Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 11 of 11 for “"Network utility maximization"”.
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Network Traffic Control Based on Modern Control Techniques: Fuzzy Logic and Network Utility Maximization
… traffic control protocols that have to estimate network parameters (e.g., link latency, bottleneck bandwidth, packet loss rate, or the number of flows), our fuzzy-logic-based explicit controller can measure the router queue size directly. Hence it avoids various potential performance problems …
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Recovery of primal solution in dual subgradient schemes
… performance of the scheme in the framework of Network Utility Maximization (NUM), which has recently drawn great research interest. Specifically for the NUM problems, which can have concave or nonconcave utility functions and linear constraints, we apply the dual-based decentralized subgradient …
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Centralized performance control for datacenter networks
An ideal datacenter network should allow operators to specify policy for resource allocation between users or applications, while providing several properties, including low median and tail latency, high utilization (throughput), and congestion (loss) avoidance. Current datacenter networks inherit …
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Value function approximation architectures for neuro-dynamic programming
… In the cross-layer wireless control problem, the network utility maximization (NUM) and adaptive modulation (AM) are combined to balance the network performance and transmission power. In these applications, we show how to model the real problems by using the MDP model with reasonable assumptions …
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Distributed Newton-type algorithms for network resource allocation
Most of today's communication networks are large-scale and comprise of agents with local information and heterogeneous preferences, making centralized control and coordination impractical. This motivated much interest in developing and studying distributed algorithms for network resource allocation …
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Learning-NUM: Utility Maximization in Stochastic Queueing Networks
Network Utility Maximization (NUM) studies the problems of allocating traffic rates to network users in order to maximize the users’ total utility subject to network resource constraints. We propose a new paradigm of utility maximization in stochastic queueing networks where the utility functions …
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Network optimization in adversarial environments
Stochastic models have been dominant in network optimization theory for over two decades, due to their analytical tractability. However, an increasing number of real-world networked systems exhibit complex behaviors that cannot be captured by the simple stochastic models, such as networks under …
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Topics in Routing and Network Coding for Wireless Networks
This dissertation presents topics in routing and network coding for wireless networks. We present a multipurpose multipath routing mechanism. We propose an efficient packet encoding algorithm that can easily integrate a routing scheme with network coding. We also discuss max-min fair rate …
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Optimal Control for Uncooperative Networks
Modern networks are complex and may include uncooperative components that cannot be fully controlled or observed. However, classic network optimization theory focuses on network models with all nodes being observable and controllable. In this thesis, we focus on developing optimal control …
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Robustness and Optimality in CSMA Wireless Networks
In today's widely diffused CSMA wireless networks, problems of coordination in the access to the channel by multiple transmitters can lead to unfair situations where some of the flows receive much of the network throughput while others suffer from poor performance. As a solution to this problem, …
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Delay composition theory: A reduction-based schedulability theory for distributed real-time systems
… systems such as holistic analysis and network calculus. Evaluation using simulations suggest that the new reduction-based analysis is able to significantly outperform existing analysis techniques, and the improvement is more pronounced for larger systems. We develop an algebra, called …