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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 ...
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.
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 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:
In psychology, it refers to the process of defining the general idea behind a project—purpose, research question, and hypotheses. This step can be done in collaboration between several researchers to scan a broader spectrum of ideas and select those of broadest interest and impact. [ 4 ]
In social network analysis and related network science fields, the contagion metaphor has been described as potentially misleading in various ways. For example, an actual virus can affect someone after a single exposure, whereas typically with social contagion, people need several exposures before adopting the new behavior or emotion. [28]
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Network science is an academic field which studies complex networks such as telecommunication networks, computer networks, biological networks, cognitive and semantic networks, and social networks, considering distinct elements or actors represented by nodes (or vertices) and the connections between the elements or actors as links (or edges).