Scalable monitoring support for resource management and service assurance

Abstract

Continuous monitoring of network status and its resources are necessary to ensure proper network operation. Deployment of QoS-based value-added services in IP networks necessitates the employment of resource management techniques and specifically the use of traffic engineering. The latter typically relies on monitoring data for both offline proactive and dynamic reactive solutions. The variety of data to be collected and analyzed using different measurement methods and tools, and the extent of monitoring information to use demand a proper QoS monitoring infrastructure. A monitoring system should be scalable in terms of network size, speed, and number of customers subscribed to value-added services. This article investigates the requirements of scalable monitoring system architectures, proposes principles for designing such systems, and validates them through the design and implementation of a scalable monitoring system for QoS delivery in IP differentiated services networks. Experimental assessment results prove the accuracy and scalability of the proposed monitoring system.

AMPLE: an adaptive traffic engineering system based on virtual routing topologies

“…AMPLE adopts a hop-by-hop based monitoring mechanism that is similar to the proposal of [8]. The basic idea is that, a dedicated monitoring agent deployed at every PoP node is responsible for monitoring: (1) the volume of the traffic originated by the local customers towards other PoPs (intra-PoP traffic is ignored), and (2) …”

A Cooperative Network Monitoring Overlay

“…However, capturing network behaviour combining hop-by-hop measures is not an efficient and easy solution as it involves : (i) a high-degree of metrics' concatenation; (ii) monitoring agents in all network nodes; and (iii) additional traffic in the network for reporting metrics to management stations. To reduce the amount of data exchanged between management stations and MPs, several solutions have been pointed out, namely the use of flow aggregation [5], statistical summarisation [6] and network thresholds crossing alerts [7].…”

On the Performance and Scalability of Web Services for Monitoring MPLS-based Networks

“…Examples of such work are the frameworks proposed by the TEQUILA [46,47], CADENUS [48], and ENTHRONE [49] projects. QoS is currently provided on the basis of a set of terms that clients and service providers have to abide by, called Service Level Agreements (SLAs).…”

“…Two types of measurements can be identified: active and passive ones. Active measurements are performed by injecting synthetic traffic to the network in order to monitor delay, jitter and packet loss, whereas passive measurements can be conducted using Management Information Bases from SNMP and involve measuring throughput, load and packet discards at the PHB, SLS and LSP levels [46,47,49]. The type and the specific points where passive measurements can be performed are the following:…”