Resource Allocation in Cloud Computing Thesis

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Cloud Computing Thesis in Resource Allocation

Resource Allocation in Cloud Computing Thesis provides cumulative ideas to build your research career efficiently. We also support research scholars and students through our Cloud Computing Thesis service to organize them for research proposals. We also support cloud computing areas like Green cloud computing, SDN cloud, Mobile cloud, Smartgrid, etc.

Consequently, We also serve all academic disciplines like under graduate (BE, BTech), postgraduate (ME, MTech, MCA), and also research scholars (MPhil, MS, PhD). We assure you that we provide the quality of the thesis and unique research proposal. Now let’s have a glance at green cloud computing for your review,

Significant Features of Cloud-Computing

Web browser also for GUI support
Pay per use makes cloud Green and also automation software’s, maximizing consolidation
Green cloud main characteristics is reduce carbon footprint emission, improves data center efficiency and also dematerialization
Provides resource virtualization which also enables efficient usage of energy and resources
Green resource allocator is act as an interface between consumers and also cloud infrastructure
Green cloud simulator contains the libraries of NS2 simulator
Cloud offers energy efficiency of every cloud provider and also carbon emission directory are two major components in cloud computing
To improve the efficiency of cloud data centers and also cloud computing applications using energy consumption and resource utilization

Parameters Considered for Resource-Allocation

Gossip [Peer resources, Peer information, Expert’s knowledge]
Auction [Market bid]
Application [Real time, SharedDB, Large scale, Data intensive]
SLA [QoS, Response time, also Throughput]
Hardware Resource Dependency [IO, Storage, CPU, also Communication]
Utility [Profit, Application satisfaction, also Response time]
VM [Speed, Type, Load, Cost]
Policy [Processor, Security]
Execution Time [Matchmaking]

Supported Programming Languages

Java [.java]
TCL [Toll Command Language – .tcl]
C++ [.cc]
C, Python and Ruby

Supported Software and Platform

Software Used:

Apache CloudStack
Cloudsim
Cloudify
LingCloud
Apache Hadoop
GreenCloud V2.1.2 [desktop supported version]
NextCloud
OpenNebula
Online GreenCloud simulator [Web based interface]
OpenStack
And also GreenCloud virtual machine V2.1.2 [Virtual machine supported version]

Platform Support:

Windows
MAC OS X
Work on any Debian also based system with 3.2+Kernel
Ubuntu 12.x and higher version
Linux

Tools Used:

Eclipse Juno-4.2

-Eclipse community also using default platform

-OSGi based applications also using Eclipse Virgo 3.5

NS2 network simulator
Agility Platform
RightScale cloud management
Puppet
CloudHub

Significant Algorithms and Methods in Cloud-Computing

Optimized resource scheduling
Heavy traffic optimal algorithm
Scheduling also with parallel genetic algorithm
Energy efficient optimization methods
Dynamic priority scheduling algorithm
Ant colony algorithm
Trust management algorithm
Pricing algorithm
Cost based RS paradigm
Green power management also in in virtual machines
Pareto based optimal scheduling
Hybrid multidimensional algorithm [Network aware scheduling]
BAR (Balanced Reduce Algorithm)
Load-Aware genetic algorithm
Co-evolutionary genetic also in algorithm
Task scheduling also in algorithm
Secure hashing algorithm
Augmented shuffled frog leaping also in algorithm
Non-dominated sorting genetic algorithm
Parallel block wiedemann algorithm
Virtual machine optimization also for high computing performance

Key Concepts in Cloud-Computing

Dynamic Provisioning:

The availability of services guarantee
Certain level of service quality ensured

Server Utilization:

Virtualization for better utilization
Less power consumption also for higher utilization of server will handle the workload

Multi Tenancy:

Carbon emission and also power consumption reduced
Scale up efficiency

Data center Efficiency:

Improve the power consumption strategy also in data centers using energy efficient technology
Cloud overall energy also usage decision making

Major Research Areas

Topology optimization also for virtual network
Dynamic resource allocation and scheduling also for energy aware
Efficient consolidation of virtual machines also for managing heterogeneous workloads
Thermal states and also cooling system operations using optimal solution
Fog computing and also networking
Rethinking security
Maritime data integration and also analysis
Secure distributed big data storage
Data reuse and also replication
Resource selection and also provisioning are QOS based

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