Fairness and Optimal Stochastic Control for Heterogeneous Networks

By Michael J. Neely, Eytan H. Modiano, Chih-Ping Li. 2005

739 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

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Citations in the corpus

Fair Resource Allocation in Federated Learning (2019, background): “Fair resource allocation has been extensively studied in fields such as network management (Ee & Bajcsy, 2004; Hahne, 1991; Kelly et al., 1998; Neely et al., 2008) and wireless communications (Eryilmaz & Srikant, 2006; Nandagopal et al.”
Network Congestion Control of Airport Surface Operations (2014, background): “The airport surface congestion problems considered in this paper are similar to those encountered in wireless networks [9,10], Transmission Control Protocol (TCP) congestion control [11], and manufacturing systems [12–14].”
Layering as Optimization Decomposition: A Mathematical Theory of Network Architectures (2007, methodology): “3) Channel level stochastic: Models in [17], [35], [81], [99], [128] consider random channel fluctuations.”
Energy optimal control for time-varying wireless networks (2005, methodology): “In this paper, we develop a simple Lyapunov drift technique that enables system stability and performance optimization to be achieved simultaneously [2], [1], [31].”
A tutorial on cross-layer optimization in wireless networks (2006, background): “Channel variations: Both formulations can be generalized to the case with channel variations (e.g., due to fading and/or mobility of the nodes), in which case only the scheduling component needs to be changed [30] , [33], [40].”
On the Complexity of Scheduling in Wireless Networks (2006, methodology): “Motivated by the works on fair resource allocation in wireline networks [16, 26, 3, 35], researchers have also incorporated congestion control into the cross-layer optimization framework [4, 19, 21, 33, 28, 36, 24].”
Decentralized Learning in Online Queuing Systems (2021, methodology): “Stable decentralized algorithms were later introduced in speciﬁc cases [Neely et al., 2008, Jiang and Walrand, 2009, Shah and Shin, 2012], when the rewards X k ( t ) are observed before deciding which server to send the packet.”
A Distributed CSMA Algorithm for Throughput and Utility Maximization in Wireless Networks (2010, background): “(This is similar in spirit to the weighting factor us ed in [15].”
Fairness in Wireless Networks:Issues, Measures and Challenges (2014, background): “Fair routing protocol in distributed wireless networks is more complex because of the negotiation strategies among neighbors and the lack of information about the networks [120].”
Opportunistic Scheduling with Reliability Guarantees in Cognitive Radio Networks (2008, methodology): “The analysis presented in this paper applies the stochastic network optimization framework of [14].”
User-Centric Cell-Free Massive MIMO Networks: A Survey of Opportunities, Challenges and Solutions (2021, background): “Importantly, the cyclic preﬁx in orthogonal frequency division multiplexing (OFDM) systems can help in tolerating this requirement.”
Joint congestion control, routing, and MAC for stability and fairness in wireless networks (2006, methodology): “In [9], [15], [20], and [25], the authors propose and study rate control algorithms that adapt the flow rates instantaneously as a function of the entry queue-lengths.”
Federated Learning in Mobile Edge Networks: A Comprehensive Survey (2019, background): “One consequence of this unfair resource allocation, a topic that is commonly explored in resource allocation for wireless networks [122] and ML [123].”
Resource Allocation and Cross-Layer Control in Wireless Networks (2006, background): “LIMITATION OF ABSTRACT UL NSN 7540-01-280-5500 Standard Form 298 (Rev.2-89) Prescribed by ANSI Std. 239-18 298-102 Vol. , No (2006) 1 143 c 2006 now Publishers Inc. Resource Allocation and Cross Layer Control in Wireless Networks Leonidas Georgiadis1, Michael Neely2 and Leandros Tassiulas3”
Fair Resource Allocation in Wireless Networks Using Queue-Length-Based Scheduling and Congestion Control (2005, result): “note that [ 26 ] is a recent work that provides an alternate analysis of a similar problem to ours.”