Browsing by Subject "Communication networks"

Now showing 1 - 3 of 3

Open Access
Decentralised robust flow controller design for networks with multiple bottlenecks
(Taylor & Francis, 2009) Munyas, I.; Yelbaşi, Ö.; Biberovic, E.; İftar, A.; Özbay, Hitay
Decentralised rate-based flow controller design in multi-bottleneck data-communication networks is considered. An H∞ problem is formulated to find decentralised controllers which can be implemented locally at the bottleneck nodes. A suboptimal solution to this problem is found and the implementation of the decentralised controllers is presented. The controllers are robust to time-varying uncertain multiple time-delays in different channels. They also satisfy tracking and weighted fairness requirements. Lower bounds on the actual stability margins are derived and their relation to the design parameters is analysed. A number of simulations are also included to illustrate the time-domain performance of the proposed controllers.
Open Access
Multi-armed bandit algorithms for communication networks and healthcare
(2022-06) Demirel, İlker
Multi-armed bandits (MAB) is a well-established sequential decision-making framework. While the simplest MAB framework is useful in modeling a wide range of real-world applications ranging from adaptive clinical trial design to financial portfolio management, it requires further extensions for other problems. We propose three novel MAB algorithms that are useful in optimizing bolus-insulin dose recommendation in type-1 diabetes, best channel identification in cognitive radio networks, and online recommender systems. First, we introduce and study the “safe leveling” problem, where the learner's objective is to keep the arm outcomes close to a target level rather than maximize them. We propose a novel algorithm, ESCADA, with cumulative regret and safety guarantees. We demonstrate its effectiveness against the straightforward adaptations of standard MAB algorithms to the “leveling task”. Next, we study the “federated multi-armed bandit” (FMAB) problem, where a cohort of clients play the same MAB game to learn the globally best arm. We consider adversarial “Byzantine” clients disturbing the learning process with false model updates and propose a robust algorithm, Fed-MoM-UCB. We provide theoretical guarantees on Fed-MoM-UCB while identifying the certain performance sacrifices that robustness requires. Finally, we study the “combinatorial multi-armed bandits with probabilistically triggered arms” (CMAB-PTA), where the learner chooses a set of arms at each round that may trigger other arms. CMAB-PTA is useful in modeling various problems such as influence maximization on graphs and online recommendation systems. We propose a Gaussian process-based algorithm, ComGP-UCB. We provide upper bounds on its regret and demonstrate its effectiveness against the state-of-the-art baselines when arm outcomes are correlated.
Open Access
On the design of AQM supporting TCP flows using robust control theory
(IEEE, 2004) Quet, P-F.; Özbay, Hitay
Recently it has been shown that the active queue management schemes implemented in the routers of communication networks supporting transmission control protocol (TCP) flows can be modeled as a feedback control system. Based on a delay differential equations model of TCPs congestion-avoidance mode different control schemes have been proposed. Here a robust controller is designed based on the known techniques for H∞ control of systems with time delays.