![](bg5.png)
2. When receives the request of task assignment
from Task Tracker, Job Tracker takes one of the
tasks of the current job to the Task Tracker which
sent a request just now to get it execute. At the same
time, the value of ‘thisRoundTask’ should be minus
1. After that, if the result is less than 1, then pointer
will be moved to the next job, or the pointer will
keep unmoved and waiting until the next request
from Task Tracker arrives.
3. When the pointer is at the end of the queue, all
information of the whole queue will be updated. If
there is some job finished or just arriving at the
moment, all the values of ‘thisRoundTask’ of each
job will be reset and recalculated and the pointer will
be moved to the beginning of the queue again.
Using PBWRR to run the Cloud Computing
system based on Hadoop again, with the compare
with those older algorithms, it is proved that
PBWRR is more suitable for Cloud Computing,
since in Cloud Computing environment, it is the
users’ fee rather than the sequence of them sending a
request that the system provide users with different
levels of service through. PBWRR extends from the
characteristics of transparent of Hadoop to
developers and customers, and has a high capacity of
clearly distinguishing the level of customer service,
while ensuring a degree of fairness to ensure that the
situation that most of the resource is kept by a
minority of high-priority customers can not happen.
Hence, it is a good complement and improvement of
the existing scheduling algorithms of Hadoop.
5 CONCLUSIONS
This paper studies the key technologies of cloud
Computing and the principle of Hadoop with the
method to implement Cloud Computing based on it.
The main problem is how to optimize and improve
the scheduling algorithm of this architecture. Of
course, after all of these, we are more familiar with
Cloud Computing and have the ability to skillfully
build up such a computing platform in practice. The
file configuration and algorithm optimization are
originally achieved and brought up by hard working
during writing this paper. However, in spite of
finding out an improved version of algorithm
‘PBWRR’, there may be lots of risks and
deficiencies since it has not been though extensive,
rigorous testing. In the future, how to build up
private cloud for commercial systems should be on
focus (Pearson, 2009), with improved ‘PBWRR’ and
to make customers more and more safe with their
private information. It is believed that with the rapid
development of Cloud Computing, there will be
more and more efficient and practical algorithms for
scheduling, computing and so on. In addition, there
will even be more and more architectures sufficient
and safe enough for Cloud Computing. I am looking
forward to it.
ACKNOWLEDGEMENTS
This work is supported by the National Key
project of Scientific and Technical Supporting
Programs of China (Grant Nos.2008BAH24B04,
2008BAH21B03; the National Natural Science
Foundation of China (Grant No.61072060) ; the
program of the Co-Construction with Beijing
Municipal Commission of Education of China.
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