arXiv subjects

Jonas Höchst

Publications and source records attributed to Jonas Höchst.

7 recordsLinked to original sources

arXiv2020

INetCEP: In-Network Complex Event Processing for Information-Centric Networking

Emerging network architectures like Information-centric Networking (ICN) offer simplicity in the data plane by addressing named data. Such flexibility opens up the possibility to move data processing inside network elements for high-performance computation, known as in-network processing. However, existing ICN architectures are limited in terms of data plane programmability due to the lack of (i) in-network processing and (ii) data plane programming abstractions. Such architectures can benefit from Complex Event Processing (CEP), an in-network processing paradigm to efficiently process data inside the data plane. Yet, it is extremely challenging to integrate CEP because the current communication model of ICN is limited to consumer-initiated interaction that comes with significant overhead in a number of requests to process continuous data streams. In contrast, a change to producer-initiated interaction, as favored by CEP, imposes severe limitations for request-reply interactions. In this paper, we propose an in-network CEP architecture, INetCEP that supports unified interaction patterns (consumer- and producer-initiated). In addition, we provide a CEP query language and facilitate CEP operations while increasing the range of applications that can be supported by ICN. We provide an open-source implementation and evaluation of INetCEP over an ICN architecture, Named Function Networking, and two applications: energy forecasting in smart homes and a disaster scenario.

cs.DC↗

arXiv2020

Efficient Complex Event Processing in Information-centric Networking at the Edge

Information-centric Networking (ICN) is an emerging Internet architecture that offers promising features, such as in-network caching and named data addressing, to support the edge computing paradigm, in particular Internet-of-Things (IoT) applications. ICN can benefit from Complex Event Processing (CEP), which is an in-network processing paradigm to specify and perform efficient query operations on data streams. However, integrating CEP into ICN is a challenging task due to the following reasons: (1) typical ICN architectures do not provide support for forwarding and processing continuous data streams; (2) IoT applications often need short response times and require robust event detection, which both are hard to accomplish using existing CEP systems. In this article, we present a novel network architecture, called INetCEP, for efficient CEP-based in-network processing as part of ICN. INetCEP enables efficient data processing in ICN by means of (1) a unified communication model that supports continuous data streams, (2) a meta query language for CEP to specify data processing operations in the data plane, and (3) query processing algorithms to resolve the specified operations. Our experimental results for two IoT use cases and datasets show that INetCEP offers very short response times of up to 73 μs under high workload and is more than 15X faster in terms of forwarding events than the state-of-the-art CEP system Flink. Furthermore, the delivery and processing of complex queries is around 32X faster than Flink and more than 100X faster than a naive pull-based reference approach, while maintaining 100% accuracy.

cs.DC↗

arXiv2020

Mind the GAP: Security & Privacy Risks of Contact Tracing Apps

Google and Apple have jointly provided an API for exposure notification in order to implement decentralized contract tracing apps using Bluetooth Low Energy, the so-called "Google/Apple Proposal", which we abbreviate by "GAP". We demonstrate that in real-world scenarios the current GAP design is vulnerable to (i) profiling and possibly de-anonymizing infected persons, and (ii) relay-based wormhole attacks that basically can generate fake contacts with the potential of affecting the accuracy of an app-based contact tracing system. For both types of attack, we have built tools that can easily be used on mobile phones or Raspberry Pis (e.g., Bluetooth sniffers). The goal of our work is to perform a reality check towards possibly providing empirical real-world evidence for these two privacy and security risks. We hope that our findings provide valuable input for developing secure and privacy-preserving digital contact tracing systems.

cs.CR↗

arXiv2020

PIMOD: A Tool for Configuring Single-Board Computer Operating System Images

Computer systems used in the field of humanitarian technology are often based on general-purpose single-board computers, such as Raspberry Pis. While these systems offer great flexibility for developers and users, configuration and deployment either introduces overhead by executing scripts on multiple devices or requires deeper technical understanding when building operating system images for such small computers from scratch. In this paper, we present PIMOD, a software tool for configuring operating system images for single-board computer systems. We propose a simple yet comprehensive configuration language. In a configuration profile, called Pifile, a small set of commands is used to describe the configuration of an operating system image. Virtualization techniques are used during the execution of the profile in order to be distribution and platform independent. Commands can be issued in the guest operating system, providing access to the distribution specific tools, e.g., to configure hardware parameters. The implementation of PIMOD is made public under a free and open source license. PIMOD is evaluated in terms of user benefits, performance compared to on-system configuration, and applicability across different hardware platforms and operating systems.

cs.OS↗

arXiv2019

DTN7: An Open-Source Disruption-tolerant Networking Implementation of Bundle Protocol 7

In disruption-tolerant networking (DTN), data is transmitted in a store-carry-forward fashion from network node to network node. In this paper, we present an open source DTN implementation, called DTN7, of the recently released Bundle Protocol Version 7 (draft version 13). DTN7 is written in Go and provides features like memory safety and concurrent execution. With its modular design and interchangeable components, DTN7 facilitates DTN research and application development. Furthermore, we present results of a comparative experimental evaluation of DTN7 and other DTN systems including Serval, IBR-DTN, and Forban. Our results indicate that DTN7 is a flexible and efficient open-source multi-platform implementation of the most recent Bundle Protocol Version 7.

cs.NI↗

arXiv2019

Smart Street Lights and Mobile Citizen Apps for Resilient Communication in a Digital City

Currently, nearly four billion people live in urban areas. Since this trend is increasing, natural disasters or terrorist attacks in such areas affect an increasing number of people. While information and communication technology is crucial for the operation of urban infrastructures and the well-being of its inhabitants, current technology is quite vulnerable to disruptions of various kinds. In future smart cities, a more resilient urban infrastructure is imperative to handle the increasing number of hazardous situations. We present a novel resilient communication approach based on smart street lights as part of the public infrastructure. It supports people in their everyday life and adapts its functionality to the challenges of emergency situations. Our approach relies on various environmental sensors and in-situ processing for automatic situation assessment, and a range of communication mechanisms (e.g., public WiFi hotspot functionality and mesh networking) for maintaining a communication network. Furthermore, resilience is not only achieved based on infrastructure deployed by a digital city's municipality, but also based on integrating citizens through software that runs on their mobile devices (e.g., smartphones and tablets). Web-based zero-installation and platform-agnostic apps can switch to device-to-device communication to continue benefiting people even during a disaster situation. Our approach, featuring a covert channel for professional responders and the zero-installation app, is evaluated through a prototype implementation based on a commercially available street light.

cs.HC↗

arXiv2019

Learning Wi-Fi Connection Loss Predictions for Seamless Vertical Handovers Using Multipath TCP

We present a novel data-driven approach to perform smooth Wi-Fi/cellular handovers on smartphones. Our approach relies on data provided by multiple smartphone sensors (e.g., Wi-Fi RSSI, acceleration, compass, step counter, air pressure) to predict Wi-Fi connection loss and uses Multipath TCP to dynamically switch between different connectivity modes. We train a random forest classifier and an artificial neural network on real-world sensor data collected by five smartphone users over a period of three months. The trained models are executed on smartphones to reliably predict Wi-Fi connection loss 15 seconds ahead of time, with a precision of up to 0.97 and a recall of up to 0.98. Furthermore, we present results for four DASH video streaming experiments that run on a Nexus 5 smartphone using available Wi-Fi/cellular networks. The neural network predictions for Wi-Fi connection loss are used to establish MPTCP subflows on the cellular link. The experiments show that our approach provides seamless wireless connectivity, improves quality of experience of DASH video streaming, and requires less cellular data compared to handover approaches without Wi-Fi connection loss predictions.

cs.NI↗