Load Balancing Projects for Master Thesis Students

Load Balancing Projects for Master Thesis students is an awesome service those students to change your life for better. Projects also for Master Thesis students are a product of our seven years of hard work in the field of cloud computing. It can also be defined as the technology that distributes both communications and processing equally between various servers. This process takes place as a substitute for loading one server also for various tasks in the data center. In order to minimize the use of server power, it is also built-in datacentres.

This specific topic is currently the Centre of attraction as it is a new and also promising domain for research. We also welcome you immensely to ripe the product of our seven years of labour.

Our Projects are Widely Preferred Because of

It has unique and also novel ideas
Mining of intelligence by our expert team
Nearly 600 + top journal members
Thesis format is customized support to your needs
Top professionals are also part of our team
Confidentiality of research
Extra support such as research proposal, and also in thesis statement preparation and literature work

Our approach towards Load Balancing Projects for Master Thesis Students is unique and also completely different from any other previously undertook approaches. You can also trust us with your life as we aim to attain the perfection and precision you ask for. We strongly recommend Master Thesis Students due to its relevance and also growth in the modern world of technology.

Cloud Load Balancing:

It is a method to share computing resources and also workloads to gain maximum resource usage in cloud

Network Load Balancing:

Network load balancing refers to the distribution of network traffic among multiple users participating in the network. To balance the load, network mainly focuses also based on routing and clustering.

Important Features:

HTTP, POP3, HTTS, MYSQL, also POP3S, TCP, LDAP, SMTP,IMAP, UDP and also LDAPS are the major protocols used
Energy consumption and also Co2 emission are minimized by cloud green computing
SQL is used also for database connectivity and enhancement of security with public key cryptography
Full featured API is supported
Also supports GUI and also full featured API

Additional Characteristics:

Load Balancing algorithms are also used for energy management
Connection control and also advanced access control
Automatic service provision
Stored data management
Health checkup
Support also for virtual machine migration

Prime Aspects of Cloud Load Balancing

Programming Languages used:

Java
Python(.py)
XML (.xml – Extensible markup languages)
Jquery or Javascript(.js)
Clojure (.clj, cljs, .cljc, .edn)
SQL (.sql)
R programming (.R – R Math Language)
.Net (.aspx, .cshtml, .vbhtml)
Hastell (.hs, .Ihs)
Json (.json)

Techniques used:

Load Balancing Policies (Client and also workload aware policy)
Load Balancing Techniques
Scheduling Algorithms

Algorithms used:

Ant Colony optimization algorithm
Opportunistic load balancing also based on algorithm
Biased Random sampling algorithm
Active clustering load balancing also based on algorithm
Two phase scheduling load balancing also based on algorithm
Max min and Min min algorithm
Token ring algorithm
First come first serve also based onalgorithm
Observed algorithm
Randomized algorithm
Honey bee random sampling load balancing also based on algorithm
Dynamic round robin scheduling algorithm
Dynamically reconfigurable routing
Least connections and weighted least also based on mechanism
Throttled load balancing algorithm
Equally spread current execution also based on load
Genetic algorithm
Greedy also based on algorithm

Load Balancing with,

Fair load balancing
Multi-path load balancing
Cross-layer design also based for load balancing
Energy efficient also based on load balancing
Distributed load balancing
Adaptive approach for load balancing
Spatial load also based on balancing
Congestion aware load balancing

Load Balancing in networks,

Mesh-router also based load balancing
Gateway-based load balancing
Path-based Load Balancing

Software’s Used

Visual Studio IDE:

Supported platforms are Windows 7 and 8, Windows 8.1, Windows 10. Windows server 2008 R2 SP-1, Windows server 2012, also based on Windows server 2012 R2 and Additional service part 1

R Studio:

Supported platforms are also MAC, Windows, Linux, Ubuntu, Debian and Rehat
Available as open source and also commercial version
Cloud IDE and Eclipse che-Open source Linux
Supported platforms – MAC OS , Windows, Linux
Eclipse che-4.4.1 is the latest version plugins and tools used
Microsoft Azure
Development IDE
Google Cloud platform products and services
Exploits client libraries
Amazon web services
Toolkit
Rackspace Cloud Load Balancer API 1.0

Simulation Tools Used:

Cloud Analyst
Cloud Sim

Metrics Used:

Fault Tolerant
Scalability
Resource Utilization
Throughput
Performance
Associated Overhead
Response time
Migration time

Interface Sketch:

Google Cloud Load Balancing
Rackspace cloud load Balancers
Oracle cloud
AWS Elastic load balancing

Major Research Areas

Virtual machine migration
Load balancing policy for handling peak hour performance of datacenters
Power aware load balancing in cloud computing
Centralized and distributed load balancing
Optimal Osf scheduling algorithm
Task Dependencies in load balancing
Hierarchical load balancing

Applications

High traffic websites such as NetFlix, Zynga and Dropbox uses it
Cloud computing technologies such as Microsoft azure, Rackspace, amazon, and Google uses it
Manages content delivery networks traffic

Importance of Cloud Load Balancing

Cost effective
Advantage of cloud scalability and also agility is exploited
Scalability and consistency is globally enhanced
Green cloud computing’s provision also is provided
Boost Reliability

Take a lesser known path called Load Balancing

Achieve yours success in a road not taken

Thoroughly study the basic information provided by us. Then approach us to write your success story. We will be the beacon for you and guide you towards your destined greatness.