An initial approach to distributed adaptive fault-handling in networked systems

We present a distributed adaptive fault-handling algorithm applied in networked systems. The probabilistic approach that we use makes the proposed method capable of adaptively detect and localize network faults by the use of simple end-to-end test transactions. Our method operates in a fully distributed manner, such that each network element detects faults using locally extracted information as input. This allows for a fast autonomous adaption to local network conditions in real-time, with significantly reduced need for manual configuration of algorithm parameters. Initial results from a small synthetically generated network indicate that satisfactory algorithm performance can be achieved, with respect to the number of detected and localized faults, detection time and false alarm rate

deTector: a Topology-aware Monitoring System for Data Center Networks

Troubleshooting network performance issues is a challenging task especially in large-scale data center networks. This paper presents deTector, a network monitoring system that is able to detect and localize network failures (manifested mainly by packet losses) accurately in near real time while minimizing the monitoring overhead. deTector achieves this goal by tightly coupling detection and localization and carefully selecting probe paths so that packet losses can be localized only according to end-to-end observations without the help of additional tools (e.g., tracert). In particular, we quantify the desirable properties of the matrix of probe paths, i.e., coverage and identifiability, and leverage an efficient greedy algorithm with a good approximation ratio and fast speed to select probe paths. We also propose a loss localization method according to loss patterns in a data center network. Our algorithm analysis, experimental evaluation on a Fattree testbed and supplementary large-scale simulation validate the scalability, feasibility and effectiveness of deTector.published_or_final_versio

EFFICIENT BANDWIDTH ESTIMATION MANAGEMENT FOR VOIP CONCURRENT MULTIPATH TRANSFER

Concurrent Multipath Transfer distributes incoming traffic simultaneously between several paths to maximize network resource utilization and to improve quality of service. Voices over IP real time application is more sensitive to delay and requires bandwidth guarantee. In this paper, Efficient Bandwidth Estimation Management for VoIP Concurrent Multipath Transfer is proposed. The proposed technique estimates the bandwidth of each path from a group and selects multiple paths from SCTP multihoming association to transmit VoIP traffic with assured bandwidth guarantees. Simulation results are reported using Ns2 network simulator to show the efficiency of the proposed syste

Overlay networks monitoring

The phenomenal growth of the Internet and its entry into many aspects of daily life has led to a great dependency on its services. Multimedia and content distribution applications (e.g., video streaming, online gaming, VoIP) require Quality of Service (QoS) guarantees in terms of bandwidth, delay, loss, and jitter to maintain a certain level of performance. Moreover, E-commerce applications and retail websites are faced with increasing demand for better throughput and response time performance. The most practical way to realize such applications is through the use of overlay networks, which are logical networks that implement service and resource management functionalities at the application layer. Overlays offer better deployability, scalability, security, and resiliency properties than network layer based implementation of services. Network monitoring and routing are among the most important issues in the design and operation of overlay networks. Accurate monitoring of QoS parameters is a challenging problem due to: (i) unbounded link stress in the underlying IP network, and (ii) the conflict in measurements caused by spatial and temporal overlap among measurement tasks. In this context, the focus of this dissertation is on the design and evaluation of efficient QoS monitoring and fault location algorithms using overlay networks. First, the issue of monitoring accuracy provided by multiple concurrent active measurements is studied on a large-scale overlay test-bed (PlanetLab), the factors affecting the accuracy are identified, and the measurement conflict problem is introduced. Then, the problem of conducting conflict-free measurements is formulated as a scheduling problem of real-time tasks, its complexity is proven to be NP-hard, and efficient heuristic algorithms for the problem are proposed. Second, an algorithm for minimizing monitoring overhead while controlling the IP link stress is proposed. Finally, the use of overlay monitoring to locate IP links\u27 faults is investigated. Specifically, the problem of designing an overlay network for verifying the location of IP links\u27 faults, under cost and link stress constraints, is formulated as an integer generalized flow problem, and its complexity is proven to be NP-hard. An optimal polynomial time algorithm for the relaxed problem (relaxed link stress constraints) is proposed. A combination of simulation and experimental studies using real-life measurement tools and Internet topologies of major ISP networks is conducted to evaluate the proposed algorithms. The studies show that the proposed algorithms significantly improve the accuracy and link stress of overlay monitoring, while incurring low overheads. The evaluation of fault location algorithms show that fast and highly accurate verification of faults can be achieved using overlay monitoring. In conclusion, the holistic view taken and the solutions developed for network monitoring provide a comprehensive framework for the design, operation, and evolution of overlay networks

RMD-QOSM: The NSIS Quality-of-Service Model for Resource Management in Diffserv

This document describes a Next Steps in Signaling (NSIS) Quality-of- Service (QoS) Model for networks that use the Resource Management in Diffserv (RMD) concept. RMD is a technique for adding admission control and preemption function to Differentiated Services (Diffserv) networks. The RMD QoS Model allows devices external to the RMD network to signal reservation requests to Edge nodes in the RMD network. The RMD Ingress Edge nodes classify the incoming flows into traffic classes and signals resource requests for the corresponding traffic class along the data path to the Egress Edge nodes for each flow. Egress nodes reconstitute the original requests and continue forwarding them along the data path towards the final destination. In addition, RMD defines notification functions to indicate overload situations within the domain to the Edge nodes

An Overview on Application of Machine Learning Techniques in Optical Networks

Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data. This information can be retrieved from network traffic traces, network alarms, signal quality indicators, users' behavioral data, etc. Advanced mathematical tools are required to extract meaningful information from these data and take decisions pertaining to the proper functioning of the networks from the network-generated data. Among these mathematical tools, Machine Learning (ML) is regarded as one of the most promising methodological approaches to perform network-data analysis and enable automated network self-configuration and fault management. The adoption of ML techniques in the field of optical communication networks is motivated by the unprecedented growth of network complexity faced by optical networks in the last few years. Such complexity increase is due to the introduction of a huge number of adjustable and interdependent system parameters (e.g., routing configurations, modulation format, symbol rate, coding schemes, etc.) that are enabled by the usage of coherent transmission/reception technologies, advanced digital signal processing and compensation of nonlinear effects in optical fiber propagation. In this paper we provide an overview of the application of ML to optical communications and networking. We classify and survey relevant literature dealing with the topic, and we also provide an introductory tutorial on ML for researchers and practitioners interested in this field. Although a good number of research papers have recently appeared, the application of ML to optical networks is still in its infancy: to stimulate further work in this area, we conclude the paper proposing new possible research directions

On Dynamic Monitoring Methods for Networks-on-Chip

Rapid ongoing evolution of multiprocessors will lead to systems with hundreds of processing cores integrated in a single chip. An emerging challenge is the implementation of reliable and efficient interconnection between these cores as well as other components in the systems. Network-on-Chip is an interconnection approach which is intended to solve the performance bottleneck caused by traditional, poorly scalable communication structures such as buses. However, a large on-chip network involves issues related to congestion problems and system control, for instance. Additionally, faults can cause problems in multiprocessor systems. These faults can be transient faults, permanent manufacturing faults, or they can appear due to aging. To solve the emerging traffic management, controllability issues and to maintain system operation regardless of faults a monitoring system is needed. The monitoring system should be dynamically applicable to various purposes and it should fully cover the system under observation. In a large multiprocessor the distances between components can be relatively long. Therefore, the system should be designed so that the amount of energy-inefficient long-distance communication is minimized. This thesis presents a dynamically clustered distributed monitoring structure. The monitoring is distributed so that no centralized control is required for basic tasks such as traffic management and task mapping. To enable extensive analysis of different Network-on-Chip architectures, an in-house SystemC based simulation environment was implemented. It allows transaction level analysis without time consuming circuit level implementations during early design phases of novel architectures and features. The presented analysis shows that the dynamically clustered monitoring structure can be efficiently utilized for traffic management in faulty and congested Network-on-Chip-based multiprocessor systems. The monitoring structure can be also successfully applied for task mapping purposes. Furthermore, the analysis shows that the presented in-house simulation environment is flexible and practical tool for extensive Network-on-Chip architecture analysis.Siirretty Doriast

Raising the Datagram API to Support Transport Protocol Evolution

Some application developers can wield huge resources to build new transport protocols, for these developers the present UDP Socket API is perfectly fine. They have access to large test beds and sophisticated tools. Many developers do not have these resources. This paper presents a new high-level Datagram API that is for everyone else, this has an advantage of offering a clear evolutionary path to support new requirements. This new API is needed to move forward the base of the system, allowing developers with limited resources to evolve their applications while accessing new network services