Enabling Heterogeneous Network Function Chaining

Today’s data center operators deploy network policies in both physical (e.g., middleboxes, switches) and virtualized (e.g., virtual machines on general purpose servers) network function boxes (NFBs), which reside in different points of the network, to exploit their efficiency and agility respectively. Nevertheless, such heterogeneity has resulted in a great number of independent network nodes that can dynamically generate and implement inconsistent and conflicting network policies, making correct policy implementation a difficult problem to solve. Since these nodes have varying capabilities, services running atop are also faced with profound performance unpredictability. In this paper, we propose a Heterogeneous netwOrk Policy Enforcement (HOPE) scheme to overcome these challenges. HOPE guarantees that network functions (NFs) that implement a policy chain are optimally placed onto heterogeneous NFBs such that the network cost of the policy is minimized. We first experimentally demonstrate that the processing capacity of NFBs is the dominant performance factor. This observation is then used to formulate the Heterogeneous Network Policy Placement problem, which is shown to be NP-Hard. To solve the problem efficiently, an online algorithm is proposed. Our experimental results demonstrate that HOPE achieves the same optimality as Branch-and-bound optimization but is 3 orders of magnitude more efficient.

[1]  Dan Alistarh,et al.  The SprayList: a scalable relaxed priority queue , 2015, PPoPP.

[2]  Mark Handley,et al.  Re-architecting datacenter networks and stacks for low latency and high performance , 2017, SIGCOMM.

[3]  Lucien Avramov,et al.  The Policy Driven Data Center with ACI: Architecture, Concepts, and Methodology , 2014 .

[4]  Ying Zhang,et al.  PGA: Using Graphs to Express and Automatically Reconcile Network Policies , 2015, Comput. Commun. Rev..

[5]  Dan Li,et al.  PACE: Policy-Aware Application Cloud Embedding , 2013, 2013 Proceedings IEEE INFOCOM.

[6]  Albert G. Greenberg,et al.  Data center TCP (DCTCP) , 2010, SIGCOMM '10.

[7]  Pengfei Duan,et al.  Toward Latency-Aware Dynamic Middlebox Scheduling , 2015, 2015 24th International Conference on Computer Communication and Networks (ICCCN).

[8]  Amin Vahdat,et al.  TIMELY: RTT-based Congestion Control for the Datacenter , 2015, Comput. Commun. Rev..

[9]  Vyas Sekar,et al.  The middlebox manifesto: enabling innovation in middlebox deployment , 2011, HotNets-X.

[10]  Robert E. Tarjan,et al.  Fibonacci heaps and their uses in improved network optimization algorithms , 1984, JACM.

[11]  Zhi Liu,et al.  Towards efficient load distribution in big data cloud , 2015, 2015 International Conference on Computing, Networking and Communications (ICNC).

[12]  Minlan Yu,et al.  CloudPolice: taking access control out of the network , 2010, Hotnets-IX.

[13]  Weifa Liang,et al.  Near-Optimal Deployment of Service Chains by Exploiting Correlations Between Network Functions , 2020, IEEE Transactions on Cloud Computing.

[14]  Fung Po Tso,et al.  Synergistic policy and virtual machine consolidation in cloud data centers , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.

[15]  Justine Sherry,et al.  Silo: Predictable Message Latency in the Cloud , 2015, Comput. Commun. Rev..

[16]  Ramesh Govindan,et al.  Scalable Rule Management for Data Centers , 2013, NSDI.

[17]  Shunsuke Homma,et al.  Service Function Chaining Use Cases In Data Centers , 2017 .

[18]  Aditya Akella,et al.  OpenNF , 2014, SIGCOMM.

[19]  Meral Shirazipour,et al.  StEERING: A software-defined networking for inline service chaining , 2013, 2013 21st IEEE International Conference on Network Protocols (ICNP).

[20]  Cong Wang,et al.  Toward Secure Outsourced Middlebox Services: Practices, Challenges, and Beyond , 2018, IEEE Network.

[21]  Hua Chen,et al.  Pingmesh: A Large-Scale System for Data Center Network Latency Measurement and Analysis , 2015, SIGCOMM.

[22]  Minlan Yu,et al.  Enforcing Network-Wide Policies in the Presence of Dynamic Middlebox Actions using FlowTags , 2014, NSDI.

[23]  Fang Hao,et al.  Network function virtualization enablement within SDN data plane , 2017, IEEE INFOCOM 2017 - IEEE Conference on Computer Communications.

[24]  Jinsong Wu,et al.  Service Chaining for Hybrid Network Function , 2019, IEEE Transactions on Cloud Computing.

[25]  Peter Phaal,et al.  InMon Corporation's sFlow: A Method for Monitoring Traffic in Switched and Routed Networks , 2001, RFC.

[26]  Scott Shenker,et al.  Elastic Scaling of Stateful Network Functions , 2018, NSDI.

[27]  Anat Bremler-Barr,et al.  OpenBox: A Software-Defined Framework for Developing, Deploying, and Managing Network Functions , 2016, SIGCOMM.

[28]  Tarik Taleb,et al.  Service Function Chaining in Next Generation Networks: State of the Art and Research Challenges , 2017, IEEE Communications Magazine.

[29]  Fang Hao,et al.  Application-aware data plane processing in SDN , 2014, HotSDN.

[30]  Minlan Yu,et al.  SIMPLE-fying middlebox policy enforcement using SDN , 2013, SIGCOMM.

[31]  Weijia Jia,et al.  Heterogeneous NetwOrk Policy Enforcement in data centers , 2017, 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM).

[32]  Scott Shenker,et al.  SoftFlow: A Middlebox Architecture for Open vSwitch , 2016, USENIX ATC.

[33]  Devavrat Shah,et al.  Fastpass , 2014, SIGCOMM.

[34]  Robert N. M. Watson,et al.  Queues Don't Matter When You Can JUMP Them! , 2015, NSDI.

[35]  Chadi Assi,et al.  A Cut-and-Solve Based Approach for the VNF Assignment Problem , 2017 .

[36]  Brigitte Jaumard,et al.  Energy-efficient service function chain provisioning , 2018, IEEE/OSA Journal of Optical Communications and Networking.

[37]  Aditya Akella,et al.  Toward software-defined middlebox networking , 2012, HotNets-XI.

[38]  Amin Vahdat,et al.  TIMELY: RTT-based Congestion Control for the Datacenter , 2015, Comput. Commun. Rev..

[39]  Tamás Lukovszki,et al.  It's a Match!: Near-Optimal and Incremental Middlebox Deployment , 2016, CCRV.

[40]  Libin Liu,et al.  RepNet: Cutting Latency with Flow Replication in Data Center Networks , 2018, IEEE Transactions on Services Computing.

[41]  Fung Po Tso,et al.  Joint virtual machine and network policy consolidation in cloud data centers , 2015, 2015 IEEE 4th International Conference on Cloud Networking (CloudNet).

[42]  T. S. Eugene Ng,et al.  The Impact of Virtualization on Network Performance of Amazon EC2 Data Center , 2010, 2010 Proceedings IEEE INFOCOM.

[43]  Chadi Assi,et al.  A Logic-Based Benders Decomposition Approach for the VNF Assignment Problem , 2019, IEEE Transactions on Cloud Computing.

[44]  Fernando A. Kuipers,et al.  OpenNetMon: Network monitoring in OpenFlow Software-Defined Networks , 2014, 2014 IEEE Network Operations and Management Symposium (NOMS).

[45]  Thomas D. Nadeau,et al.  Problem Statement for Service Function Chaining , 2015, RFC.

[46]  Hello Branch and Bound , 2017, Encyclopedia of GIS.

[47]  Deng Pan,et al.  SDN-Based Traffic Aware Placement of NFV Middleboxes , 2017, IEEE Transactions on Network and Service Management.

[48]  Weijia Jia,et al.  PLAN: Joint Policy- and Network-Aware VM Management for Cloud Data Centers , 2017, IEEE Transactions on Parallel and Distributed Systems.