Load balancing in cloud computing.pdf

Load Balancing Algorithm
An Eﬀicient Dynamic Load Balancing Algorithm for Virtual Machine in
Cloud Computing
Himanshu Moliya
Department of research and development
Planetoid Inc.
October, 2022
Himanshu Moliya (Planetoid) Load Balancing Algorithm October, 2022

Summary
1 Overview
2 Literature Survey
3 Proposed Work
4 Results
5 Conclusion
6 References

Overview
Overview

Overview
Overview (Abstract)
Load balancing process is useful to adjust the load on a virtual machine
using distributing the load on another underloaded node.
Objective: Main objective of load balancing is to make the virtual machine
balanced which should be not underloaded or overloaded.
In the given paper, Author has proposed a load balancing algorithm by
combining two algorithms...
Algorithms:
Honey bee behavior inspired algorithm for priority based tasks,
Enhanced weighted round-robin algorithm used for non-priority

Literature Survey
Literature Survey

Literature Survey
LITERATURE SURVEY
Honeybee bee algorithm for load balancing :
Select task with priority and assign it to the virtual machine which
have minimum number of similar prioritized task
The honey bee algorithm works on executing the task with higher
priority first so during that time other tasks with less priority need to
wait in a queue.
Drawback:
If the system gets crashed then the task in a queue will be lost.

Proposed Work
Proposed Work

Proposed Work
PROPOSED WORK
Author introduce new hybrid effective load balancing method. They used
two modules...
first is a scheduler (Proposed modified round robin algorithm)
second load balancer (Proposed modified honey bee behavior inspired
algorithm)

Proposed Work
PROPOSED WORK (Flow Diagram)
Figure: 1 Flow Diagram of Proposed work

Proposed Work
Algorithm 1: Scheduling algorithm
Step 1: Create a Virtual Machine
Step 2: Create a Data Centre
Step 3: Enter the number of Task
Step 4: Calculating the current state of the load in virtual machine
Step 5: Arrange a load of the virtual machine in the lowest loaded
machine to highest loaded machine
Step 6: Assigning the incoming task to the low loaded virtual machine
based on the Modified Round robin algorithm (refer algorithm-2)
Step 7: Remove all assigned task from the list

Proposed Work
Algorithm 2: Modified Round Robin Algorithm
Step 1: Calculating the mean value of burst time
Step 2: Set dynamically time quantum TQ by using the mean value
of burst time
Step 3: Allocate the task to a least loaded virtual machine
Step 4: Continue until waiting list is vacant

Proposed Work
Algorithm 3: Load Balancing Algorithm
Step 1: Find the capacity of the virtual machine
Step 2: Calculating the load of all virtual machine
Step 3: Identifying the virtual machine is balanced or not
Step 4: Find the virtual machine is Overloaded or Underloaded virtual
machine
Step 5: Remove the task from a heavily loaded virtual machine and
check whether the task is priority based or not IF Priority exist Then
Used Modified honeybee behavior inspired algorithm (refer
Algorithm-4) Else Priority does not exist then Used Enhanced
Weighted round robin algorithm (refer Algorithm-5)
Step 6: Update the load on a virtual machine

Proposed Work
Algorithm 4: Modified Honey Bee behavior inspired algo.
Step 1: Group the VMs based on load (OVM, UVM and BVM)
Step 2: Sort the OVMs in descending order and UVMs in ascending
order
Step 3: Sort the task in VMs by priority (i.e. maximum execution
time)
Step 4: Allocating Virtual Machine
Th → VMd | min (number of Th) Expected minimum completion
time
Tm → VMd | min (number of Tm + number of Th) and Expected
minimum completion time
Tl → VMd | min (number of T) and Expected minimum completion
time
Th, Tm, Tl= All Task with High, Medium and Low priority
Step 5: Modify the number of the task as per newly added task to
VMd
Modify the number of priority based tasks assigned VMd

Proposed Work
Algorithm 5: Enhanced Weighted Round Robin Algorithm
Step 1: Calculate the pending execution time for all virtual machines
and arrange virtual machines in ascending order of execution time.
Step 2: Assign the tasks from higher execution time virtual machines
to lower execution time virtual machine
Step 3: Add the task to the assigned list
Step 4: Step 1, step 2 and step 3 will be repeated after each task
completion on any virtual machine.

Results
Results

Results
SIMULATION RESULTS
A CloudSim is a software that allows to simulate the physical and logical
structure of the cloud data centers and number of the virtual machine
Author used CloudSim for various experiments to find processing time of
CPU and completion time of the task.
During implantation, time consider the five virtual machine and twelve
user request for analyzing the Quality of service (QoS) parameter.

Results
SIMULATION RESULTS
Figure: 2 Performance analysis of Shortest Job First Algorithm
Source: https://ieeexplore.ieee.org/mediastore_new/IEEE/content/media/9046169/

Results
SIMULATION RESULTS
Figure: 3 Analysis of the performance of Weighted RR
9065289/9065292/patel9-p6-patel-large.gif

Results
SIMULATION RESULTS
Figure: 4 A Performance analysis of Honey Bee Behavior Algorithm

Results
SIMULATION RESULTS
Figure: 5 Performance analysis of Proposed Algorithm

Results
SIMULATION RESULTS
Figure: 6 Comparison of overall performance of system

Conclusion
Conclusion

Conclusion
Conclusion
As per figure. 6 minimum completion time and better CPU
processing time is achieved.
This proposed work is developed for achieving better resource
utilization, minimum completion time and improve the system of
performance in a cloud computing environment.
In the future, this research work can be enhanced by considering other
QoS parameter like migration cost, waiting time, etc.

References
References

References
References
[1] Patel, Karan D., and Tosal M. Bhalodia. ”An eﬀicient dynamic load
balancing algorithm for virtual machine in cloud computing.” 2019
International conference on intelligent computing and control systems
(ICCS). IEEE, 2019.

Thank you!

Load balancing in cloud computing.pdf

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