J
Jing Yuan
Researcher at Nanjing University
Publications - 22
Citations - 352
Jing Yuan is an academic researcher from Nanjing University. The author has contributed to research in topics: Computer science & Submodular set function. The author has an hindex of 5, co-authored 14 publications receiving 311 citations. Previous affiliations of Jing Yuan include University of Illinois at Urbana–Champaign & University of Illinois at Chicago.
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Proceedings ArticleDOI
Towards Optimal Bidding Strategy for Amazon EC2 Cloud Spot Instance
TL;DR: This paper formulate this problem as a Constrained Markov Decision Process (CMDP), and is able to obtain an optimal randomized bidding strategy through linear programming, and compares several adaptive check-pointing schemes in terms of monetary costs and job completion time.
Proceedings ArticleDOI
RASPberry: A stable reader activation scheduling protocol in multi-reader RFID systems
TL;DR: This work analytically proves that their scheduling protocol, RASPberry, is stable if the arrival rate of tags is less than the processing rate of all readers, and it is proved that this is the first work to address the stability problem of reader activation scheduling in RFID systems.
Proceedings ArticleDOI
Relationship classification in large scale online social networks and its impact on information propagation
TL;DR: This work first investigates identifying the relationships among social network users based on certain social network property and limited pre-known information, and shows how to exploit these relationships to maximize the marketing efficacy.
Journal ArticleDOI
A Framework for Amazon EC2 Bidding Strategy under SLA Constraints
TL;DR: A set of bidding strategies under several service-level agreement (SLA) constraints is proposed to minimize the monetary cost and volatility of resource provisioning and is able to obtain an optimal randomized bidding strategy through linear programming.
Proceedings ArticleDOI
DAWN: Energy efficient data aggregation in WSN with mobile sinks
TL;DR: This work considers a more realistic model where the moving speed and path for mobile sinks are constrained and proposes a number of motion stratifies for the mobile sink to gather real time data from static sensor network, with the objective to maximize the network lifetime.