Workflow scheduling in cloud computing

Title: - PPR-RM: Performance-to-Power Ratio, Reliability and Makespan — aware scientific workflow scheduling based on a coalitional game in the cloud
--------------------------------------------------------------------------------------------------------------------------------------------------------

Implementation Plan:
-------------------------------------

Step 1: Initially we create a cloud-sim environment with n number of users, n number of data centers, n number of virtual machines, n number of brokers and n number of cloud service providers.

Step 2: Next, we Perform the Users submit data requests to the cloud service providers. In this process the incoming data requests are Clustered using the Reliability-aware Scheduling Selection (RSS) algorithm is employed to schedule the data requests.

Step 3: Next, we perform the Task management process, In this process the Priority values are computed for each of the data requests and utilized in task clustering, followed by task scheduling. It performs task prioritization and estimates the earliest execution time through a cloud scheduler.

Step 4: Then next Cloud manager: It serves the following components.

(4.1) Service analyzer: It reviews the SLA constraint based on the user’s preferences. If the SLA negotiation i s successful, the scheduler will direct the requests to cloud processing nodes.

(4.2) Request evaluator: It accepts or rejects the assigned tasks based on their makespans. More precisely, it determines whether the task is executed on local resources or forwarded to foreign resources for better resource utilization.

(4.3) Resource monitor: It continuously monitors the actual usage of cloud resources and decides whether the nodes operate at their best PPR.

(4.4) VM manager updates VM status to provision new VMs and reuses existing VMs.

Step 5: Next we implement the VM ALLOCATION step, In this step the data requests with the highest priority is transferred to the VM allocation method. The Heuristic algorithm considers the capacity and client connectivity of servers, is employed to trades-off makespan and reliability constraints that reduce energy consumption when processing nodes are allocated for data requests.

Step 6: Finally, The Proposed Work evaluate the performance metrics,

(i) Number Of data requests vs. Response time
(ii) Number Of VM's vs. Response time
(iii) Number of data requests vs. Average makespan time.
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Software Requirement:
----------------------

1. Tool: Net-beans 12.3\Cloud-sim
2. Language: JAVA
3. OS: Windows 10 – (64-bit)
--------------------------------------------------------------------------------------------------------------------------------------------------------------
This video aims to provide guidance towards the resolution of your inquiry
regarding the provision of assistance in selecting a topic for cloud computing
studies.

We have an experienced research team for your cloud computing research
study.

For Research Support contact us:

Our website: https://cloudcomputingprojects.net/

Mail us at: [email protected]

Call us at : +91 94448 69228

Тэги:

#Performance-to-Power_Ratio #Reliability_and_Makespan_—_aware_scientific_workflow_scheduling #scheduling_based_on_a_coalitional_game_in_the_cloud #Workflow_scheduling_in_cloud_computing

Скачать видео