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The massive deployment of 5G and beyond will require high capacity and low latency connectivity services, so network operators will have either to overprovision capacity in their transport networks or to upgrade the optical network controllers to make decisions nearly in real time; both solutions entail high capital and operational expenditures. A different approach could be to move the decision making toward the nodes and subsystems, so they can adapt dynamically the capacity to the actual needs and thus reduce operational costs in terms of energy consumption. To achieve this, several technological challenges need to be addressed. In this paper, we focus on the autonomous operation of Digital Subcarrier Multiplexing (DSCM) systems, which enable the transmission of multiple and independent subcarriers (SC). Herein, we present several solutions enabling the autonomous DSCM operation, including: i) SC quality of transmission estimation; ii) autonomous SC operation at the transmitter side and blind SC configuration recognition at the receiver side; and iii) intent-based capacity management implemented through Reinforcement Learning. We provide useful guidelines for the application of autonomous SC management supported by the extensive results presented. The research leading to these results has received funding from the European Community's through the MSCA REAL-NET project (G.A. 813144), by the AEI/FEDER through the TWINS project (TEC2017-90097-R), and by the ICREA institution.

In network architectures based on Software Defined Networking (SDN) the control plane (control logic) is separated from the network data plane (forwarding plane) while traditional network routers combine both. Software Defined networks facilitates a centralized networking system where a logical controller manages the global view of the network. In this paper, we first propose a new metric on the controller placement problem (CPP) that simultaneously considers the communication latency and communication reliability both between switches and controllers and between controllers. Reliability is considered for single-link failure. We model the problem of determining the optimal controller placement to provide low latencies in the control plane traffic. The objective of this study is to minimize the average accumulated latency by jointly taking into account the latency between controller to switches and inter-controller while optimizing their placement for achieving an optimal balance simultaneously. The optimization problem is formulated as a mixed-integer linear programming (MILP) model under the constraints of latency and reliability. We evaluated the performance of our proposed metric by using the Internet2 OS3E network topology. Different from previous work, we focus on the control traffic exchanged among controllers to synchronize their shared data structure. Results demonstrate that the proposed method is promising. This research was supported by the Spanish Ministry of Economy and Competitiveness under contract TEC2017-90034-C2-1-R (ALLIANCE).

Over the years, different techniques have been proposed to detect bottleneck bandwidth and available bandwidth of an end-to-end path. However, to the author's knowledge, no work has been conducted on detecting which link or node on the path could be the narrow link. In this paper, we present a novel technique based on packet pairs dispersion analysis, whose objective is twofold: first, it allows to estimate the narrow link capacity using a new approach which takes into account both inter-packet time and packet propagation delay. Its second objective is to induce the specific hop in the end-to-end path which represents the narrow link. This is achieved by injecting packets trains with intermediate TTL-expiring packets which decrease the train rate when they cross the narrow link (red-shift effect). We validate our approach in simulations showing the tool robustness in very complex scenarios. This work was supported by the Industrial PhD grant 2015DI023 of AGAUR and Gencat and the project Efficient Smart Multi Connected Networks co-financed by the Spanish Ministry of Ciencia Innovacion y Universidades with reference RTC-2017-6655-7, The Spanish Agenda Estatal de Investigacin and the European Regional Development Fund (FEDER).

Metasurfaces are envisaged to play a key role in next-generation wireless systems due to their powerful control over electromagnetic waves. The last decade has witnessed huge advances in this regard, shifting from static to programmable metasurfaces. The HyperSurface (HSF) paradigm takes one step further by integrating a network of controllers within the device with the aim of adding intelligence, connectivity, and autonomy. However, little is known about the traffic that this network will have to support as the target electromagnetic function or boundary conditions change. In this paper, we lay down the foundations of a methodology to characterize the workload of programmable metasurfaces and then employ it to analyze the case of beam steering HSFs. We observe that traffic is bursty and highly dependent on the position of the target. These results will enable the early-stage evaluation of intra-HSF networks, as well as the estimation of the system performance and cost. This work was supported by the European Union’s Horizon 2020 research and innovation programme-Future Emerging Topics (FETOPEN) under grant agreement No 736876.

The Guifi.net community network has evolved during the past 15 years into a telecommunications infrastructure that offers Internet access to more than 80.000 people. The monitoring system currently in place for this network is lagging behind the growth of the infrastructure, requiring manual intervention and counting several single points of failure. In this paper we present REDEMON, a resilient decentralized monitoring system, hosted on distributed and interconnected edge devices, for a reliable, eventually-consistent monitoring of the Guifi.net network, leveraging CRDT-based data structures implemented on AntidoteDB. We developed the REDEMON system as a prototype featuring resilience, decentralization and automation, in order to replace the legacy monitoring system. To assess the system, this prototype was deployed on resource-constraint edge nodes in the Guifi.net production network and evaluated under realistic conditions. The decentralized assignment mechanism successfully achieves setting the minimum number of monitoring servers per network device that satisfies the established system requirements. Besides, by concentrating the workload on the minimum required number of servers running at their maximum capacity, the remaining devices can idle away, reducing the consumption footprint of the system. With regard to computing resources, we measure a moderate CPU and RAM usage by the monitoring system on low-capacity devices, while we observe that a considerable network traffic is required for achieving a resilient and consistent data storage layer. This resilient and decentralized architecture could lay the basis for other edge applications in the cloud computing domain that need to coordinate over distributed and consistent shared data. This work was supported by the European H2020 framework programme project LightKone (H2020-732505), by the Spanish State Research Agency (AEI) under contracts PCI2019- 111850-2 and PCI2019-111851-2, and the Catalan government AGAUR SGR 990.

By leveraging resources from the Fed4Fire+ City-Lab testbed, we design the PiGeon edge computing platform that experiments solution that enable ICN based edge services in wireless mesh networks (WMNs). PiGeon combines into a platform several trends in edge computing namely the ICN (Information-Centric Networking), the containerization of services exemplified by Docker, novel service placement algorithms and the increasing availability of energy efficient but still powerful hardware at user premises (Raspberry Pi, mini-PCs, and enhanced home gateways). We underpin the PiGeon platform with Docker container-based service that can be seamlessly delivered, cached and deployed at the network edge. The core of the PiGeon platform is the Decision Engine making a decision on where and when to deploy a service instance to satisfy the service requirements while considering the network status and available hardware resources. We collect network data from a real citywide mesh network such as CityLab FIRE testbed located at the city of Antwerp, Belgium. The collected data is used to feed our service placement heuristic within the PiGeon platform. Through a real deployment in CityLab testbed, we show that our service placement heuristic improves the response time up to 37% for stateful services (Web2.0 service). Apart from improving the QoS for end-users, our results show that ICN plays a key role in improving the service delivery time as well as reducing the traffic consumption in WMNs. The overall effect of ICN in our platform is that most content and service delivery requests can be satisfied very close to the client device, many times just one hop away, decoupling QoS from intra-network traffic and origin server load. This work was supported by the European H2020 framework programme project Fed4Fire+ (732638), by the Spanish State Research Agency (AEI) under contracts PCI2019-111850-2 and PCI2019-111851-2, and the Catalan government AGAUR SGR 990.

In this paper, we evaluate five different architectures for implementing the Add/Drop module of future Spatial Division Multiplexing (SDM)-enabled Re-configurable Optical Add & Drop Multiplexers (ROADMs) with different degrees of flexibility, from a completely static transponder to spatial channel assignment to a fully-flexible transceiver to fibre and spatial channel assignment. The performance of the proposed architectures is compared in a single SDM-enabled ROADM scenario, where local as well as bypass traffic is injected, supported by spectral super-channels at diverse bit-rates and employing different modulation formats. The obtained results illustrate the additional benefits attainable by more flexible Add/Drop architectures versus their increased hardware complexity. The work included in this paper has been supported by the Spanish Government through project ALLIANCE (TEC2017-90034-C2-1-R and TEC2017-90034-C2-2-R) with FEDER contribution. The work of M. Klinkowski was supported by National Science Centre, Poland under Grant 2016/21/B/ST7/02212.

In this article, we focus on the design of different node architectures suitable for few-mode multi-core fibers (FMMCFs) based networks. Both dimensions, core and mode, open different possible ways to group spatial channels depending on the physical impairments of the space-division multiplexed (SDM) optical fibers. Moreover, the channel switching across a group of cores/modes at once and the end-to-end routing are not only mandatory aspects for certain spatial channels, but also recommendable in order to reduce the node complexity/cost. Thus, we propose various SDM-capable node architectures based on versatile and homogeneous spatial group configurations. Then, a unified physical-layer-aware Quality of Transmission (QoT) estimator is formulated to not only evaluate these node architectures in a simulation tool, but also validate them in a real experimental environment using a stateful path computation element (PCE) as a central controller. The obtained results disclose that the cost-efficient node design parameter, namely, the size of the spatial group G, depends on both the network and traffic profile size. Specifically, for a national optical backbone network equipped with a homogeneous and hexagonally arranged 6-weakly-coupled modes and 7-weakly-coupled cores fibers, G equals 6, while for a continental backbone network, G can raise up to 14. In any case, we demonstrate that the cost-benefit tradeoff in node design must be analyzed in detail in order to meet the huge traffic volumes of the next years. This work was supported by the Spanish Project AURORAS under Grant RTI2018-099178-B-I00.

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., The automation of Network Services (NS) consisting of virtual functions connected through a multilayer packet-over-optical network requires predictable Quality of Service (QoS) performance, measured in terms of throughput and latency, to allow making proactive decisions. QoS is typically guaranteed by overprovisioning capacity dedicated to the NS, which increases costs for customers and network operators, especially when the traffic generated by the users and/or the virtual functions highly varies over the time. This article presents the PILOT methodology for modeling the performance of connectivity services during commissioning testing in terms of throughput and latency. Benefits are double: first, an accurate per-connection model allows operators to better operate their networks and reduce the need for overprovisioning; and second, customers can tune their applications to the performance characteristics of the connectivity. PILOT runs in a sandbox domain and constructs a scenario where an efficient traffic flow simulation environment, based on the CURSA-SQ model, is used to generate large amounts of data for Machine Learning (ML) model training and validation. The simulation scenario is tuned using real measurements of the connection (including throughput and latency) obtained from a set of active probes in the operator network. PILOT has been experimentally validated on a distributed testbed connecting UPC and Telefónica premises, This work was partially supported by the EC through the METRO-HAUL (G.A. nº 761727) project, from the Spanish MINECO/FEDER TWINS (TEC2017-90097-R) and TRÁFICA (TEC2015-69417-C2-1-R) projects and from the Catalan Institution for Research and Advanced Studies.

Spectrum fragmentation is one of the main drawbacks of Flex-Grid Optical Networks, and it becomes especially harmful under dynamic traffic conditions. When evolving from single fibre networks to spatial division multiplexed (SDM) ones, where many parallel cores/fibres are deployed, spectrum fragmentation still limits their eventual performance. In this work, the total available spectrum is partitioned according to the SDM dimension, and each one of the resulting partitions is assigned to each type of connections. This strategy is proposed as a simple method to eliminate spectrum fragmentation. By allocating all same sized connections onto the same spectral/spatial partition, the randomness in the size of the spectral voids left by torn down connections is eliminated. The proposal is numerically evaluated using different network topologies. The obtained results show that spatial partitioning is an interesting solution for spectrum fragmentation avoidance in these scenarios. This work has been partially funded by Spanish projects TWINS (TEC2017-90097-R) and ALLIANCE (TEC2017-90034-C2-1-R).

©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The independent operation of mobile and fixed network segments is one of the main barriers that prevents improving network performance while reducing capital expenditures coming from overprovisioning. In particular, a coordinated dynamic network operation of both network segments is essential to guarantee end-to-end Key Performance Indicators (KPI), on which new network services rely on. To achieve such dynamic operation, accurate estimation of end-to-end KPIs is needed to trigger network reconfiguration before performance degrades. In this paper, we present a methodology to achieve an accurate, scalable, and predictive estimation of end-to-end KPIs with sub-second granularity near real-time in converged fixed-mobile networks. Specifically, we extend our CURSA-SQ methodology for mobile network traffic analysis, to enable converged fixed-mobile network operation. CURSA-SQ combines simulation and machine learning fueled with real network monitoring data. Numerical results validate the accuracy, robustness, and usability of the proposed CURSA-SQ methodology for converged fixed-mobile network scenarios. The research leading to these results has received funding from the Spanish MINECO TWINS project (TEC2017-90097-R), and from the Catalan Institution for Research and Advanced Studies (ICREA).

Future optical core networks realizing Flex-Grid and Space Division Multiplexing (Flex-Grid/SDM) will be key to effectively cope with the rapid growth of the Internet traffic, thanks to their superior capacity and spectrum utilization flexibility. Specifically about SDM, the spatial dimension can be considered either fixed or flexible. The goal of this work is two-fold. Firstly, it aims at quantifying the capacity (in terms of throughput) of Flex-Grid/SDM networks assuming either a fixed or a flexible spatial dimension. To this end, we scale up the spatial multiplicity from 7 to 30 spatial channels, considering Multi-Fiber (MF) and Multi-Core Fiber (MCF) solutions. Secondly, it also aims at analyzing the throughput scalability in these networks versus their hardware requirements, especially from the transponder requirements point of view. The obtained results show that, for a 4.3× spatial multiplicity scaling factor, the throughput of spatially fixed Flex-Grid/SDM networks scales up to 3.5×. Conversely, when the spatial dimension is considered flexible, throughput can be pushed up to a 5× factor for both MF and MCF solutions. However, a long-term realization of spectrally-spatially flexible optical networks (SS-FONs) requires up to 9.6× more laser sources and 2.7× electronic complexity (per required connection) in the transponders compared to spatially fixed Flex-Grid/SDM networks. Furthermore, SS-FONs enable different options for assigning the spectral and spatial resources to traffic demands. In this sense, another contribution of this work is the introduction of a novel methodology that trades network throughput for transponder (the major network equipment cost in SDM networks) complexity reduction.

We present a control module for software edge routers called Receive Window Modulation - RWM. Its main objective is to mitigate what we define as self-induced congestion: the result of traffic emission patterns at the source that cause buffering and packet losses in any of the intermediate routers along the path between the connection's endpoints. The controller modifies the receiver's TCP advertised window to match the computed bandwidth-delay product, based on the connection round-trip time estimation and the bandwidth locally available at the edge router. The implemented controller does not need any endpoint modification, allowing it to be deployed in corporate edge routers, increasing visibility and control capabilities. This scheme, when used in real-world experiments with loss-based congestion control algorithms such as CUBIC, is shown to optimize access link utilization and per-connection goodput, and to reduce latency variability and packet losses. This work was supported by the grant 2015DI023 in the framework of the Industrial PhD grants of AGAUR and Generalitat de Catalunya.

Looking at the ever-increasing amount of heterogeneous distributed applications supported on current data transport networks, it seems evident that best-effort packet delivery falls short to supply their actual needs. Multiple approaches to Quality of Service (QoS) differentiation have been proposed over the years, but their usage has always been hindered by the rigidness of the TCP/IP-based Internet model, which does not even allow for applications to express their QoS needs to the underlying network. In this context, the Recursive InterNetwork Architecture (RINA) has appeared as a clean-slate network architecture aiming to replace the current Internet based on TCP/IP. RINA provides a well-defined QoS support across layers, with standard means for layers to inform of the different QoS guarantees that they can support. Besides, applications and other processes can express their flow requirements, including different QoS-related measures, like delay and jitter, drop probability or average traffic usage. Greedy end-users, however, tend to request the highest quality for their flows, forcing providers to apply intelligent data rate limitation procedures at the edge of their networks. In this work, we propose a new rate limiting policy that, instead of enforcing limits on a per QoS class basis, imposes limits on several independent QoS dimensions. This offers a flexible traffic control to RINA network providers, while enabling end-users freely managing their leased resources. The performance of the proposed policy is assessed in an experimental RINA network test-bed and its performance compared against other policies, either RINA-specific or adopted from TCP/IP. Results show that the proposed policy achieves an effective traffic control for high QoS traffic classes, while also letting lower QoS classes to take profit of the capacity initially reserved for the former ones when available.

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This paper reports the definition, setup and obtained results of the Fed4FIRE + medium experiment ERASER, aimed to evaluate the actual Quality of Service (QoS) guarantees that the clean-slate Recursive InterNetwork Architecture (RINA) can deliver to heterogeneous applications at largescale. To this goal, a 37Node 5G metro/regional RINA network scenario, spanning from the enduser to the server where applications run in a datacenter has been configured in the Virtual Wall experimentation facility. This scenario has initially been loaded with synthetic application traffic flows, with diverse QoS requirements, thus reproducing different network load conditions. Next,their experienced QoS metrics endtoend have been measured with two different QTAMux (i.e., the most accepted candidate scheduling policy for providing RINA with its QoS support) deployment scenarios. Moreover, on this RINA network scenario loaded with synthetic application traffic flows, a real HD (1080p) video streaming demonstration has also been conducted, setting up video streaming sessions to endusers at different network locations, illustrating the perceived Quality of Experience (QoE). Obtained results in ERASER disclose that, by appropriately deploying and configuring QTAMux, RINA can yield effective QoS support, which has provided perfect QoE in almost all locations in our demo when assigning video traffic flows the highest (i.e., Gold) QoS Cube.

The digital world demands a network infrastructure to supply connectivity to any participant anywhere. Sustainable networks require balanced value flows. Value is connectivity delivered at a material and service cost to compensate, involving diverse participants, ranging from consumers to providers, such as last mile access, regional transport, Internet carriers, or content providers. We focus on the case of wireless mesh networks that deliver connectivity through access points and a mesh network that routes traffic to Internet gateways, provisioned by several device owners and service operators [1, 2, 3]. The presented work is motivated by the need for balance and automation among services delivered, costs and incentives for participation in these decentralised networks. This balance is key for achieving extensible network infrastructures that can deliver widespread availability of Internet connectivity with minimal barriers of entry. This paper has been partially supported by the AmmbrTech Group, the Spanish government TIN2016-77836-C2-2-R and the Catalan government AGAUR SGR 990.

In multi-domain elastic optical networks with alien wavelengths, each domain needs to consider intradomain and interdomain alien traffic to estimate and guarantee the required quality of transmission (QoT) for each lightpath and perform provisioning operations. This paper experimentally demonstrates an alien wavelength performance monitoring technique and machine-learning-aided QoT estimation for lightpath provisioning of intradomain/interdomain traffic. Testbed experiments demonstrate modulation format recognition, QoT monitoring, and cognitive routing for a 160 Gbaud alien multi-wavelength lightpath. By using experimental training datasets from the testbed and an artificial neural network, we demonstrated an accurate optical-signal-to-noise ratio prediction with an accuracy of ~95% when using 1200 data points.

Automating the provisioning of 5G services, deployed over a heterogeneous infrastructure (in terms of domains, technologies, and management platforms), remains a complex task, yet driven by the constant need to provide end-to-end connections at network slices at reducing costs and service deployment time. At the same time, such services are increasingly conceived around interconnected functions and require allocation of computing, storage, and networking resources. The METRO-HAUL 5G research initiative acknowledges the need for automation and strives to develop an orchestration platform for services and resources that extends, integrates, and builds on top of existing approaches, macroscopically adopting Transport Software Defined Networking principles, and leveraging the programmability and open control of Transport SDN. © 2018 Elsevier B.V.

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The question of how to specify, provide and measure service quality for network end-users has been of utmost interest for service and network infrastructure providers and their clients as well. The Service Level Agreement (SLA) is a beneficial tool in formalizing the interrelationships resulting from a negotiation among all participating actors with the target of achieving a common comprehension concerning delivery of services, its priorities, quality, responsibilities, and other relevant parameters. A horizontal SLA is an agreement between two service-providers existing at the same architectural layer (as for example two Internet Protocol (IP) or two Optical Transport Network (OTN) domains). A vertical SLA is an agreement between two individual providers at two different architectural layers (for instance, between an optical network and the core MPLS network). A service has to be defined without ambiguity utilizing Service Level Specifications (SLS) and three information types must be described: i) The QoX metrics as well as their corresponding thresholds; ii) A method of service performance measurement; iii) Service schedule. In this work we present preliminary simulation results that enable the development of a generic methodology for SLA modeling and establishment that will lead to a win-win situation for all involved actors. As an example, we put special attention in the benefits obtained by Optical Networks operators.

Dragonfly networks arrange network routers in a two-level hierarchy, providing a competitive cost-performance solution for large systems. Non-minimal adaptive routing (adaptive misrouting) is employed to fully exploit the path diversity and increase the performance under adversarial traffic patterns. Network fairness issues arise in the dragonfly for several combinations of traffic pattern, global misrouting and traffic prioritization policy. Such unfairness prevents a balanced use of the resources across the network nodes and degrades severely the performance of any application running on an affected node. This paper reviews the main causes behind network unfairness in dragonflies, including a new adversarial traffic pattern which can easily occur in actual systems and congests all the global output links of a single router. A solution for the observed unfairness is evaluated using age-based arbitration. Results show that age-based arbitration mitigates fairness issues, especially when using in-transit adaptive routing. However, when using source adaptive routing, the saturation of the new traffic pattern interferes with the mechanisms employed to detect remote congestion, and the problem grows with the network size. This makes source adaptive routing in dragonflies based on remote notifications prone to reduced performance, even when using age-based arbitration.

Modern web protocols like HTTP/2 and QUIC aim to make the web faster by addressing well-known problems of HTTP/1.1 running on top of TCP. Both HTTP/2 and QUIC are specified to run on a single connection, in contrast to the usage of multiple TCP connections in HTTP/1.1. Reducing the number of open connections brings a positive impact on the network infrastructure, besides improving fairness among applications. However, the usage of a single connection may result in poor application performance in common adverse scenarios, such as under high packet losses. In this paper we first investigate these scenarios, confirming that the use of a single connection sometimes impairs application performance. We then propose a practical solution (here called H2-Parallel) that implements multiple TCP connection mechanism for HTTP/2 in Chromium browser. We compare H2-Parallel with HTTP/1.1 over TCP, QUIC over UDP, as well as HTTP/2 over Multipath TCP, which creates parallel connections at the transport layer opaque to the application layer. Experiments with popular live websites as well as controlled emulations show that H2-Parallel is simple and effective. By opening only two connections to load a page with H2-Parallel, the page load time can be reduced substantially in adverse network conditions.

Web Real-Time Communication Web Real-Time Communication (WebRTC) is seeing a rapid rise in adoption footprint. This standard provides an audio/video platform-agnostic communications framework for the Web build-in right in the browser. The complex technology stack of a full implementation of the standard is vast and includes elements of various computational disciplines like: content delivery, audio/video processing, media transport and quality of experience control, for both P2P and Cloud relayed communications. To the best of our knowledge, no previous study examines the impact of Cloud back-end load and media quality at production scale for a media stream processing application, as well as load mitigation for Cloud media Selective Forwarding Units. The contribution of this work is the analysis and exploitation of server workload (predictable session size, strong periodical load patterns) and media bit rate patterns that are derived from real user traffic (toward our test environment), over an extended period of time. Additionally, a simple and effective load balancing scheme is discussed to fairly distribute big sessions over multiple servers by exploiting the discovered patterns of stable session sizes and server load predictability. A Cloud simulation environment was built to compare the performance of the algorithm with other load allocation policies. This work is a basis for more advanced resource allocation algorithms and media Service Level Objectives (SLO) spanning multiple Cloud entities.

In this work we analyze the communication load imbalance generated by irregular-data applications running in a multi-node cluster. Experimental approaches to diminish communication load imbalance are evaluated using a hybrid programming model MPI+OpenMP including certain optimizations like computation-communication overlap, issuing communications in parallel and a new proposal based on message fragmentation in order to take advantage of the eager-protocol. Performance results show that overlapped versions can obtain a great benefit of this optimization because it avoids switching to rendez-vous protocols. However, non-overlapped versions showed better performance than overlapped ones. To evaluate also the impact due to network latency, the work has been tested on two high-speed interconnection networks: Infiniband and 10Gigabit Ethernet. In this case, the optimizations in the non-overlapped miniFE benchmark reached and improvement up to 7% on Infiniband and 11% on 10Gigabit.

Radio Access Network (RAN) slicing is a key technology, based on Software Defined Networks (SDN) and Network Function Virtualization (NFV), which aims at providing a more efficient utilization of the available network resources and the reduction of the operational costs. On that respect, in this demo a Wireless LAN hypervisor is presented that is based on a time variant scheduling mechanism and that is able to follow the dynamicity of the traffic variations seen by the different tenants in the network Access Points (APs). The work builds upon the 5G-EmPOWER tool kit, which is provided with SDN and NFV capabilities. During this demo it will be shown that the proposed hypervisor is able to dynamically assign, in every AP of the network, the appropriate resources per tenant according to their traffic requirements. This work has been supported by the RAMSES (Ref. TEC2013-41698-R), funded by CICYT (Spain).

Traditional smart city resources management rely on cloud based solutions to provide a centralized and rich set of open data. The advantages of cloud based frameworks are their ubiquity, (almost) unlimited resources capacity, cost efficiency, as well as elasticity. However, accessing data from the cloud implies large network traffic, high data latencies, and higher security risks. Alternatively, fog computing emerges as a promising technology to absorb these inconveniences. The use of devices at the edge provides closer computing facilities, reduces network traffic and latencies, and improves security. We have defined a new framework for data management in the context of smart city through a global fog to cloud management architecture; in this paper we present the data acquisition block. As a first experiment we estimate the network traffic during data collection, and compare it with a traditional real system. We also show the effectiveness of some basic data aggregation techniques in the model, such as redundant data elimination and data compression.

The network functions virtualization paradigm is rapidly gaining interest among Internet service providers. However, the transition to this paradigm on ISP networks comes with a unique set of challenges: legacy equipment already in place, heterogeneous traffic from multiple clients, and very large scalability requirements. In this article we thoroughly analyze such challenges and discuss NFV design guidelines that address them efficiently. Particularly, we show that a decentralization of NFV control while maintaining global state improves scalability, offers better per-flow decisions and simplifies the implementation of virtual network functions. Building on top of such principles, we propose a partially decentralized NFV architecture enabled via an enhanced software-defined networking infrastructure. We also perform a qualitative analysis of the architecture to identify advantages and challenges. Finally, we determine the bottleneck component, based on the qualitative analysis, which we implement and benchmark in order to assess the feasibility of the architecture.

As current traffic growth is expected to strain capacity of today¿s metro network, novel content distribution architectures where contents are placed closer to the users are being investigated. In that regard, telecom operators can deploy datacenters (DCs) in metro areas, thus reducing the impact of the traffic between users and DCs. In this paper, a hierarchical content distribution architecture for the telecom cloud is investigated: core DCs placed in geographically distributed locations, are interconnected through permanent “per content provider” (CP) virtual network topologies (CP-VNT); additionally, metro DCs need to be interconnected with the core DCs. CP¿s data is replicated in the core DCs through the CP-VNTs, while metro-to-core (M2C) anycast connections are established periodically for content synchronization. Since network failures might disconnect the CP-VNTs, recovery mechanisms are proposed to reconnect both topologies and anycast connections. Topology creation, anycast provisioning, and recovery problems are first formally stated and modeled as Integer Linear Programs (ILP) and heuristic algorithms are proposed. Exhaustive simulation results show significant improvements in both supported traffic and restorability. Workflows to implement the algorithms within the Applications-based Network Operations (ABNO) architecture and extensions for PCEP are proposed. Finally, the architecture is experimentally validated in UPC's SYNERGY test-bed running our ABNO-based iONE architecture.

Deep reinforcement learning (DRL) has recently revolutionized the resolution of decision-making and automated control problems. In the context of networking, there is a growing trend in the research community to apply DRL algorithms to optimization problems such as routing. However, existing proposals fail to achieve good results, often under-performing traditional routing techniques. We argue that the reason behind this poor performance is that they use straightforward representations of networks. In this paper, we propose a DRL-based solution for routing in optical transport networks (OTNs). Contrary to previous works, we propose a more elaborate representation of the network state that reduces the level of knowledge abstraction required for DRL agents and easily captures the singularities of network topologies. Our evaluation results show that using our novel representation, DRL agents achieve better performance and learn how to route traffic in OTNs significantly faster compared to state-of-the-art representations. Additionally, we reverse engineered the routing strategy learned by our DRL agent, and as a result, we found a routing algorithm that outperforms well-known traditional routing heuristics.

Wireless mesh networks (WMNs) are cost-efficient networks that have the potential to serve as an infrastructure for advanced location-based services. Location service is a desired feature for WMNs to support location-oriented applications. WMNs are also interesting infrastructures for supporting ubiquitous multimedia Internet access for mobile or fixed mesh clients. In order to efficiently support such services and offering QoS, the optimized placement of mesh router nodes is very important. Indeed, such optimized mesh placement can support location service managed in the mesh and keep the rate of location updates low. This node location-based problem has been shown to be NP-hard and thus is unlikely to be solvable in reasonable amount of time. Therefore, heuristic methods, such as genetic algorithms (GAs), are used as resolution methods. In this paper, we deal with the effect of population size for location-aware node placement in WMNs. Our WMN-GA system uses GA to determine the positions of the mesh routers and mesh clients in the grid area. We used a location-aware node placement of mesh router in cells of considered grid area to maximize network connectivity and user coverage. We evaluate the performance of the proposed and implemented WMN-GA system for low and high density of clients considering different distributions and considering giant component and number of covered users parameters. The simulation results show that for low-density networks, with the increasing of population size, GA obtains better result. However, with the increase in the population size, the GA needs more computational time. The proposed system has better performance in dense networks like hot spots for Weibull distribution when the population size is big.

The continuous evolution of Internet traffic and its applications makes the classification of network traffic a topic far from being completely solved. An essential problem in this field is that most of proposed techniques in the literature are based on a static view of the network traffic (i.e., they build a model or a set of patterns from a static, invariable dataset). However, very little work has addressed the practical limitations that arise when facing a more realistic scenario with an infinite, continuously evolving stream of network traffic flows. In this paper, we propose a streaming flow-based classification solution based on Hoeffding Adaptive Tree, a machine learning technique specifically designed for evolving data streams. The main novelty of our proposal is that it is able to automatically adapt to the continuous evolution of the network traffic without storing any traffic data. We apply our solution to a 12 + 1 year-long dataset from a transit link in Japan, and show that it can sustain a very high accuracy over the years, with significantly less cost and complexity than existing alternatives based on static learning algorithms, such as C4.5.

Concerns regarding the scalability of the interdomain routing have encouraged researchers to start elaborating a more robust Internet architecture. While consensus on the exact form of the solution is yet to be found, the need for a semantic decoupling of a node's location and identity is generally accepted as a promising way forward. However, this typically requires the use of caches that store temporal bindings between the two namespaces, to avoid hampering router packet forwarding speeds. In this article, we propose a methodology for an analytical analysis of cache performance that relies on the working-set theory. We first identify the conditions that network traffic must comply with for the theory to be applicable and then develop a model that predicts average cache miss rates relying on easily measurable traffic parameters. We validate the result by emulation, using real packet traces collected at the egress points of a campus and an academic network. To prove its versatility, we extend the model to consider cache polluting user traffic and observe that simple, low intensity attacks drastically reduce performance, whereby manufacturers should either overprovision router memory or implement more complex cache eviction policies.

Dragonfly networks have a two-level hierarchical arrangement of the network routers, and allow for a competitive cost-performance solution in large systems. Non-minimal adaptive routing is employed to fully exploit the path diversity and increase the performance under adversarial traffic patterns. Throughput unfairness prevents a balanced use of the resources across the network nodes and degrades severely the performance of any application running on an affected node. Previous works have demonstrated the presence of throughput unfairness in Dragonflies under certain adversarial traffic patterns, and proposed different alternatives to effectively combat such effect. In this paper we introduce a new traffic pattern denoted adversarial consecutive (ADVc), which portrays a real use case, and evaluate its impact on network performance and throughput fairness. This traffic pattern is the most adversarial in terms of network fairness. Our evaluations, both with or without transitover-injection priority, show that global misrouting policies do not properly alleviate this problem. Therefore, explicit fairness mechanisms are required for these networks. This work has been supported by the Spanish Ministry of Education, FPU grant FPU13/00337, the Spanish Science and Technology Commission (CICYT) under contracts TIN2012-34557 and TIN2013-46957-C2-2-P, the European Union FP7 under Agreement ERC-321253 (RoMoL), the European HiPEAC Network of Excellence, and the JSA no. 2013-119 as part of the IBM/BSC Technology Center for Supercomputing agreement.

Deep Packet Inspection (DPI) is the state-of-the-art technology for traffic classification. According to the conventional wisdom, DPI is the most accurate classification technique. Consequently, most popular products, either commercial or open-source, rely on some sort of DPI for traffic classification. However, the actual performance of DPI is still unclear to the research community, since the lack of public datasets prevent the comparison and reproducibility of their results. This paper presents a comprehensive comparison of 6 well-known DPI tools, which are commonly used in the traffic classification literature. Our study includes 2 commercial products (PACE and NBAR) and 4 open-source tools (OpenDPI, L7-filter, nDPI, and Libprotoident). We studied their performance in various scenarios (including packet and flow truncation) and at different classification levels (application protocol, application and web service). We carefully built a labeled dataset with more than 750 K flows, which contains traffic from popular applications. We used the Volunteer-Based System (VBS), developed at Aalborg University, to guarantee the correct labeling of the dataset. We released this dataset, including full packet payloads, to the research community. We believe this dataset could become a common benchmark for the comparison and validation of network traffic classifiers. Our results present PACE, a commercial tool, as the most accurate solution. Surprisingly, we find that some open-source tools, such as nDPI and Libprotoident, also achieve very high accuracy.

This paper provides a theoretical performance analysis of different classes of multicast routing algorithms, namely the Shortest Path Tree, the Steiner Tree, compact routing and greedy routing. Our motivation is to determine the routing scheme which would yield the best trade-off between the stretch of the multicast routing paths, the memory space required to store the routing information and routing table as well as the communication cost. For this purpose, we also confront these results to those obtained by simulation on the CAIDA map of the Internet topology comprising 32k nodes.

The real-world node deployment aspect is investigated, while considering cost minimization for resolving the energy hole around the sink, which represents a serious problem in typical sensor networks with uniform distribution. A novel strategy is proposed that is based on the use of two sinks and a few extra relay nodes close to the sinks' areas. The traffic is then alternatively sent to the sinks in every other cycle. As a second contribution, an efficient data collection mechanism has been developed to determine the optimal data rate that meets delay requirements of individual sensor reports and improves the network lifetime. The comparison of the proposed node deployment strategy with uniform, non-uniform geometric and linear increase node distributions demonstrates that the cost of the proposed solution is very close to that of the uniform distribution and much lower than all the others, while achieving a load balancing at the same order of the state-of-the-art solutions.

High-radix hierarchical networks are cost-effective topologies for large scale computers. In such networks, routers are organized in super nodes, with local and global interconnections. These networks, known as Dragonflies, outperform traditional topologies such as multi-trees or tori, in cost and scalability. However, depending on the traffic pattern, network congestion can lead to degraded performance. Misrouting (non-minimal routing) can be employed to avoid saturated global or local links. Nevertheless, with the current deadlock avoidance mechanisms used for these networks, supporting misrouting implies routers with a larger number of virtual channels. This exacerbates the buffer memory requirements that constitute one of the main constraints in high-radix switches. In this paper we introduce two novel deadlock-free routing mechanisms for Dragonfly networks that support on-the-fly adaptive routing. Using these schemes both global and local misrouting are allowed employing the same number of virtual channels as in previous proposals. Opportunistic Local Misrouting obtains the best performance by providing the highest routing freedom, and relying on a deadlock-free escape path to the destination for every packet. However, it requires Virtual Cut-Through flow-control. By contrast, Restricted Local Misrouting prevents the appearance of cycles thanks to a restriction of the possible routes within super nodes. This makes this mechanism suitable for both Virtual Cut-Through and Wormhole networks. Evaluations show that the proposed deadlock-free routing mechanisms prevent the most frequent pathological issues of Dragonfly networks. As a result, they provide higher performance than previous schemes, while requiring the same area devoted to router buffers. This work has been supported by the Spanish Ministry of Science under contracts TIN2010-21291-C02-02, TIN2012-34557, and by the European HiPEAC Network of Excellence. The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. ERC-2012-Adg-321253-RoMoL. M. Garc´ıa and M. Odriozola participated in this research work while they were affiliated with the University of Cantabria.

Network virtualization opens the door to novel infrastructure services offering connectivity and node manageability. In this letter, we focus on the cost-efficient embedding of on-demand virtual optical network requests for interconnecting geographically distributed data centers. We present a mixed integer linear programming formulation that introduces flexibility in the virtual-physical node mapping to optimize the usage of the underlying physical resources. Illustrative results show that flexibility in the node mapping can reduce the number of add-drop ports required to serve the offered demands by 40%.

Current inter-data-center connections are configured as static big fat pipes, which entails large bit rate over-provisioning and thus high operational costs for DC operators. On the other hand, network operators cannot share such connections between customers, because DC traffic varies greatly over time. Those connections are used to perform virtual machine migration and database synchronization among federated DCs, allowing elastic DC operations. To improve resource utilization and save costs, dynamic inter-DC connectivity is currently being targeted from a research point of view and in standardization form. In this article, we show that dynamic connectivity is not enough to guarantee elastic DC operations and might lead to poor performance provided that not enough overprovisioning of network resources is performed. To alleviate it to some extent, we propose using the flexgrid optical technology that enables finer spectrum granularity adaptation and the ability to dynamically increase and decrease the amount of optical resources assigned to connections. DCs can be interconnected through a flexgrid-based network controlled using a centralized software defined network, based on the architecture currently being proposed by the IETF; a cross-stratum orchestrator architecture coordinates DC and network elastically. Illustrative results show that dynamic elastic connectivity provides benefits by reducing the amount of overprovisioned network resources and facilitating elastic DC operations. The research leading to these results has received funding from the European Community’s Seventh Framework Pro- gramme FP7/2007-2013 under grant agreement no. 317999 IDEALIST project. Moreover, it was supported by the Span- ish science ministry through the TEC2011-27310 ELASTIC project.

Current literature defines the effective capacity of a wireless link as the maximum throughput that can be supported while meeting specific Quality of Service targets on packet delay. This metric can be harnessed for a wide variety of QoS control routines within wireless networks such as traffic optimisation and delay sensitive admission control and routing. However to date, no empirical evaluation of the effective capacity of 802.11 wireless links has been carried out. We present an empirical study of the effective capacity throughput of 802.11 wireless links under a number of network scenarios. We evaluate an analytical effective capacity model and compare the result with an empirical evaluation. We find that with an accurate measurement of the channel service delay, the effective capacity model can approximate the empirical measurement quite well. We also evaluate the relationship between the effective bandwidth of multimedia traffic and demonstrate that when the effective bandwidth exceeds the effective capacity threshold of a wireless link, the probability of QoS violations increases. We conclude that the effective capacity measurement is usable within an operational setting, and can lead to optimized utilization of bandwidth in a wide range of delay sensitive control operations.

Energy consumption of communication networks is growing very fast due to the rapidly increasing traffic demand. Consequently, design of green communication networks gained a lot of attention. In this paper we focus on optical Wavelength Division Multiplexing (WDM) networks, able to support this growing traffic demand. Several energy-aware routing and wavelength assignment (EA-RWA) techniques have been proposed for WDM networks in order to minimize their operational cost. These techniques aim at minimizing the number of active links by packing the traffic as much as possible, thus avoiding the use of lightly loaded links. As a result, EA-RWA techniques may lead to longer routes and to a high utilization on some specific links. This has a detrimental effect on the signal quality of the optical connections, i.e., lightpaths. In this study we quantify the impact of power consumption minimization on the optical signal quality. and address this problem by proposing a combined impairment and energy-aware RWA (IEA-RWA) approach. Towards this goal we developed a complete mathematical model that incorporates both linear and non-linear physical impairments together with an energy efficiency objective. The IEA-RWA problem is formulized as a Mixed Integer Linear Programming (MILP) model where both energy efficiency and signal quality considerations are jointly optimized. By comparing the proposed IEA-RWA approach with existing RWA (IA-RWA and EA-RWA) schemes, we demonstrate that our solution allows for a reduction of energy consumption close to the one obtained by EA-RWA approaches, while still guaranteeing a sufficient level of the optical signal quality.

Network traffic has traditionally exhibited temporal locality in the header field of packets. Such locality is intuitive and is a consequence of the semantics of network protocols. However, in contrast, the locality in the packet payload has not been studied in significant detail. In this work we study temporal locality in the packet payload. Temporal locality can also be viewed as redundancy, and we observe significant redundancy in the packet payload. We investigate mechanisms to exploit it in a networking application. We choose Intrusion Detection Systems (IDS) as a case study. An IDS like the popular Snort operates by scanning packet payload for known attack strings. It first builds a Finite State Machine (FSM) from a database of attack strings, and traverses this FSM using bytes from the packet payload. So temporal locality in network traffic provides us an opportunity to accelerate this FSM traversal. Our mechanism dynamically identifies redundant bytes in the packet and skips their redundant FSM traversal. We further parallelize our mechanism by performing the redundancy identification concurrently with stages of Snort packet processing. IDS are commonly deployed in commodity processors, and we evaluate our mechanism on an Intel Core i3. Our performance study indicates that the length of the redundant chunk is a key factor in performance. We also observe important performance benefits in deploying our redundancy-aware mechanism in the Snort IDS[32].

© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Channel assignment has been extensively researched for multi-radio wireless mesh networks, but it is still very challenging when it comes to its implementation. In this paper we propose a semi-dynamic and distributed channel assignment mechanism called SICA that uses game theory. To the best of our knowledge this is the first game formulation of channel assignment which takes the co-channel interference into account. SICA is an interference aware, distributed channel assignment which preserves the network connectivity without relying on a common channel nor central node for coordination between mesh routers. SICA applies an on-line learner algorithm which assumes that nodes do not have perfect information. We have simulated SICA and compared against another interference-aware channel assignment mechanism proposed in the literature called Urban-X. Simulation results show that SICA outperforms Urban-X, even using fewer radio interfaces per node.

A great part of core network operators’ gross profit comes from the provisioned connectivity services. In this work, we analyze the provisioning of differentiated services in current Shared Path Protection (SPP) environments. This analysis concludes that, with current resource assignment policies, only a very poor grade of service can be provided to the carried best effort traffic. Hence, we propose diff-WS, a resource partitioning scheme that differentiates those wavelengths supporting each class of service in the network. The benefits of diff-WS in front of current resource assignment policies are afterwards evaluated from an economic perspective. To this goal, we define the NORMA problem as a revenue maximization problem. To solve NORMA, we introduce statistical models to obtain, for a given grade of service, the highest traffic intensity for each supported class of service and resource assignment scheme. From the numerical results, we show that diff-WS maximizes resource utilization in the network and, thus, network operator’s profit.

Compact routing schemes address the fundamental tradeoff between the memory space required to store the routing table entries and the length of the routing paths that these schemes produce. This paper introduces the first known name-independent, leaf-initiated dynamic compact routing scheme that allows the distribution of traffic from any source to any set of leaf nodes along a multicast routing path that defines a distribution tree. By means of the proposed scheme, a multicast distribution tree dynamically evolves according to the arrival of leaf-initiated join/leave requests. To evaluate the performance we consider the following metrics: the stretch of the produced routing paths, the size and the number of routing table entries, and the communication cost. The results obtained by simulation on synthetic power law graphs (modeling the Internet topology) show that our scheme can successfully handle leaf-initiated dynamic setup of multicast distribution trees. Two reference multicast routing schemes (the Shortest Path Tree and the Steiner Tree algorithm) are used to compare the performance of the proposed scheme. While increasing the communication cost compared to the Shortest Path Tree, the proposed scheme achieves considerable reduction of the routing table size compared to both reference schemes. Moreover, the stretch of the resulting multicast routing paths show limited deterioration compared to the minimum value obtained with Steiner Trees.

Differentiated services provision according to clients or applications is an added feature that network operators ambition to fully provide. One of the possible approaches is to map DiffServ into MPLS based network. However in an IP over WDM (Wavelength Division Multiplexing) network data flow traverse multiple layers and, therefore, Class-Type information from the MPLS DiffServ layer is eventually lost. Besides, with the implement of a Path Computation Element (PCE) on multi-layer and multi-domain networks, the bandwidth constraints used to differentiate services are no longer applied. This paper presents a proposal for a QoS DiffServ approach applied on PCE as a traffic grooming technique for WDM core networks and the problematic involved on the application of this technology on multilayer and multi-domain networks.

The mobile cellular systems are expected to support multiple services with guaranteed Quality of Service(QoS). But, the ability of wireless systems to accommodate expected growth of traffic load and broadband services is limited by available radio frequency spectrum. Call Admission Control (CAC) is one of the resource management functions, which regulates network access to ensure QoS provisioning. However, the decision for CAC is very challenging issue due to user mobility, limited radio spectrum, and multimedia traffic characteristics. To deal with these problems, we implemented a Fuzzy Admission Control System (FACS). We compared the performance of FACS with Shadow Cluster Concept (SCC). In another work, we extended FACS by considering the priority of the on-going connections. We called this system FACS-P. As priority parameter, we considered only one parameter (service request). In this work, we improve our previous system by adding different priorities. We call this system FACS-MP. We evaluate and compare the performance of implemented systems by simulations. From the simulations results, we conclude that the FACS-MP can differentiate better different services compared with previous systems.

The mobile cellular systems are expected to support multiple services with guaranteed Quality of Service(QoS). But, the ability of wireless systems to accommodate expected growth of traffic load and broadband services is limited by available radio frequency spectrum. Call Admission Control (CAC) is one of the resource management functions, which regulates network access to ensure QoS provisioning. However, the decision for CAC is very challenging issue due to user mobility, limited radio spectrum, and multimedia traffic characteristics. In our previous work, we proposed a fuzzy-based CAC system by considering the priority of the on-going connections. As priority parameter, we considered only one parameter (service request). In this work, we extend our work by adding different priorities. We call this system FACS-MP. We evaluate by simulations the performance of the proposed system. From the simulations results, we conclude that the FACS-MP can differentiate better different services compared with previous system.

A Mobile Ad hoc Network (MANET) is a collection of wireless mobile terminals that are able to dynamically form a temporary network without any aid from fixed infrastructure or centralized administration. In recent years, MANETs are continuing to attract the attention for their potential use in several fields such as military activities, rescue operations and time-critical applications. In this paper, we present the implementation and analysis of our implemented wireless multi-hop network testbed considering the Optimized Link State Routing (OLSR) protocol for wireless multi-hop networking. We investigate the effect of mobility and topology changing in MANET. We study the impact of best-effort traffic for non line of sight communication. In this work, we consider three models: stationary, mobility and non line of sight communication models. We assess the performance of our testbed in terms of throughput and packet loss. From the experimental results, we found that OLSR has not a good performance when the relay node is moving. Also, the performance deteriorates when the CBR is higher.

The architecture definition, design, and validation of the interconnect networks is a key step in the design of modern on-chip systems. This paper proposes a mathematical formulation of the problem of simultaneously defining the topology of the network and the message routes for the traffic among the processing elements of the system. The solution of the problem meets the physical and performance constraints defined by the designer. The method guarantees that the generated solution is deadlock free. It is also capable of automatically discovering topologies that have been previously used in industrial systems. The applicability of the method has been validated by solving realistic size interconnect networks modeling the typical multiprocessor systems.

This paper presents a Cross-layer Network Management System (NMS) that allows Service Providers (SPs) to perform cost-effective network resource reservations with their Network Operators (NOs). The novelty of our NMS is that it offers a fresh and promising approach to use the endusers satisfaction level as the metric to perform the resource management. We show that our system is capable of achieving considerable reductions in the operational costs of SPs, while keeping proper bounds in the end-user satisfaction for the offered multimedia services.