The Community for Technology Leaders
Green Image
Issue No. 03 - March (2013 vol. 12)
ISSN: 1536-1233
pp: 581-595
E. Talipov , Dept. of Comput. Sci., Yonsei Univ., Seoul, South Korea
Yohan Chon , Dept. of Comput. Sci., Yonsei Univ., Seoul, South Korea
Hojung Cha , Dept. of Comput. Sci., Yonsei Univ., Seoul, South Korea
With the growing number of smartphone users, peer-to-peer ad hoc content sharing is expected to occur more often. Thus, new content sharing mechanisms should be developed as traditional data delivery schemes are not efficient for content sharing due to the sporadic connectivity between smartphones. To accomplish data delivery in such challenging environments, researchers have proposed the use of store-carry-forward protocols, in which a node stores a message and carries it until a forwarding opportunity arises through an encounter with other nodes. Most previous works in this field have focused on the prediction of whether two nodes would encounter each other, without considering the place and time of the encounter. In this paper, we propose discover-predict-deliver as an efficient content sharing scheme for delay-tolerant smartphone networks. In our proposed scheme, contents are shared using the mobility information of individuals. Specifically, our approach employs a mobility learning algorithm to identify places indoors and outdoors. A hidden Markov model is used to predict an individual's future mobility information. Evaluation based on real traces indicates that with the proposed approach, 87 percent of contents can be correctly discovered and delivered within 2 hours when the content is available only in 30 percent of nodes in the network. We implement a sample application on commercial smartphones, and we validate its efficiency to analyze the practical feasibility of the content sharing application. Our system approximately results in a 2 percent CPU overhead and reduces the battery lifetime of a smartphone by 15 percent at most.
smart phones, ad hoc networks, delay tolerant networks, hidden Markov models, learning (artificial intelligence), mobile computing, peer-to-peer computing, protocols, battery lifetime, smartphone-based delay-tolerant network, peer-to-peer ad hoc content sharing, data delivery, sporadic connectivity, store-carry-forward protocol, forwarding opportunity, discover-predict-deliver, mobility information, mobility learning algorithm, hidden Markov model, CPU overhead, Routing, Routing protocols, Peer to peer computing, Accelerometers, Mobile computing, Global Positioning System, IEEE 802.11 Standards, pervasive computing, Store and forward networks, wireless communication, location dependent and sensitive

Yohan Chon, E. Talipov and Hojung Cha, "Content Sharing over Smartphone-Based Delay-Tolerant Networks," in IEEE Transactions on Mobile Computing, vol. 12, no. , pp. 581-595, 2013.
186 ms
(Ver 3.3 (11022016))