Content Centric Peer Data Sharing in Pervasive Edge Computing Environments

Xinong Song; Yaodong Huang; Qian Zhou; Fan Ye; Yuanyuan Yang; Xiaoming Li

doi:10.1109/ICDCS.2017.26

Content Centric Peer Data Sharing in Pervasive Edge Computing Environments

Xinong Song
, Yaodong Huang
, Qian Zhou
, Fan Ye
, Yuanyuan Yang
, Xiaoming Li

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

40 Citations (Scopus)

Abstract

The proliferation and daily congregation of modern mobile devices have created abundant opportunities for peer edge devices to share valuable data with each other. The short contact durations, relatively small sharing sizes, and uncertain data availability, demand agile, light weight peer based data sharing. In this paper, we propose Peer Data Sharing (PDS) that enables edge devices to discover which data exist in nearby peers, and retrieve interested data robustly and efficiently. PDS uses novel lingering queries, mixedcast and en-route message rewriting techniques to minimize redundant transmissions and maximize opportunistic overhearing thus caching in data discovery and retrieval. Extensive evaluations based on an Android prototype show that PDS discovers and retrieves almost 100% data in tens of seconds, and remains robust despite wireless contention, simultaneous consumer requests and user mobility. © 2017 IEEE.

Original language	English
Title of host publication	Proceedings - IEEE 37th International Conference on Distributed Computing Systems, ICDCS 2017
Publisher	IEEE
Pages	287-297
ISBN (Print)	9781538617915
DOIs	https://doi.org/10.1109/ICDCS.2017.26
Publication status	Published - 13 Jul 2017
Externally published	Yes
Event	37th IEEE International Conference on Distributed Computing Systems, ICDCS 2017 - Atlanta, United States Duration: 5 Jun 2017 → 8 Jun 2017

Publication series

Name	Proceedings - International Conference on Distributed Computing Systems

Conference

Conference	37th IEEE International Conference on Distributed Computing Systems, ICDCS 2017
Place	United States
City	Atlanta
Period	5/06/17 → 8/06/17

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Funding

This work was supported in part by US NSF grant CSR-1513719 and China National 973 grant 2014CB340405.

Research Keywords

Data Discovery
Data Retrieval
Mobile Sensing
Peer Data Sharing

Access Output

10.1109/ICDCS.2017.26

Other Access Options

Check CityUHK Library

Permanent Link

Right click to copy link

Cite this

Song, X., Huang, Y., Zhou, Q., Ye, F., Yang, Y., & Li, X. (2017). Content Centric Peer Data Sharing in Pervasive Edge Computing Environments. In Proceedings - IEEE 37th International Conference on Distributed Computing Systems, ICDCS 2017 (pp. 287-297). Article 7979975 (Proceedings - International Conference on Distributed Computing Systems). IEEE. https://doi.org/10.1109/ICDCS.2017.26

@inproceedings{3dfa6e6e384a4da3aec25c115f82a5cc,

title = "Content Centric Peer Data Sharing in Pervasive Edge Computing Environments",

abstract = "The proliferation and daily congregation of modern mobile devices have created abundant opportunities for peer edge devices to share valuable data with each other. The short contact durations, relatively small sharing sizes, and uncertain data availability, demand agile, light weight peer based data sharing. In this paper, we propose Peer Data Sharing (PDS) that enables edge devices to discover which data exist in nearby peers, and retrieve interested data robustly and efficiently. PDS uses novel lingering queries, mixedcast and en-route message rewriting techniques to minimize redundant transmissions and maximize opportunistic overhearing thus caching in data discovery and retrieval. Extensive evaluations based on an Android prototype show that PDS discovers and retrieves almost 100\% data in tens of seconds, and remains robust despite wireless contention, simultaneous consumer requests and user mobility. {\textcopyright} 2017 IEEE.",

keywords = "Data Discovery, Data Retrieval, Mobile Sensing, Peer Data Sharing",

author = "Xinong Song and Yaodong Huang and Qian Zhou and Fan Ye and Yuanyuan Yang and Xiaoming Li",

note = "Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected]. ; 37th IEEE International Conference on Distributed Computing Systems, ICDCS 2017 ; Conference date: 05-06-2017 Through 08-06-2017",

year = "2017",

month = jul,

day = "13",

doi = "10.1109/ICDCS.2017.26",

language = "English",

isbn = "9781538617915",

series = "Proceedings - International Conference on Distributed Computing Systems",

publisher = "IEEE",

pages = "287--297",

booktitle = "Proceedings - IEEE 37th International Conference on Distributed Computing Systems, ICDCS 2017",

address = "United States",

}

Song, X, Huang, Y, Zhou, Q, Ye, F, Yang, Y & Li, X 2017, Content Centric Peer Data Sharing in Pervasive Edge Computing Environments. in Proceedings - IEEE 37th International Conference on Distributed Computing Systems, ICDCS 2017., 7979975, Proceedings - International Conference on Distributed Computing Systems, IEEE, pp. 287-297, 37th IEEE International Conference on Distributed Computing Systems, ICDCS 2017, Atlanta, United States, 5/06/17. https://doi.org/10.1109/ICDCS.2017.26

Content Centric Peer Data Sharing in Pervasive Edge Computing Environments. / Song, Xinong; Huang, Yaodong; Zhou, Qian et al.
Proceedings - IEEE 37th International Conference on Distributed Computing Systems, ICDCS 2017. IEEE, 2017. p. 287-297 7979975 (Proceedings - International Conference on Distributed Computing Systems).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Content Centric Peer Data Sharing in Pervasive Edge Computing Environments

AU - Song, Xinong

AU - Huang, Yaodong

AU - Zhou, Qian

AU - Ye, Fan

AU - Yang, Yuanyuan

AU - Li, Xiaoming

N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

PY - 2017/7/13

Y1 - 2017/7/13

N2 - The proliferation and daily congregation of modern mobile devices have created abundant opportunities for peer edge devices to share valuable data with each other. The short contact durations, relatively small sharing sizes, and uncertain data availability, demand agile, light weight peer based data sharing. In this paper, we propose Peer Data Sharing (PDS) that enables edge devices to discover which data exist in nearby peers, and retrieve interested data robustly and efficiently. PDS uses novel lingering queries, mixedcast and en-route message rewriting techniques to minimize redundant transmissions and maximize opportunistic overhearing thus caching in data discovery and retrieval. Extensive evaluations based on an Android prototype show that PDS discovers and retrieves almost 100% data in tens of seconds, and remains robust despite wireless contention, simultaneous consumer requests and user mobility. © 2017 IEEE.

AB - The proliferation and daily congregation of modern mobile devices have created abundant opportunities for peer edge devices to share valuable data with each other. The short contact durations, relatively small sharing sizes, and uncertain data availability, demand agile, light weight peer based data sharing. In this paper, we propose Peer Data Sharing (PDS) that enables edge devices to discover which data exist in nearby peers, and retrieve interested data robustly and efficiently. PDS uses novel lingering queries, mixedcast and en-route message rewriting techniques to minimize redundant transmissions and maximize opportunistic overhearing thus caching in data discovery and retrieval. Extensive evaluations based on an Android prototype show that PDS discovers and retrieves almost 100% data in tens of seconds, and remains robust despite wireless contention, simultaneous consumer requests and user mobility. © 2017 IEEE.

KW - Data Discovery

KW - Data Retrieval

KW - Mobile Sensing

KW - Peer Data Sharing

UR - https://www.scopus.com/pages/publications/85027279175

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85027279175&origin=recordpage

U2 - 10.1109/ICDCS.2017.26

DO - 10.1109/ICDCS.2017.26

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781538617915

T3 - Proceedings - International Conference on Distributed Computing Systems

SP - 287

EP - 297

BT - Proceedings - IEEE 37th International Conference on Distributed Computing Systems, ICDCS 2017

PB - IEEE

T2 - 37th IEEE International Conference on Distributed Computing Systems, ICDCS 2017

Y2 - 5 June 2017 through 8 June 2017

ER -

Content Centric Peer Data Sharing in Pervasive Edge Computing Environments

Abstract

Publication series

Conference

Bibliographical note

Funding

Research Keywords

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Cite this