arXiv subjects

Cedric Westphal

Publications and source records attributed to Cedric Westphal.

At least 19 recordsLinked to original sources

arXiv2024

Towards a Dynamic Future with Adaptable Computing and Network Convergence (ACNC)

In the context of advancing 6G, a substantial paradigm shift is anticipated, highlighting comprehensive everything-to-everything interactions characterized by numerous connections and stringent adherence to Quality of Service/Experience (QoS/E) prerequisites. The imminent challenge stems from resource scarcity, prompting a deliberate transition to Computing-Network Convergence (CNC) as an auspicious approach for joint resource orchestration. While CNC-based mechanisms have garnered attention, their effectiveness in realizing future services, particularly in use cases like the Metaverse, may encounter limitations due to the continually changing nature of users, services, and resources. Hence, this paper presents the concept of Adaptable CNC (ACNC) as an autonomous Machine Learning (ML)-aided mechanism crafted for the joint orchestration of computing and network resources, catering to dynamic and voluminous user requests with stringent requirements. ACNC encompasses two primary functionalities: state recognition and context detection. Given the intricate nature of the user-service-computing-network space, the paper employs dimension reduction to generate live, holistic, abstract system states in a hierarchical structure. To address the challenges posed by dynamic changes, Continual Learning (CL) is employed, classifying the system state into contexts controlled by dedicated ML agents, enabling them to operate efficiently. These two functionalities are intricately linked within a closed loop overseen by the End-to-End (E2E) orchestrator to allocate resources. The paper introduces the components of ACNC, proposes a Metaverse scenario to exemplify ACNC's role in resource provisioning with Segment Routing v6 (SRv6), outlines ACNC's workflow, details a numerical analysis for efficiency assessment, and concludes with discussions on relevant challenges and potential avenues for future research.

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arXiv2023

Networking for the Metaverse: The Standardization Landscape

New applications are being supported by current and future networks. In particular, it is expected that Metaverse applications will be deployed in the near future, as 5G and 6G network provide sufficient bandwidth and sufficiently low latency to provide a satisfying end-user experience. However, networks still need to evolve to better support this type of application. We present here a basic taxonomy of the metaverse, which allows to identify some of the networking requirements for such an application; we also provide an overview of the current state of balthe standardization efforts in different standardization organizations, including ITU-T, 3GPP, IETF and MPAI.

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arXiv2023

LEO Satellite Networking Relaunched: Survey and Current Research Challenges

This document surveys recent and current developments in LEO satellite networking. It presents a brief overview of satellite networking in order to contextualize the issue. It then focuses on current research work in emerging domains, such as Machine Learning, SDN, low latency networking, green networking, Information-Centric Networks, etc. For each, it presents recent works and a direction of the research community within that emerging domain. The paper also describes the current state of standardization efforts in 3GPP and in IETF for LEO satellite networking. In particular, we present in some detail the direction these standards body are pointing towards for LEO networking with inter-satellites links. Finally, some future challenges and interesting research directions are described and motivated. This is an overview of the current state of the LEO satellite research in both academic and industrial standardization environments which we believe will be helpful to understand the current state of the art.

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arXiv2023

Optimization Framework for Green Networking

Reducing energy consumption - and especially carbon emissions - is one of the most important challenges facing humankind. ICT (Information and Communication Technology) is a powerful tool to reduce emissions as it offers alternatives to activities that are costly in energy: video streaming saves energy vs driving to a movie theater, for instance. Still, the carbon footprint of ICT in general and networking in particular have been growing, despite better energy efficiency per transmitted bit, due to the sheer growth in Internet usage and traffic. The information and communication technology (ICT) sector is currently estimated to create 2.7% of all global CO2 emissions and expected to continue to increase. Hence, monitoring and reducing the CO2 emissions from ICT is increasingly important. Networks are responsible for around 13% of ICT energy consumption, a third of which in turn is attributable to backbone (core) networks. As such, it is important to offer new mechanisms to reduce the energy footprint of networks. In this paper, we present a framework to include energy considerations (as a proxy for carbon footprint) into the management plane of a network. We apply this framework to optimize the network topology so as to minimize the energy spending while at the same time providing a satisfactory Quality of Experience (QoE) to the end users. We present this framework along high-level considerations, as its deployment and evaluation is left for future work.

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arXiv2019

Reversing The Meaning of Node Connectivity for Content Placement in Networks of Caches

It is a widely accepted heuristic in content caching to place the most popular content at the nodes that are the best connected. The other common heuristic is somewhat contradictory, as it places the most popular content at the edge, at the caching nodes nearest the users. We contend that neither policy is best suited for caching content in a network and propose a simple alternative that places the most popular content at the least connected node. Namely, we populate content first at the nodes that have the lowest graph centrality over the network topology. Here, we provide an analytical study of this policy over some simple topologies that are tractable, namely regular grids and trees. Our mathematical results demonstrate that placing popular content at the least connected nodes outperforms the aforementioned alternatives in typical conditions.

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arXiv2019

A Framework for Qualitative Communications Using Big Packet Protocol

In the current Internet architecture, a packet is a minimal or fundamental unit upon which different actions such as classification,forwarding, or discarding are performed by the network nodes.When faced with constrained or poor network conditions, a packet is subjected to undesirable drops and re-transmissions, resulting in unpredictable delays and subsequent traffic overheads in the network. Alternately, we introduce qualitative communication services which allow partial, yet timely, delivery of a packet instead of dropping it entirely. These services allow breaking down packet payloads into smaller units (called chunks), enabling much finer granularity of bandwidth utilization. We propose Packet Wash as a new operation in forwarding nodes to support qualitative services. Upon packet error or network congestion, the forwarding node selectively removes some chunk(s)from the payload based on the relationship among the chunks or the individual significance level of each chunk. We also present a qualitative communication framework as well as a Packet Wash directive implemented in a newly evolved data plane technology,called Big Packet Protocol (BPP)

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arXiv2017

Offloading Content with Self-organizing Mobile Fogs

Mobile users in an urban environment access content on the internet from different locations. It is challenging for the current service providers to cope with the increasing content demand from a large number of collocated mobile users. In-network caching to offload content at nodes closer to users alleviate the issue, though efficient cache management is required to find out who should cache what, when and where in an urban environment, given nodes limited computing, communication and caching resources. To address this, we first define a novel relation between content popularity and availability in the network and investigate a node's eligibility to cache content based on its urban reachability. We then allow nodes to self-organize into mobile fogs to increase the distributed cache and maximize content availability in a cost-effective manner. However, to cater rational nodes, we propose a coalition game for the nodes to offer a maximum "virtual cache" assuming a monetary reward is paid to them by the service/content provider. Nodes are allowed to merge into different spatio-temporal coalitions in order to increase the distributed cache size at the network edge. Results obtained through simulations using realistic urban mobility trace validate the performance of our caching system showing a ratio of 60-85% of cache hits compared to the 30-40% obtained by the existing schemes and 10% in case of no coalition.

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arXiv2017

A Content-based Centrality Metric for Collaborative Caching in Information-Centric Fogs

Information-Centric Fog Computing enables a multitude of nodes near the end-users to provide storage, communication, and computing, rather than in the cloud. In a fog network, nodes connect with each other directly to get content locally whenever possible. As the topology of the network directly influences the nodes' connectivity, there has been some work to compute the graph centrality of each node within that network topology. The centrality is then used to distinguish nodes in the fog network, or to prioritize some nodes over others to participate in the caching fog. We argue that, for an Information-Centric Fog Computing approach, graph centrality is not an appropriate metric. Indeed, a node with low connectivity that caches a lot of content may provide a very valuable role in the network. To capture this, we introduce acontent-based centrality (CBC) metric which takes into account how well a node is connected to the content the network is delivering, rather than to the other nodes in the network. To illustrate the validity of considering content-based centrality, we use this new metric for a collaborative caching algorithm. We compare the performance of the proposed collaborative caching with typical centrality based, non-centrality based, and non-collaborative caching mechanisms. Our simulation implements CBC on three instances of large scale realistic network topology comprising 2,896 nodes with three content replication levels. Results shows that CBC outperforms benchmark caching schemes and yields a roughly 3x improvement for the average cache hit rate.

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arXiv2017

Resolution-Based Content Discovery in Network of Caches: Is the Control Traffic an Issue?

As networking attempts to cleanly separate the control plane and forwarding plane abstractions, it also defines a clear interface between these two layers. An underlying network state is represented as a view to act upon in the control plane. We are interested in studying some fundamental properties of this interface, both in a general framework, and in the specific case of content routing. We try to evaluate the traffic between the two planes based on allowing a minimum level of acceptable distortion in the network state representation in the control plane. We apply our framework to content distribution, and see how we can compute the overhead of maintaining the location of content in the control plane. This is of importance to evaluate resolution-based content discovery in content-oriented network architectures: we identify scenarios where the cost of updating the control plane for content routing overwhelms the benefit of fetching the nearest copy. We also show how to minimize the cost of this overhead when associating costs to peering traffic and to internal traffic for network of caches.

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arXiv2016

Fundamental Limits on Throughput Capacity in Information-Centric Network

Wireless information-centric networks consider storage as one of the network primitives, and propose to cache data within the network in order to improve latency and reduce bandwidth consumption. We study the throughput capacity and latency in an information-centric network when the data cached in each node has a limited lifetime. The results show that with some fixed request and cache expiration rates, the order of the data access time does not change with network growth, and the maximum throughput order is not changing with the network growth in grid networks, and is inversely proportional to the number of nodes in one cell in random networks. Comparing these values with the corresponding throughput and latency with no cache capability (throughput inversely proportional to the network size, and latency of order $\sqrt{n}$ and the inverse of the transmission range in grid and random networks, respectively), we can actually quantify the asymptotic advantage of caching. Moreover, we compare these scaling laws for different content discovery mechanisms and illustrate that not much gain is lost when a simple path search is used.

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arXiv2016

Resource Provisioning and Profit Maximization for Transcoding in Information Centric Networking

Adaptive bitrate streaming (ABR) has been widely adopted to support video streaming services over heterogeneous devices and varying network conditions. With ABR, each video content is transcoded into multiple representations in different bitrates and resolutions. However, video transcoding is computing intensive, which requires the transcoding service providers to deploy a large number of servers for transcoding the video contents published by the content producers. As such, a natural question for the transcoding service provider is how to provision the computing resource for transcoding the video contents while maximizing service profit. To address this problem, we design a cloud video transcoding system by taking the advantage of cloud computing technology to elastically allocate computing resource. We propose a method for jointly considering the task scheduling and resource provisioning problem in two timescales, and formulate the service profit maximization as a two-timescale stochastic optimization problem. We derive some approximate policies for the task scheduling and resource provisioning. Based on our proposed methods, we implement our open source cloud video transcoding system Morph and evaluate its performance in a real environment. The experiment results demonstrate that our proposed method can reduce the resource consumption and achieve a higher profit compared with the baseline schemes.

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arXiv2015

Scaling Laws of the Throughput Capacity and Latency in Information-Centric Networks

Wireless information-centric networks consider storage as one of the network primitives, and propose to cache data within the network in order to improve latency and reduce bandwidth consumption. We study the throughput capacity and delay in an information-centric network when the data cached in each node has a limited lifetime. The results show that with some fixed request and cache expiration rates, the order of the data access time does not change with network growth, and the maximum throughput order is inversely proportional to the square root and logarithm of the network size $n$ in cases of grid and random networks, respectively. Comparing these values with the corresponding throughput and latency with no cache capability (throughput inversely proportional to the network size, and latency of order $\sqrt{n}$ and $\sqrt{\frac{n}{\log n}}$ in grid and random networks, respectively), we can actually quantify the asymptotic advantage of caching. Moreover, we compare these scaling laws for different content discovery mechanisms and illustrate that not much gain is lost when a simple path search is used.

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arXiv2015

Service Provisioning and Profit Maximization in Network-assisted Adaptive HTTP Streaming

Adaptive HTTP streaming with centralized consideration of multiple streams has gained increasing interest. It poses a special challenge that the interests of both content provider and network operator need to be deliberately balanced. More importantly, the adaptation strategy is required to be flexible enough to be ported to various systems that work under different network environments, QoE levels, and economic objectives. To address these challenges, we propose a Markov Decision Process (MDP) based network-assisted adaptation framework, wherein cost of buffering, significant playback variation, bandwidth management and income of playback are jointly investigated. We then demonstrate its promising service provisioning and maximal profit for a mobile network in which fair or differentiated service is required.

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arXiv2015

Exploiting Network Awareness to Enhance DASH Over Wireless

The introduction of Dynamic Adaptive Streaming over HTTP (DASH) helped reduce the consumption of resource in video delivery, but its client-based rate adaptation is unable to optimally use the available end-to-end network bandwidth. We consider the problem of optimizing the delivery of video content to mobile clients while meeting the constraints imposed by the available network resources. Observing the bandwidth available in the network's two main components, core network, transferring the video from the servers to edge nodes close to the client, and the edge network, which is in charge of transferring the content to the user, via wireless links, we aim to find an optimal solution by exploiting the predictability of future user requests of sequential video segments, as well as the knowledge of available infrastructural resources at the core and edge wireless networks in a given future time window. Instead of regarding the bottleneck of the end-to-end connection as our throughput, we distribute the traffic load over time and use intermediate nodes between the server and the client for buffering video content to achieve higher throughput, and ultimately significantly improve the Quality of Experience for the end user in comparison with current solutions.

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arXiv2014

The Price of Updating the Control Plane in Information-Centric Networks

We are studying some fundamental properties of the interface between control and data planes in Information-Centric Networks. We try to evaluate the traffic between these two planes based on allowing a minimum level of acceptable distortion in the network state representation in the control plane. We apply our framework to content distribution, and see how we can compute the overhead of maintaining the location of content in the control plane. This is of importance to evaluate content-oriented network architectures: we identify scenarios where the cost of updating the control plane for content routing overwhelms the benefit of fetching a nearby copy. We also show how to minimize the cost of this overhead when associating costs to peering traffic and to internal traffic for operator-driven CDNs.

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arXiv2014

A Stable Fountain Code Mechanism for Peer-to-Peer Content Distribution

Most peer-to-peer content distribution systems require the peers to privilege the welfare of the overall system over greedily maximizing their own utility. When downloading a file broken up into multiple pieces, peers are often asked to pass on some possible download opportunities of common pieces in order to favor rare pieces. This is to avoid the missing piece syndrome, which throttles the download rate of the peer-to-peer system to that of downloading the file straight from the server. In other situations, peers are asked to stay in the system even though they have collected all the file's pieces and have an incentive to leave right away. We propose a mechanism which allows peers to act greedily and yet stabilizes the peer-to-peer content sharing system. Our mechanism combines a fountain code at the server to generate innovative new pieces, and a prioritization for the server to deliver pieces only to new peers. While by itself, neither the fountain code nor the prioritization of new peers alone stabilizes the system, we demonstrate that their combination does, through both analytical and numerical evaluation.

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arXiv2013

On the Benefit of Information Centric Networks for Traffic Engineering

Current Internet performs traffic engineering (TE) by estimating traffic matrices on a regular schedule, and allocating flows based upon weights computed from these matrices. This means the allocation is based upon a guess of the traffic in the network based on its history. Information-Centric Networks on the other hand provide a finer-grained description of the traffic: a content between a client and a server is uniquely identified by its name, and the network can therefore learn the size of different content items, and perform traffic engineering and resource allocation accordingly. We claim that Information-Centric Networks can therefore provide a better handle to perform traffic engineering, resulting in significant performance gain. We present a mechanism to perform such resource allocation. We see that our traffic engineering method only requires knowledge of the flow size (which, in ICN, can be learned from previous data transfers) and outperforms a min-MLU allocation in terms of response time. We also see that our method identifies the traffic allocation patterns similar to that of min-MLU without having access to the traffic matrix ahead of time. We show a very significant gain in response time where min MLU is almost 50% slower than our ICN-based TE method.

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arXiv2013

WARP: A ICN architecture for social data

Social network companies maintain complete visibility and ownership of the data they store. However users should be able to maintain full control over their content. For this purpose, we propose WARP, an architecture based upon Information-Centric Networking (ICN) designs, which expands the scope of the ICN architecture beyond media distribution, to provide data control in social networks. The benefit of our solution lies in the lightweight nature of the protocol and in its layered design. With WARP, data distribution and access policies are enforced on the user side. Data can still be replicated in an ICN fashion but we introduce control channels, named \textit{thread updates}, which ensures that the access to the data is always updated to the latest control policy. WARP decentralizes the social network but still offers APIs so that social network providers can build products and business models on top of WARP. Social applications run directly on the user's device and store their data on the user's \textit{butler} that takes care of encryption and distribution. Moreover, users can still rely on third parties to have high-availability without renouncing their privacy.

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