Integrating Variability Management in Data Center Networks

Data centers have an important role in supporting cloud computing services (i.e. checking social media, sending emails, video conferencing,..). Hence, data centers topologies design became more important and must be able to respond to ever changing service requirements and application demands. An ultimate challenge in this research is the design of data center network that interconnects the massive number of servers, and provides efficient and fault-tolerant routing algorithm. Several topologies such as DCell, FlatNet and ScalNet have been proposed. However, these topologies generally seek to improve the scalability without taking into consideration the energy usage neither the network nfrastructure cost which is critical parameters in data centers. Motivated by these challenges, we propose a new network topology for data center, called AdyNet. It is an adaptive, dynamic, cost effective and highly performing topology. While reducing largely the infrastructure cost and the energy consumption, AdyNet outperforms FlatNet and ScalNet in terms of Average Path Length.

[1]  Yogendra Joshi,et al.  Rapid modeling tools for energy analysis of modular data centers , 2016, 2016 15th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITherm).

[2]  Sebti Foufou,et al.  ScalNet: A Novel Network Architecture for Data Centers , 2015, 2015 IEEE Globecom Workshops (GC Wkshps).

[3]  Sebti Foufou,et al.  VacoNet: Variable and connected architecture for data center networks , 2016, 2016 IEEE Wireless Communications and Networking Conference.

[4]  Ion Stoica,et al.  A cost comparison of datacenter network architectures , 2010, CoNEXT.

[5]  Haitao Wu,et al.  BCube: a high performance, server-centric network architecture for modular data centers , 2009, SIGCOMM '09.

[6]  Sebti Foufou,et al.  Adaptative Network Topology for Data Centers , 2016 .

[7]  Lei Shi,et al.  Dcell: a scalable and fault-tolerant network structure for data centers , 2008, SIGCOMM '08.

[8]  Dong Lin,et al.  FlatNet: Towards a flatter data center network , 2012, 2012 IEEE Global Communications Conference (GLOBECOM).

[9]  Mark Seymour Is energy efficiency enough? Filling the engineering gap in data center design and operation , 2016, 2016 15th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITherm).

[10]  Haitao Wu,et al.  FiConn: Using Backup Port for Server Interconnection in Data Centers , 2009, IEEE INFOCOM 2009.

[11]  Sebti Foufou,et al.  A survey of wireless data center networks , 2015, 2015 49th Annual Conference on Information Sciences and Systems (CISS).

[12]  Sebti Foufou,et al.  PTNet: A parameterizable data center network , 2016, 2016 IEEE Wireless Communications and Networking Conference.

[13]  Rajiv Ranjan,et al.  Survey of Techniques and Architectures for Designing Energy-Efficient Data Centers , 2016, IEEE Systems Journal.

[14]  Rajkumar Buyya,et al.  Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges , 2010, PDPTA.