Quantum Network Code for Multiple-Unicast Network with Quantum Invertible Linear Operations

This paper considers the communication over a quantum multiple-unicast network where r sender-receiver pairs communicate independent quantum states. We concretely construct a quantum network code for the quantum multiple-unicast network as a generalization of the code [Song and Hayashi, arxiv:1801.03306, 2018] for the quantum unicast network. When the given node operations are restricted to invertible linear operations between bit basis states and the rates of transmissions and interferences are restricted, our code certainly transmits a quantum state for each sender-receiver pair by n-use of the network asymptotically, which guarantees no information leakage to the other users. Our code is implemented only by the coding operation in the senders and receivers and employs no classical communication and no manipulation of the node operations. Several networks that our code can be applied are also given

Secure Quantum Network Code without Classical Communication

We consider the secure quantum communication over a network with the presence of a malicious adversary who can eavesdrop and contaminate the states. The network consists of noiseless quantum channels with the unit capacity and the nodes which applies noiseless quantum operations. As the main result, when the maximum number m1 of the attacked channels over the entire network uses is less than a half of the network transmission rate m0 (i.e., m1 < m0 / 2), our code implements secret and correctable quantum communication of the rate m0 - 2m1 by using the network asymptotic number of times. Our code is universal in the sense that the code is constructed without the knowledge of the specific node operations and the network topology, but instead, every node operation is constrained to the application of an invertible matrix to the basis states. Moreover, our code requires no classical communication. Our code can be thought of as a generalization of the quantum secret sharing

Managing Network Delay for Browser Multiplayer Games

Latency is one of the key performance elements affecting the quality of experience (QoE) in computer games. Latency in the context of games can be defined as the time between the user input and the result on the screen. In order for the QoE to be satisfactory the game needs to be able to react fast enough to player input. In networked multiplayer games, latency is composed of network delay and local delays. Some major sources of network delay are queuing delay and head-of-line (HOL) blocking delay. Network delay in the Internet can be even in the order of seconds. In this thesis we discuss what feasible networking solutions exist for browser multiplayer games. We conduct a literature study to analyze the Differentiated Services architecture, some salient Active Queue Management (AQM) algorithms (RED, PIE, CoDel and FQ-CoDel), the Explicit Congestion Notification (ECN) concept and network protocols for web browser (WebSocket, QUIC and WebRTC). RED, PIE and CoDel as single-queue implementations would be sub-optimal for providing low latency to game traffic. FQ-CoDel is a multi-queue AQM and provides flow separation that is able to prevent queue-building bulk transfers from notably hampering latency-sensitive flows. WebRTC Data-Channel seems promising for games since it can be used for sending arbitrary application data and it can avoid HOL blocking. None of the network protocols, however, provide completely satisfactory support for the transport needs of multiplayer games: WebRTC is not designed for client-server connections, QUIC is not designed for traffic patterns typical for multiplayer games and WebSocket would require parallel connections to mitigate the effects of HOL blocking

Měření Triple play služeb v hybridní síti

The master's thesis deals with a project regarding the implementation, design and the quality of IPTV, VoIP and Data services within the Triple Play services. In heterostructural networks made up of GEPON and xDSL technologies. Different lengths of the optical and metallic paths were used for the measurements. The first part of the thesis is theoretically analyzed the development and trend of optical and metallic networks. The second part deals with the measurement of typical optical and metallic parameters on the constructed experimental network, where its integrity was tested. Another part of the thesis is the evaluation of Triple play results, regarding the test where the network was variously tasked/burdened with data traffic and evaluated according to defined standards. The last part is concerned with the Optiwave Software simulation environment.Diplomová práce se zabývá návrhem, realizací a kvalitou služeb IPTV, VoIP a Data v rámci Triple play služeb v heterostrukturní sítí tvořené GEPON a xDSL technologiemi. Pro měření byli využity různé délky optické a metalické trasy. První části diplomové práce je teoreticky rozebrán vývoj a trend optických a metalických sítí. Druhá část se zaměřuje na měření typických optických a metalických parametrů na vybudované experimentální síti, kde byla následně testována její integrita. Dalším bodem práce je vyhodnocení výsledků Triple play, kde síť je různě zatěžována datovým provozem a následně vyhodnocována podle definovaných norem. Závěr práce je věnovaný simulačnímu prostředí Optiwave.440 - Katedra telekomunikační technikyvýborn

Recent Trends in Communication Networks

In recent years there has been many developments in communication technology. This has greatly enhanced the computing power of small handheld resource-constrained mobile devices. Different generations of communication technology have evolved. This had led to new research for communication of large volumes of data in different transmission media and the design of different communication protocols. Another direction of research concerns the secure and error-free communication between the sender and receiver despite the risk of the presence of an eavesdropper. For the communication requirement of a huge amount of multimedia streaming data, a lot of research has been carried out in the design of proper overlay networks. The book addresses new research techniques that have evolved to handle these challenges

Proceedings of the 35th WIC Symposium on Information Theory in the Benelux and the 4th joint WIC/IEEE Symposium on Information Theory and Signal Processing in the Benelux, Eindhoven, the Netherlands May 12-13, 2014

Compressive sensing (CS) as an approach for data acquisition has recently received much attention. In CS, the signal recovery problem from the observed data requires the solution of a sparse vector from an underdetermined system of equations. The underlying sparse signal recovery problem is quite general with many applications and is the focus of this talk. The main emphasis will be on Bayesian approaches for sparse signal recovery. We will examine sparse priors such as the super-Gaussian and student-t priors and appropriate MAP estimation methods. In particular, re-weighted l2 and re-weighted l1 methods developed to solve the optimization problem will be discussed. The talk will also examine a hierarchical Bayesian framework and then study in detail an empirical Bayesian method, the Sparse Bayesian Learning (SBL) method. If time permits, we will also discuss Bayesian methods for sparse recovery problems with structure; Intra-vector correlation in the context of the block sparse model and inter-vector correlation in the context of the multiple measurement vector problem

Proceedings of the 35th WIC Symposium on Information Theory in the Benelux and the 4th joint WIC/IEEE Symposium on Information Theory and Signal Processing in the Benelux, Eindhoven, the Netherlands May 12-13, 2014

Compressive sensing (CS) as an approach for data acquisition has recently received much attention. In CS, the signal recovery problem from the observed data requires the solution of a sparse vector from an underdetermined system of equations. The underlying sparse signal recovery problem is quite general with many applications and is the focus of this talk. The main emphasis will be on Bayesian approaches for sparse signal recovery. We will examine sparse priors such as the super-Gaussian and student-t priors and appropriate MAP estimation methods. In particular, re-weighted l2 and re-weighted l1 methods developed to solve the optimization problem will be discussed. The talk will also examine a hierarchical Bayesian framework and then study in detail an empirical Bayesian method, the Sparse Bayesian Learning (SBL) method. If time permits, we will also discuss Bayesian methods for sparse recovery problems with structure; Intra-vector correlation in the context of the block sparse model and inter-vector correlation in the context of the multiple measurement vector problem