Towards efficient operation of internet data center networks: Joint data placement and flow control for cost optimization

Abstract The problem of cost-efficient operation of data center networks used to deliver file sharing services is studied. The aggregate costs are split into server-load-related and link-load-related shares. Thus, the problem of interest is formulated as one of joint data placement and flow control, and mixed integer-linear programming is used to compute the optimal solution. The high complexity of the latter motivated us to design two additional sets of strategies, based on data coding and heuristics, respectively. With coding, a distributed algorithm for the problem is developed. In the simulation experiments, carried out based on actual data center information, network topology and link cost, as well as electricity prices, the advantages of data coding, in particular in the context of multicast, and the impact of different factors such as the network topology and service popularity, on the total cost incurred by all considered strategies, are examined. Network coding with multicast is shown to provide cost savings in the order of 30–80%, depending on the specific context under consideration, relative to the other optimization strategies and heuristic methods examined in this work.

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

[2]  Bruce M. Maggs,et al.  Cutting the electric bill for internet-scale systems , 2009, SIGCOMM '09.

[3]  Kevin Skadron,et al.  Multi-mode energy management for multi-tier server clusters , 2008, 2008 International Conference on Parallel Architectures and Compilation Techniques (PACT).

[4]  Baochun Li,et al.  Joint request mapping and response routing for geo-distributed cloud services , 2013, 2013 Proceedings IEEE INFOCOM.

[5]  Abdallah Khreishah,et al.  Collaborative caching for multicell-coordinated systems , 2015, 2015 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[6]  Anees Shaikh,et al.  A comparison of overlay routing and multihoming route control , 2004, SIGCOMM 2004.

[7]  A. Neeraja,et al.  Licensed under Creative Commons Attribution Cc by Improving Network Management with Software Defined Networking , 2022 .

[8]  Lachlan L. H. Andrew,et al.  Greening geographical load balancing , 2011, PERV.

[9]  Issa M. Khalil,et al.  Joint Caching and Routing for Greening Computer Networks with Renewable Energy Sources , 2014, 2014 International Conference on Future Internet of Things and Cloud.

[10]  Albert G. Greenberg,et al.  Optimizing Cost and Performance in Online Service Provider Networks , 2010, NSDI.

[11]  Lorenz M. Hilty,et al.  The Direct Energy Demand of Internet Data Flows , 2013 .

[12]  Mingwei Xu,et al.  Energy-aware routing in data center network , 2010, Green Networking '10.

[13]  Mikkel Thorup,et al.  Traffic engineering with estimated traffic matrices , 2003, IMC '03.

[14]  Lachlan L. H. Andrew,et al.  Geographical load balancing with renewables , 2011, PERV.

[15]  Mor Harchol-Balter,et al.  Are sleep states effective in data centers? , 2012, 2012 International Green Computing Conference (IGCC).

[16]  Xue Liu,et al.  Minimizing Electricity Cost: Optimization of Distributed Internet Data Centers in a Multi-Electricity-Market Environment , 2010, 2010 Proceedings IEEE INFOCOM.

[17]  Tracey Ho,et al.  A Random Linear Network Coding Approach to Multicast , 2006, IEEE Transactions on Information Theory.

[18]  Jie Wu,et al.  Asymptotically-Optimal Incentive-Based En-Route Caching Scheme , 2014, 2014 IEEE 11th International Conference on Mobile Ad Hoc and Sensor Systems.

[19]  Wei Tan,et al.  CAWSAC: Cost-Aware Workload Scheduling and Admission Control for Distributed Cloud Data Centers , 2016, IEEE Transactions on Automation Science and Engineering.

[20]  Tracey Ho,et al.  Optimal content delivery with network coding , 2009, 2009 43rd Annual Conference on Information Sciences and Systems.

[21]  Biswanath Mukherjee,et al.  On Routing and Transmission-Range Determination of Multi-Bit-Rate Signals Over Mixed-Line-Rate WDM Optical Networks for Carrier Ethernet , 2011, IEEE/ACM Transactions on Networking.

[22]  Dimitri P. Bertsekas,et al.  Convex Analysis and Optimization , 2003 .

[23]  Fang Zhao,et al.  Minimum-cost multicast over coded packet networks , 2005, IEEE Transactions on Information Theory.

[24]  Jie Wu,et al.  The Benefits of Cooperation Between the Cloud and Private Data Centers for Multi-rate Video Streaming , 2014 .

[25]  Jacob Chakareski,et al.  Joint optimization of flow allocation and data center placement in multi-service networks , 2012, 2012 19th International Packet Video Workshop (PV).

[26]  Muriel Médard,et al.  Minimum Cost Mirror Sites Using Network Coding: Replication versus Coding at the Source Nodes , 2009, IEEE Transactions on Information Theory.

[27]  P. Cochat,et al.  Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.

[28]  Yin Zhang,et al.  Optimizing cost and performance for multihoming , 2004, SIGCOMM 2004.

[29]  John N. Tsitsiklis,et al.  Parallel and distributed computation , 1989 .

[30]  Amir-Hamed Mohsenian-Rad,et al.  Energy-Information Transmission Tradeoff in Green Cloud Computing , 2010 .

[31]  Achyut Sakadasariya,et al.  Software defined network: Future of networking , 2018, 2018 2nd International Conference on Inventive Systems and Control (ICISC).

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

[33]  Jie Wu,et al.  Cache content placement using triangular network coding , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).

[34]  Laurent Massoulié,et al.  Greening the internet with nano data centers , 2009, CoNEXT '09.