دانلود A hybrid meta-heuristic algorithm for VM scheduling with load balancing in cloud computing

Abstract

Virtual  machine  (VM)  scheduling  with  load balancing  in  cloud  computing  aims  to  assign  VMs  to suitable servers and balance the resource usage among all of the servers. In an infrastructure-as-a-service framework, there will be dynamic input requests, where the system is in charge of creating VMs without considering what types of tasks run on them. Therefore, scheduling that focuses only on fixed task sets or that requires detailed task information is  not  suitable  for  this  system.  This  paper  combines  ant colony  optimization  and  particle  swarm  optimization  to solve  the  VM  scheduling  problem,  with  the  result  being known  as  ant  colony  optimization  with  particle  swarm(ACOPS).  ACOPS  uses  historical  information  to  predict the  workload  of  new  input  requests  to  adapt  to  dynamic environments without additional task information. ACOPS also rejects requests that cannot be satisfied before scheduling  to  reduce  the  computing  time  of  the  scheduling procedure. Experimental results indicate that the proposed algorithm  can  keep  the  load  balance  in  a  dynamic  environment and outperform other approaches.