TY - GEN
T1 - MINERVA
T2 - 2013 IEEE 2013 22nd International Conference on Computer Communication and Networks, ICCCN 2013
AU - Wang, Shiguang
AU - Hu, Shaohan
AU - Li, Shen
AU - Liu, Hengchang
AU - Uddin, Md Yusuf Sarwar
AU - Abdelzaher, Tarek
PY - 2013
Y1 - 2013
N2 - In this paper, we introduce Minerva; an information-centric programming paradigm and toolkit for social sensing. The toolkit is geared for smartphone applications whose main objective is to collect and share information about the physical world. Information-centric programming refers to a publish-subscribe paradigm that maximizes the amount of information delivered. Unlike a traditional publish-subscribe system where publishers are assumed to have independent content, Minerva is geared for social sensing applications where different sources (participants sharing sensor data) often overlap in information they share. For example, through lack of coordination, they might collect redundant pictures of the same scene or redundant speed measurements of the same street. The main contribution of Minerva, therefore, lies in a data prioritization scheme that maximizes information delivery from publishers to subscribers by reducing redundancy, taking into account the non-independent nature of content. The algorithm is implemented on Android phones on top of the recently introduced named data networking framework. Evaluation results from both two smartphone-based experiments and a large-scale real data driven simulation demonstrate that the prioritization algorithm outperforms other candidates in terms of information coverage.
AB - In this paper, we introduce Minerva; an information-centric programming paradigm and toolkit for social sensing. The toolkit is geared for smartphone applications whose main objective is to collect and share information about the physical world. Information-centric programming refers to a publish-subscribe paradigm that maximizes the amount of information delivered. Unlike a traditional publish-subscribe system where publishers are assumed to have independent content, Minerva is geared for social sensing applications where different sources (participants sharing sensor data) often overlap in information they share. For example, through lack of coordination, they might collect redundant pictures of the same scene or redundant speed measurements of the same street. The main contribution of Minerva, therefore, lies in a data prioritization scheme that maximizes information delivery from publishers to subscribers by reducing redundancy, taking into account the non-independent nature of content. The algorithm is implemented on Android phones on top of the recently introduced named data networking framework. Evaluation results from both two smartphone-based experiments and a large-scale real data driven simulation demonstrate that the prioritization algorithm outperforms other candidates in terms of information coverage.
UR - http://www.scopus.com/inward/record.url?scp=84891458948&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84891458948&partnerID=8YFLogxK
U2 - 10.1109/ICCCN.2013.6614152
DO - 10.1109/ICCCN.2013.6614152
M3 - Conference contribution
AN - SCOPUS:84891458948
SN - 9781467357746
T3 - Proceedings - International Conference on Computer Communications and Networks, ICCCN
BT - 22nd International Conference on Computer Communications and Networks, ICCCN 2013 - Conference Proceedings
Y2 - 30 July 2013 through 2 August 2013
ER -