Main Reference PaperA hierarchical control framework of load balancing and resource allocation of cloud computing services, Computer and Electrical Engineering, 2018 [Java/CloudSim].
  • It proposes a two-layer control architecture that addresses cooperatively the problems of load balancing, application placement, capacity allocation and admission control with respect to satisfaction of QoS metrics and optimal recource allocation. In detail, the local (lower) level includes distributed individual controllers based on fuzzy Takagi–Sugeno modeling for each application. A set of feasible operation points is determined based on the derived models by solving a dynamic programming problem. Inputs of local controllers are the allocated capacity (CPU share) and the admitted load while the regulated output is the response time of each application’s VMs (vertical scaling). The global (upper) level supervisory controller, considering the available set of VM’s operating points implied by the local controllers, determines the number and the size of necessary VMs for meeting the total incoming request rate (horizontal scaling). The distribution of the workload among the activated VMs and the placement of them in the cluster of servers are made in such a way that the minimum number of active servers.

Description
  • It proposes a two-layer control architecture that addresses cooperatively the problems of load balancing, application placement, capacity allocation and admission control with respect to satisfaction of QoS metrics and optimal recource allocation. In detail, the local (lower) level includes distributed individual controllers based on fuzzy Takagi–Sugeno modeling for each application. A set of feasible operation points is determined based on the derived models by solving a dynamic programming problem. Inputs of local controllers are the allocated capacity (CPU share) and the admitted load while the regulated output is the response time of each application’s VMs (vertical scaling). The global (upper) level supervisory controller, considering the available set of VM’s operating points implied by the local controllers, determines the number and the size of necessary VMs for meeting the total incoming request rate (horizontal scaling). The distribution of the workload among the activated VMs and the placement of them in the cluster of servers are made in such a way that the minimum number of active servers.

  • To reduce the energy consumption of a data center with satisfaction of the system’s constraints and the user’s requirements towards the fluctuations of incoming requests.

Aim & Objectives
  • To reduce the energy consumption of a data center with satisfaction of the system’s constraints and the user’s requirements towards the fluctuations of incoming requests.

  • In this proposed model the netwrok resources are also considered.

Contribution
  • In this proposed model the netwrok resources are also considered.

  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

Project Recommended For
  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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