Title : 
Chargeback model for resource pools in the cloud
         
        
            Author : 
Gmach, Daniel ; Rolia, Jerry ; Cherkasova, Ludmila
         
        
            Author_Institution : 
HP Labs., Palo Alto, CA, USA
         
        
        
        
        
        
            Abstract : 
This paper presents three methods for apportioning server costs among workloads in shared resource environments such as computing clouds. We consider a fine sharing of resources, the impact of time varying resource usage, large ratios for peak to mean workload demands, and the influence of random choices for the co-placement of workloads on shared servers. These features can affect the quantity of servers needed to support workloads as well as the robustness of the cost values assigned to each workload. We compare the three methods for apportioning costs and recommend the method that assigns costs in the most repeatable manner. A detailed study involving 312 workloads from an HP customer environment demonstrates the result.
         
        
            Keywords : 
cloud computing; shared memory systems; HP customer environment; apportioning cost; chargeback model; cloud computing; resource pool; shared resource environment; time varying resource usage; Pricing; Cloud Computing; Cost models; Shared Resources; Virtualization;
         
        
        
        
            Conference_Titel : 
Integrated Network Management (IM), 2011 IFIP/IEEE International Symposium on
         
        
            Conference_Location : 
Dublin
         
        
            Print_ISBN : 
978-1-4244-9219-0
         
        
            Electronic_ISBN : 
978-1-4244-9220-6
         
        
        
            DOI : 
10.1109/INM.2011.5990586