Cloud Computing Resource Scheduling Problem Based On Heuristic Algorithm

With the gradual increase of the scale of the Internet,the amount of data that computers need to process is growing rapidly.At the same time,people put forward a new concept-cloud computing.This paper studies the resource allocation and scheduling of deploying cloud computing virtual machines,hoping to give a series of decision-making schemes for the purchase,deployment and migration of cloud computing servers,make full use of server resources and save costs.Firstly,this paper redefines the cloud resource scheduling problem.Taking the packing problem as the background and aiming at the actual scene,the first adaptation algorithm,next adaptation algorithm and best adaptation algorithm are combined with the descending adaptation algorithm respectively.The descending next adaptation algorithm,descending best adaptation algorithm and descending first adaptation algorithm are proposed to purchase and deploy servers.Program and calculate the server purchase cost and daily energy consumption cost of the above three heuristic algorithms under the condition of daily capacity expansion,and compare the operation efficiency of the three algorithms.Numerical simulation shows that within the acceptable range of running time,the cost of descending next adaptation algorithm and descending best adaptation algorithm is lower than that of descending first adaptation algorithm.For the cloud resource scheduling problem,this paper adds migration constraints,studies the migration decision-making scheme,and uses linear regression analysis data to optimize the parameters of the deployment algorithm.Numerical simulation shows that the descending optimal adaptation algorithm with migration decision saves a lot of cost than the non migration algorithm.