arXiv subjects

Itamar Cohen

Publications and source records attributed to Itamar Cohen.

17 recordsLinked to original sources

arXiv2026

On the generation of astrophysically-relevant intermittent magnetic turbulence in the laboratory

Intermittent magnetic turbulence, namely the presence of non-ordered and clusterized fields, is a ubiquitous phenomenon in space and astrophysical plasmas. It is currently understood that it plays a crucial role in the dynamics of astrophysical systems at all scales, from influencing the evolution of the cosmos as a whole to governing local particle acceleration. While there is direct evidence of turbulence in the solar wind, and despite progress obtained through multi-wavelength observations, most of our knowledge of it outside the solar system derives from indirect evidence, through modeling. Here we show that magnetic turbulence, that quantitatively matches that measured in space, can be reproduced in the laboratory. Starting from a homogeneous magnetized plasma, we randomly perturb it using a speckled laser beam. Using proton radiography, we can follow the development and quantitatively characterize the produced intermittent turbulence from its inception.

physics.plasm-ph↗

arXiv2026

Tidal Response and Thermodynamics of Black Holes

In this work, we revisit black hole Love numbers from two complementary perspectives. First, we develop a manifestly gauge-invariant framework that directly integrates out the short-distance degrees of freedom of a static black hole in arbitrary spacetime dimensions. This approach yields the effective point-particle action and its associated Love numbers without relying on the standard matching procedure or on the Regge-Wheeler equation and its associated master field. Second, we investigate the role of Love numbers in black hole thermodynamics by analyzing a Schwarzschild black hole subjected to various types of external perturbations. We show that Love numbers govern the induced polarization of the black hole and control the leading corrections to its thermodynamic properties, thereby clarifying their physical significance in black hole thermodynamics.

hep-th↗

arXiv2024

Characterization and performance of the Apollon main short-pulse laser beam following its commissioning at 2 PW level

We present the results of the second commissioning phase of the short-focal-length area of the Apollon laser facility (located in Saclay, France), which was performed with the main laser beam (F1), scaled to a peak power of 2 PetaWatt. Under the conditions that were tested, this beam delivered on-target pulses of maximum energy up to 45 J and 22 fs duration. Several diagnostics were fielded to assess the performance of the facility. The on-target focal spot and its spatial stability, as well as the secondary sources produced when irradiating solid targets, have all been characterized, with the goal of helping users design future experiments. The laser-target interaction was characterized, as well as emissions of energetic ions, X-ray and neutrons recorded, all showing good laser-to-target coupling efficiency. Moreover, we demonstrated the simultaneous fielding of F1 with the auxiliary 0.5 PW F2 beam of Apollon, enabling dual beam operation. The present commissioning will be followed in 2025 by a further commissioning stage of F1 at the 8 PW level, en route to the final 10 PW goal.

physics.plasm-ph↗

arXiv2024

Floating-floating point: a highly accurate number representation with flexible Counting ranges

Efficient number representation is essential for federated learning, natural language processing, and network measurement solutions. Due to timing, area, and power constraints, such applications use narrow bit-width (e.g., 8-bit) number systems. The widely used floating-point systems exhibit a trade-off between the counting range and accuracy. This paper introduces Floating-Floating-Point (F2P) - a floating point number that varies the partition between mantissa and exponent. Such flexibility leads to a large counting range combined with improved accuracy over a selected sub-range. Our evaluation demonstrates that moving to F2P from the state-of-the-art improves network measurement accuracy and federated learning.

cs.NI↗

arXiv2024

Bandwidth Efficient Cache Selection and Content Advertisement

Caching is extensively used in various networking environments to optimize performance by reducing latency, bandwidth, and energy consumption. To optimize performance, caches often advertise their content using indicators, which are data structures that trade space efficiency for accuracy. However, this tradeoff introduces the risk of false indications. Existing solutions for cache content advertisement and cache selection often lead to inefficiencies, failing to adapt to dynamic network conditions. This paper introduces SALSA2, a Scalable Adaptive and Learning-based Selection and Advertisement Algorithm, which addresses these limitations through a dynamic and adaptive approach. SALSA2 accurately estimates mis-indication probabilities by considering inter-cache dependencies and dynamically adjusts the size and frequency of indicator advertisements to minimize transmission overhead while maintaining high accuracy. Our extensive simulation study, conducted using a variety of real-world cache traces, demonstrates that SALSA2 achieves up to 84\% bandwidth savings compared to the state-of-the-art solution and close-to-optimal service cost in most scenarios. These results highlight SALSA2's effectiveness in enhancing cache management, making it a robust and versatile solution for modern networking challenges.

cs.NI↗

arXiv2024

Ion acceleration from micrometric targets immersed in an intense laser field

We report on an experimental study of proton acceleration by intense laser irradiation of micrometric bar targets, whose dimensions are transversely immersed in the laser focal volume and are longitudinally smaller than half its wavelength. With only 120 mJ of laser energy, we recorded proton energies in excess of 6~MeV, three times higher than those achieved with flat-foil irradiation using similar pulse energies. 3D particle-in-cell simulations revealed that the efficient energy transfer from the diffracted laser fields to electrons on both sides of the target, combined with its reduced surface area, results in a thicker electron sheath and higher acceleration gradients. We demonstrated numerically how this technique opens up the possibility of laser-ion acceleration in a cascaded manner, allowing manipulation of the ion spectrum by optical means.

physics.plasm-ph↗

arXiv2023

Distributed Asynchronous Service Deployment in the Edge-Cloud Multi-tier Network

In an edge-cloud multi-tier network, datacenters provide services to mobile users, with each service having specific latency constraints and computational requirements. Deploying such a variety of services while matching their requirements with the available computing resources is challenging. In addition, time-critical services may have to be migrated as the users move, to keep fulfilling their latency constraints. Unlike previous work relying on an orchestrator with an always-updated global view of the available resources and the users' locations, this work envisions a distributed solution to the above problems. In particular, we propose a distributed asynchronous framework for service deployment in the edge-cloud that increases the system resilience by avoiding a single point of failure, as in the case of a central orchestrator. Our solution ensures cost-efficient feasible placement of services, while using negligible bandwidth. Our results, obtained through trace-driven, large-scale simulations, show that the proposed solution provides performance very close to those obtained by state-of-the-art centralized solutions, and at the cost of a small communication overhead.

cs.NI↗

arXiv2023

A Comprehensive Characterization of the Neutron Fields Produced by the Apollon Petawatt Laser

Since two decades, laser-driven neutron emissions are studied as they represent a complementary source to conventional neutron sources, with further more different characteristics (i.e. shorter bunch duration and higher number of neutrons per bunch). We report here a global, thorough characterization of the neutron fields produced at the Apollon laser facility using the secondary laser beam (F2). A Double Plasma Mirror (DPM) was used to improve the temporal contrast of the laser which delivers pulses of 24 fs duration, a mean on-target energy of ~10 J and up to 1 shot/min. The interaction of the laser with thin targets (few tens or hundreds of nm) in ultra-high conditions produced enhanced proton beams (up to 35 MeV), which were then used to generate neutrons via the pitcher-catcher technique. The characterization of these neutron emissions is presented, with results obtained from both simulations and measurements using several diagnostics (activation samples, bubble detectors and Time-of-Flight detectors), leading to a neutron yield of ~$4.10^{7}$ neutrons/shot. Similar neutron emissions were observed during shots with and without DPM, while fewer X-rays are produced when the DPM is used, making this tool interesting to adjust the neutrons/X-rays ratio for some applications like combined neutron/X-ray radiography.

physics.acc-ph↗

arXiv2023

Asynchronous Distributed Protocol for Service Provisioning in the Edge-Cloud Continuum

In the edge-cloud continuum, datacenters provide microservices (MSs) to mobile users, with each MS having specific latency constraints and computational requirements. Deploying such a variety of MSs matching their requirements with the available computing resources is challenging. In addition, time-critical MSs may have to be migrated as the users move, to keep meeting their latency constraints. Unlike previous work relying on a central orchestrator with an always-updated global view of the available resources and of the users' locations, this work envisions a distributed solution to the above issues. In particular, we propose a distributed asynchronous protocol for MS deployment in the cloud-edge continuum that (i) dramatically reduces the system overhead compared to a centralized approach, and (ii) increases the system stability by avoiding having a single point of failure as in the case of a central orchestrator. Our solution ensures cost-efficient feasible placement of MSs, while using negligible bandwidth.

cs.NI↗

arXiv2022

On the Power of False Negative Awareness in Indicator-based Caching Systems

Distributed caching systems such as content distribution networks often advertise their content via lightweight approximate indicators (e.g., Bloom filters) to efficiently inform clients where each datum is likely cached. While false-positive indications are necessary and well understood, most existing works assume no false-negative indications. Our work illustrates practical scenarios where false-negatives are unavoidable and ignoring them has a significant impact on system performance. Specifically, we focus on false-negatives induced by indicator staleness, which arises whenever the system advertises the indicator only periodically, rather than immediately reporting every change in the cache. Such scenarios naturally occur, e.g., in bandwidth-constraint environments or when latency impedes the ability of each client to obtain an updated indicator. Our work introduces novel false-negative aware access policies that continuously estimate the false-negative ratio and sometimes access caches despite negative indications. We present optimal policies for homogeneous settings and provide approximation guarantees for our algorithms in heterogeneous environments. We further perform an extensive simulation study with multiple real system traces. We show that our false-negative aware algorithms incur a significantly lower access cost than existing approaches or match the cost of these approaches while requiring an order of magnitude fewer resources (e.g., caching capacity or bandwidth).

cs.NI↗

arXiv2022

False Negative Awareness in Indicator-based Caching Systems

Distributed caching systems such as content distribution networks often advertise their content via lightweight approximate indicators (e.g., Bloom filters) to efficiently inform clients where each datum is likely cached. While false-positive indications are necessary and well understood, most existing works assume no false-negative indications. Our work illustrates practical scenarios where false-negatives are unavoidable and ignoring them significantly impacts system performance. Specifically, we focus on false-negatives induced by indicator staleness, which arises whenever the system advertises the indicator only periodically, rather than immediately reporting every change in the cache. Such scenarios naturally occur, e.g., in bandwidth-constraint environments or when latency impedes each client's ability to obtain an updated indicator. Our work introduces novel false-negative aware access policies that continuously estimate the false-negative ratio and sometimes access caches despite negative indications. We present optimal policies for homogeneous settings and provide approximation guarantees for our algorithms in heterogeneous environments. We further perform an extensive simulation study with multiple real system traces. We show that our false-negative aware algorithms incur a significantly lower access cost than existing approaches or match the cost of these approaches while requiring an order of magnitude fewer resources (e.g., caching capacity or bandwidth).

cs.NI↗

arXiv2022

Dynamic Service Provisioning in the Edge-cloud Continuum with Provable Guarantees

We consider a hierarchical edge-cloud architecture in which services are provided to mobile users as chains of virtual network functions. Each service has specific computation requirements and target delay performance, which require placing the corresponding chain properly and allocating a suitable amount of computing resources. Furthermore, chain migration may be necessary to meet the services' target delay, or convenient to keep the service provisioning cost low. We tackle such issues by formalizing the problem of optimal chain placement and resource allocation in the edge-cloud continuum, taking into account migration, bandwidth, and computation costs. Specifically, we first envision an algorithm that, leveraging resource augmentation, addresses the above problem and provides an upper bound to the amount of resources required to find a feasible solution. We use this algorithm as a building block to devise an efficient approach targeting the minimum-cost solution, while minimizing the required resource augmentation. Our results, obtained through trace-driven, large-scale simulations, show that our solution can provide a feasible solution by using half the amount of resources required by state-of-the-art alternatives.

cs.NI↗

arXiv2022

Parallel Virtual Machines Placement with Provable Guarantees

Network Function Virtualization (NFV) carries the potential for on-demand deployment of network algorithms in virtual machines (VMs). In large clouds, however, VM resource allocation incurs delays that hinder the dynamic scaling of such NFV deployment. Parallel resource management is a promising direction for boosting performance, but it may significantly increase the communication overhead and the decline ratio of deployment attempts. Our work analyzes the performance of various placement algorithms and provides empirical evidence that state-of-the-art parallel resource management dramatically increases the decline ratio of deterministic algorithms but hardly affects randomized algorithms. We, therefore, introduce APSR -- an efficient parallel random resource management algorithm that requires information only from a small number of hosts and dynamically adjusts the degree of parallelism to provide provable decline ratio guarantees. We formally analyze APSR, evaluate it on real workloads, and integrate it into the popular OpenStack cloud management platform. Our evaluation shows that APSR matches the throughput provided by other parallel schedulers, while achieving up to 13x lower decline ratio and a reduction of over 85% in communication overheads.

cs.NI↗

arXiv2021

T-Plots: A Novel Approach to Network Design

It is accepted wisdom that changes in the traffic matrix entail capacity over-provisioning, but there is no simple measure of just how much over-provisioning can buy. In this Thesis, we aim to provide the network designer with a simple view of the network robustness to traffic matrix changes. We first present the Traffic Load Distribution Plots, or T-Plots, a class of plots illustrating the percentage of traffic matrices that can be serviced as a function of the capacity over-provisioning. For instance, from a simple look at their T- Plots, network designers can guarantee that their network services all admissible traffic matrices, or 99% of permutation traffic matrices, or all traffic matrices with ingress/egress load at most half the maximum. We further show that, unfortunately, in the general case plotting T-Plots is #P-Complete, i.e., that it is impossible to plot a T-plot in a polynomial time by the noon tools. However, we show that T-Plots can sometimes be closely modeled as Gaussian, thus only using two values (mean and variance) to quantify the robustness of a capacity allocation to traffic matrix changes. We further utilize these Gaussian T-Plots to provide a more robust capacity allocation. Finally, we demonstrate the benefits of using T-Plots by showing results of extensive Monte Carlo simulations in a real backbone network. This Thesis was submitted in 2007. Since then, the results that appeared in it were applied in various networking environments. In this newer version, we revisit the results 13 years later and explain their relevance to state-of-the-art problems in network design.

cs.NI↗

arXiv2021

Advanced Algorithms in Heterogeneous and Uncertain Networking Environments

Communication networks are used today everywhere and on every scale: starting from small Internet of Things (IoT) networks at home, via campus and enterprise networks, and up to tier-one networks of Internet providers. Accordingly, network devices should support a plethora of tasks with highly heterogeneous characteristics in terms of processing time, bandwidth energy consumption, deadlines and so on. Evaluating these characteristics and the amount of currently available resources for handling them requires analyzing all the arriving inputs, gathering information from numerous remote devices, and integrating all this information. Performing all these tasks in real time is very challenging in today's networking environments, which are characterized by tight bounds on the latency, and always-increasing data rates. Hence, network algorithms should typically make decisions under uncertainty. This work addresses optimizing performance in heterogeneous and uncertain networking environments. We begin by detailing the sources of heterogeneity and uncertainty and show that uncertainty appears in all layers of network design, including the time required to perform a task; the amount of available resources; and the expected gain from successfully completing a task. Next, we survey current solutions and show their limitations. Based on these insights we develop general design concepts to tackle heterogeneity and uncertainty, and then use these concepts to design practical algorithms. For each of our algorithms, we provide rigorous mathematical analysis, thus showing worst-case performance guarantees. Finally, we implement and run the suggested algorithms on various input traces, thus obtaining further insights as to our algorithmic design principles.

cs.NI↗

arXiv2021

Self-adjusting Advertisement of Cache Indicators with Bandwidth Constraints

Cache advertisements reduce the access cost by allowing users to skip the cache when it does not contain their datum. Such advertisements are used in multiple networked domains such as 5G networks, wide area networks, and information-centric networking. The selection of an advertisement strategy exposes a trade-off between the access cost and bandwidth consumption. Still, existing works mostly apply a trial-and-error approach for selecting the best strategy, as the rigorous foundations required for optimizing such decisions is lacking. Our work shows that the desired advertisement policy depends on numerous parameters such as the cache policy, the workload, the cache size, and the available bandwidth. In particular, we show that there is no ideal single configuration. Therefore, we design an adaptive, self-adjusting algorithm that periodically selects an advertisement policy. Our algorithm does not require any prior information about the cache policy, cache size, or workload, and does not require any apriori configuration. Through extensive simulations, using several state-of-the-art cache policies, and real workloads, we show that our approach attains a similar cost to that of the best static configuration (which is only identified in retrospect) in each case.

cs.NI↗

arXiv2019

Queueing in the Mist: Buffering and Scheduling with Limited Knowledge

Scheduling and managing queues with bounded buffers are among the most fundamental problems in computer networking. Traditionally, it is often assumed that all the properties of each packet are known immediately upon arrival. However, as traffic becomes increasingly heterogeneous and complex, such assumptions are in many cases invalid. In particular, in various scenarios information about packet characteristics becomes available only after the packet has undergone some initial processing. In this work, we study the problem of managing queues with limited knowledge. We start by showing lower bounds on the competitive ratio of any algorithm in such settings. Next, we use the insight obtained from these bounds to identify several algorithmic concepts appropriate for the problem, and use these guidelines to design a concrete algorithmic framework. We analyze the performance of our proposed algorithm, and further show how it can be implemented in various settings, which differ by the type and nature of the unknown information. We further validate our results and algorithmic approach by a simulation study that provides further insights as to our algorithmic design principles in face of limited knowledge.

cs.NI↗