Using Machine Learning Algorithms for Cloud Client Prediction Models in a Web VM Resource Provisioning Environment
Journal Title: Transactions on Machine Learning and Artificial Intelligence - Year 2016, Vol 4, Issue 1
Abstract
In order to meet Service Level Agreement (SLA) requirements, efficient scaling of Virtual Machine (VM) resources in cloud computing needs to be provisioned ahead due to the instantiation time required by the VM. One way to do this is by predicting future resource demands. The existing research on VM resource provisioning are either reactive in their approach or use only non-business level metrics. In this research, a Cloud client prediction model for TPC-W benchmark web application is developed and evaluated using three machine learning techniques: Support Vector Regression (SVR), Neural Networks (NN) and Linear Regression (LR). Business level metrics for Response Time and Throughput are included in the prediction model with the aim of providing cloud clients with a more robust scaling decision choice. Results and analysis from the experiments carried out on Amazon Elastic Compute Cloud (EC2) show that Support Vector Regression provides the best prediction model for random-like workload traffic pattern.
Authors and Affiliations
Samuel A. Ajila, Akindele A. Bankole
Keywords
Related Articles
- EP ID EP278157
- DOI 10.14738/tmlai.41.1690
- Views 81
- Downloads 0
Functional Implementation of Multiple Traversals Program with Attribute Grammars in Scala
Attribute grammars are a powerful specification paradigm for many language processing tasks, particularly the semantic analysis of programming languages. To functionally evaluate attributes grammar in Scala, the studies...
A Comparative Study Between Operating Systems (Os) for the Internet of Things (IoT)
Abstract : We describe The Internet of Things (IoT) as a network of physical objects or "things" embedded with electronics, software, sensors, and network connectivity, which enables these objects to collect and exchange...
Random Key Cuckoo Search for the Quadratic Assignment Problem
This paper proposes an adaptation of the RandomKey Cuckoo Search (RKCS) algorithm for solving the famous Quadratic Assignment Problem (QAP). We used a simplified and efficient randomkey encoding scheme to convert a conti...
Novel Compact CPW LowPass Filter Integrating Periodic Triangle DGS Cells
In this paper, we introduce a new periodic structure for CPW of a low pass filter based on the DGS technique with triangle slot cell forme. The proposed structure is a minuature low pass filter that exhibits low insertio...
Opinion Mining Using Sequence Labelling
Opinion mining aims to determine the attitude of a person by identifying and extracting subjective information. The attitude is the judgement, evaluation or emotional state of the person towards a product, or service or...