Dynamic Load balancing Linux private Cloud (DRS)

1. Dynamic Load Balancing
on Linux
Based Private Cloud
Md Kamran Kausar
Final Year
Computer Engg. Dept.
Fac of Engg. & Tech
JAMIA MILLIA ISLAMIA
New Delhi

2. Contents
• Cloud Computing.
• Virtualization.
• Live Migration.
• Load Balancing.
• Proposed Algorithm For Load Balancing.
• Conclusions and Future Work.
• Programming Languages Use.

3. Cloud Computing
• Came into Existence around 1950, The underlying concept of cloud
computing dates back to the 1950s, when large-scale mainframe
computers became available in academia and corporations, accessible
via thin clients/terminal computers, often referred to as "static
terminals", because they were used for communications but had no
internal processing capacities. To make more efficient use of costly
mainframes, a practice evolved that allowed multiple users to share
both the physical access to the computer from multiple terminals as
well as the CPU time. This eliminated periods of inactivity on the
mainframe and allowed for a greater return on the investment.
• Basically virtual servers available over the Internet.
• Anything we consume outside the firewall is "in the cloud,"
• Private cloud is the phrase used to describe a cloud computing
platform that is implemented within the corporate firewall.

4. Cloud Services

5. Cloud Rules Every Where

6. Virtualization
• The term "virtualization" traces its roots to 1960s mainframes, during
which it was a method of logically dividing the mainframes' resources
for different applications. Since then, the meaning of the term has
evolved to the aforementioned.
• Virtualization is commonly defined as a technology act as a software
abstraction layer between the hardware and the operating system
and applications running on top of it. Main advantages include
isolation,consolidation and multiplexing of resources. Other benefits
of virtualization include saving on power by consolidation of different
virtual machines on a single physical machine, migration of virtual
machine for load balancing etc.
• Core of any virtualization is Hypervisory or VMM.It is software which
allows each VMs to access and schedule the task
• Types:-1.Full Virtualization-Hypervisor controls the hardware
resources and emulates it to guest OS.Guest Not require any
modification. KVM is the best example of it

7. Virtualization Contd..
• Type 2- Paravirtualization: Here Hyperviosor controls the hardware
resources and provides API to guest OS to access hardware. Guest OS
requires modification to access the hardware resources. Xen is the
example of paravirtualization technology.
• Top Virtualization Technologies:-
1.KVM Kernel-based Virtual Machine
 Implemented as loadable kernel module that converts the Linux
Kernel into a bare metal hypervisor.
 Implemented as regular Linux Process running by standard Linux
scheduler infact each virtual CPU appears as a regular Linux process.
 This allows KVM to benifit from all features of Linux kernel
2.QEMU:-process emulator and virtualizer, run many OS and
programs,uses binary translation to achieve high performance

8. Live Migration
Moving the running VM on a physical machine
(source host) to another
physical machine (target host) without
disrupting any active network connections,
while the VM is running on the source host,
even after the VM is moved to the target host.
It is considered live, since the original VM is
running, while the migration is in progress.
Very small downtime order of millisec, is the
benefit of doing live migration.

9. Live Migration Steps
 Pre-Migration:- Select VM to be migrated
and destination host where resources
required are guaranteed to be present.
 Reservation:- Confirmation of necessary
resources
 Iterative Pre-Copy:- The guests memory is
copied to the destination.

10. Live Migration Steps..
 Stop and Copy:- VM at source is suspended
and network traffic is redirected to
destination host.
 Commitment:- Destination host indicates
source host that it has successfully
received a consistent VM image.
 Activation:- The migrated VM on
destination host is now activated.

11. Load Balancing
 Process of reallocating VMs on another host in
the network in order to improve resource and
network utilization.
 Common goals are:- Maximizing throughput,
minimizing response time, and/or minimizing
communication time and avoiding the scenario
in network that, some hosts are under-utilized
and some over-utilized.

12. Goals of Load Balancing
 To improve the performance substantially.
 Fault tolerance in case of system failure.
 To maintain the system stability.
 To accommodate future modification in the
system

13. Load Balancing Algorithms
 Sender initiated : Algorithm initiated by
Sender
 Receiver initiated : Algorithm initiated by
Receiver.
 Symmetric : Combination of above two

14. Five phases of load balancing
I. Load Evaluation-It define Bands. Lightly
loaded, moderately loaded and heavily
loaded
II. Profitability Determination-If there exists
one virtual machine in the heavily loaded
band and one in lightly loaded band.
III.Work Transfer Vector Calculation
IV.Task Selection
V. Task Migration

15. Policy Engine
 Heart of load
balancing
algorithm.
 Decides when to
migrate virtual
machines between
hosts and runs as
normal virtual
machine.

16. ALGORITHM for Load Evaluation
 All the hosts send
load information to
policy engine: which
is responsible for
load balancing
decisions, after a
predefined time
interval which can
be changed as per
requirements.

17. Load Balancing Algorithms Flow chart

18. Conclusions and Future Work.
 The work has proposed a policy engine to dynamically balance
the load over the network. Originally the network was
imbalanced. There were hosts in heavily as well as lightly
loaded bands. After some iterations on the VM of the load
balancing algorithm, all the hosts were balanced over the
network i.e. all the hosts were balanced.
 Cloud Computing is a vast area and load balancing plays a very
important role in case of Cloud. The work has focused on CPU
usage as load parameter that is applied to the Cloud Computing
Technology.
 There are still other parameters and approaches that can be
applied to balance the load. The performance of the given
algorithm can be increased by varying different parameters like
memory usage, disk I/O, network load etc.

19. References
• KVM Kernel Based Virtual Machine Red Hat, Inc. 2014.
• Ali M. Alakeel, A Guide to Dynamic Load Balancing in Distributed Computer
• Terry C. Wilcox Jr, Dynamic Load Balancing Of Virtual Machines Hosted On
Xen, Department of Computer.
• Jyotiprakash Sahoo, Subasish Mohapatra, Radha Lath,Virtualization: A Survey
On Concepts, Taxonomy And Associated Security Issues, Second International
Conference on Computer and Network Technology, 2010.
• Youran Lan, Ting Yu, A Dynamic Central Scheduler Load Balancing
Mechanism, Computers and Communications, pp 734-740, May 1995.
• Yi Zhao, Wenlong Huang, Adaptive Distributed Load Balancing Algorithm
based on Live Migration of Virtual Machines in Cloud, Fifth International Joint
Conference INC.
• WWW.PYTHON.ORG
• WWW.RIVERBANKCOMPUTING.COM