Falloc: Fair network bandwidth allocation in IaaS datacenters via a bargaining game approach

With wide application of virtualization technology, tenants are able to access isolated cloud services by renting the shared resources in datacenters. Unlike resources such as CPU and memory, datacenter network, which relies on traditional transport-layer protocols, suffers unfairness due to a lack of VM-level network isolation. In this paper, we propose Falloc, a new bandwidth allocation protocol, towards VM-based fairness across the datacenter with two main objectives: (i) guarantee bandwidth for VMs based on their base bandwidth requirements, and (ii) share residual bandwidth in proportion to weights of VMs. To design Falloc, we model the datacenter bandwidth allocation as a bargaining game and propose a distributed algorithm to achieve the asymmetric Nash bargaining solution (NBS). We apply the theory to practice by implementing Falloc with OpenFlow in experiments under diversed scenarios, which shows that Falloc can achieve fairness by adapting to different network requirements of VMs, and balance the tradeoff between bandwidth guarantee and proportional bandwidth share. By carrying out large scale trace-driven simulations using real-world Mapreduce workload, we show that Falloc achieves high utilization and maintains fairness among VMs in datacenters.

[1]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[2]  Dan Li,et al.  Towards bandwidth guarantee in multi-tenancy cloud computing networks , 2012, 2012 20th IEEE International Conference on Network Protocols (ICNP).

[3]  Bo Li,et al.  Collaborative Caching in Wireless Video Streaming Through Resource Auctions , 2012, IEEE Journal on Selected Areas in Communications.

[4]  Hai Jin,et al.  Carbon-Aware Load Balancing for Geo-distributed Cloud Services , 2013, 2013 IEEE 21st International Symposium on Modelling, Analysis and Simulation of Computer and Telecommunication Systems.

[5]  I. Stoica,et al.  FairCloud: sharing the network in cloud computing , 2011, CCRV.

[6]  Stephen P. Boyd,et al.  Subgradient Methods , 2007 .

[7]  Bo Li,et al.  Flash Crowd in P2P Live Streaming Systems: Fundamental Characteristics and Design Implications , 2012, IEEE Transactions on Parallel and Distributed Systems.

[8]  Hai Jin,et al.  A cooperative game based allocation for sharing data center networks , 2013, 2013 Proceedings IEEE INFOCOM.

[9]  Mark Handley,et al.  Improving datacenter performance and robustness with multipath TCP , 2011, SIGCOMM.

[10]  Catherine Rosenberg,et al.  A game theoretic framework for bandwidth allocation and pricing in broadband networks , 2000, TNET.

[11]  Albert G. Greenberg,et al.  Sharing the Data Center Network , 2011, NSDI.

[12]  Albert G. Greenberg,et al.  VL2: a scalable and flexible data center network , 2009, SIGCOMM '09.

[13]  A. Rowstron,et al.  Towards predictable datacenter networks , 2011, SIGCOMM.

[14]  George Varghese,et al.  NetShare: Virtualizing Bandwidth within the Cloud , 2009 .

[15]  Helen J. Wang,et al.  SecondNet: a data center network virtualization architecture with bandwidth guarantees , 2010, CoNEXT.

[16]  Di Xie,et al.  The only constant is change: incorporating time-varying network reservations in data centers , 2012, CCRV.

[17]  Tim Roughgarden,et al.  Algorithmic Game Theory , 2007 .

[18]  Bo Li,et al.  FS2You: Peer-Assisted Semipersistent Online Hosting at a Large Scale , 2010, IEEE Transactions on Parallel and Distributed Systems.

[19]  Dorgival O. Guedes,et al.  Gatekeeper: Supporting Bandwidth Guarantees for Multi-tenant Datacenter Networks , 2011, WIOV.

[20]  Brahim Bensaou,et al.  Fair bandwidth sharing algorithms based on game theory frameworks for wireless ad-hoc networks , 2004, IEEE INFOCOM 2004.

[21]  Holger Boche,et al.  Non-symmetric Nash bargaining solution for resource allocation in wireless networks and connection to interference calculus , 2007, 2007 15th European Signal Processing Conference.

[22]  Bo Li,et al.  Gearing resource-poor mobile devices with powerful clouds: architectures, challenges, and applications , 2013, IEEE Wireless Communications.