國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Optimal Provisioning for Elastic Service Oriented Virtual Network Request in Cloud Computing

101062558 劉冠逸

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Outline Introduction Problem description Genetic Algorithm-based Heuristic Algorithm

(GAH) Simulations

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Introduction Cloud computing paradigm enables users to

access services and applications hosted in data centers based on their requirements.

The service or application request submitted to a data center can be abstracted as a virtual network (VN) request, which consists of a set of VN nodes and VN edges.

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Virtual Network

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Introduction How to efficiently provision VN requests in

multi datacenters is of utmost importance

For the elastic resource requirement services, providers need to make sure the QoS or SLAs are satisfied.

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Problem description (I)

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Problem description (II) For a provisioned VN request , we define the

gross income GI() as:

The cost C() of provisioning a VN request :

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Problem description (III) The revenue R(GV) generated by provisioning a VN

request can be calculated as follows:

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Greedy VN Provisioning Algorithm(GVNP) sss

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Greedy VN Provisioning Algorithm(GVNP) sss

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Genetic Algorithm-based Heuristic Algorithm (GAH)

Chromosome Coding Chromosome Operations Genetic Algorithm-based Heuristic Algorithm

(GAH)

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Chromosome Coding The number of columns in the array equals to the

number of server nodes in substrate network The total number of element “1” in the array equals

to the number of VN nodes in a VN request

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Chromosome Operations Cloning Crossover Mutation Feasibility checking Selection

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Chromosome Operations Cloning

The cloning operation involves generating theinitial population

The GA procedure begins its iterations from this population

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Chromosome Operations Crossover

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Chromosome Operations Mutation

The mutation operation is used to prevent solutions from being trapped at a local optimum

Mutation is done in the children population, by changing the values of some genes with a small probability pm (from 0.001 to 0.1)

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Chromosome Operations Feasibility checking

Some of the newly generated children may not be feasible solutions for the original problem.

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Chromosome Operations Selection

The chromosome selection is to select parent chromosomes from the particular generation of population, and assign reproductive opportunities to these selected chromosomes

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Genetic Algorithm-based Heuristic Algorithm (GAH)

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Simulations Use the ITALYNET (Figure 4) with 20 nodes and 36

links as substrate network in our simulation

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Simulations

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Simulations

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

Conclusion In this work we address the problem of optimal

provisioning for elastic service oriented VN request in cloud-based datacenters.

We model this problem as a mathematical optimization problem by using mixed integer programming and propose a genetic algorithm based heuristic algorithm for solving this NP-hard problem efficiently.

The experimental results demonstrate that the solution obtained by our approach is near to the optimal solution

國立清華大學高速通訊與計算實驗室NTHU High-Speed Communication & Computing Laboratory

The End