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Personal Details

Name : Shalmali Sahasrabudhe
Email : shalmali.sahasrabudhe@gmail.com
Name of the College : Maharashtra Institute of Technology, Pune, India
Name of the University : Pune University
Education : Pursuing Master of Engineering in Computer
IRC nickname[freenode] : shalmaliss
Other contact methods (mobile no) : (+91) 9765492170


Academic Background Graduation : B.E Computer Science and Engineering Graduation Year : 2011 College : KIT's College of Engineering, Kolhapur. University : Shivaji University, Kolhapur. Percentage : 66.67 %

Post Graduation : M.E Computer Engineering (Pursuing) Post Graduation Completion Year : 2014 College : MIT, Pune University : Pune University C.G.P.A First year : 6.95 Academic Project Description

Work Expierience Organization : Afour Technologies Pvt. Ltd. Duration : 10 months (27th Sept 2011 To 31st July 2012) Work : Automation Testing Programming Language : J2EE, C# .net

Internship Organization : Avaya India Pvt. Ltd. Duration : 1 year (15th July 2013 to 11th July 2014) Project : IT-LaaS Project Description : Using OpenStack deploying a multi-hypervisor cloud. This cloud will be used for hosting various Avaya products and for internal use also. Also administering infrastructure using this cloud so that avaialable resources will be utilized optimally.

Academic Project (M.E.) I have selected Project titled " Optimized Resource Scheduling Algorithm in OpenStack " as my academic project. This project is about optimizing the current resource scheduling algorithm i.e. filter-scheduler algorithm to improve its performance. Following is my suggested Plan for this :

Off-line Scheduling: In this instead of going through filtering and weighing steps in filter-weight scheduler each time when request is there, a pool of hosts selected after these steps is maintained. The request is scheduled using the host from this pool. And this pool is updated based on events i.e. whenever any vm is created, deleted or updated. This will save the time required by filtering and weighting steps.

Conflict Resolution Policy: After filtering and weighing steps if there are multiple hosts with the same weight then hosts are selected in FCFS way. So resolving the conflict of same weight we can use following things: check for network bandwidth utilization or vCPU utilization or user preference for the hypervisor.

Interested GSoC Project  : Common Scheduler (Gantt)


Project : Business Rules and Policies driven Constraints-based Smart Resource Placement in Openstack