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Bajpai, Abhishek
- An Optimal Resource Provisioning Algorithm for Cloud Computing Environment
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Authors
Affiliations
1 Department of Computer Application, Shri Ramswaroop Memorial University, Deva Road, Lucknow, IN
1 Department of Computer Application, Shri Ramswaroop Memorial University, Deva Road, Lucknow, IN
Source
Oriental Journal of Computer Science and Technology, Vol 10, No 2 (2017), Pagination: 371-384Abstract
Resource Provisioning in a Cloud Computing Environment ensures flexible and dynamic access of the cloud resources to the end users. The Multi-Objective Decision Making approach considers assigning priorities to the decision alternatives in the environment. Each alternative represents a cloud resource defined in terms of various characteristics termed as decision criteria. The provisioning objectives refer to the heterogeneous requirements of the cloud users. This research study proposes a Resource Interest Score Evaluation Optimal Resource Provisioning (RISE-ORP) algorithm which uses Analytical Hierarchy Process (AHP) and Ant Colony Optimization (ACO) as a unified MOMD approach to design an optimal resource provisioning system. It uses AHP as a method to rank the cloud resources for provisioning. The ACO is used to examine the cloud resources for which resource traits best satisfy the provisioning. The performance of this approach is analyzed using CloudSim. The experimental results show that our approach offers improvement in the performance of previously used AHP approach for resource provisioning.
Keywords
Cloud Computing, Resource Provisioning, Analytical Hierarchy Process, Ant Colony Optimization.Full Text
References
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- Identifying Various Roadways Obstacles in Infrastructure less Environment Using Depth Learning Approach
Abstract Views :229 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Application,Shri Ramswaroop Memorial University, Deva Road, Barabanki, Uttar Pradesh, IN
2 Department of Computer Application,Shri Ramswaroop Memorial Group of Professional Colleges, Lucknow, Uttar Pradesh, IN
1 Department of Computer Application,Shri Ramswaroop Memorial University, Deva Road, Barabanki, Uttar Pradesh, IN
2 Department of Computer Application,Shri Ramswaroop Memorial Group of Professional Colleges, Lucknow, Uttar Pradesh, IN
Source
Oriental Journal of Computer Science and Technology, Vol 10, No 3 (2017), Pagination: 585-592Abstract
Traffic conditions in infrastructure-less environment are in many ways not ideal for driving. This is due to undefined road curvature, faded and unmaintained lane markings and various obstacles situations cause vital life loses and damage of vehicles in accidents. This paper provides an efficient approach of finding various roadways obstacles situation using our depth learning approach based on the data collected through a Smartphone. The existing methods are suitable for planned or structured roads. The proposed approach is suitable for planed as well as unplanned roads i.e. for infrastructure-less environment. The approach is capable of effectively classifying roadways obstacles into predefined categories using depth learning approach. While compared with other similar approach this approach is a cost effective approach.Keywords
Smartphone, Accelerometer, Global Positioning System, Actionable Obstacles, Non-Actionable Obstacles, Advanced Driver Assistance System.Full Text
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