arXiv subjects

Henning Schulzrinne

Publications and source records attributed to Henning Schulzrinne.

At least 19 recordsLinked to original sources

arXiv2025

Advancing IoT System Dependability: A Deep Dive into Management and Operation Plane Separation

We propose to enhance the dependability of large-scale IoT systems by separating the management and operation plane. We innovate the management plane to enforce overarching policies, such as safety norms, operation standards, and energy restrictions, and integrate multi-faceted management entities, including regulatory agencies and manufacturers, while the current IoT operational workflow remains unchanged. Central to the management plane is a meticulously designed, identity-independent policy framework that employs flexible descriptors rather than fixed identifiers, allowing for proactive deployment of overarching policies with adaptability to system changes. Our evaluation across three datasets indicates that the proposed framework can achieve near-optimal expressiveness and dependable policy enforcement.

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arXiv2025

Conducting Mission-Critical Voice Experiments with Automated Speech Recognition and Crowdsourcing

Mission-critical voice (MCV) communications systems have been a critical tool for the public safety community for over eight decades. Public safety users expect MCV systems to operate reliably and consistently, particularly in challenging conditions. Because of these expectations, the Public Safety Communications Research (PSCR) Division of the National Institute of Standards and Technology (NIST) has been interested in correlating impairments in MCV communication systems and public safety user quality of experience (QoE). Previous research has studied MCV voice quality and intelligibility in a controlled environment. However, such research has been limited by the challenges inherent in emulating real-world environmental conditions. Additionally, there is the question of the best metric to use to reflect QoE accurately. This paper describes our efforts to develop the methodology and tools for human-subject experiments with MCV. We illustrate their use in human-subject experiments in emulated real-world environments. The tools include a testbed for emulating real-world MCV systems and an automated speech recognition (ASR) robot approximating human subjects in transcription tasks. We evaluate QoE through a Levenshtein Distance-based metric, arguing it is a suitable proxy for measuring comprehension and the QoE. We conducted human-subject studies with Amazon MTurk volunteers to understand the influence of selected system parameters and impairments on human subject performance and end-user QoE. We also compare the performance of several ASR system configurations with human-subject performance. We find that humans generally perform better than ASR in accuracy-related MCV tasks and that the codec significantly influences the end-user QoE and ASR performance.

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arXiv2024

eSIM Technology in IoT Architecture

eSIM(embedded SIM) is an advanced alternative to traditional physical SIM cards initially developed by the GSM Association(GSMA) in 2013 [1][2]. The eSIM technology has been deployed in many commercial products such as mobile devices. However, the application of the eSIM technology in IoT devices has yet to start being primarily deployed. Understanding the eSIM architecture and the basic ideas of the eSIM provisioning and operations is very important for engineers to promote eSIM technology deployment in more areas, both academics and industries. The report focuses on the eSIM technology in the IoT architecture and two major operations of Remote SIM Provisioning(RSP) procedure: the Common Mutual Authentication procedure, a process used to authenticate eSIM trusted communication parties over the public internet, and the Profile Downloading procedure, the way to download the Profile from the operator SM-DP+ server and eventually remotely provision the end-user devices.

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arXiv2021

Roadmap for Edge AI: A Dagstuhl Perspective

Based on the collective input of Dagstuhl Seminar (21342), this paper presents a comprehensive discussion on AI methods and capabilities in the context of edge computing, referred as Edge AI. In a nutshell, we envision Edge AI to provide adaptation for data-driven applications, enhance network and radio access, and allow the creation, optimization, and deployment of distributed AI/ML pipelines with given quality of experience, trust, security and privacy targets. The Edge AI community investigates novel ML methods for the edge computing environment, spanning multiple sub-fields of computer science, engineering and ICT. The goal is to share an envisioned roadmap that can bring together key actors and enablers to further advance the domain of Edge AI.

cs.DC↗

arXiv2021

NSF Broadband Research 2020 Report

The internet has become a critical communications infrastructure, and access is among the ``assets, systems, and networks, whether physical or virtual, [that] are considered so vital to the United States that their incapacitation or destruction would have a debilitating effect on security, national economic security, national public health or safety, or any combination thereof.'' [CISA] But the internet is more than an issue for the nation as a whole. Internet access affects the security, health, safety, and opportunities in life for individuals and communities, and the economic vitality of businesses everywhere. On the one hand, the COVID-19 pandemic has revealed the success of broadband access in allowing society to function, even during lockdowns. On the other hand, the pandemic has exposed weak, unreliable, or even nonexistent, broadband access and usability in many areas and for many individuals, including especially rural residents and children in many school districts, urban, and rural, as well as a compelling need for universal reach and affordability. It was thus timely that in November 2020, the National Science Foundation (NSF) sponsored a series of workshops to identify new research areas to drive the broadband NSF agenda for the next five years. This request followed similar initiatives during the past twenty years, the most recent in 2016. This Broadband Research Workshop Report of 2021 discusses the research questions and challenges that need to be addressed to provide robust, affordable, and meaningful broadband access to every resident of the United States.

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arXiv2021

Centralization is about Control, not Protocols (Position Paper)

Many common ``consumer'' applications, i.e., applications widely used by non-technical users, are now provided by a very small number of companies, even if that set of companies differ across geographic regions, or rely on a very small number of implementations even if the applications are largely standards-based. While likely only a partial solution, we can draw on earlier regulatory experiences to facilitate competition or at least lessen the impact of the lack thereof.

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arXiv2021

An Analysis of Amazon Echo's Network Behavior

With over 20 million units sold since 2015, Amazon Echo, the Alexa-enabled smart speaker developed by Amazon, is probably one of the most widely deployed Internet of Things consumer devices. Despite the very large installed base, surprisingly little is known about the device's network behavior. We modify a first generation Echo device, decrypt its communication with Amazon cloud, and analyze the device pairing, Alexa Voice Service, and drop-in calling protocols. We also describe our methodology and the experimental setup. We find a minor shortcoming in the device pairing protocol and learn that drop-in calls are end-to-end encrypted and based on modern open standards. Overall, we find the Echo to be a well-designed device from the network communication perspective.

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arXiv2021

Checkpointing and Migration of IoT Edge Functions

The serverless and functions as a service (FaaS) paradigms are currently trending among cloud providers and are now increasingly being applied to the network edge, and to the Internet of Things (IoT) devices. The benefits include reduced latency for communication, less network traffic and increased privacy for data processing. However, there are challenges as IoT devices have limited resources for running multiple simultaneous containerized functions, and also FaaS does not typically support long-running functions. Our implementation utilizes Docker and CRIU for checkpointing and suspending long-running blocking functions. The results show that checkpointing is slightly slower than regular Docker pause, but it saves memory and allows for more long-running functions to be run on an IoT device. Furthermore, the resulting checkpoint files are small, hence they are suitable for live migration and backing up stateful functions, therefore improving availability and reliability of the system.

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arXiv2021

Talking After Lights Out: An Ad Hoc Network for Electric Grid Recovery

When the electric grid in a region suffers a major outage, e.g., after a catastrophic cyber attack, a "black start" may be required, where the grid is slowly restarted, carefully and incrementally adding generating capacity and demand. To ensure safe and effective black start, the grid control center has to be able to communicate with field personnel and with supervisory control and data acquisition (SCADA) systems. Voice and text communication are particularly critical. As part of the Defense Advanced Research Projects Agency (DARPA) Rapid Attack Detection, Isolation, and Characterization Systems (RADICS) program, we designed, tested and evaluated a self-configuring mesh network architecture and prototype called the Phoenix Secure Emergency Network (PhoenixSEN). PhoenixSEN is designed as a drop-in replacement for primary communication networks, combines existing and new technologies, can work with a variety of link-layer protocols, emphasizes manageability and auto-configuration, and provides a core set of services and applications for coordination of people and devices including voice, text, and SCADA communication. The PhoenixSEN prototype was evaluated in the field through a series of DARPA-led exercises. The same system is also likely to support coordination of recovery efforts after large-scale natural disasters.

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arXiv2021

Social Distancing and the Internet: What Can Network Performance Measurements Tell Us?

The COVID-19 pandemic and related restrictions forced many to work, learn, and socialize from home over the internet. There appears to be consensus that internet infrastructure in the developed world handled the resulting traffic surge well. In this paper, we study network measurement data collected by the Federal Communications Commission's Measuring Broadband America program before and during the pandemic in the United States (US). We analyze the data to understand the impact of lockdown orders on the performance of fixed broadband internet infrastructure across the US, and also attempt to correlate internet usage patterns with the changing behavior of users during lockdown. We found the key metrics such as change in data usage to be generally consistent with the literature. Through additional analysis, we found differences between metro and rural areas, changes in weekday, weekend, and hourly internet usage patterns, and indications of network congestion for some users.

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arXiv2021

Computing Research Challenges in Next Generation Wireless Networking

By all measures, wireless networking has seen explosive growth over the past decade. Fourth Generation Long Term Evolution (4G LTE) cellular technology has increased the bandwidth available for smartphones, in essence, delivering broadband speeds to mobile devices. The most recent 5G technology is further enhancing the transmission speeds and cell capacity, as well as, reducing latency through the use of different radio technologies and is expected to provide Internet connections that are an order of magnitude faster than 4G LTE. Technology continues to advance rapidly, however, and the next generation, 6G, is already being envisioned. 6G will make possible a wide range of powerful, new applications including holographic telepresence, telehealth, remote education, ubiquitous robotics and autonomous vehicles, smart cities and communities (IoT), and advanced manufacturing (Industry 4.0, sometimes referred to as the Fourth Industrial Revolution), to name but a few. The advances we will see begin at the hardware level and extend all the way to the top of the software "stack." Artificial Intelligence (AI) will also start playing a greater role in the development and management of wireless networking infrastructure by becoming embedded in applications throughout all levels of the network. The resulting benefits to society will be enormous. At the same time these exciting new wireless capabilities are appearing rapidly on the horizon, a broad range of research challenges loom ahead. These stem from the ever-increasing complexity of the hardware and software systems, along with the need to provide infrastructure that is robust and secure while simultaneously protecting the privacy of users. Here we outline some of those challenges and provide recommendations for the research that needs to be done to address them.

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arXiv2019

SynGAN: Towards Generating Synthetic Network Attacks using GANs

The rapid digital transformation without security considerations has resulted in the rise of global-scale cyberattacks. The first line of defense against these attacks are Network Intrusion Detection Systems (NIDS). Once deployed, however, these systems work as blackboxes with a high rate of false positives with no measurable effectiveness. There is a need to continuously test and improve these systems by emulating real-world network attack mutations. We present SynGAN, a framework that generates adversarial network attacks using the Generative Adversial Networks (GAN). SynGAN generates malicious packet flow mutations using real attack traffic, which can improve NIDS attack detection rates. As a first step, we compare two public datasets, NSL-KDD and CICIDS2017, for generating synthetic Distributed Denial of Service (DDoS) network attacks. We evaluate the attack quality (real vs. synthetic) using a gradient boosting classifier.

cs.LG↗

arXiv2019

Capacity and Energy-Efficiency of Delayed Access Scheme for Small Cell Networks

Data applications may typically tolerate a moderate delay before packet transmission between user equipment (UE) and cell begins. This delay can be taken advantage to reduce the communication distance, improve coverage probability, and increase overall energy-efficiency of the small cell network. To demonstrate such merits, we suggest a simple access scheme and analyze the distribution of coverage probability and throughput as a function of delay and transmit distance. Sufficient number of small base stations (SBSs) handle the peak traffic load. To improve energy-efficiency of the network, a number of SBSs are switched off at low traffic periods. Energy-efficiency can be further improved by turning all of the SBSs on and off, rather than selecting a subset and leaving them off. By doing so, coverage probability and bit-rate can be improved by delaying their transmissions and waiting for a closer SBS to become available. Results show that by turning SBSs on and off continuously and taking advantage of initial delay to connect a SBS yield an order of magnitude improvement in energy-efficiency, improves the coverage probability significantly at low signal to interference and noise (SINR) regime.

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arXiv2019

Should I stay or should I go: Analysis of the impact of application QoS on user engagement in YouTube

To improve the quality of experience (QoE), especially under moderate to high traffic demand, it is important to understand the impact of the network and application QoS on user experience. This paper comparatively evaluates the impact of impairments, their intensity and temporal dynamics, on user engagement in the context of video streaming. The analysis employed two large YouTube datasets. To characterize the user engagement and the impact of impairments, several new metrics were defined. We assessed whether or not there is a statistically significant relationship between different types of impairments and QoE and user engagement metrics, taking into account not only the characteristics of the impairments but also the covariates of the session (e.g., video duration, mean datarate). After observing the relationships across the entire dataset, we tested whether these relationships also persist under specific conditions with respect to the covariates. The introduction of several new metrics and of various covariates in the analysis are two innovative aspects of this work. We found that the number of negative bitrate changes (BR-) is a stronger predictor of abandonment than rebufferrings (RB). Even positive bitrate changes (BR+) are associated with increases in abandonment. Specifically, BR+ in low resolution sessions is not well received. Temporal dynamics of the impairments have also an impact: a BR- that follows much later a RB appears to be perceived as a worse impairment than a BR- that occurs immediately after a RB. These results can be used to guide the design of the video streaming adaptation as well as suggest which parameters should be varied in controlled field studies.

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arXiv2019

The Dagstuhl Beginners Guide to Reproducibility for Experimental Networking Research

Reproducibility is one of the key characteristics of good science, but hard to achieve for experimental disciplines like Internet measurements and networked systems. This guide provides advice to researchers, particularly those new to the field, on designing experiments so that their work is more likely to be reproducible and to serve as a foundation for follow-on work by others.

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arXiv2018

Load-Based On/Off Scheduling for Energy-Efficient Delay-Tolerant 5G Networks

Dense deployment of small cells is seen as one of the major approaches for addressing the traffic demands in next-generation 5G wireless networks. The energy efficiency, however, becomes a key concern together with this massive amount of small cells. In this study, we therefore consider the energy-efficient small cell networks (SCN) using smart on/off scheduling (OOS) strategies, where a certain fraction of small base stations (SBS) are put into less energy-consuming sleeping states to save energy. To this end, we first represent the overall SCN traffic by a new load variable, and analyze its statistics rigorously using Gamma approximation. We then propose two novel OOS algorithms exploiting this load variable in centralized and distributed fashions. We show that proposed load based OOS algorithms can lead to as high as 50\% of energy savings without sacrificing the average SCN throughput. In addition, load based strategies are shown to work well under high SCN traffic and delay-intolerant circumstances, and can be implemented efficiently using the load statistics. We also show that the performance of load based algorithms gets maximized for certain length of sleeping periods, where assuming short sleep periods is as energy-inefficient as keeping SBSs in sleep states for very long.

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arXiv2018

Predicting Floor-Level for 911 Calls with Neural Networks and Smartphone Sensor Data

In cities with tall buildings, emergency responders need an accurate floor level location to find 911 callers quickly. We introduce a system to estimate a victim's floor level via their mobile device's sensor data in a two-step process. First, we train a neural network to determine when a smartphone enters or exits a building via GPS signal changes. Second, we use a barometer equipped smartphone to measure the change in barometric pressure from the entrance of the building to the victim's indoor location. Unlike impractical previous approaches, our system is the first that does not require the use of beacons, prior knowledge of the building infrastructure, or knowledge of user behavior. We demonstrate real-world feasibility through 63 experiments across five different tall buildings throughout New York City where our system predicted the correct floor level with 100% accuracy.

cs.CY↗

arXiv2018

Networking Research - A Reflection in the Middle Years

Networking is no longer a new area of computer science and engineering -- it has matured as a discipline and the major infrastructure it supports, the Internet, is long past being primarily a research artifact. I believe that we should consider ourselves as the civil engineers of the Internet, primarily helping to understand and improve a vast and critical infrastructure. This implies that implementing changes takes decades, not conference cycles, and that implementation is largely driven by compatibility with existing infrastructure and considerations of cost effectiveness, where resources that research focuses on, such as bandwidth and compute cycles, often play a much smaller role than limited organizational capacity for change. Telecommunications carriers, in particular, have become akin to airlines, largely operating equipment designed by others, with emphasis on marketing, not innovation. Even more than in other engineering disciplines, standards matter, whether set by standards bodies or dominant players. Given the multi-year time frames of standards and the limited willingness of national funding bodies to support standardization work, this makes research impact harder, as does the increasing complexity of cellular networks and barriers to entry that shut out most researchers from contributing to large parts of commercial mobile networks.

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