Multimedia Networking

7.7.2 Policing: The Leaky Bucket

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Introduction
7.1 Multimedia Networking Applications
7.1.1 Examples of Multimedia Applications
7.1.2 Hurdles for Multimedia in Today's Internet
7.1.3 How Should the Internet Evolve to Support Multimedia Better?
7.1.4 Audio and Video Compression
7.2 Streamimg Stored Audio and Video
7.2.1 Accessing Audio and Video Through a Web Server
7.2.2 Sending Multimedia from a Streaming Server to a Helper Application
7.2.3 Real-Time Streaming Protocol (RTSP)
7.3 Making the Best of the Best-Effort Service: An Internet Phone Example
7.3.1 The Limitations of a Best-Effort Service
7.3.2 Removing Jitter at the Receiver for Audio
7.3.3 Recovering from Packet Loss
7.4 Protocols for Real-Time Interactive Applications
7.4.1 RTP
7.4.2 RTP Control Protocol (RTCP)
7.4.3 SIP
7.4.4 H.323
7.5 Distributing Multimedia: Content Distribution Networks
7.6 Beyond Best Effort
7.6.1 Scenario 1: A 1 Mbps Audio Application and an FTP
7.6.2 Scenario 2: A 1 Mbps Audio Application and a High-Priority FTP Transfer
7.6.3 Scenario 3: A Misbehaving Audio Application and an FTP Transfer
7.6.4 Scenario 4: Two 1 Mbps Audio Applications over an Overload 1.5 Mbps Link
7.7 Scheduling and Policing Mechanisms
7.7.1 Scheduling Mechanisms
7.7.2 Policing: The Leaky Bucket
7.8 Intergrated Services and Differentiated Services
7.8.1 Intserv
7.8.2 Diffserv
7.9 RSVP
7.9.1 The Essence of RSVP
7.9.2 A Few Simple Examples
Policing: The Leaky Bucket

Policing the regulation of the rate at which a flow is allowed to inject packets into the network, as on of the cornerstones of any QoS architecture.  But what aspects of a flow's packet rate should be policed?  We can identify three important policing criteria, each differing from the other according to the time scale over which the packet flow is policed:
Average rate-The network may wish to limit the long-term average rate at which a flow's packets can be sent into the network.
Peak rate-While the average rate constraint limits the amount of traffic that can be sent into the network over a relatively long period of time, a peak-rate constraint limits the maximum number of packets that can be sent over a shorter period of time.
Burst size-The network may also wish to limit the maximum number of packets that can be sent into the network over an extremely short interval of times.
 
The leaky bucket mechanism is an abstraction that can be used to characterize these policing limits.  A leaky bucket consists of a bucket that can hold up to b tokens.  Tookens are added to this bucket as folows.  New tokens, which may poorentially be added to the bucket, are always being generated at a rate of r tokens per second.  If the bucket is filled with less than b tokens when a token is gererated, the newly generated token is added to the bucket; otherwise the newly generated token is ignored, and the token bucket remains full with b tokens.

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