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Toward sensor-cloud integration as a service: optimizing three-tier communication in cloud-integrated sensor networks

Authors:

Junichi Suzuki,

Katsuya ObaAuthors Info & Claims

BodyNets '13: Proceedings of the 8th International Conference on Body Area Networks

Pages 355 - 362

https://doi.org/10.4108/icst.bodynets.2013.253639

Published: 30 September 2013 Publication History

Abstract

This paper proposes a cloud-integrated sensor networking architecture, called Sensor-Cloud Integration Platform as a Service (SC-iPaaS), which hosts virtualized sensors in clouds and operates physical sensors through their virtual counterparts. SC-iPaaS performs push-pull hybrid communication between three layers: cloud, edge and sensor layers. This paper formulates an optimization problem for SC-iPaaS to seek the optimal data transmission rates for individual nodes and examines evolutionary optimization with respect to multiple conflicting objectives subject to given constraints. Simulation results show that multiobjective analysis is critical in configuring and operating three-tier push-pull hybrid communication in SC-iPaaS.

References

[1]

K. Aberer, M. Hauswirth, and A. Salehi. Infrastructure for data processing in large-scale interconnected sensor networks. In Proc. the 8th IEEE Int'l Conference on Mobile Data Management, 2007.

Digital Library

[2]

P. Boonma, Q. Han, and J. Suzuki. Leveraging biologically-inspired mobile agents supporting composite needs of reliability and timeliness in sensor applications. In Proc. IEEE Int'l Conf. on Frontiers in the Convergence of Biosci. and Info. Tech., 2007.

Digital Library

[3]

P. Boonma and J. Suzuki. Toward interoperable publish/subscribe communication between wireless sensor networks and access networks. In Proc. IEEE Int'l Workshop on Information Retrieval in Sensor Networks, 2009.

Digital Library

[4]

P. Boonma and J. Suzuki. TinyDDS: An interoperable and configurable publish/subscribe middleware for wireless sensor networks. In A. Hinze and A. Buchmann, editors, Principles and Apps. of Dist. Event-Based Systems, chapter 9. IGI Global, 2010.

[5]

A. Cuzzocrea, G. Fortino, and O. Rana. Managing data and processes in cloud-enabled large-scale sensor networks: State-of-the-art and future research directions.

[6]

K. Deb, S. Agrawal, A. Pratap, and T. Meyarivan. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In Proc. of Int'l Conference on Parallel Problem Solving from Nature, 2001.

Digital Library

[7]

G. Fortino, M. Pathan, and G. D. Fatta. BodyCloud: Integration of cloud computing and body sensor networks. In Proc. IEEE Int'l Conference on Cloud Computing Technology and Science, 2012.

Digital Library

[8]

M. Gaynor, M. Welsh, S. Moulton, A. Rowan, E. LaCombe, and J. Wynne. Integrating wireless sensor networks with the grid. IEEE Internet Computing, July/August 2004.

Digital Library

[9]

J. Goldman, N. Ramanathan, R. Ambrose, D. A. Caron, D. Estrin, J. C. Fisher, R. Gilbert, M. H. Hansen, T. C. Harmon, J. Jay, W. J. Kaiser, G. S. Sukhatme, and Y.-C. Tai. Distributed sensing systems for water quality assessment and management. Technical report, Woodrow Wilson Int'l Center for Scholars, 2007.

[10]

Y. Hao and R. Foster. Wireless body sensor networks for health-monitoring applications. Physiological Measurement, 29(11), 2008.

[11]

M. M. Hassan, B. Song, and E.-N. Huh. A framework of sensor-cloud integration opportunities and challenges. In Proc. the 3rd ACM Int'l Conference on Ubiquitous Info. Mgt. and Comm., 2009.

Digital Library

[12]

S. Kapadia and B. Krishnamachari. Comparative analysis of push-pull query strategies for wireless sensor networks. In Proc. International Conference on Distributed Computing in Sensor Systems, 2006.

Digital Library

[13]

W. C. Lee, M. Wu, J. Xu, and X. Tang. Monitoring top-k query in wireless sensor networks. In Proc. IEEE International Conference on Data Engineering, 2006.

Digital Library

[14]

M. Li, D. Ganesan, and P. Shenoy. PRESTO: Feedback-driven data management in sensor networks. In Proc. USENIX Symposium on Networked Systems Design and Implementation, 2006.

Digital Library

[15]

W. Liu, Y. Zhang, W. Lou, and Y. Fang. Managing wireless sensor networks with supply chain strategy. In Proc. Int'l Conference on Quality of Service in Heterogeneous Wired/Wireless Networks, 2004.

Digital Library

[16]

B. O'Flynn, F. Martinez-Catala, S. Harte, C. O'Mathuna, J. Cleary, C. Slater, F. Regan, D. Diamond, and H. Murphy. SmartCoast: A wireless sensor network for water quality monitoring. In Proc. IEEE Conference on Local Computer Networks, 2007.

Digital Library

[17]

S. Patel, H. Park, P. Bonato, L. Chan, and M. Rodgers. A review of wearable sensors and systems with application in rehabilitation. Journal of Neuroengineering and Rehabilitation, 9(21), 2012.

[18]

L. A. Seders, C. A. Shea, M. D. Lemmon, P. A. Maurice, and J. W. Talley. LakeNet: An integrated sensor network for environmental sensing in lakes. Environmental Engineering Science, 24(2), 2007.

[19]

J. Shneidman, P. Pietzuch, J. Ledlie, M. Roussopoulos, M. Seltzer, and M. Welsh. Hourglass: An infrastructure for connecting sensor networks and applications. Technical report, Harvard University, TR-21-04, 2004.

[20]

N. Srinivas and K. Deb. Multiobjective function optimization using nondominated sorting genetic algorithms. Evol. Computat., 2(3), 1995.

Digital Library

[21]

H. Wada, P. Boonma, and J. Suzuki. Chronus: A spatiotemporal macroprogramming language for autonomic wireless sensor networks. In N. Agoulmine, editor, Autonomic Network Mgt. Principles: From Concepts to Applications, chapter 8. Elsevier, 2010.

[22]

Y. Xu, S. Helal, M. Thai, and M. Scmalz. Optimizing push/pull envelopes for energy-efficient cloud-sensor systems. In Proc. the 14th ACM Int'l Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, 2011.

Digital Library

[23]

M. Yuriyama and T. Kushida. Sensor-cloud infrastructure - physical sensor management with virtualized sensors on cloud computing. In Proc. the 13th Int'l Conf. on Network-Based Info. Sys., 2010.

Digital Library

[24]

E. Zitzler and L. Thiele. Multiobjective optimization using evolutionary algorithms: A comparative study. In Proc. Int'l Conf. on Parallel Problem Solving from Nature, 1998.

Digital Library

Cited By

Subramanian MNarayanan MBhasker BGnanavel SHabibur Rahman MPradeep Reddy C(2022)Hybrid Electro Search with Ant Colony Optimization Algorithm for Task Scheduling in a Sensor Cloud Environment for Agriculture Irrigation Control SystemComplexity10.1155/2022/45252202022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/4525220
Hyrynsalmi SMelegati J(2022)The state-of-the-art of the integration platforms as a service researchProceedings of the 5th International Workshop on Software-intensive Business: Towards Sustainable Software Business10.1145/3524614.3528634(17-22)Online publication date: 18-May-2022
https://dl.acm.org/doi/10.1145/3524614.3528634
Zhao QWang GPeng YLu Y(2020)OEDDBOSWireless Communications & Mobile Computing10.1155/2020/43804622020Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1155/2020/4380462

Index Terms

Toward sensor-cloud integration as a service: optimizing three-tier communication in cloud-integrated sensor networks
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
      1. Heuristic function construction
2. Networks
  1. Network architectures

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Information & Contributors

Information

Published In

cover image ACM Other conferences

BodyNets '13: Proceedings of the 8th International Conference on Body Area Networks

September 2013

610 pages

ISBN:9781936968893

General Chair:
Junichi Suzuki
University of Massachusetts Boston
,
Program Chair:
Honggang Wang
University of Massachusetts Dartmouth

Sponsors

ICST

In-Cooperation

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering)

Brussels, Belgium

Publication History

Published: 30 September 2013

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Cited By

Subramanian MNarayanan MBhasker BGnanavel SHabibur Rahman MPradeep Reddy C(2022)Hybrid Electro Search with Ant Colony Optimization Algorithm for Task Scheduling in a Sensor Cloud Environment for Agriculture Irrigation Control SystemComplexity10.1155/2022/45252202022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/4525220
Hyrynsalmi SMelegati J(2022)The state-of-the-art of the integration platforms as a service researchProceedings of the 5th International Workshop on Software-intensive Business: Towards Sustainable Software Business10.1145/3524614.3528634(17-22)Online publication date: 18-May-2022
https://dl.acm.org/doi/10.1145/3524614.3528634
Zhao QWang GPeng YLu Y(2020)OEDDBOSWireless Communications & Mobile Computing10.1155/2020/43804622020Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1155/2020/4380462

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