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Endpoint Admission Control : Network Based Approach Byung Kyu Choi Riccardo Bettati Apr. 17th, 2001 Dept. of Computer Science Texas A&M University {choib, bettati}@cs.tamu.edu 1 Introduction (1/2) : Integrated/Differentiated Services Architectures • Best-Effort Services – No guarantee on timeliness or actual delivery – No admission control • Integrated Services – Each flow is treated differently based on its requirement – Available services :Guaranteed service, Controlled-load service – Scalability ? • Differentiated Services – Edge routers : classify, police, shape, and schedule input packets – Core routers : schedule packets based on aggregate behavior – Available services : Premium service, Assured service – Scalability ? • Flow aggregation ---> Data plane ! • Bandwidth Broker ---> Control plane ? 2 Introduction (2/2) : Scalability in Real-Time Communication Services For traditional computer network Best-Effort For guaranteed real-time services Integrated Services For scalability Data Plane Packet forwarding Flow Aggregation Differentiated Services Control Plane Admission control Bandwidth Broker 3 Motivation (1/3) : Signaling Procedure and Signaling Overhead Service Network Request Response Service Request N1 N1 N2 N3 Network Response N2 B.B. N5 N4 N5 N3 RSVP style N4 Bandwidth Broker Approach On-demand Premium Service : RFC 2638 4 Motivation (2/3) : Observations on signaling • A core router can maintain hundreds of thousands of flows ! – If a large number of real-time flows come on-demand, because the user can be anywhere at anytime on the Internet ... • Signaling explosion ? – A huge amount of signaling activity is expected for establishment and tear-down • If the admission decision can be made at the entrance of the network: – The number of signaling messages is greatly reduced. – The load of admission control is shared across ingress routers. – As a result, the latency in setting up a flow is greatly reduced too. • If resource can be reserved in a hard fashion: – Refresh can be eliminated. 5 Motivation (3/3) : Endpoint Admission Control and Hard Reservations RSVP style Bandwidth Broker Approach Hard Resource Reservation Endpoint Admission Control 6 This paper presents : Design and evaluate an endpoint admission control for real-time services in a single domain which supports : Signaling Low signaling overhead Low admission decision time Efficiency High admission probability High resource utilization Fast flow set-up 7 Previous work (1/2) : Work on signaling overhead • Host-based endpoint admission control – Measurement-based admission control (packet probing) – No signaling messages exchanged – Nothing needs to be changed on router • Hard to guarantee fast flow set-up : long probing time • Hard to guarantee end-to-end delay & bandwidth for lifetime : vulnerable allocation • Light weight signaling protocols : RSVP, YESSIR, BGRP, Boomerang, .. All IntServ rooted – Soft reservation with refresh messages – Hard to guarantee end-to-end delay, – Hard to guarantee bandwidth • Not appropriate for real-time applications 8 Previous work (2/2) : Scalable admission control • Our approach: Off-Line bandwidth assignment to classes and delay verification during system (re-)configuration. • Assign portion of link bandwidths to each class. • Then, perform delay test for connections of each class in a flowunaware fashion. • If delay test passes (less than the requirement), the bandwidth allocation is a valid one. • On-line end-to-end delay calculation: Eliminated by checking available bandwidth only • Publication1 : “Utilization-based Admission Control for Real-Time Communication,” Accepted by Journal of Real-Time System, 2000. • Publication2 : “Scalable QoS Guaranteed Communication Services for Real-Time Applications, ICDCS 2000, pp. 180-187. 9 Sink-tree paradigm (1/5) • Benefit : Endpoint admission control and hard reservation • How ? – Distribute admission control to ingress nodes – Allocate bandwidth to links on trees one for each egress router • Question : How to find such a set of sink trees ? – Three constraints in bandwidth allocation • Link Capacity • Depth-aware Bandwidth Allocation • Bounded Worst-case End-to-End Delay • Finding such a set of sink-trees is NP-hard. • Heuristic algorithm for finding a set of sink-trees for a given network – Use MST (Minimum Spanning Tree) • Strictly partitioned resource ? ----> Resource sharing 10 Sink-tree paradigm (2/5) : sink-tree example B : Bandwidth Allocated N7 Root (Sink) B=30 Core router : N5, N6 N5 Egress router : N7 B=70 N6 B=10 B=20 B=30 B=40 N1 N2 N3 N4 Ingress router : N1, N2, N3, N4 11 Sink-tree paradigm (3/5) : Operation example Uniform Resource Allocation Admission Blocking in Uniform N1 B=10 N1 F=10 B=10 N4 N2 B=10 B=10 N3 Total bandwidth allocated : 40 F=10 N4 N2 B=10 B=10 N3 Total real-time flows admitted to N1 : 20 12 Sink-tree paradigm (4/5) : Operation example Sink-tree Resource Allocation Improved Admission in Sink-tree N1 B=10 N1 F=10 B=20 N4 N2 F=20 N4 N2 B=10 F=10 N3 N3 Total bandwidth allocated : 40 Total real-time flows admitted to N1 : 30 13 Sink tree paradigm (5/5) : Resource Sharing • Study on Resource Sharing in the sink tree – – – – Fixed partitioning of resources will be inefficient On-line re-computation of resource allocation will be expensive Light weight method is needed for adaptive resource usage We investigate performances in the four steps of resource sharing : • No sharing, Path sharing, Tree sharing, Link sharing Service Request N1 Service Request B=10 N2 Service Request B=20 N3 B=30 N4 14 Performance evaluation (1/5) • For a single DS Domain – Admission probability and resource utilization – The worst-case end-to-end delays • Comparison against “uniform resource allocation” – Bandwidth allocation : uniform to each link – Path selection : Shortest-Path-First Routing – We call this “Flat-Fixed” system. • Sink tree-based system – Bandwidth allocation : sink-tree construction – Path selection : pre-defined along sink-tree 15 Perf. evaluation (2/5) : Simulation spec. • Call generation – Call arrival : Poisson process with rate – Flow lifetime : exponentially distributed with 180 sec., in average – Source and destination routers : chosen randomly • Network : MCI backbone topology – Homogeneous links : 155 Mbps • Real-time application : Voice-over-IP • Traffic characteristics – Fixed packet length : 640 bits (RTP, UDP, IP headers + 2 voice frame.) – Flow rate : 32 Kbps – End-to-end delay requirement : 100 ms 16 Perf. Evaluation (3/5) : Network topology for simulation 17 Perf. evaluation (4/5) : Admission probability 18 Perf. Evaluation (5/5) : Configuration effect on admission probability 19 Conclusions High admission probability Endpoint admission control based on sink tree Endpoint-limited signaling Ingress node admission decision Pre-determined path & resource allocation Low signaling overhead Fast flow set-up Low routing overhead 20