Convergence of Probability Measures. By P. Billingsley. Chichester, Sussex, Wiley, 1968. xii, 253 p. 9 1/4“. 117s.

Convergence of Probability Measures

Social Network Analysis

The Internet has led to the creation of a digital society, where (almost) everything is connected and is accessible from anywhere. However, despite their widespread adoption, traditional IP networks are complex and very hard to manage. It is both difficult to configure the network according to predefined policies, and to reconfigure it to respond to faults, load, and changes. To make matters even more difficult, current networks are also vertically integrated: the control and data planes are bundled together. Software-defined networking (SDN) is an emerging paradigm that promises to change this state of affairs, by breaking vertical integration, separating the network's control logic from the underlying routers and switches, promoting (logical) centralization of network control, and introducing the ability to program the network. The separation of concerns, introduced between the definition of network policies, their implementation in switching hardware, and the forwarding of traffic, is key to the desired flexibility: by breaking the network control problem into tractable pieces, SDN makes it easier to create and introduce new abstractions in networking, simplifying network management and facilitating network evolution. In this paper, we present a comprehensive survey on SDN. We start by introducing the motivation for SDN, explain its main concepts and how it differs from traditional networking, its roots, and the standardization activities regarding this novel paradigm. Next, we present the key building blocks of an SDN infrastructure using a bottom-up, layered approach. We provide an in-depth analysis of the hardware infrastructure, southbound and northbound application programming interfaces (APIs), network virtualization layers, network operating systems (SDN controllers), network programming languages, and network applications. We also look at cross-layer problems such as debugging and troubleshooting. In an effort to anticipate the future evolution of this new paradigm, we discuss the main ongoing research efforts and challenges of SDN. In particular, we address the design of switches and control platforms—with a focus on aspects such as resiliency, scalability, performance, security, and dependability—as well as new opportunities for carrier transport networks and cloud providers. Last but not least, we analyze the position of SDN as a key enabler of a software-defined environment.

https://publications.uni.lu/bitstream/10993/20596/1/survey_on_SDN.pdf

Software-Defined Networking: A Comprehensive Survey

Infectious Diseases Society of America.

The structure and dynamics of multilayer networks

Many network operations, ranging from attack investigation and mitigation to traffic management, require answering network-wide flow queries in seconds. Although flow records are collected at each router, using available traffic capture utilities, querying the resulting datasets from hundreds of routers across sites and over time, remains a significant challenge due to the sheer traffic volume and distributed nature of flow records. 
In this paper, we investigate how to improve the response time for a priori unknown network-wide queries. We present Flowyager, a system that is built on top of existing traffic capture utilities. Flowyager generates and analyzes tree data structures, that we call Flowtrees, which are succinct summaries of the raw flow data available by capture utilities. Flowtrees are self-adjusted data structures that drastically reduce space and transfer requirements, by 75% to 95%, compared to raw flow records. Flowyager manages the storage and transfers of Flowtrees, supports Flowtree operators, and provides a structured query language for answering flow queries across sites and time periods. By deploying a Flowyager prototype at both a large Internet Exchange Point and a Tier-1 Internet Service Provider, we showcase its capabilities for networks with hundreds of router interfaces. Our results show that the query response time can be reduced by an order of magnitude when compared with alternative data analytics platforms. Thus, Flowyager enables interactive network-wide queries and offers unprecedented drill-down capabilities to, e.g., identify DDoS culprits, pinpoint the involved sites, and determine the length of the attack.

/pdf/exploring-network-wide-flow-data-with-flowyager-agzz2u8s44.pdf

Exploring Network-Wide Flow Data with Flowyager

In today's Internet, mobile devices are connected to multiple access networks, e.g., WiFi/DSL and LTE. To take advantage of the networks' diverse paths characteristics (delay, bandwidth, and reliability) and aggregate bandwidth, we need smart strategies for choosing which interface(s) to use for what traffic. In this paper, we present an approach how to tackle this challenge as part of the Operating System (OS): With the concept of Socket Intents, applications can express what they know about their communication pattern and their preferences. Using our Socket Intents Prototype and our modified BSD Socket Interface, this information is used to choose the most appropriate path or path combination on a per message or per connection basis. We evaluate our system based on the use case of Web browsing: Using our prototype and a client-side proxy, we show the feasibility and benefits of our design. Using a flow-based simulator and a full factorial experimental design, we study a broad range of access network combinations (based on typical DSL and LTE scenarios) and real workloads (Alexa Top 100 and Top 1000 Web Sites). Our policies achieve performance benefits in more than 50% of the cases and speedups of more than factor two in 20% of the cases without adding overhead in the other cases.

Socket Intents: OS Support for Using Multiple Access Networks and its Benefits for Web Browsing

QAnon is a far-right conspiracy theory that became popular and mainstream over the past few years Worryingly, the QAnon conspiracy theory has implications in the real world, with supporters of the theory participating in real-world violent acts like the US capitol attack in 2021 At the same time, the QAnon theory started evolving into a global phenomenon by attracting followers across the globe and, in particular, in Europe Therefore, it is imperative to understand how the QAnon theory became a worldwide phenomenon and how this dissemination has been happening in the online space This paper performs a large-scale data analysis of QAnon through Telegram by collecting 45M messages posted in 161 QAnon groups/channels Using Google's Perspective API, we analyze the toxicity of QAnon content across languages and over time Also, using a BERT-based topic modeling approach, we analyze the QAnon discourse across multiple languages Among other things, we find that the German language is prevalent in QAnon groups/channels on Telegram, even overshadowing English after 2020 Also, we find that content posted in German and Portuguese tends to be more toxic compared to English Our topic modeling indicates that QAnon supporters discuss various topics of interest within far-right movements, including world politics, conspiracy theories, COVID-19, and the anti-vaccination movement Taken all together, we perform the first multilingual study on QAnon through Telegram and paint a nuanced overview of the globalization of the QAnon theory

On the Globalization of the QAnon Conspiracy Theory Through Telegram

Lots of new features are added to the Internet every day to improve quality of service. These features include RED, fair queuing, etc. Unfortunately testing and evaluation of the effectiveness of these mechanisms in test environments is often limited by the simplicity of the test setup. Yet, variability is necessary to locate equipment bugs and to evaluate the features benefits. As a result the real test is the deployment in the operational network - not a sound testing methodology.As a first step towards addressing this problem, we are building a tool that can generate realistic routing tables of arbitrary size and updates of arbitrary frequency. To this end, we first define a set of metrics that can capture important characteristics of routing tables and routing updates. Next, we present insights of a characterization of measured routing tables and updates and identify some key insights. These results are then used to parameterize our tool. Finally, we describe the key ideas behind the tool and conclude with a brief discussion of future work.

Generating realistic routing tables in a test-lab

Prostate cancer is the most common noncutaneous malignancy in men. The prostate stem cell Ag (PSCA) is a promising target for immunotherapy of advanced disease. Based on a novel mAb directed to PSCA, we established and compared a series of murine and humanized anti-CD3–anti-PSCA single-chain bispecific Abs. Their capability to redirect T cells for killing of tumor cells was analyzed. During these studies, we identified a novel bispecific humanized Ab that efficiently retargets T cells to tumor cells in a strictly Ag-dependent manner and at femtomolar concentrations. T cell activation, cytokine release, and lysis of target cells depend on a cross-linkage of redirected T cells with tumor cells, whereas binding of the anti-CD3 domain alone does not lead to an activation or cytokine release. Interestingly, both CD8+ and CD4+ T cells are activated in parallel and can efficiently mediate the lysis of tumor cells. However, the onset of killing via CD4+ T cells is delayed. Furthermore, redirecting T cells via the novel humanized bispecific Abs results in a delay of tumor growth in xenografted nude mice.

Anja Feldmann

Papers

Exploring Network-Wide Flow Data with Flowyager

Socket Intents: OS Support for Using Multiple Access Networks and its Benefits for Web Browsing

On the Globalization of the QAnon Conspiracy Theory Through Telegram

Generating realistic routing tables in a test-lab

Novel Humanized and Highly Efficient Bispecific Antibodies Mediate Killing of Prostate Stem Cell Antigen-Expressing