time sharing


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time sharing

Computing
a. a system by which users at different terminals of a computer can, because of its high speed, apparently communicate with it at the same time
b. (as modifier): a time-sharing computer
Collins Discovery Encyclopedia, 1st edition © HarperCollins Publishers 2005

timesharing

A computer environment that supports multiple users simultaneously. The term originated in the 1960s when multiple terminals were first connected to a single mainframe, allowing programmers and students simultaneous access to computing resources. Today's networks of servers within the enterprise or throughout the Internet provide a similar computing model, with hundreds or thousands of users accessing the same server or cluster of servers at the same time.

The major difference today is that users have their own computers that perform a great deal of the processing, mostly to render the user interface but often to perform some or all of the business processing. The terminals in the 1960s and 1970s were primarily keyboards and screens. See cloud computing and dumb terminal.
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References in periodicals archive ?
Each backup VM serves its dedicated primary VM and can be shared by secondary VMs during its idle time using the heuristic time sharing policy.
Regret of the heuristic time sharing policy can be regarded as the lost reward value compared with the optimal policy when the states of all the backup VMs can be observed, which is defined as:
The description of the heuristic time sharing policy Algorithm: The Heuristic Time Sharing Policy Input: the state-transition matrices of backup VMs, the initial belief state [OMEGA](1) = {[[omega].sub.1](l), ..., [[omega].sub.N](1)} where [[omega].sub.f](1) = [p.sup.j.sub.01]/([p.sup.j.sub.01] + [p.sup.j.sub.11]), j [member of] {1, 2, ..., N}.
Theorem 1 The heuristic time sharing policy for backup VMs achieves optimality under the condition 1/E([D.sup.j.sub.f]) + 1/E([D.sup.j.sub.r]) < 1.
So the proposed heuristic time sharing policy for the backup VMs achieves optimality under the condition 1/E([D.sup.j.sub.f]) + 1/E([D.sup.j.sub.r]) < 1.
Theorem 2 The heuristic time sharing policy for backup VMs achieves optimality under the condition [[summation].sup.T.sub.i=1][([max.sub.j [member or] N] (E([D.sup.j.sub.f])-1/E([D.sup.j.sub.f]) - 1/E([D.sup.j.sub.r]))).sup.i] < 1.
Compared with the exponential complexity imposed by dynamic programming methods, the time complexity is significantly reduced using the heuristic time sharing policy.
In this section, the evaluation of the heuristic time sharing policy is given with numeric simulation experiment and a prototype system deployed in a small-scale cloud platform.