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Application caching for cloud-sensor systems

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Application caching for cloud-sensor systems. / Xu, Y.; Helal, Sumi.

MSWiM '14 Proceedings of the 17th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems. New York : ACM, 2014. p. 303-306.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Xu, Y & Helal, S 2014, Application caching for cloud-sensor systems. in MSWiM '14 Proceedings of the 17th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems. ACM, New York, pp. 303-306. https://doi.org/10.1145/2641798.2641814

APA

Xu, Y., & Helal, S. (2014). Application caching for cloud-sensor systems. In MSWiM '14 Proceedings of the 17th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems (pp. 303-306). ACM. https://doi.org/10.1145/2641798.2641814

Vancouver

Xu Y, Helal S. Application caching for cloud-sensor systems. In MSWiM '14 Proceedings of the 17th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems. New York: ACM. 2014. p. 303-306 doi: 10.1145/2641798.2641814

Author

Xu, Y. ; Helal, Sumi. / Application caching for cloud-sensor systems. MSWiM '14 Proceedings of the 17th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems. New York : ACM, 2014. pp. 303-306

Bibtex

@inproceedings{e307fc5db2a9403293c31a12f45af9ae,
title = "Application caching for cloud-sensor systems",
abstract = "Driven by critical and pressing smart city applications, accessing massive numbers of sensors by cloud-hosted services is becoming an emerging and inevitable situation. Na{\"i}vely connecting massive numbers of sensors to the cloud raises major scalability and energy challenges. An architecture embodying distributed optimization is needed to manage the scale and to allow limited energy sensors to last longer in such a dynamic and high-velocity big data system. We developed a multi-tier architecture which we call Cloud, Edge and Beneath (CEB). Based on CEB, we propose an Application Fragment Caching Algorithm (AFCA) which selectively caches application fragments from the cloud to lower layers of CEB to improve cloud scalability. Through experiments, we show and measure the effect of AFCA on cloud scalability. Copyright 2014 ACM.",
keywords = "Application caching, Cloud computing, Cloud-sensor systems, Big data, Information management, Scalability, Application-caching, Data systems, Distributed optimization, Fragment caching, High velocity, Limited energies, Multi tier architecture, Sensor systems, Distributed computer systems",
author = "Y. Xu and Sumi Helal",
year = "2014",
doi = "10.1145/2641798.2641814",
language = "English",
isbn = "9781450330305",
pages = "303--306",
booktitle = "MSWiM '14 Proceedings of the 17th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems",
publisher = "ACM",

}

RIS

TY - GEN

T1 - Application caching for cloud-sensor systems

AU - Xu, Y.

AU - Helal, Sumi

PY - 2014

Y1 - 2014

N2 - Driven by critical and pressing smart city applications, accessing massive numbers of sensors by cloud-hosted services is becoming an emerging and inevitable situation. Naïvely connecting massive numbers of sensors to the cloud raises major scalability and energy challenges. An architecture embodying distributed optimization is needed to manage the scale and to allow limited energy sensors to last longer in such a dynamic and high-velocity big data system. We developed a multi-tier architecture which we call Cloud, Edge and Beneath (CEB). Based on CEB, we propose an Application Fragment Caching Algorithm (AFCA) which selectively caches application fragments from the cloud to lower layers of CEB to improve cloud scalability. Through experiments, we show and measure the effect of AFCA on cloud scalability. Copyright 2014 ACM.

AB - Driven by critical and pressing smart city applications, accessing massive numbers of sensors by cloud-hosted services is becoming an emerging and inevitable situation. Naïvely connecting massive numbers of sensors to the cloud raises major scalability and energy challenges. An architecture embodying distributed optimization is needed to manage the scale and to allow limited energy sensors to last longer in such a dynamic and high-velocity big data system. We developed a multi-tier architecture which we call Cloud, Edge and Beneath (CEB). Based on CEB, we propose an Application Fragment Caching Algorithm (AFCA) which selectively caches application fragments from the cloud to lower layers of CEB to improve cloud scalability. Through experiments, we show and measure the effect of AFCA on cloud scalability. Copyright 2014 ACM.

KW - Application caching

KW - Cloud computing

KW - Cloud-sensor systems

KW - Big data

KW - Information management

KW - Scalability

KW - Application-caching

KW - Data systems

KW - Distributed optimization

KW - Fragment caching

KW - High velocity

KW - Limited energies

KW - Multi tier architecture

KW - Sensor systems

KW - Distributed computer systems

U2 - 10.1145/2641798.2641814

DO - 10.1145/2641798.2641814

M3 - Conference contribution/Paper

SN - 9781450330305

SP - 303

EP - 306

BT - MSWiM '14 Proceedings of the 17th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems

PB - ACM

CY - New York

ER -