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Achieving optimal admission control with dynamic scheduling in energy constrained network systems.

, , , , , and . J. Network and Computer Applications, (2014)

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Vessel trajectory partitioning based on hierarchical fusion of position data., , , , and . FUSION, page 1230-1237. IEEE, (2015)Improving Both Energy and Time Efficiency of Depth-Based Routing for Underwater Sensor Networks., , , , and . IJDSN, (2015)Odometer in the pocket., , , , and . MobiSys, page 549-550. ACM, (2013)Multi-objective Pruning for CNNs Using Genetic Algorithm., , , , and . ICANN (2), volume 11728 of Lecture Notes in Computer Science, page 299-305. Springer, (2019)TDMA versus CSMA/CA for wireless multi-hop communications: A comparison for soft real-time networking., , , , , and . WFCS, page 1-4. IEEE, (2016)Optimal scheduling for energy harvesting mobile sensing devices., , , , , and . Computer Communications, (2016)Rethinking the Number of Channels for the Convolutional Neural Network., , , , , and . CoRR, (2019)EENA: Efficient Evolution of Neural Architecture., , , , and . CoRR, (2019)A Reliable Depth-Based Routing Protocol with Network Coding for Underwater Sensor Networks., , , , , , and . ICPADS, page 270-277. IEEE Computer Society, (2016)DRNet: Dissect and Reconstruct the Convolutional Neural Network via Interpretable Manners., , , , , and . CoRR, (2019)