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12/18/2020
Additive Link Metrics Identification: Proof of Selected Lemmas and Propositions
This is a technical report, containing all the lemma and proposition pro...
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12/18/2020
Identification of Additive Link Metrics: Proof of Selected Theorems
This is a technical report, containing all the theorem proofs in the fol...
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12/17/2020
Efficient Identification of Additive Link Metrics: Theorem Proof and Evaluations
This is a technical report, containing all the theorem proofs and additi...
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12/17/2020
Partial Network Identifiability: Theorem Proof and Evaluation
This is a technical report, containing all the theorem proofs and additi...
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12/17/2020
Link Identifiability with Two Monitors: Proof of Selected Theorems
This is a technical report, containing all the theorem proofs in paper "...
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12/17/2020
Fundamental Theories in Node Failure Localization
This is a technical report, containing all the theorem proofs in paper "...
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12/17/2020
Failure Localization Capability: Theorem Proof and Evaluation
This is a technical report, containing all the theorem proofs and additi...
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12/17/2020
Node Failure Localization: Theorem Proof
This is a technical report, containing all the theorem proofs in paper "...
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11/09/2020
Resource Allocation in One-dimensional Distributed Service Networks with Applications
We consider assignment policies that allocate resources to users, where ...
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11/05/2020
On the Analysis of Spatially Constrained Power of Two Choice Policies
We consider a class of power of two choice based assignment policies for...
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10/09/2020
Joint State-Action Embedding for Efficient Reinforcement Learning
While reinforcement learning has achieved considerable successes in rece...
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07/14/2020
Energy-Efficient Resource Management for Federated Edge Learning with CPU-GPU Heterogeneous Computing
Edge machine learning involves the deployment of learning algorithms at ...
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06/05/2020
State Action Separable Reinforcement Learning
Reinforcement Learning (RL) based methods have seen their paramount succ...
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01/22/2020
Data Selection for Federated Learning with Relevant and Irrelevant Data at Clients
Federated learning is an effective way of training a machine learning mo...
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01/14/2020
Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach
Federated learning (FL) is an emerging technique for training machine le...
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01/13/2020
Fast-Fourier-Forecasting Resource Utilisation in Distributed Systems
Distributed computing systems often consist of hundreds of nodes, execut...
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01/13/2020
Resource Sharing in the Edge: A Distributed Bargaining-Theoretic Approach
The growing demand for edge computing resources, particularly due to inc...
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01/02/2020
Let's Share: A Game-Theoretic Framework for Resource Sharing in Mobile Edge Clouds
Mobile edge computing seeks to provide resources to different delay-sens...
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09/19/2019
MACS: Deep Reinforcement Learning based SDN Controller Synchronization Policy Design
In distributed software-defined networks (SDN), multiple physical SDN co...
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07/13/2019
Energy-Efficient Radio Resource Allocation for Federated Edge Learning
Edge machine learning involves the development of learning algorithms at...
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05/22/2019
Online Collection and Forecasting of Resource Utilization in Large-Scale Distributed Systems
Large-scale distributed computing systems often contain thousands of dis...
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04/01/2019
A Game-Theoretic Framework for Resource Sharing in Clouds
Providing resources to different users or applications is fundamental to...
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01/25/2019
Learning the Optimal Synchronization Rates in Distributed SDN Control Architectures
Since the early development of Software-Defined Network (SDN) technology...
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01/08/2019
Resource Allocation in One-dimensional Distributed Service Networks
We consider assignment policies that allocate resources to users, where ...
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01/08/2019
A queueing-theoretic model for resource allocation in one-dimensional distributed service network
We consider assignment policies that allocate resources to requesting us...
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12/03/2018
DQ Scheduler: Deep Reinforcement Learning Based Controller Synchronization in Distributed SDN
In distributed software-defined networks (SDN), multiple physical SDN co...
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08/21/2018
A Game-Theoretic Approach to Multi-Objective Resource Sharing and Allocation in Mobile Edge Clouds
Mobile edge computing seeks to provide resources to different delay-sens...
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04/14/2018
When Edge Meets Learning: Adaptive Control for Resource-Constrained Distributed Machine Learning
Emerging technologies and applications including Internet of Things (IoT...
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01/06/2018
Joint Data Compression and Caching: Approaching Optimality with Guarantees
We consider the problem of optimally compressing and caching data across...
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12/12/2017
How Better is Distributed SDN? An Analytical Approach
Distributed software-defined networks (SDN), consisting of multiple inte...
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12/10/2017
Optimal Energy Consumption with Communication, Computation, Caching and QoI-Guarantee
Energy efficiency is a fundamental requirement of modern data communicat...
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12/10/2017