@inproceedings{6b84da9650ca43b2a86f73a8161df01b,
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.",
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 = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 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",
series = "Proceedings - International Conference on Distributed Computing Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "287--297",
editor = "Kisung Lee and Ling Liu",
booktitle = "Proceedings - IEEE 37th International Conference on Distributed Computing Systems, ICDCS 2017",
}