Resource Allocation in Cloud Computing Thesis

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 for research scholars and students through our Cloud Computing Thesis service effectively to organize them for research proposal. We also provide support in 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 that the quality of thesis and also unique research proposal that are provide by us. Now let’s have glance of 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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