SDN-enabled headroom services for high-speed data transfers

WAN provider links are often operated at low utilization levels, which leaves large unused capacity (headroom). In this paper, we propose using Software Defined Networking (SDN) controllers to support novel Static Headroom (SH) and Dynamic Headroom (DH) services to allow customers to fill this headroom with Elephant Flows (EFs) without adversely affecting the provider's ability to meet its Best-Effort (BE) service-level agreements, and ability to absorb extra traffic load created during failure recovery periods. Our solution calls for the use of lower-priority service for EFs. We use simulations to compare SH service with BE service, and DH service with SH service. When EFs are sent on BE service, they could cause packet losses in general-purpose IP traffic, especially when the burstiness of the latter is high, while with SH service, this packet loss rate is reduced to 0. While DH service requires the added complexity of a provider SDN controller, the ability to dynamically route EFs on lower-utilized links results in higher average EF throughput. The higher the non-uniformity (from a node-pair perspective) in network traffic, the greater the DH gain factor.

[1]  José Soler,et al.  SDN-Based QoS Aware Network Service Provisioning , 2015, MSPN.

[2]  Doreid Ammar,et al.  A new tool for generating realistic internet traffic in NS-3 , 2011, SimuTools.

[3]  Ilias Giechaskiel,et al.  Delay Tolerant Bulk Data Transfers on the Internet , 2014 .

[4]  Xiaoying Zheng,et al.  Delay Tolerant Bulk Transfers on Inter-Datacenter Networks , 2016, 2016 IEEE Globecom Workshops (GC Wkshps).

[5]  Srikanth Kandula,et al.  Achieving high utilization with software-driven WAN , 2013, SIGCOMM.

[6]  Igor Radusinovic,et al.  Fast and efficient bandwidth-delay constrained routing algorithm for SDN networks , 2016, 2016 IEEE NetSoft Conference and Workshops (NetSoft).

[7]  Nen-Fu Huang,et al.  A dynamic QoS management system with flow classification platform for software-defined networks , 2015, 2015 8th International Conference on Ubi-Media Computing (UMEDIA).

[8]  Chase Qishi Wu,et al.  On Periodic Scheduling of Bandwidth Reservations with Deadline Constraint for Big Data Transfer , 2016, 2016 IEEE 41st Conference on Local Computer Networks (LCN).

[9]  Kaiqi Xiong,et al.  Quality of Service (QoS)-Guaranteed Network Resource Allocation via Software Defined Networking (SDN) , 2014, 2014 IEEE 12th International Conference on Dependable, Autonomic and Secure Computing.

[10]  Min Zhu,et al.  B4: experience with a globally-deployed software defined wan , 2013, SIGCOMM.

[11]  Moshe Zukerman,et al.  Performance evaluation of a queue fed by a Poisson Pareto burst process , 2002, Comput. Networks.

[12]  Konstantinos Psounis SIFT : A low-complexity scheduler for reducing fl ow delays in the Internet CENG-2004-01 , University of Southern California , 2006 .

[13]  Zongpeng Li,et al.  Orchestrating Bulk Data Transfers across Geo-Distributed Datacenters , 2017, IEEE Transactions on Cloud Computing.

[14]  Ellen W. Zegura,et al.  iDTT: Delay Tolerant Data Transfer for P2P File Sharing Systems , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.

[15]  Jordi Ferrer Riera,et al.  An OpenNaaS Based SDN Framework for Dynamic QoS Control , 2013, 2013 IEEE SDN for Future Networks and Services (SDN4FNS).

[16]  Fred Baker,et al.  Configuration Guidelines for DiffServ Service Classes , 2006, RFC.