AQUILA network architecture: first trial experiments, Journal of Telecommunications and Information Technology, 2002, nr 2

The paper presents trial experiments with IP QoS network services (NS) defined and implemented in the AQUILA pilot installation. The AQUILA NSs (premium CBR, premium VBR, premium multimedia and premium mission critical) provide a framework for supporting a variety of applications generating both streaming and elastic traffic. The measurement experiments confirm that AQUILA architecture differentiates the QoS offered to these NSs. The presented numerical results were obtained in the test network installed in the Polish Telecom (Warsaw) consisting of 8 CISCO routers

FLEXNET: Flexible Networks for IoT based services

Internet of Things is becoming one of the main triggers in designing and deploying new services aiming at fulfilling the wide demand imposed by end-users. Usually, concrete solutions addressing the optimization of the wireless segment are found in the literature. However, it is much less frequent to find end-to-end solutions to be easily adopted by the corresponding stakeholders. It is in this context that FLEXNET brings an integrated solution, relying on cutting-edge technologies, dealing with a wide set of technical requirements imposed by the different applications and services.This work was supported by FLEXNET Project: "Flexible IoT Networks for Value Creators" (Celtic 2016/3), in the Eureka Celtic-Next Cluster

Artificial Intelligence Control Logic in Next-Generation Programmable Networks

The new generation of programmable networks allow mechanisms to be deployed for the efficient control of dynamic bandwidth allocation and ensure Quality of Service (QoS) in terms of Key Performance Indicators (KPIs) for delay or loss sensitive Internet of Things (IoT) services. To achieve flexible, dynamic and automated network resource management in Software-Defined Networking (SDN), Artificial Intelligence (AI) algorithms can provide an effective solution. In the paper, we propose the solution for network resources allocation, where the AI algorithm is responsible for controlling intent-based routing in SDN. The paper focuses on the problem of optimal switching of intents between two designated paths using the Deep-Q-Learning approach based on an artificial neural network. The proposed algorithm is the main novelty of this paper. The Developed Networked Application Emulation System (NAPES) allows the AI solution to be tested with different patterns to evaluate the performance of the proposed solution. The AI algorithm was trained to maximize the total throughput in the network and effective network utilization. The results presented confirm the validity of applied AI approach to the problem of improving network performance in next-generation networks and the usefulness of the NAPES traffic generator for efficient economical and technical deployment in IoT networking systems evaluation

Towards Operator-managed P2P Content Delivery with Application Layer Traffic Optimization

P2P technology provides a flexible and very popular way of content delivery for various services, including networked media applications. However, P2P-based content delivery generates large amount of backbone traffic. Recently, several approaches have been proposed for guiding P2P services based on operator preferences, in order to reduce the amount of costly backbone traffic generated by P2P applications. Application Layer Traffic Optimization (ALTO) is a one key approach for such managed P2P applications. In short, ALTO is a dedicated service, operated by a network operator or ISP, which can provide useful network layer information to application layer clients for improved peer selection and corresponding content delivery. This paper provides an overview of standardisation and research activities for improving P2P content delivery with ALTO which are carried out within the EU FP7 project NAPA-WINE. In particular, we give an overview on standardisation efforts, present simulation results, explain our prototypical implementation of the ALTO concept, and highlight ongoing large-scale operational trials we are currently conducting within the network of Polish Telecom and among NAPA-WINE partnersEU FP-7 NAPA-WIN

Experiences with large-scale operational trials of ALTO-enhanced P2P filesharing in an intra-ISP scenario

Application Layer Traffic Optimization (ALTO) has recently gained attention in the research and standardisation community as a way for a network operator to guide the peer selection process of distributed applications by providing network layer topology information. In particular P2P applications are expected to gain from ALTO, due to the many connections peers form among each other, often without taking network layer topology information into account. In this paper, we present results of an extensive intra-ISP trial with an ALTO-enhanced P2P filesharing software. In summary, our results show that—depending on the concrete setting and on the distribution of upload capacity in the network—ALTO enables an ISP to save operational costs significantly while not degrading application layer performance noticeably. In addition, based on our experience we are able to give advice to operators on how to save costs with ALTO while not sacrificing application layer performance at all

Project Number: IST-1999-10077

This deliverable details the system architecture used for the prototypes in the first trial