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How is performance measured? #3 Victor S. Frost Dan F. Servey Distinguished Professor Electrical Engineering and Computer Science University of Kansas 2335 Irving Hill Dr. Lawrence, Kansas 66045 Phone: (785) 864-4833 FAX:(785) 864-7789 e-mail: [email protected] http://www.ittc.ku.edu/ All material copyright 2006 Victor S. Frost, All Rights Reserved #3 1 Outline • • • • • • What is ideal? Application types Barriers to achieving the ideal Performance metrics Network Performance Perspective What performance can the network guarantee #3 2 Goals • What is the ideal? – Meet customer expectations • Service experience satisfies customer requirements • Motivate customers to stay with service provider • Motivate customers to even recommend the service provider – With finite resources • • • • • Capacity Power Processing Buffers Other considerations – Unequal cost for resources – Sometimes stated as satisfy customer expectations while “maximizing” network utilization. However that only considers “one” dimension of the problem #3 3 What is the service experience? • Web page download in X sec, where X [5,10] • For voice, no network busy • For IM, message delivered in X Min, where X [5-15] • For E-mail, delivery in X min where X [10-30] • Noticeable video impairments greater than X min apart where X ~30min • Noticeable voice impairments greater than X min apart where X ~10min #3 4 Another perspective on application requirements • Elastic – Non-real-time, does not need a fixed amount of capacity – No deadline – Examples • • • • File transfer E-mail MP3 download Video download What is the contradiction? • Loss-tolerant/Loss-intolerant • Real-time – All packets must be delivered, e.g., file transfer – Occasional packet loss may not impact the service, e.g., voice and video – – – – Deadlines May require playout timing Late packets as bad as lost packets Examples • Real-time viewing of sporting event • Interactive speech #3 5 More examples From: Computer Networking: A Top Down Approach Featuring the Internet, 2nd edition. Jim Kurose, Keith RossAddison-Wesley, July 2002. #3 6 Barriers to the Ideal • Many of the barriers are in the access (last mile) segment of the network • Propagation delay lack of accurate knowledge of the network state • Efficiency of access network protocols • Access connection conditions and variability, e.g., – Noise • Thermal • Interference • Intentional jamming – Multipath fading • Interaction of end-to-end and link protocols • Limited network capacity #3 7 Barriers to the ideal • Limited capacity of end server: with an ideal network the application server maybe be: – Overloaded – Mis-configured • Issues with the application server are not considered here #3 8 What is the perceived QoS for this end-to-end path? #3 9 Network Performance Criteria • • • • • • Or How to rate how close to ideal can we get Response Time Throughput b/s Channel Utilization Channel Efficiency Channel Capacity (not Shannon’s information theory capacity) Blocking Probability – Packet – Call • Fairness • Security • Reliability #3 10 Network Performance Criteria Response time TR: The time to “correctly” transmit a packet from Source to destination. “correctly” implies Response time includes acknowledgments Source Host Network Interface Card Network Network Interface Card Destination Host #3 11 Network Performance Criteria: Response Time • Time from source applications to NIC • Waiting time in NIC to enter the network: buffering time • Time to transmit the packet: clock the packet into the network • Time for the network to deliver the packet to the destination’s NIC • Time for destination’s NIC to generate an acknowledgment • Time for the acknowledgment to reach the source host: repeating the above steps #3 12 Network Performance Criteria: Response Time Dependencies • State of the network – Current topology – Active nodes – Active links • State of the other users • • • • • – Congestion Errors State of source/destination host Link speeds Message sizes Message priorities #3 13 Network Performance Criteria: Response Time Statistics • Response time, TR is a random variable • Probability density function characterizes TR • % packets observed with delays greater than T • Variance • Mean #3 14 Network Performance Criteria • Network designers focus on the components of response time that are a function of the network • Find the one-way delay as a function of: – traffic load – packet length – topology • Focus on average response time or delay in the access network #3 15 Network Performance Criteria • Throughput in b/s, packets/sec, cells/sec • Normalized throughput R where C R = Average error free rate (b/s) passing a S reference point in the network C = Link Capacity (b/s) S = % time the network is carrying error free packets-goodput #3 16 Network Performance Criteria • Channel (or link) utilization: – The % time the channel (or link is busy) • Channel Efficiency – The % time the channel is carrying user information (impact of overhead) Let D = #user data bits / packet H = # network overhead bits / packet then Channel efficiency = S( D ) D+ H #3 17 Network Performance Criteria • Channel Capacity, Smax, is the maximum obtainable throughput over the entire range of input traffic intensities, i.e., offered load. Throughput Ideal Case 1 smax 1 Offered Load #3 18 Network Performance Criteria: Other Throughput Metrics • Maximum lossless throughput • Peak throughput • Full load throughput Transfer from local to remote host memory as fast as possible #3 19 Network Performance Criteria: Case Study From: ATM WAN performance tools, experiments, and results, L.A DaSilva, J.B Evans, D. Niehaus, V.S. Frost, R. Jonkman, Beng Ong Lee, G.Y. Lazarou; IEEE Communications Magazine, Vol. 35, No. 8; August 1997, pp. 118-125. #3 20 Network Performance Criteria: Case Study From: ATM WAN performance tools, experiments, and results, L.A DaSilva, J.B Evans, D. Niehaus, V.S. Frost, R. Jonkman, Beng Ong Lee, G.Y. Lazarou; IEEE Communications Magazine, Vol. 35, No. 8; August 1997, pp. 118-125. #3 21 Network Performance Criteria: Case Study With DS3 Access Lines From: ATM WAN performance tools, experiments, and results, L.A DaSilva, J.B Evans, D. Niehaus, V.S. Frost, R. Jonkman, Beng Ong Lee, G.Y. Lazarou; IEEE Communications Magazine, Vol. 35, No. 8; August 1997, pp. 118-125. #3 22 Network Performance Criteria • Reliability: The reliability of a network can be defined as the probability that the functioning nodes are connected to working links. Reliability = 1 - Network Failure • Here lets assume all nodes are working and analyze simple ring and tree networks #3 23 Network Performance Criteria 5 links: every node has two paths 4 links Tree Network Topology Ring Network Topology #3 24 Network Performance Criteria • Reliability for a 5 node tree network • Any of the 4 links fail the network is down • Let p = probability of link failure and failures are statistically independent • Then Prob[no link failure] = (1-p)4 • Prob[network failure] = 1 - (1-p)4 #3 25 Network Performance Criteria • But (1-p)4 = 1 - 4p + 6p2- 4p3 + p4 • Prob[network failure] = 4p - 6p2 + 4p3 - p4 • Assuming p is small then for 5 node tree network the Prob[network failure] 4p #3 26 Network Performance Criteria • Reliability for a 5 node ring network • Ring network has 5 links • Ring network can have one link failure and still be working, note one more link can fail • Let q = 1 - p=probability of link good • Prob[network good]=Prob[all good or one failed and 4 good] = q5+ 5p q4 5 Prob[link j failed and all other links good] 5pq 4 j 1 • So Prob[network failure] = 1 - q5 - 5p q4 #3 27 Network Performance Criteria • Expanding Prob[network failure] = 10p2q3 + 10p3q2 + 5p4q +p5 • The dominant term (assuming p small) is 10p2q3 p 0.01 0.001 10-5 10-7 Tree 4p 0.04 0.004 4x10-5 4x10-7 Ring 10p2q3 0.00097 10-5 10-9 10-13 #3 28 Network Performance Perspective: User-Oriented • Minimum application response time (Delay guarantee) • Maximum application throughput (Throughput (b/s) guarantee) • Low loss (Maximum packet loss guarantee) • Highly reliable (Availability guarantee) • Very flexible • Secure • Low cost #3 29 Network Performance Perspective: Network Manager/Provider • • • • • • • • Maximum throughput for all users Effective congestion control Power = Throughput/Delay Easy of management Highly reliable Fairness Ease of billing Low cost #3 30 Network Performance Perspective: Network Designer/Developer/Vendor • Simple design • Robust • Scales – Number of users – Geographical distribution – Speed • Efficient use of resources, CPU, links and memory • Evolvable #3 31 Network Performance: What Can the Network Guarantee? • Quality of Service (QoS)- Absolute/Contractual performance guarantees Examples: – Sustainable rate – Peak rate – Packet delay (average and standard deviation) – Packet/Cell loss rate • Network must reserve resources to provide QoS • ATM is designed to provide QoS #3 32 Network Performance: What Can the Network Guarantee? • Class of Service (CoS)-Relative performance guarantees Examples: – Best Effort (lowest priority) [Current Internet is Best Effort] • e-mail • ftp – Gold (medium priority) • Point of sales transaction – Platinum (highest priority) • Voice • Video • Network performs packet ‘labeling’ and priority queueing to provide CoS • Differential Services (IP-DiffServ) provides CoS in the Internet • IEEE 802.1p is a LAN packet prioritization mechanism to provide CoS #3 33 Some examples • Push-to-Talk (PTT) over Cellular (PoC) – Operates half duplex (like walkie-talkie) – Start-to-Speak Delay from pressing the PTT button until indication of permission to talk – Voice delay time time from spoken until received • Networking gaming service – Action games (shoot’em) • end-to-end delays of 75-100 ms are noticeable in first person shooter and car racing games – Real-time strategy games • end-to-end delays greater than 200 ms are ”noticeable” and “annoying” to end-users – Turn-based games #3 34 References • • • • Gâomez, G. and R. Sâanchez, End-to-end quality of service over cellular networks : data services performance and optimization in 2G/3G. 2005, John Wiley. T. Beigbeder, R. Coughlan, C. Lusher, J. Plunkett, E. Agu, and M. Claypool, “The effects of loss and latency on user performance in unreal tournament 2003,” in Proceedings of ACM SIGCOMM 2004 Workshops on NetGames ’04, pp. 144–151, 2004. J. Nichols and M. Claypool, “The effects of latency on online Madden NFL football,” in NOSSDAV ’04: Proceedings of the 14th International Workshop on Network and Operating Systems Support for Digital Audio and Video, pp. 146–151, 2004. L. Pantel and L. C. Wolf, “On the impact of delay on real-time multiplayer games,” in NOSSDAV ’02: Proceedings of the 12th International Workshop on Network and Operating Systems Support for Digital Audio and Video, pp. 23–29, 2002. #3 35