Abstract: How to effectively allocate system resource to process
the Client request by Gateway servers is a challenging problem. In
this paper, we propose an improved scheme for autonomous
performance of Gateway servers under highly dynamic traffic loads.
We devise a methodology to calculate Queue Length and Waiting
Time utilizing Gateway Server information to reduce response time
variance in presence of bursty traffic. The most widespread
contemplation is performance, because Gateway Servers must offer
cost-effective and high-availability services in the elongated period,
thus they have to be scaled to meet the expected load. Performance
measurements can be the base for performance modeling and
prediction. With the help of performance models, the performance
metrics (like buffer estimation, waiting time) can be determined at
the development process. This paper describes the possible queue
models those can be applied in the estimation of queue length to
estimate the final value of the memory size. Both simulation and
experimental studies using synthesized workloads and analysis of
real-world Gateway Servers demonstrate the effectiveness of the
proposed system.
Abstract: In the present communication, we have studied
different variations in the entropy measures in the different states of
queueing processes. In case of steady state queuing process, it has
been shown that as the arrival rate increases, the uncertainty
increases whereas in the case of non-steady birth-death process, it is
shown that the uncertainty varies differently. In this pattern, it first
increases and attains its maximum value and then with the passage of
time, it decreases and attains its minimum value.