In communication networks, such as Ethernet or packet radio, throughput is the average rate of successful message delivery over a communication channel. This data may be delivered over a physical or logical link, over a wireless channel, or that is passing through a certain network node, such as data passed between two specific computers. The throughput is usually measured in bits per second (bit/s or bps), and sometimes in data packets per second or data packets per time slot.
The system throughput or aggregate throughput is the sum of the data rates that are delivered to all terminals in a network.
The throughput can be analyzed mathematically by means of queueing theory, where the load in packets per time unit is denoted arrival rate λ, and the throughput in packets per time unit is denoted departure rate μ.
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 are often interested in selecting 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. When examining throughput, the term 'Maximum Throughput' is tossed about. Measuring end-user throughput is discussed in more detail here.
Four different values have meaning 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', and 'peak measured throughput' and 'maximum sustained throughput'. These represent different quantities and care must be taken that the same definitions are used when comparing different 'maximum throughput' values. Comparing throughput values is also dependent on each bit carrying the same amount of information. Data compression can significantly skew throughput calculations, including generating values greater than 100%. 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.
This number is closely related to the channel capacity of the system, 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 to take into account format and specification 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.
While maximum theoretical throughput assumes only data packets on a channel, maximum achievable throughput takes into account handshake and control packets, which reduce the amount of channel space available for data packets, as well as considerations such as reduced data packet length. Additionally, this value takes into account hardware limitations of the systems on both ends of the channel, within the channel itself, and normally includes the additional overhead related to the specific control requirements of the system, and sometimes assumptions about the behavior of a system as a whole, such as . Maximum achievable throughput is typically an optimistic assumption of network performance, but provides more useful insight into expected system performance than maximum theoretical throughput and is often an active area of research. Most simulations of systems based on certain assumptions can be described using this number.
The above values are theoretical or calculated values. 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.
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 very 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 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.
The channel utilization, also known as bandwidth utilization efficiency, in percentage is the achieved throughput related to the net bitrate in bit/s of a digital communication channel). For example, if the throughput is 70 Mbit/s in a 100 Mbit/s Ethernet connection, the channel utilization is 70%.
In a point-to-point or point-to-multipoint communication link, where only one terminal is transmitting, the maximum throughput is often equivalent to or very near the physical data rate (the channel capacity), since the channel utilization can be almost 100% in such a network, except for a small inter-frame gap.
For example, in Ethernet the maximum frame size 1526 bytes (maximum 1500 byte payload + 8 byte preamble + 14 byte header + 4 Byte trailer). An additional minimum interframe gap corresponding to 12 byte is inserted after each frame. This corresponds to a maximum channel utilization of 1526/(1526+12)•100% = 99.22%, or a maximum throughput of 99.22 Mbit/s inclusive of Ethernet datalink layer protocol overhead in a 100 Mbit/s Ethernet connection. The maxmimum throughput is 1500/(1526+12) = 97.5 Mbit/s exclusive of Ethernet protocol overhead
The throughput of a communication system will be limited by a huge number of factors. Some of these are described below:
The maximum achievable throughput (the channel capacity) is affected by the bandwidth in hertz and signal-to-noise ratio of the analog physical medium.
Despite the conceptual simplicity of digital information, all electrical signals traveling over wires are analog. The analog limitations of wires or wireless systems inevitably provide an upper bound on the amount of information that can be sent. The dominant equation here is the Shannon-Hartley theorem, and analog limitations of this type can be understood as factors that affect either the analog bandwidth of a signal or as factors that affect the signal to noise ratio. It should be noted that the bandwidth of wired systems can be in fact surprisingly narrow, with the bandwidth of Ethernet wire limited to approximately 1 GHz, and PCB traces limited by a similar amount.
Digital systems refer to the 'knee frequency' , the amount of time the digital voltage to rise from 10% of a nominal digital '0' to a nominal digital '1' or vice-verse. The knee frequency is related to the required bandwidth of a channel, and can be related to the 3 db bandwidth of a system by the equation : Where Tr is the 10% to 90% rise time, and K is a constant of proportionality related to the pulse shape, equal to 0.35 for exponential rise, and 0.338 for Gaussian rise.
Computational systems have finite processing power, and can drive finite current. Limited current drive capability can limit the effective signal to noise ratio for high capacitance links.
Large data loads that require processing impose data processing requirements on hardware (such as routers). For example, a gateway router supporting a populated class B subnet, handling 10 x 100 Mbit/s Ethernet channels, must examine 16 bits of address to determine the destination port for each packet. This translates into 81913 packets per second (assuming maximum data payload per packet) with a table of 2^16 addresses this requires the router to be able to perform 5.368 billion lookup operations per second. In a worse case scenario, where the payloads of each Ethernet packet are reduced to 100 bytes, this number of operations per second jumps to 520 billion. This router would require a multi-teraflop processing core to be able to handle such a load.
The achieved throughput may be lower than the maximum achievable throughput for several reasons. Many data communication protocols call for specific controls in an attempt to ensure a
Ensuring that multiple users can harmoniously share a single communications link requires some kind of equitable sharing of the link. If a bottle neck communication link offering data rate R is shared by "N" active users (with at least one data packet in queue), every user typically achieves a throughput of approximately R/N, if fair queuing best-effort communication is assumed.
The throughput is not a well-defined metric when it comes to how to deal with protocol overhead. It is typically measured at a reference point below the network layer and above the physical layer.
The most simple definition is the number of bits per second that are physically delivered. A typical example where this definition is practised is an Ethernet network. In this case the maximum throughput is the gross bitrate or raw bitrate.
However, in schemes that include forward error correction codes (channel coding), the redundant error code is normally excluded from the throughput. An example in modem communication, where the throughput typically is measured in the interface between the Point-to-Point Protocol (PPP) and the circuit switched modem connection. In this case the maximum throughput is often called net bitrate or useful bitrate.
To determine the actual speed of a network or connection, the goodput measurement definition may be used. For example in file transmission, the goodput corresponds to the file size (in bits) divided by the file transmission time.
The goodput is the amount of useful information that is delivered per second to the application layer protocol. Dropped packets or packet retransmissions as well as protocol overhead are excluded. Because of that, the goodput is lower than the throughput. Technical factors that affect the difference are presented in the goodput article.
Normally, throughput and latency are opposed goals. To improve latency, you typically want to increase how much the computer checks to see if you are trying to interact. This checking overhead slows you down. However, there is one very common exception to this rule. Network protocols and programs tend to synchronize both ends regularly. If these synchronizations are slow, then throughput can suffer tremendously.
The perceived speed is mostly based on the speed of requests made or responsiveness. As such, responsiveness has far less to do with throughput than latency. To illustrate this, consider a truck full of magnetic tape en route from Moscow to Paris. The time or latency it takes to deliver the data may be several days, but the amount or throughput of data delivered will exceed the throughput of a broadband connection. In contrast, the broadband connection, which has a throughput many times less than that of the truck, has a relatively low latency and can deliver smaller amounts of data much faster. For a user, surfing the Internet for instance, the latter which has a lower latency is perceived as "faster".
Latency is measured from the time a request (e.g., a single packet) leaves the client to the time the response (e.g. an acknowledgment) arrives back at the client from the serving entity. The dimension of latency is time. Throughput on the other hand is the amount of data that is transferred over a period of time. For example, if over ten seconds twenty packets are transferred then the throughput would be packets per second. Throughput can have many units (for example: "bits/second," "bytes/second," or "packets/second"), but it is always expressed as the ratio of volume to time.
Often, a block in a data flow diagram has a single input and a single output, and operate on discrete packets of information. Examples of such blocks are FFT modules or hardware multipliers. Because the units of throughput are the reciprocal of the unit for propagation delay, which is 'seconds per message' or 'seconds per output', throughput can be used to relate a computational device performing a dedicated function such as an ASIC or embedded processor to a communications channel, simplifying system analysis.
In wireless networks or cellular systems, the system spectral efficiency in bit/s/Hz/area unit, bit/s/Hz/site or bit/s/Hz/cell, is the maximum system throughput (aggregate throughput) divided by the analog bandwidth and some measure of the system coverage area.
Throughput over analog channels is defined entirely by the modulation scheme, the signal to noise ratio, and the available bandwidth. Since throughput is normally defined in terms of quantified digital data, the term 'throughput' is not normally used; the term 'bandwidth' is more often used instead.