Resource allocation in a network-based cloud computing environment: design challenges

Cloud computing is a utility computing paradigm that has become a solid base for a wide array of enterprise and end-user applications. Providers offer varying service portfolios that differ in resource configurations and provided services. A comprehensive solution for resource allocation is fundamental to any cloud computing service provider. Any resource allocation model has to consider computational resources as well as network resources to accurately reflect practical demands. Another aspect that should be considered while provisioning resources is energy consumption. This aspect is getting more attention from industrial and government parties. Calls for the support of green clouds are gaining momentum. With that in mind, resource allocation algorithms aim to accomplish the task of scheduling virtual machines on the servers residing in data centers and consequently scheduling network resources while complying with the problem constraints. Several external and internal factors that affect the performance of resource allocation models are introduced in this article. These factors are discussed in detail, and research gaps are pointed out. Design challenges are discussed with the aim of providing a reference to be used when designing a comprehensive energy-aware resource allocation model for cloud computing data centers.

[1]  Martín Casado,et al.  Applying NOX to the Datacenter , 2009, HotNets.

[2]  Nagarajan Kandasamy,et al.  Power and performance management of virtualized computing environments via lookahead control , 2008, 2008 International Conference on Autonomic Computing.

[3]  Amin Vahdat,et al.  Managing energy and server resources in hosting centers , 2001, SOSP.

[4]  Lemin Li,et al.  Optimal provisioning for elastic service oriented virtual network request in cloud computing , 2012, 2012 IEEE Global Communications Conference (GLOBECOM).

[5]  Feng Zhao,et al.  Energy aware consolidation for cloud computing , 2008, CLUSTER 2008.

[6]  Hamid Farhadi,et al.  Software-Defined Networking: A survey , 2015, Comput. Networks.

[7]  Chadi Assi,et al.  Scheduling advance reservation requests for wavelength division multiplexed networks with static traffic demands , 2008, IET Commun..

[8]  Cullen E. Bash,et al.  Smart cooling of data centers , 2003 .

[9]  Suman Nath,et al.  Energy-Aware Server Provisioning and Load Dispatching for Connection-Intensive Internet Services , 2008, NSDI.

[10]  Rob Sherwood,et al.  The controller placement problem , 2012, HotSDN '12.

[11]  Randy H. Katz,et al.  Above the Clouds: A Berkeley View of Cloud Computing , 2009 .

[12]  Randy H. Katz,et al.  An energy case for hybrid datacenters , 2010, OPSR.

[13]  R. Srikant,et al.  Stochastic models of load balancing and scheduling in cloud computing clusters , 2012, 2012 Proceedings IEEE INFOCOM.

[14]  Laurent Broto,et al.  Approaches to cloud computing fault tolerance , 2012, 2012 International Conference on Computer, Information and Telecommunication Systems (CITS).

[15]  T. V. Lakshman,et al.  Network aware resource allocation in distributed clouds , 2012, 2012 Proceedings IEEE INFOCOM.

[16]  Abdelkader H. Ouda,et al.  A resource scheduling model for cloud computing data centers , 2013, 2013 9th International Wireless Communications and Mobile Computing Conference (IWCMC).