Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

Browse

Author: search.filters.author.Annappa, B.Subject: search.filters.subject.Prediction

Search Results

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Survey of dynamic resource management approaches in virtualized data centers
    (IEEE Computer Society help@computer.org, 2013) Bane, R.R.; Annappa, B.; Shet, K.C.
    Virtualization technology enabled hosting of applications and services in an isolated and resource guaranteed virtual machines (VMs). Typically single physical machine (PM) runs multiple virtual machines and application resource demands are changing with time. To achieve this, dynamic resource provisioning of physical machine resources to VMs in virtualized data center is necessary. Data center requires this provisioning should be elastic so that its cost can be minimized and service level objectives (SLO) can be met by allocating exact amount of resources. It invites two main challenges: (1) determining how many resources need to be allocated to the application where resource demand is dynamic and (2) prediction of the application resource need in advance so that resource allocation could be adjusted ahead of the actual need. In this paper we have given various ways of handling above mentioned challenges for dynamic resource management and their comparisons. © 2013 IEEE.
  • No Thumbnail Available
    Item
    On predicting the frequent execution patterns in information systems
    (Institute of Electrical and Electronics Engineers Inc., 2017) Manoj Kumar, M.V.; Thomas, L.; Annappa, B.
    Process mining research discipline offers a spectrum of techniques for analysing event logs. Event logs represent the history of process execution. This information can be used for monitoring, analysing and improving the operational processes. The currently available methods in process mining emphasise on constructing the static process model. These models depict various dimensions of the process under analysis. But, models can only represent the past execution history and can't be used to guide and control the prospectus execution of the process. There is a need for the methods and techniques which guide the future execution of process in the light of recorded information. This paper introduces a technique for identifying and predicting the frequent control-flow execution patterns in information systems. The proposed Position Weight Matrix proven to be efficient during experimentation and validation studies. © 2017 IEEE.