arXiv subjects

György Dán

Publications and source records attributed to György Dán.

22 records · Page 2Linked to original sources

arXiv2017

Performance Analysis of Reliable Video Streaming with Strict Playout Deadline in Multi-Hop Wireless Networks

Motivated by emerging vision-based intelligent services, we consider the problem of rate adaptation for high quality and low delay visual information delivery over wireless networks using scalable video coding. Rate adaptation in this setting is inherently challenging due to the interplay between the variability of the wireless channels, the queuing at the network nodes and the frame-based decoding and playback of the video content at the receiver at very short time scales. To address the problem, we propose a low-complexity, model-based rate adaptation algorithm for scalable video streaming systems, building on a novel performance model based on stochastic network calculus. We validate the model using extensive simulations. We show that it allows fast, near optimal rate adaptation for fixed transmission paths, as well as cross-layer optimized routing and video rate adaptation in mesh networks, with less than $10$\% quality degradation compared to the best achievable performance.

cs.MM↗

arXiv2016

Selfish Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks

Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations via multiple access points (APs) to a mobile cloud so as to minimize their computation costs, and we provide a game theoretical analysis of the problem. We show that in the case of an elastic cloud, all improvement paths are finite, and thus a pure strategy Nash equilibrium exists and can be computed easily. In the case of a non-elastic cloud we show that improvement paths may cycle, yet we show that a pure Nash equilibrium exists and we provide an efficient algorithm for computing one. Furthermore, we provide an upper bound on the price of anarchy (PoA) of the game. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the PoA under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the cost difference is due to too many mobile users offloading simultaneously.

cs.NI↗

arXiv2015

Differentially Private State Estimation in Distribution Networks with Smart Meters

State estimation is routinely being performed in high-voltage power transmission grids in order to assist in operation and to detect faulty equipment. In low- and medium-voltage power distribution grids, on the other hand, few real-time measurements are traditionally available, and operation is often conducted based on predicted and historical data. Today, in many parts of the world, smart meters have been deployed at many customers, and their measurements could in principle be shared with the operators in real time to enable improved state estimation. However, customers may feel reluctance in doing so due to privacy concerns. We therefore propose state estimation schemes for a distribution grid model, which ensure differential privacy to the customers. In particular, the state estimation schemes optimize different performance criteria, and a trade-off between a lower bound on the estimation performance versus the customers' differential privacy is derived. The proposed framework is general enough to be applicable also to other distribution networks, such as water and gas networks.

math.OC↗

arXiv2010

A Cyber Security Study of a SCADA Energy Management System: Stealthy Deception Attacks on the State Estimator

The electrical power network is a critical infrastructure in today's society, so its safe and reliable operation is of major concern. State estimators are commonly used in power networks, for example, to detect faulty equipment and to optimally route power flows. The estimators are often located in control centers, to which large numbers of measurements are sent over unencrypted communication channels. Therefore cyber security for state estimators becomes an important issue. In this paper we analyze the cyber security of state estimators in supervisory control and data acquisition (SCADA) for energy management systems (EMS) operating the power network. Current EMS state estimation algorithms have bad data detection (BDD) schemes to detect outliers in the measurement data. Such schemes are based on high measurement redundancy. Although these methods may detect a set of basic cyber attacks, they may fail in the presence of an intelligent attacker. We explore the latter by considering scenarios where stealthy deception attacks are performed by sending false information to the control center. We begin by presenting a recent framework that characterizes the attack as an optimization problem with the objective specified through a security metric and constraints corresponding to the attack cost. The framework is used to conduct realistic experiments on a state-of-the-art SCADA EMS software for a power network example with 14 substations, 27 buses, and 40 branches. The results indicate how state estimators for power networks can be made more resilient to cyber security attacks.

math.OC↗