Grooming Algorithm Research Articles

Dynamic multicast traffic grooming in light-trail WDM optical mesh networks

A light trail in a WDM optical network is an optical communication channel that allows intermediate nodes to access the channel providing the flexibility for multiplexing traffic of multiple connections into the optical communication channel at intermediate nodes. The technique of multiplexing traffic of multiple connections into a single communication channel is known as traffic grooming. This paper studies the problem of dynamic multicast traffic grooming that deals with dynamically arriving and departing multicast connections in light-trail WDM optical networks. Our objective is to reduce blocking ratio. This paper proposes an auxiliary graph model for light-trail WDM optical networks that can be used for routing and traffic grooming purposes. Based on the auxiliary graph model, two dynamic multicast traffic grooming algorithms are studied. Compared with existing algorithms in the literature, the two algorithms yield significantly better performance.

Evaluation of lossless and lossy algorithms for the compression of scientific datasets in netCDF-4 or HDF5 files

Abstract. The increasing volume of scientific datasets requires the use of compression to reduce data storage and transmission costs, especially for the oceanographic or meteorological datasets generated by Earth observation mission ground segments. These data are mostly produced in netCDF files. Indeed, the netCDF-4/HDF5 file formats are widely used throughout the global scientific community because of the useful features they offer. HDF5 in particular offers a dynamically loaded filter plugin so that users can write compression/decompression filters, for example, and process the data before reading or writing them to disk. This study evaluates lossy and lossless compression/decompression methods through netCDF-4 and HDF5 tools on analytical and real scientific floating-point datasets. We also introduce the Digit Rounding algorithm, a new relative error-bounded data reduction method inspired by the Bit Grooming algorithm. The Digit Rounding algorithm offers a high compression ratio while keeping a given number of significant digits in the dataset. It achieves a higher compression ratio than the Bit Grooming algorithm with slightly lower compression speed.

Predictions for energy correlators probing substructure of groomed heavy quark jets

We develop an effective field theory (EFT) framework to perform an analytic calculation for energy correlator observables computed on groomed heavy-quark jets. A soft-drop grooming algorithm is applied to a jet initiated by a massive quark to minimize soft contamination effects such as pile-up and multi-parton interactions. We specifically consider the two-particle energy correlator as an initial application of this EFT framework to compute heavy quark jet substructure. We find that there are different regimes for the event shapes, depending on the size of the measured correlator observable, that require the use of different EFT formulations, in which the quark mass and grooming parameters may be relevant or not. We use the EFT to resum large logarithms in the energy correlator observable in terms of the momentum of a reconstructed heavy hadron to NLL′ accuracy and subsequently match it to a full QCD mathcal{O} (αs) cross section, which we also compute. We compare our predictions to simulations in Pythia for e+e− collisions. We find a good agreement with partonic simulations, as well as hadronic ones with an appropriate shape function used to describe nonperturbative effects and the heavy quark hadron decay turned off. We also predict the scaling behavior for the leading nonperturbative power correction due to hadronization. Consequently, we can give a prediction for the energy correlator distribution at the level of the reconstructed heavy hadron. This work provides a general framework for the analysis of heavy quark jet substructure observables.

Probing transverse-momentum distributions with groomed jets

We present the transverse momentum spectrum of groomed jets in di-jet events for e+e− collisions and semi-inclusive deep inelastic scattering (SIDIS). The jets are groomed using a soft-drop grooming algorithm which helps in mitigating effects of non-global logarithms and underlying event. At the same time, by reducing the final state hadronization effects, it provides a clean access to the non-perturbative part of the evolution of transverse momentum dependent (TMD) distributions. In SIDIS experiments we look at the transverse momentum of the groomed jet measured w.r.t. the incoming hadron in the Breit frame. Because the final state hadronization effects are significantly reduced, the SIDIS case allows to probe the TMD parton distribution functions. We discuss the sources of non-perturbative effects in the low transverse momentum region including novel (but small) effects that arise due to grooming. We derive a factorization theorem within SCET and resum any large logarithm in the measured transverse momentum up to NNLL accuracy using the ζ-prescription as implemented in the artemide package and provide a comparison with simulations.

Jet grooming through reinforcement learning

We introduce a novel implementation of a reinforcement learning (RL) algorithm which is designed to find an optimal jet grooming strategy, a critical tool for collider experiments. The RL agent is trained with a reward function constructed to optimize the resulting jet properties, using both signal and background samples in a simultaneous multi-level training. We show that the grooming algorithm derived from the deep RL agent can match state-of-the-art techniques used at the Large Hadron Collider, resulting in improved mass resolution for boosted objects. Given a suitable reward function, the agent learns how to train a policy which optimally removes soft wide-angle radiation, allowing for a modular grooming technique that can be applied in a wide range of contexts. These results are accessible through the corresponding GroomRL framework.

5G-Ready Multi-Failure Resilient and Cost-Effective Transport Networks

Data explosion and higher service level agreements (SLA) are common terminologies in modern communication networks. Recent advancements toward 5G networks add to the complexity where billions of devices, both static and mobile, are connected generating trillions of megabits of data flooding the network and where service providers scuffle daily to deliver key performance indicators: Lower latency, longer battery life, higher data rates, ultra-high reliability, and more connected devices. The optical-fiber world simultaneously witnesses a denser, fiber-rich network infrastructure which is critically challenged in fast economically developing countries by heavy construction of roads and other infrastructures that inflict repeated and unpredictable cuts to the extent that traffic is simultaneously interrupted in up to 10% of the optical links. Thus, network resiliency to fiber failures is already and will continue to be a top priority for operators. Depending on the SLA, operators choose from various resiliency options, e.g., at single network layers or across multiple ones, with dedicated protection or shared restoration, depending on decisive factors like network availability and total cost of ownership (TCO). With traditional network architectures, high resiliency comes with significantly increased TCO involving optical transport network (OTN) switches, L1 protection switching, and L1 restoration. This translates into high CAPEX and excessive space and power consumption, hampering the desirable seamless scalability with the continuously increasing demand for more capacity. This paper explores an alternative hyperscale network architecture, which is adaptable and resilient to multiple fiber failures, thus delivering committed service levels to the end users and which, at the same time, significantly reduces network cost compared to a traditional all OTN-switched network. The hyperscale architecture exploits low footprint carrier grade, data center interconnect type high-density transponders and cost-effective optical protection switching and restoration via software defined networking control. The paper also describes a routing and grooming algorithm to dimension a shared resource pool for optical restoration and a statistical simulation method for time effective execution, simulating failures over a carefully selected sub-set of failure scenarios to guarantee a high degree of network availability. Via network simulation, the paper demonstrates that multiple failure resiliency and cost effectiveness do not necessarily represent a contradiction in transport networks as long as an appropriate network architecture is chosen and that efficient network planning and optimization are applied.

Aspects of track-assisted mass

Track-assisted mass is a proxy for jet mass that only uses direction information from charged particles, allowing it to be measured at the Large Hadron Collider with very fine angular resolution. In this paper, we introduce a generalization of track-assisted mass and analyze its performance in both parton shower generators and resummed calculations. For the original track-assisted mass, the track-only mass is rescaled by the charged energy fraction of the jet. In our generalization, the rescaling factor includes both per-jet and ensemble-averaged information, facilitating a closer correspondence to ordinary jet mass. Using the track function formalism in electron-positron collisions, we calculate the spectrum of generalized track-assisted mass to next-to-leading-logarithmic order with leading-order matching. These resummed calculations provide theoretical insight into the close correspondence between track-assisted mass and ordinary jet mass. With the growing importance of jet grooming algorithms, we also calculate track-assisted mass on soft-drop groomed jets.

A novel auxiliary graph model for effective dynamic traffic grooming in light-trail optical WDM mesh networks

A light trail is a unidirectional bus from a convener node to an end node. The main advantage of a light trail over a light path is that the communication channel of a light trail can be accessed by intermediate nodes providing more flexibility for traffic grooming. Several auxiliary graph models have been developed in the literature for traffic grooming in light-trail optical WDM mesh networks. These auxiliary graph models have one or more drawbacks that do not fully reflect the characteristics of a light trail. This paper develops a novel auxiliary graph model that has none of the drawbacks and is able to reflect all characteristics of a light trail. Based on the auxiliary graph model, two effective dynamic traffic grooming algorithms are proposed. The proposed dynamic traffic grooming algorithms are shown to yield low request blocking ratio.

Measurements of the differential jet cross section as a function of the jet mass in dijet events from proton-proton collisions at sqrt{s}=13 TeV

Measurements of the differential jet cross section are presented as a function of the jet mass in dijet events, in bins of jet transverse momentum, with and without a jet grooming algorithm. The data have been recorded by the CMS Collaboration in proton-proton collisions at the LHC at a center-of-mass energy of 13 TeV and correspond to an integrated luminosity of 2.3 fb−1. The absolute cross sections show slightly different jet transverse momentum spectra in data and Monte Carlo event generators for the settings used. Removing this transverse momentum dependence, the normalized cross section for ungroomed jets is consistent with the prediction from Monte Carlo event generators for masses below 30% of the transverse momentum. The normalized cross section for groomed jets is measured with higher precision than the ungroomed cross section. Semi-analytical calculations of the jet mass beyond leading logarithmic accuracy are compared to data, as well as predictions at leading order and next-to-leading order, which include parton showering and hadronization. Overall, in the normalized cross section, the theoretical predictions agree with the measured cross sections within the uncertainties for masses from 10 to 30% of the jet transverse momentum.

The groomed and ungroomed jet mass distribution for inclusive jet production at the LHC

We study jet mass distributions measured in the single inclusive jet production in proton-proton collisions pp → jet+X at the LHC. We consider both standard ungroomed jets as well as soft drop groomed jets. Within the Soft Collinear Effective Theory (SCET), we establish QCD factorization theorems for both cases and we study their relation. The developed framework allows for the joint resummation of several classes of logarithmic corrections to all orders in the strong coupling constant. For the ungroomed case, we resum logarithms in the jet radius parameter and in the small jet mass. For the groomed case, we resum in addition the logarithms in the soft threshold parameter zcut which is introduced by the soft drop grooming algorithm. In this way, we are able to reliably determine the absolute normalization of the groomed jet mass distribution in proton-proton collisions. All logarithmic corrections are resummed to the next-to-leading logarithmic accuracy. We present numerical results and compare with the available data from the LHC. For both the groomed and ungroomed jet mass distributions we find very good agreement after including non-perturbative corrections.

Transverse momentum spectra at threshold for groomed heavy quark jets

We present the transverse momentum spectrum for a heavy hadron at threshold in a groomed jet initiated by a heavy quark. The cross section is doubly differential in the energy fraction of an identified heavy hadron in the jet and its transverse momentum measured with respect to the groomed (recoil free) jet axis. The grooming is implemented using a soft-drop grooming algorithm and helps us in mitigating the effects of Non-Global logarithms and pile up. For the particular case of a B meson, we identify two distinct regimes of the transverse momentum spectrum and develop an EFT within the formalisms of Soft Collinear Effective Theory (SCET) and Heavy Quark Effective Theory (HQET) for each of these regions. We show how each region can be matched smoothly into the other to provide a prediction for the perturbative transverse momentum spectrum. The EFT also predicts the scaling behavior of the leading non-perturbative power corrections and implements a simple shape function to account for hadronization. We work in the threshold region where the heavy hadron carries most of the energy of the jet since in this regime, we have a very good discriminating power between heavy quark and gluon initiated jets. We observe that the shape of the spectrum is independent of the energy of the jet over a large range of transverse momentum. We propose that this spectrum can be used as a probe of evolution for heavy quark TMD fragmentation function. At the same time, it can be treated as a jet substructure observable for probing Quark-Gluon Plasma (QGP).

Traffic load-aware dynamic energy-efficient routing strategy with spectrum reservation and load balance in elastic optical networks

Abstract For reducing the energy consumption in elastic optical networks (EONs) and mitigating the increasement of bandwidth blocking probability (BBP), a spectrum reservation and load balancing routing strategy (SRLBRS) is proposed. In SRLBRS, a spectrum state formula of node is designed to report the link spectrum usage of node-related links on the shortest path of traffic. Then, the node spectrum state can be determined by comparing the spectrum status of node-related links on the shortest path and average spectrum status in the EON. At the same time, the load state of candidate lightpath is decided by node spectrum state and available frequency slots of candidate lightpath. Available spectrum aware reservation grooming algorithm (ASARG) and load balancing routing algorithm (LBRA) are proposed and performed independently based on load state of candidate path. The ASARG focuses on energy saving by reserving lightpath dynamically according to available frequency slots of lightpath. While LBRA focuses on BBP by designing a lightpath cost formula, which is with respect to hops and spectrum continuity. Moreover, a balance index is designed to evaluate the balance between energy efficiency and blocking performance. Compared with the green grooming algorithms of distance-adaptive spectrum resource allocation (GGA + DASRA), simulation results show that the proposed SRLBRS can balance the energy consumption and blocking probability significantly. For instance in terms of balance index, our proposal achieved 57.9% better results averagely in a NSFNET topology.

Intelligent Requests Algorithm Based Scheduling and Efficient Dynamic Bandwidth Allocation to Improve QoS for EPONs

Abstract The proposed traffic grooming methodology for long-reach-passive optical networks will decrease the latency in upstream. The scheduling and wavelength assignment for ethernet passive optical networks has been shown to perform much better in terms of delay. The dynamic traffic grooming algorithm based on intelligent water drop is proposed in which new depositions function has been introduced for efficient handling of bandwidth. Therefore, once equally distanced optical network units were scheduled on constant wavelengths, the void formation impact is reduced. The outcomes conjointly depict the result of the planned methodology on bandwidth utilization improvement and jitter by 1.46 and 408.66 µs improvements respectively, even overall latency is improved by 465.83 µs by value. These results depict the validity of the planned dynamic bandwidth allocation methodology for traffic grooming.

Factorization and resummation for groomed multi-prong jet shapes

ABSTRACTObservables which distinguish boosted topologies from QCD jets are playing an increasingly important role at the Large Hadron Collider (LHC). These observables are often used in conjunction with jet grooming algorithms, which reduce contamination from both theoretical and experimental sources. In this paper we derive factorization formulae for groomed multi-prong substructure observables, focusing in particular on the groomed D2 observable, which is used to identify boosted hadronic decays of electroweak bosons at the LHC. Our factorization formulae allow systematically improvable calculations of the perturbative D2 distribution and the resummation of logarithmically enhanced terms in all regions of phase space using renormalization group evolution. They include a novel factorization for the production of a soft subjet in the presence of a grooming algorithm, in which clustering effects enter directly into the hard matching. We use these factorization formulae to draw robust conclusions of experimental relevance regarding the universality of the D2 distribution in both e+e− and pp collisions. In particular, we show that the only process dependence is carried by the relative quark vs. gluon jet fraction in the sample, no non-global logarithms from event-wide correlations are present in the distribution, hadronization corrections are controlled by the perturbative mass of the jet, and all global color correlations are completely removed by grooming, making groomed D2 a theoretically clean QCD observable even in the LHC environment. We compute all ingredients to one-loop accuracy, and present numerical results at next-to-leading logarithmic accuracy for e+e− collisions, comparing with parton shower Monte Carlo simulations. Results for pp collisions, as relevant for phenomenology at the LHC, are presented in a companion paper [1].

A Cross-layer Traffic Grooming Algorithm in Joint Optimization of the IP over Elastic Optical Network

Abstract To fully utilize the existing optical network resource, the dynamic traffic grooming technology, which could efficiently multiplex many low-speed services arriving dynamically onto high-capacity optical channels, has been studied extensively and used widely. In this article, the problem of dynamic traffic grooming in joint optimization of IP over elastic optical network (EON) is studied. This problem consists of three sub-problems at two layers: the routing problem at the IP-layer (IPR), the routing, modulation level (RML), and the spectrum allocation (SA) problems at the optical layers. We proposed a novel topology-integration and adaptive-modulation based in cross-layer routing spectrum allocation (CL-RSA) algorithm, which follows a multi-cost approach that solves the IPR, the RML, and the SA problems jointly. The most important features of the proposed algorithm are merging physical topology with virtual topology and using the minimum-weight preferred method for route selection. Meanwhile, the effect of physical-layer impairments (PLI) on signal transmission is considered. In addition, the adaptive modulation scheme is used to allocate the spectrum resource. The simulation results show that the algorithm can effectively improve the spectrum resource utilization and reduce the network blocking probability compared to other algorithms in various network conditions, especially in the high load condition effectively.

Priority Scheduling Algorithm for Traffic in a LTE-based Defence Mesh Network Incorporating Centralised Scheduling Architecture

<p>Wireless mesh networks (WMN) are the networks of future and can operate on multiple protocols ranging from WiFi, WiMax to long term evolution (LTE). As a recent trend defence networks are incorporating off-the-shelf, state of the art commercial protocols to enhance the capability of their networks. LTE is one such commercially available protocol which is easy to deploy and provide high data rate which can be ideally implemented in WMN for defence networks. To enable these high data rate services LTE-based defence mesh networks (DMN) are the requirement of the day and future. However, LTE-based DMN are prone to congestion at times of active operations or full-fledged war. The congestion scenarios may lead to LTE packet loss. Hence, it is pertinent that these networks amalgamate information grooming algorithms to alleviate the throughput of the network in peak hour conditions. An efficient priority scheduling algorithm based on class of service prioritisation, data rate consumption and location of origin of traffic in the DMN is proposed. The simulations demonstrate that by incorporating the proposed priority scheduling algorithm, the overall packet loss of priority packets in the DMN reduces substantially.</p>

Casimir meets Poisson: improved quark/gluon discrimination with counting observables

Charged track multiplicity is among the most powerful observables for discriminating quark- from gluon-initiated jets. Despite its utility, it is not infrared and collinear (IRC) safe, so perturbative calculations are limited to studying the energy evolution of multiplicity moments. While IRC-safe observables, like jet mass, are perturbatively calculable, their distributions often exhibit Casimir scaling, such that their quark/gluon discrimination power is limited by the ratio of quark to gluon color factors. In this paper, we introduce new IRC-safe counting observables whose discrimination performance exceeds that of jet mass and approaches that of track multiplicity. The key observation is that track multiplicity is approximately Poisson distributed, with more suppressed tails than the Sudakov peak structure from jet mass. By using an iterated version of the soft drop jet grooming algorithm, we can define a “soft drop multiplicity” which is Poisson distributed at leading-logarithmic accuracy. In addition, we calculate the next-to-leading-logarithmic corrections to this Poisson structure. If we allow the soft drop groomer to proceed to the end of the jet branching history, we can define a collinear-unsafe (but still infrared-safe) counting observable. Exploiting the universality of the collinear limit, we define generalized fragmentation functions to study the perturbative energy evolution of collinear-unsafe multiplicity.

A study of jet mass distributions with grooming

We perform a phenomenological study of the invariant mass distribution of hadronic jets produced in proton-proton collisions, in conjunction with a grooming algorithm. In particular, we consider the modified MassDrop Tagger (mMDT), which corresponds to Soft Drop with angular exponent β = 0. Our calculation, which is differential in both jet mass and jet transverse momentum, resums large logarithms of the jet mass, including the full dependence on the groomer’s energy threshold zcut, and it is matched to fixed-order QCD matrix elements at next-to-leading order. In order to account for non-perturbative contributions, originating from the hadronisation process and from the underlying event, we also include a phenomenological correction factor derived from Monte Carlo parton shower simulations. Furthermore, we consider two different possibilities for the jet transverse momentum: before or after grooming. We show that the former should be preferred for comparisons with upcoming experimental data essentially because the mMDT transverse momentum spectrum is not collinear safe, though the latter exhibits less sensitivity to underlying event and displays properties that may provide complementary information for probing non-perturbative effects.

A New Dynamic Multicast Traffic Grooming Algorithm in Optical Networks

With the growing popularity of multicast applications and the gaining recognition of traffic grooming, the optimizing design with multicast traffic grooming in WDM networks becomes more and more important. Different grooming strategies require different resources, such as grooming ports, optical transceivers. In order to use the least of the current resources in the network for a multicast, a new dynamic multicast traffic grooming algorithm(DP_GA) is proposed. Firstly, a new traffic grooming discriminant is designed in DP_GA algorithm, which judged whether it is suitable for traffic grooming according to the network resource status in real time. Secondly, a formula named total routing cost is designed to select one grooming strategy from multi-hop, hybrid and extended optical tree. Compared with ADMGA algorithm, DP_GA algorithm can fully use of limited network resources and reduce request blocking rate.

Energy-Aware Provisioning in Optical Cloud Networks

Cloud computing has recently emerged as a dominant Internet service computing model due to its “pay-as-you-go” and “elastic service” features. Cloud computing systems are usually composed of distributed datacenters, which leverage virtualization technology to provide a scalable and reliable service. Optical networks are recognized as promising next-generation core networks for connecting these distributed datacenters due to their characteristics such as high bandwidth provisioning, low latency, low bit error rate, etc. However, concern about the ever-increasing energy consumption of cloud computing systems together with core networks has been raised due to high electricity bills as well as environmental pollution. In this paper, we study the Energy-aware Provisioning in Optical Cloud Networks (EPOCN) problem for both dynamic and static cases. When traffic requests arrive in an online fashion, we propose a polynomial-time energy-aware routing algorithm to solve the dynamic EPOCN problem. Simulations show that our energy-aware routing algorithm brings more energy savings in comparison to a shortest path-based routing algorithm and a traffic grooming algorithm. On the other hand, we show that the EPOCN problem in the static case (the traffic matrix is known in advance) is NP-hard. We further divide this problem into (1) the Energy-Aware Routing (EAR) problem in optical networks and (2) the Energy-efficient Server and Switch Allocation (ESSA) problem in datacenter networks. Considering these two (sub)problems are still NP-hard, we present an exact Integer Linear Program (ILP) and a heuristic to solve each problem. We also conduct simulations to compare the proposed ILPs and heuristics in terms of energy consumption and running time.