Factors Limiting Actual Performance, Criteria For Real Decisions
Most of the listed rates are theoretical maximum throughput measures; in practice, the actual effective throughput is almost inevitably lower in proportion to the load from other devices (network/bus contention), interframe gap, and other overhead in data link layer protocols etc. The maximum goodput (for example, the file transfer rate) may be even lower due to higher layer protocol overhead and data packet retransmissions caused by line noise or interference such as crosstalk, or lost packets in congested intermediate network nodes. All protocols lose something, and the more robust ones that deal resiliently with very many failure situations tend to lose more maximum throughput to get higher total long term rates.
Device interfaces where one bus transfers data via another will be limited to the throughput of the slowest interface, at best. For instance, SATA 6G controllers on one PCIe 5G channel will be limited to the 5G rate and have to employ more channels to get around this problem. Early implementations of new protocols very often have this kind of problem. The physical phenomena on which the device relies (such as spinning platters in a hard drive) will also impose limits; for instance, no spinning platter shipping in 2009 saturates SATA II (3 Gbit/s), so moving from this 3 Gbit/s interface to USB3 at 4.8 Gbit/s for one spinning drive will result in no increase in realized transfer rate.
Contention in a wireless or noisy spectrum, where the physical medium is entirely out of the control of those who specify the protocol, requires measures that also use up throughput. Wireless devices, BPL, and modems may produce a higher line rate or gross bit rate, due to error-correcting codes and other physical layer overhead. It is extremely common for throughput to be far less than half of theoretical maximum, though the more recent technologies (notably BPL) employ preemptive spectrum analysis to avoid this and so have much more potential to reach actual gigabit rates in practice than prior modems.
Another factor reducing throughput is deliberate policy decisions made by Internet service providers that are made for contractual, risk management, aggregation saturation, or marketing reasons. Examples are rate limiting, bandwidth throttling, and the assignment of IP addresses to groups. These practices tend to minimize the throughput available to every user, but maximize the number of users that can be supported on one backbone.
Furthermore, chips are often not available in order to implement the fastest rates. AMD, for instance, does not support the 32-bit HyperTransport interface on any CPU it has shipped as of the end of 2009. Additionally, WiMax service providers in the US typically support only up to 4 Mbit/s as of the end of 2009.
Choosing service providers or interfaces based on theoretical maxima is unwise, especially for commercial needs. A good example is large scale data centers, which should be more concerned with price per port to support the interface, wattage and heat considerations, and total cost of the solution. Because some protocols such as SCSI and Ethernet now operate many orders of magnitude faster than when originally deployed, scalability of the interface is one major factor, as it prevents costly shifts to technologies that are not backward compatible. Underscoring this is the fact that these shifts often happen involuntarily or by surprise, especially when a vendor abandons support for a proprietary system.
Read more about this topic: List Of Device Bit Rates
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