - Distributed computer systems

U2 - 10.1109/CloudCom.2014.52

DO - 10.1109/CloudCom.2014.52

M3 - Conference contribution/Paper

SP - 38

EP - 45

BT - Cloud Computing Technology and Science (CloudCom), 2014 IEEE 6th International Conference on

PB - IEEE

ER -