Network throughput: Difference between revisions

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The throughput of a communication system may be affected by various factors, including the limitations of the underlying analog physical medium, available processing power of the system components, [[end-user]] behavior, etc. When taking various protocol [[Overhead (computing)|overheads]] into account, the useful rate of the data transfer can be significantly lower than the maximum achievable throughput; the useful part is usually referred to as [[goodput]].

==Maximum throughput==

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{{See also|Peak information rate}}

Users of telecommunications devices, systems designers, and researchers into communication theory are often interested in knowing the expected performance of a system. From a user perspective, this is often phrased as either "which device will get my data there most effectively for my needs?", or "which device will deliver the most data per unit cost?". Systems designers often select the most effective architecture or design constraints for a system, which drive its final performance. In most cases, the benchmark of what a system is capable of, or its "maximum performance" is what the user or designer is interested in. The term maximum throughput is frequently used when discussing end-user maximum throughput tests.  

Maximum throughput is essentially synonymous to [[digital bandwidth capacity]].

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Four different values are relevant in the context of "maximum throughput", used in comparing the 'upper limit' conceptual performance of multiple systems. They are 'maximum theoretical throughput', 'maximum achievable throughput', 'peak measured throughput', and 'maximum sustained throughput'. These values represent different quantities, and care must be taken that the same definitions are used when comparing different 'maximum throughput' values. Each bit must carry the same amount of information if throughput values are to be compared. [[Data compression]] can significantly alter throughput calculations, including generating values exceeding 100% in some cases. If the communication is mediated by several links in series with different bit rates, the maximum throughput of the overall link is lower than or equal to the lowest bit rate. The lowest value link in the series is referred to as the [[bottleneck (traffic)|bottleneck]].

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===Maximum theoretical throughput===

This number is closely related to the [[channel capacity]] of the system,<ref>Blahut, 2004, p.4</ref> and is the maximum possible quantity of data that can be transmitted under ideal circumstances. In some cases this number is reported as equal to the channel capacity, though this can be deceptive, as only non-packetized systems (asynchronous) technologies can achieve this without data compression. Maximum theoretical throughput is more accurately reported taking into account format and specification [[protocol overhead|overhead]] with best case assumptions. This number, like the closely related term 'maximum achievable throughput' below, is primarily used as a rough calculated value, such as for determining bounds on possible performance early in a system design phase.

===Asymptotic throughput===

The '''asymptotic throughput''' (less formal ''asymptotic bandwidth'') for a packet-mode [[communication network]] is the value of the [[maximum throughput]] function, when the incoming network load approaches [[infinity]], either due to a [[Message passing|message size]],<ref>''Modeling Message Passing Overhead'' by C.Y Chou et al. in Advances in Grid and Pervasive Computing: First International Conference, GPC 2006 edited by Yeh-Ching Chung and José E. Moreira {{ISBN|3540338098}} pages 299-307</ref> or the number of data sources. As other [[bit rate]]s and [[data bandwidth]]s, the asymptotic throughput is measured in [[bits per second]] (bit/s) or (rarely) [[byte]]s per second (B/s), where 1 B/s is 8 bit/s. [[Decimal prefix]]es are used, meaning that 1&nbsp;Mbit/s is 1000000 bit/s.

Asymptotic throughput is usually estimated by sending or [[network simulation|simulating]] a very large message (sequence of data packets) through the network, using a [[greedy source]] and no [[flow control (data)|flow control]] mechanism (i.e., [[User Datagram Protocol|UDP]] rather than [[Transmission Control Protocol|TCP]]), and measuring the network path throughput in the destination node. Traffic load between other sources may reduce this maximum network path throughput. Alternatively, a large number of sources and sinks may be modeled, with or without flow control, and the aggregate maximum network throughput measured (the sum of traffic reaching its destinations). In a network simulation model with infinite packet queues, the asymptotic throughput occurs when the [[Network latency|latency]] (the packet queuing time) goes to infinity, while if the packet queues are limited, or the network is a multi-drop network with many sources, and collisions may occur, the packet-dropping rate approaches 100%.

A well-known application of asymptotic throughput is in modeling [[point-to-point communication]] where (following Hockney) [[Network latency|message latency]] T(N) is modeled as a function of message length N as T(N) = (M + N)/A where A is the asymptotic bandwidth and M is the half-peak length.<ref>''Recent Advances in Parallel Virtual Machine and Message Passing Interface'' by Jack Dongarra, Emilio Luque and Tomas Margalef 1999 {{ISBN|3540665498}} page 134</ref>

As well as its use in general network modeling, asymptotic throughput is used in modeling performance on [[massively parallel]] computer systems, where system operation is highly dependent on communication overhead, as well as processor performance.<ref>M. Resch et al. ''A comparison of MPI performance on different MPPs''in Recent Advances in Parallel Virtual Machine and Message Passing Interface, Lecture Notes in Computer Science, 1997, Volume 1332/1997, 25-32</ref> In these applications, asymptotic throughput is used in Xu and Hwang model (more general than Hockney's approach) which includes the number of processors, so that both the latency and the asymptotic throughput are functions of the number of processors.<ref>''High-Performance Computing and Networking'' edited by Angelo Mañas, Bernardo Tafalla and Rou Rey Jay Pallones 1998 {{ISBN|3540644431}} page 935</ref>

===Peak measured throughput===

The above values are theoretical or calculated. Peak measured throughput is throughput measured by a real, implemented system, or a simulated system. The value is the throughput measured over a short period of time; mathematically, this is the limit taken with respect to throughput as time approaches zero. This term is synonymous with ''instantaneous throughput''. This number is useful for systems that rely on burst data transmission; however, for systems with a high [[duty cycle]], this is less likely to be a useful measure of system performance.

===Maximum sustained throughput===

This value is the throughput averaged or integrated over a long time (sometimes considered infinity). For high duty cycle networks, this is likely to be the most accurate indicator of system performance. The maximum throughput is defined as the [[asymptotic throughput]] when the load (the amount of incoming data) is large. In [[packet switched]] systems where the load and the throughput always are equal (where [[packet loss]] does not occur), the maximum throughput may be defined as the minimum load in bit/s that causes the delivery time (the [[Network latency|latency]]) to become unstable and increase towards infinity. This value can also be used deceptively in relation to peak measured throughput to conceal [[packet shaping]].

==Channel utilization and efficiency==