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The channel efficiency, also known as bandwidth utilization efficiency, is the percentage of the net bit rate (in bit/s) of a digital communication channel that goes to the actually achieved throughput. For example, if the throughput is 70 Mbit/s in a 100 Mbit/s Ethernet connection, the channel efficiency is 70%. In this example, effectively 70 ...
The network throughput of a connection with flow control, for example a TCP connection, with a certain window size (buffer size), can be expressed as: Network throughput ≈ Window size / roundtrip time. In case of only one physical link between the sending and transmitting nodes, this corresponds to:
Throughput is controlled by available bandwidth, as well as the available signal-to-noise ratio and hardware limitations. Throughput for the purpose of this article will be understood to be measured from the arrival of the first bit of data at the receiver, to decouple the concept of throughput from the concept of latency.
The term Social Information Processing Theory was originally titled by Salancik and Pfeffer in 1978. [4] They stated that individual perceptions, attitudes, and behaviors are shaped by information cues, such as values, work requirements, and expectations from the social environment, beyond the influence of individual dispositions and traits. [5]
People are often concerned about measuring the maximum data throughput in bits per second of a communications link or network access. A typical method of performing a measurement is to transfer a 'large' file from one system to another system and measure the time required to complete the transfer or copy of the file.
The goodput is a ratio between delivered amount of information, and the total delivery time. This delivery time includes: Inter-packet time gaps caused by packet generation processing time (a source that does not use the full network capacity), or by protocol timing (for example collision avoidance)
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Backpressure routing is an algorithm for dynamically routing traffic over a multi-hop network by using congestion gradients. The algorithm can be applied to wireless communication networks, including sensor networks, mobile ad hoc networks (), and heterogeneous networks with wireless and wireline components.