COMM

Accelerators, such as GPUs, SmartNICs and FPGAs, are common components of research systems today. This paper focuses on the question of how to fairly compare these systems. This is challenging because it requires comparing systems that use different ...

While many network research papers address issues of deployability, with a few exceptions, this has been limited to protocol compatibility or switch-resource constraints, such as flow table sizes. We argue that good network designs must also consider ...

Compute Express Link (CXL) is a replacement for PCIe. With much lower latency than PCIe and hardware support for cache coherence, programs can efficiently access remote memory over CXL. These capabilities have opened the possibility of CXL memory pools ...

We propose logical memory pools, a memory disaggregation architecture for the emerging Compute Express Link (CXL) technology in datacenters. The key idea is to create a memory pool by carving out parts of the local memory in each server, rather than ...

Investigating Internet incidents involves significant human effort and is limited by the domain knowledge of network researchers and operators. In this paper, we propose to develop computational software agents based on emerging language models (e.g., ...

We explore the application of Large Language Models (LLMs) (specifically GPT-3.5-turbo) to extract specifications and automating understanding of networking protocols from Internet Request for Comments (RFC) documents. LLMs have proven successful in ...

Owing to its adaptability and scalability, Machine Learning (ML) has gained significant momentum in the networking community. Yet, ML models can still produce outputs that contradict knowledge, i.e., established networking rules and principles. On the ...

Reproducing research results is important for the networking community. The current best practice typically resorts to: (1) looking for publicly available prototypes; (2) contacting the authors to get a private prototype; or (3) manually implementing a ...

We are used to defining network neutrality as absence of traffic differentiation, like policing or shaping. These mechanisms, however, are often not what determines end-users' quality of experience (QoE). Most content today is accessed through edge ...

Google, Netflix, Meta, and Akamai serve content to users from offnet servers in thousands of ISPs. These offnets benefit both services and ISPs, via better performance and reduced interdomain and WAN traffic. We argue that this widespread distribution ...

The existing Internet architecture lacks support for naming locations and resolving them to the myriad addressing mechanisms we use beyond IP. We propose the Spatial Name System (SNS) that allows for the assignment of hierarchical location-based names ...

With the rise of microservices, the execution environment of many cloud applications has become a set of virtual machines or containers connected by a flexible and feature-rich virtual network. We argue that the implementation of such virtual networks ...

Cloud computing has transformed the IT industry, but managing cloud infrastructures remains a difficult task. We make a case for putting today's management practices, known as "Infrastructure-as-Code," on a firmer ground via a principled design. We call ...

Dramatic growth in Internet connectivity poses a challenge for the resource-constrained data collection efforts that support scientific and operational analysis of interdomain routing. Inspired by tradeoffs made in other disciplines, we explore a ...

Network measurement has long focused on the bits and bytes --- low-level network metrics such as latency and throughput, which have the advantage of being objective and directly characterizing the performance of the network. We argue that users provide ...

Defining a universal metric for Quality of Experience (QoE) is notoriously hard due to the complex relationship between low-level performance metrics and user satisfaction. The most common metric, the Mean Opinion Score (MOS), has well-known biases and ...

Traffic modeling of Datacenter Network (DCN) today is over-simplified, deviating from the ground truth. Adopted by numerous researchers, the common practice relies on the assumptions of traffic homogeneity and independence for ease of use. Based on our ...

Recently, much attention has been devoted to the development of generative network traces and their potential use in supplementing real-world data for a variety of data-driven networking tasks. Yet, the utility of existing synthetic traffic approaches ...

Interactive networked applications require high throughput, low latency, and high reliability from the network to provide a seamless user experience. While meeting these three requirements simultaneously is difficult, there has been an emergence of ...

Achieving the optimal balance of minimizing bandwidth consumption and end-to-end latency while preserving a satisfactory level of visual quality becomes the ultimate goal of live, interactive holographic communication, a fundamental building block of ...

Spectrum monitoring is vital for optimizing wireless spectrum usage, minimizing interference, and ensuring efficient communication systems. In large-scale monitoring systems, the issue of trust in sensor data becomes critical. Separate from the issue of ...

New methods of passive wireless communication are presented where no RF carrier is needed. Instead, data is wirelessly transmitted by modulating noise sources, from those found in electronic components to extraterrestrial noise sources. Any pair of ...

The complexity of operator networks and myriad of specialized metrics produced by network function providers present a formidable challenge in retrieving and analyzing operator data, a vital component for network operations. This necessitates specialist ...

We discuss the potential improvement large language models (LLM) can provide in incident management and how they can overhaul the ways operators conduct incident management today. We propose a holistic framework for building an AI helper for incident ...

We investigate whether Large Language Models (e.g., GPT-4) can synthesize correct router configurations with reduced manual effort. We find GPT-4 works very badly by itself, producing promising draft configurations but with egregious errors in topology, ...

Analyzing network topologies and communication graphs is essential in modern network management. However, the lack of a cohesive approach results in a steep learning curve, increased errors, and inefficiencies. In this paper, we present a novel approach ...

The conventional definition of fairness in congestion control is flow rate fairness. However, Internet users typically care about flow completion times (FCTs) and flow rate fairness does not lead to equitable FCTs for different users. Therefore, we ...

In this paper, our primary objective is to showcase that the application of machine learning techniques extends beyond network protocol design. We aim to demonstrate that performance assessment of network protocols, a vital aspect of improving network ...

Despite 40 years of active research on congestion control, there has been little or no consideration of how it impacts the energy usage of end-hosts or networking equipment. Particularly with the burgeoning energy consumption of data centers and wide-...

This paper asks whether inter-flow contention between congestion control algorithms (CCAs) is a dominant factor in determining a flow's bandwidth allocation in today's Internet. We hypothesize that CCA contention typically does not determine a flow's ...