W
Wei Gao
Researcher at University of Pittsburgh
Publications - 85
Citations - 3509
Wei Gao is an academic researcher from University of Pittsburgh. The author has contributed to research in topics: Mobile computing & Computer science. The author has an hindex of 27, co-authored 75 publications receiving 3155 citations. Previous affiliations of Wei Gao include IBM & Pennsylvania State University.
Papers
More filters
Proceedings ArticleDOI
Multicasting in delay tolerant networks: a social network perspective
TL;DR: This paper is the first to study multicast in DTNs from the social network perspective, and investigates the essential difference between multicast and unicast inDTNs, and forms relay selections for multicast as a unified knapsack problem by exploiting node centrality and social community structures.
Proceedings ArticleDOI
A hierarchical edge cloud architecture for mobile computing
Liang Tong,Yong Li,Wei Gao +2 more
TL;DR: This paper proposes to deploy cloud servers at the network edge and design the edge cloud as a tree hierarchy of geo-distributed servers, so as to efficiently utilize the cloud resources to serve the peak loads from mobile users.
Proceedings ArticleDOI
User-centric data dissemination in disruption tolerant networks
Wei Gao,Guohong Cao +1 more
TL;DR: This paper proposes a novel approach for user-centric data dissemination in DTNs, which considers satisfying user interests and maximizes the cost-effectiveness of data dissemination, based on a social centrality metric.
Journal ArticleDOI
An Incentive Framework for Cellular Traffic Offloading
TL;DR: This paper provides a novel incentive framework to motivate users to leverage their delay tolerance for cellular traffic offloading and illustrates how to predict the offloading potential of the users by using stochastic analysis for both DTN and WiFi cases.
Proceedings ArticleDOI
Win-Coupon: An incentive framework for 3G traffic offloading
TL;DR: This paper provides a novel incentive framework based on reverse auction to motivate users to leverage their delay tolerance for 3G traffic offloading and takes DTN as a case study to illustrate how to predict the offloading potential of the users by using stochastic analysis.