KEYWORDS: Signal attenuation, Performance modeling, Astatine, Failure analysis, Video, Switching, Solids, Signal detection, Positive feedback, Control systems
We show how to model the black-holing and looping of traffic during an Interior Gateway Protocol (IGP) convergence event at an IP network and how to significantly improve both the convergence time and packet loss duration through IGP parameter tuning and algorithmic improvement. We also explore some congestion avoidance and congestion control algorithms that can significantly improve stability of networks in the face of occasional massive control message storms. Specifically we show the positive impacts of prioritizing Hello and Acknowledgement packets and slowing down LSA generation and retransmission generation on detecting congestion in the network. For some types of video, voice signaling and circuit emulation applications it is necessary to reduce traffic loss durations following a convergence event to below 100 ms and we explore that using Fast Reroute algorithms based on Multiprotocol Label Switching Traffic Engineering (MPLS-TE) that effectively bypasses IGP convergence. We explore the scalability of primary and backup MPLS-TE tunnels where MPLS-TE domain is in the backbone-only or edge-to-edge. We also show how much extra backbone resource is needed to support Fast Reroute and how can that be reduced by taking advantage of Constrained Shortest Path (CSPF) routing of MPLS-TE and by reserving less than 100% of primary tunnel bandwidth during Fast Reroute.
Nationwide IP networks typically include nodes in major cities and the following elements: customer equipment, access routers, backbone routers, peering routers, access links connecting customer equipment to access routers, access routers to backbone routers, and backbone links interconnecting backbone routers. The part of this network consisting of backbone routers and related interconnecting links is referred to as the “backbone”. We develop a new approach for accurately computing the Availability measure of IP networks by directly simulating each type of backbone outage event and its impact on traffic loss. We use this approach to quantify availability improvement as a result of introducing various technological changes in the network such as IGP tuning, high availability router architecture, MPLS-TE and Fast Reroute. A situation, where operational backbone links do not have enough spare capacity to carry additional traffic during the outage time, is referred to as bandwidth loss. We concentrate on one unidirectional backbone link and derive asymptotic approximations for the expected bandwidth loss in the framework of generalized Erlang and Engset models when the total number of resource units and request arrival rates are proportionally large. Simulation results demonstrate good accuracy of the approximations.
Modern communication networks carry several grades of data, voice and video sessions typically using single-service or multi-service platforms employing IP, ATM or MPLS protocol mechanisms. It is well established that in many instances the session duration may have a heavy-tailed distribution [1-2]. We explore the impact of such distributions on the response time performance of user sessions. We concentrate mainly on a single output link (potentially a bottleneck on the data path) of a multi-service platform. First-come-first-served and processor sharing type scheduling mechanisms are considered (weighted fair queueing and weighted round robin are implementable approximations to generalized processor sharing). The output link is modeled as a single-server (no limit on individual session rate) or multiple servers (rate limit on individual sessions either inherently as for CBR applications or for congestion avoidance as in a cable access network). Also, the impacts of bandwidth differences between input and output links are considered. It is observed that in some cases, heavy-tailed session durations have significant impacts but those impacts may be effectively neutralized using appropriate scheduling or rate control mechanisms.
In order to transfer voice or some other application requiring real-time presentation over a packet network we need a de-jitter buffer to eliminate delay jitters. An important design parameter is the depth of the de-jitter buffer since it influences two important parameters controlling voice quality, namely voice-path delay and packet loss probability. In this paper we propose and study several schemes for optimally adjusting the depth of the de-jitter buffer. In addition to de-jitter-buffer depth adjustments within a call, the initial value and rates of changes of the de-jitter buffer depth are allowed to depend on the class of the call and are adaptively adjusted (upwards or downwards) for every new call based on voice-path delay and packet loss probability measurements over one or more previous calls. Parameter adjustments are geared towards either (a) minimizing voice-path delay while maintaining a packet loss probability objective, or (b) maximizing R-Factor, an objective measure of voice quality that depends both on the voice-path delay and the packet loss probability. Using simulation models it is shown that adaptive schemes perform better than static ones and adaptive schemes with learning perform better than ones without learning.
KEYWORDS: Data modeling, Nickel, Computer programming, Bismuth, Computer simulations, Video, FDA class I medical device development, Performance modeling, Algorithm development, Multiplexing
We develop exact models to analyze the performance of several types and grades of data, voice and video sessions over a cable or DSL based access network. Each session is characterized by a minimum guaranteed data-rate and a maximum allowed data-rate. Sessions would normally transmit at the maximum rate but under congestion some or all sessions would see graceful rate degradation. For each class the blocking probability and the average data-rate attained by a session are computed. In addition, a system-wide probability of rate degradation is also computed. A bufferless model with product-form structure and insensitivity to session holding time distribution except through mean (heavy-tailed distributions are allowed), and a buffered model with standard Markov chain structure are developed. The models are also generalized to allow rate degradation of real-time streaming traffic (e.g., switch from G.711 to G.728 encoding or turn on silence suppression) whenever the total bandwidth usage exceeds a certain threshold. Whenever a model is sensitive to session holding time distribution, that sensitivity is studied through simulations.
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