@article{et al._2020, title={Heterogeneous Distort-Prevention Manifold Resource Distribution Mechanism for Cloud Management}, volume={13}, url={http://sersc.org/journals/index.php/IJCA/article/view/5073}, abstractNote={<p><span class="fontstyle0">Infrastructure as a Service (IaaS) cloud innovation has pulled in a lot of consideration from clients<br>who have requests on enormous measures of registering resources. Current IaaS cloud arrangement<br>resources regarding Virtual System (VS) with homogeneous resource arrangements where various<br>sorts of resource in VS have comparative portion of the limit in a Physical System (PS). Conversely,<br>many user works claims various sums for various resources. For example, superior registering<br>occupations require more CPU centre while big-data handling applications require more memory.<br>Current homogeneous resource allotment scheme cause resource starvation where prevailing<br>resources are famished while non-predominant resources are devastated. Heterogeneous kind of<br>resource assignment approach called Distort-Prevention Manifold Resource Distribution Mechanism<br>(DPMRDM) is proposed to allot the resource as indicated by differentiated requisites on various sorts<br>of resources. VS assignment calculation is applied to guarantee heterogeneous remaining tasks at<br>hand are apportioned suitably to prevent distorted resources use in PS, and a model-based way to<br>deal with gauge the suitable number of dynamic PS to work DPMR.</span> </p&gt;}, number={1}, journal={International Journal of Control and Automation}, author={et al., Ananda R kumar Mukkala}, year={2020}, month={Feb.}, pages={45 -54} }