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Abstract

Cloud computing provides all types of resources as services. Hardware and software resources are shared with reference to the user demands. Service components are deployed to support the enterprise applications. Virtual Machines (VM) are provided for the service components based on the capacity levels. Service component consolidation or VM consolidation refers the process of mapping the Virtual Machines to the service components. The service components associated with the same application is denoted as Dependant Service Component. Intelligent service management models identify the service dependencies to achieve the low network latency. The service consolidation with low communication time reduces the communication cost for the network applications. Service components for enterprise applications are deployed in many hosts and network devices. Service components consolidation is carried out with the consideration of resource constraints, service dependency and network structure. CloudScout is a non-intrusive approach applied for automatically discovers dependent service components. The correlation among service components is analyzed with the time-series information from system monitoring logs. The log mining approach is used for the service dependency discovery with generality and privacy protection features. The iEntropy method is applied to dynamically determine the weight of each resource metric in the service distance calculation. The hierarchical and iterative k-means (HiKM) algorithm is adapted for the dependent service clustering process.The Queue network and network latency optimization are used in the VM consolidation process.
The CloudScout scheme is enhanced to support optimal service dependency discovery and service consolidation process. The service dependency discovery process is improved with sequential dependencies and complimentary dependencies. The Multi Objective Service Consolidation (MOSC) scheme is build to allocate the Virtual Machines for the service components. The service consolidation process is upgraded with resource level constraints.

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How to Cite
R. Vijayendren, J. Thanuja, P. Sathishkumar, S. Santhosh Kumar, & S. Vadivel. (2018). An Integrated Resource and Service Consolidation Approach using History Logs under Cloud Environment . International Journal of Intellectual Advancements and Research in Engineering Computations, 6(2), 1826–1830. Retrieved from https://ijiarec.com/ijiarec/article/view/742