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Using DEMO-based SLAs for Improving City Council Services., , , and . KEOD, page 431-440. SciTePress, (2012)Extended DEMO-Based SLAs to Specify Customers' Expectations., , and . IESS, volume 143 of Lecture Notes in Business Information Processing, page 292-298. Springer, (2013)C3PO: Computation Congestion Control (PrOactive)., , , and . ICN, page 231-236. ACM, (2016)FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout., , , , , and . NeurIPS, page 12876-12889. (2021)Federated mobile sensing for activity recognition., , and . MobiCom, page 858-859. ACM, (2021)A Family of Droids-Android Malware Detection via Behavioral Modeling: Static vs Dynamic Analysis., , , , , and . PST, page 1-10. IEEE Computer Society, (2018)Smart at what cost?: characterising mobile deep neural networks in the wild., , , , , and . Internet Measurement Conference, page 658-672. ACM, (2021)SPINN: synergistic progressive inference of neural networks over device and cloud., , , , and . MobiCom, page 37:1-37:15. ACM, (2020)Elastic phone: towards detecting and mitigating computation and energy inefficiencies in mobile apps.. Polytechnic University of Catalonia, Spain, (2018)EmBench: Quantifying Performance Variations of Deep Neural Networks across Modern Commodity Devices., , , , and . CoRR, (2019)