RE-FPR: flow preemption routing scheme with redundancy elimination in Software Defined Data Center Networks

Abstract With the explosive expansion of data center sizes, a large number of the same or similar contents are requested repeatedly by the users on network edge, which causes a serious waste of network bandwidth, and further makes the network energy consumption increase remarkably. The current researches achieve energy saving by increasing network link capacity as well as eliminating the data redundancy in routers. But the existing redundancy elimination may cause the increase of router's energy consumption. To solve this problem, we propose a flow preemption routing scheme with redundancy elimination (RE-FPR). The RE-FPR scheme uses software defined networking (SDN) technology to select different routing paths for the traffic flow and control RE function on the corresponding router under two modes, i.e., traffic peak and traffic valley. Specifically, the RE-FPR scheme also employs the SDN controller to update flow states and link states of the network. We then formulate the RE-FPR problem as a power consumption minimization problem subject to flow conservation constraint and link capacity constraint. Furthermore, we solve the optimization problem by using the maximum entropy principle and propose the RE-FPR algorithm. The simulation results show that the RE-FPR algorithm outperforms the traditional flow scheduling algorithms in term of flow completion time and the number of active RE-routers/links.

[1]  Cong Wang,et al.  Energy-efficient mobile data collection in energy-harvesting wireless sensor networks , 2014, 2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS).

[2]  Russell J. Clark,et al.  Advance reservation access control using software-defined networking and tokens , 2018, Future Gener. Comput. Syst..

[3]  Athanasios V. Vasilakos,et al.  Energy-Efficient Flow Scheduling and Routing with Hard Deadlines in Data Center Networks , 2014, 2014 IEEE 34th International Conference on Distributed Computing Systems.

[4]  Stephen J. Wright,et al.  Power Awareness in Network Design and Routing , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[5]  Albert G. Greenberg,et al.  The cost of a cloud: research problems in data center networks , 2008, CCRV.

[6]  Virgil Dobrota,et al.  Implementation issues for Modified Dijkstra's and Floyd-Warshall algorithms in OpenFlow , 2013, 2013 RoEduNet International Conference 12th Edition: Networking in Education and Research.

[7]  Ivan Stojmenovic,et al.  Data Centers as Software Defined Networks: Traffic Redundancy Elimination with Wireless Cards at Routers , 2013, IEEE Journal on Selected Areas in Communications.

[8]  Yunfei Shang,et al.  EXR: Greening Data Center Network with Software Defined Exclusive Routing , 2015, IEEE Transactions on Computers.

[9]  Srinivasan Keshav,et al.  It's not easy being green , 2012, CCRV.

[10]  Liren Zhang,et al.  Optimizing Network Performance Using Weighted Multipath Routing , 2012, 2012 21st International Conference on Computer Communications and Networks (ICCCN).

[11]  Luca Benini,et al.  A survey of design techniques for system-level dynamic power management , 2000, IEEE Trans. Very Large Scale Integr. Syst..

[12]  Sujata Banerjee,et al.  A Power Benchmarking Framework for Network Devices , 2009, Networking.

[13]  Sujata Banerjee,et al.  ElasticTree: Saving Energy in Data Center Networks , 2010, NSDI.

[14]  David Coudert,et al.  Robust Redundancy Elimination for Energy-Aware Routing , 2013, 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing.

[15]  Frédéric Giroire,et al.  Minimization of network power consumption with redundancy elimination , 2015, Comput. Commun..

[16]  Brighten Godfrey,et al.  Finishing flows quickly with preemptive scheduling , 2012, CCRV.

[17]  Benxiong Huang,et al.  Bandwidth-aware energy efficient flow scheduling with SDN in data center networks , 2017, Future Gener. Comput. Syst..

[18]  Vivek Managing Failures in IP Networks Using SDN Controllers by Adding Module to OpenFlow , 2016 .

[19]  Dorian Mazauric,et al.  Minimizing Routing Energy Consumption: From Theoretical to Practical Results , 2010, 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing.

[20]  Lixin Gao,et al.  Redundancy-Aware Routing with Limited Resources , 2010, 2010 Proceedings of 19th International Conference on Computer Communications and Networks.

[21]  Zhe Zhang,et al.  Lark: An effective approach for software-defined networking in high throughput computing clusters , 2017, Future Gener. Comput. Syst..

[22]  Li Xing,et al.  An Efficient Approach to a Class of Non-smooth Optimization Problems , 1994 .

[23]  Cong Wang,et al.  Joint Mobile Data Gathering and Energy Provisioning in Wireless Rechargeable Sensor Networks , 2014, IEEE Transactions on Mobile Computing.

[24]  Yuanyuan Yang,et al.  A distributed optimal framework for mobile data gathering with concurrent data uploading in wireless sensor networks , 2012, 2012 Proceedings IEEE INFOCOM.

[25]  Hong Liu,et al.  Energy proportional datacenter networks , 2010, ISCA.

[26]  Akshat Verma,et al.  pMapper: Power and Migration Cost Aware Application Placement in Virtualized Systems , 2008, Middleware.