Mengxia Zhu

TL;DR: This article explains the CHEETAH concept and describes a wide-area experimental network testbed deployed based on this concept, which currently extends between Raleigh, North Carolina, Atlanta, Georgia, and Oak Ridge, Tennessee, and uses off-the-shelf switches.

TL;DR: The Monte Carlo-based simulation results show that the proposed approach significantly improves target detection performance, and can also be used to guide the actual threshold selection in practical sensor network implementation under certain error rate constraints.

TL;DR: This research proposes a statistical summary for a database, called CS2 (Correlated Sample Synopsis), to provide rapid and accurate result size estimations for all queries with joins and arbitrary selections, and introduces a statistical technique, called reverse sample, and design a powerful estimator, to fully utilize correlated sample tuples for query estimation.

TL;DR: This work formulate a delay-constrained optimization problem to maximize resource utilization and propose a two-step workflow scheduling algorithm to minimize the cloud overhead within a user-specified execution time bound and demonstrates that this approach consistently achieves lower computing overhead or higher resource utilization than existing methods within the executed time bound.