Leobino Nascimento Sampaio

MonONTO: A Domain Ontology for Network Monitoring and Recommendation for Advanced Internet Applications Users

In order to make recommendations to users about the potential performance of advanced Internet applications - in the scope of network monitoring - it is not sufficient to just analyze the network performance metrics: it should be also considered information concerning the application type, the traffic generated, and the user profile. In the present paper, we propose a new approach for monitoring the performance of advanced Internet applications based on the use of an expert system. The expert system will infer from a domain ontology named MonONTO. This ontology amasses the main concepts and their relationships in the following sub-domains: quality of service of advanced applications, network performance measurements, and user profiles. The knowledge base, originated from MonONTO, demonstrated its use and importance in the domain described here through axioms creation and inferences performed using a specific experimental rule engine.

A knowledge and collaboration-based CBR process to improve network performance-related support activities

Abstract In a context characterized by a growing demand for networked services, users of advanced applications sometimes face network performance troubles that may actually prevent them from completing their tasks. Therefore, providing assistance for user communities that have difficulties using the network has been identified as one of the major issues of performance-related support activities. Despite the advances network management has made over the last years, there is a lack of guidance services to provide users with information that goes beyond merely presenting network properties. In this light, the research community has been highlighting the importance of User-Perceived Quality (UPQ) scores during the evaluation of network services for network applications, such as Quality of Experience (QoE) and Mean Opinion Score (MOS). However, despite their potential to assist end-users to deal with network performance troubles, only few types of network applications have well established UPQ scores. Besides that, they are defined through experiments essentially conducted in laboratory, rather than actual usage. This paper thus presents a knowledge and Collaboration-based Network Users’ Support (CNUS) Case-Based Reasoning (CBR) Process that predicts UPQ scores to assist users by focusing on the collaboration among them through the sharing of their experiences in using network applications. It builds (i) a knowledge base that includes not only information about network performance problems, but also applications’ characteristics, (ii) a case base that contains users’ opinions, and (iii) a user database that stores users’ profiles. By processing them, CNUS benefits users through the indication of the degree of satisfaction they may achieve based on the general opinion from members of their communities in similar contexts. In order to evaluate the suitability of CNUS, a CBR system was built and validated through an experimental study conducted in laboratory with a multi-agent system that simulated scenarios where users request for assistance. The simulation was supported by an ontology of network services and applications and reputation scheme implemented through the PageRank algorithm. The results of the study pointed to the effectiveness of CNUS, and its resilience to users’ collusive and incoherent behaviors. Besides that, they showed the influence of the knowledge about network characteristics, users’ profiles and application features on computer-based support activities.

Implementing and Deploying Network Monitoring Service Oriented Architectures: Brazilian National Education and Research Network Measurement Experiments

Recently there is a growing interest in accessing network measurement and status data across multiple domains, in order to detect eventual network problems which can hinder the use of advanced applications. Diversity on network technologies, technical solutions and network managers add to the complexity of providing such information. In order to facilitate the performance data access and visualization, some initiatives have been directed to the development and deployment of network monitoring service oriented architectures (NMSOA). This paper aims at presenting RNPs End-to-end Performance Working Group activities on implementing and deploying two of these architectures: piPEs-BR and perfSONAR. Initially it is presented an overview of related work, followed by a detailed presentation of these architectures. perfSONAR is being jointly developed by Internet2, Geant2, RNP, and the University of Delaware. We focus on the components developed by our WG and our experience on deploying this measurement environment at Ipe and Clara networks. The paper concludes with a presentation of the major learned lessons with these experiences and which can be useful to deploy such environment in other NRENs, followed by our concluding remarks and pointers for future directions.

BEEP: Balancing Energy, Redundancy, and Performance in Fat-Tree Data Center Networks

BEEP is an energy-efficient strategy for data center networks (DCNs) based on a fat-tree topology. This strategy combines multipaths and the global overview offered by software-defined networks (SDNs) to balance energy efficiency, equipment redundancy levels, and DCN performance. BEEP is implemented in an OpenFlow network with multipaths enabled by using Multipath TCP (MPTCP). Experimental results in different variations of the fat-tree topology and redundancy levels show gains in energy savings of 30-45 percent. Additionally, BEEP achieves better available bandwidth usage, because more alternative paths are available.

On the composition of performance metrics in multi-domain networks

Despite the advances achieved by service oriented architectures adoption, data originated from measurements are still used in an isolated manner. In multi-domain network scenarios, performance information needs to be processed and related in such a way as to present more relevant results through a metric composition process. Based on recent IETF documents, this article describes a performance metric composition process implemented via software, through a library that can be integrated into diverse visualization and monitoring applications. Experiments using ESnet and Géant backbones performance data demonstrated the effectiveness of the model, the library, and IETFs proposed approach.

Balancing Energy, Redundancy, and Performance in Datacenter Networks

The current large-scale datacenters typically adopt redundancy of servers and communication devices for increased reliability and availability. A highly redundant infrastructure, however, is one of the challenges of the area due to the high energy consumption. This paper presents BEEP, an energy-efficient strategy for datacenter networks based on the Fat Tree topology. Our strategy uses multipaths and the global view offered by software-defined networks to balance the energy efficiency, the equipment redundancy level, and the performance gain when dealing with the traffic demands. BEEP was implemented in an OpenFlow network and the multipaths were implemented using MPTCP (Multipath TCP). The experimental results in variants of the Fat Tree topology show gains in the energy efficiency with the strategy in the order of 30% to 45%, in addition to a better utilization of the available bandwidth, as more alternative paths are available.

An Instrumentation and Measurement Architecture Supporting Multiple Control Monitoring Frameworks

Virtual and/or experimental networks capable of supporting an entire new set of applications and services (Future Internet, Grids, Cloud Computing, other) use, typically, different Control and Monitoring Frameworks (CMFs). This poster addresses the multiple federated CMFs instrumentation and measurement problems. A monitoring architecture (FIBRE-BR IM the collected data control access; and, finally, the multiple CMFs I&M data integration. This poster presents the FIBRE-BR I&M Architecture that integrates diverse I&M services, tools and facilities from multiple CMFs, allowing FIBRE-BR users, possibly transparently to each specific CMF, to benefit from the corresponding infrastructure and experiment specific measurement data.

A network performance recommendation process for advanced internet applications users

Advanced applications have caused end-users to show a new interest in accessing network measurement and status data across multiple domains, in order to detect occasional network problems. Diversity of network technologies, technical solutions and network managers add to the complexity of providing such information, which, when available, includes technical details that are meaningful only to specialists. However, context awareness can ease the recommendation process underlying a monitoring infrastructure. This research investigates a novel approach for traffic monitoring in view of the context information used to provide network performance recommendations in the most productive way.