LIDS Lectures 22 &23 Flow and congestion contro Eytan Modiano Laboratory for Information and Decision Systems
QuickTime™ and a GIF decompressor are needed to see this picture. QuickTime™ and a Photo - JPEG decompressor are needed to see this picture. LIDS Lectures 22 & 23 Flow and congestion control Eytan Modiano Eytan Modiano Slide 1 Laboratory for Information and Decision Systems
FLOW CONTROL LIDS Flow control: end-to-end mechanism for regulating traffic between source and destination Congestion control: Mechanism used by the network to limit congestion The two are not really separable, and I will refer to both as flow control In either case, both amount to mechanisms for limiting the amount of traffic entering the network ometimes the load is more than the network can handle Laboratory for Information and Decision Systems
FLOW CONTROL QuickTime™ and a GIF decompressor are needed to see this picture. QuickTime™ and a Photo - JPEG decompressor are needed to see this picture. LIDS • Flow control: end-to-end mechanism for regulating traffic between source and destination • Congestion control: Mechanism used by the network to limit congestion • The two are not really separable, and I will refer to both as flow control • In either case, both amount to mechanisms for limiting the amount of traffic entering the network – Sometimes the load is more than the network can handle Eytan Modiano Slide 2 Laboratory for Information and Decision Systems
WITHOUT FLOW CONTROL LIDS when overload occurs queues build up packets are discarded Sources retransmit messages congestion increases = instability Flow control prevents network instability by keeping packets waiting outside the network rather than in queues inside the network Avoids wasting network resources Prevent"disasters” Laboratory for Information and Decision Systems
WITHOUT FLOW CONTROL QuickTime™ and a GIF decompressor are needed to see this picture. QuickTime™ and a Photo - JPEG decompressor are needed to see this picture. LIDS • When overload occurs – queues build up – packets are discarded – Sources retransmit messages – congestion increases => instability • Flow control prevents network instability by keeping packets waiting outside the network rather than in queues inside the network – Avoids wasting network resources – Prevent “disasters” Eytan Modiano Slide 3 Lab oratory for Information and Decision Systems
OBJECTIVES OF FLOW CONTROL LIDS Maximize network throughput Reduce network delays Maintain quality-of-service parameters Fairness delay etc Tradeoff between fairness, delay, throughput Laboratory for Information and Decision Systems
OBJECTIVES OF FLOW CONTROL QuickTime™ and a GIF decompressor are needed to see this picture. QuickTime™ and a Photo - JPEG decompressor are needed to see this picture. LIDS • Maximize network throughput • Reduce network delays • Maintain quality-of-service parameters – Fairness, delay, etc.. • Tradeoff between fairness, delay, throughput… Eytan Modiano Slide 4 Lab oratory for Information and Decision Systems
FAIRNESS LIDS Session 1 Session 2 Session 3 Session 4 If link capacities are each 1 unit, then Maximum throughput is achieved by giving short session one unit and zero units to the long session; total throughput of 3 units One concept of fairness would give each user 1/2 unit; total throughput of 2 units Alternatively, giving equal resources to each session would give single link users 3/4 each, and 1/4 unit to the long session Laboratory for Information and Decision Systems
FAIRNESS QuickTime™ and a GIF decompressor are needed to see this picture. QuickTime™ and a Photo - JPEG decompressor are needed to see this picture. LIDS Session 1 Session 2 Session 3 Session 4 • If link capacities are each 1 unit, then – Maximum throughput is achieved by giving short session one unit and zero units to the long session; total throughput of 3 units – One concept of fairness would give each user 1/2 unit; total throughput of 2 units – Alternatively, giving equal resources to each session would give single link users 3/4 each, and 1/4 unit to the long session Eytan Modiano Slide 5 Laboratory for Information and Decision Systems