A random graph model for massive graphs
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
A scalable, commodity data center network architecture
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
Dcell: a scalable and fault-tolerant network structure for data centers
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
The cost of a cloud: research problems in data center networks
ACM SIGCOMM Computer Communication Review
PortLand: a scalable fault-tolerant layer 2 data center network fabric
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
VL2: a scalable and flexible data center network
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
BCube: a high performance, server-centric network architecture for modular data centers
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
Why should we integrate services, servers, and networking in a data center?
Proceedings of the 1st ACM workshop on Research on enterprise networking
MDCube: a high performance network structure for modular data center interconnection
Proceedings of the 5th international conference on Emerging networking experiments and technologies
How can architecture help to reduce energy consumption in data center networking?
Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking
Proceedings of the 2nd ACM Symposium on Cloud Computing
Jellyfish: networking data centers, randomly
HotCloud'11 Proceedings of the 3rd USENIX conference on Hot topics in cloud computing
Camdoop: exploiting in-network aggregation for big data applications
NSDI'12 Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation
Jellyfish: networking data centers randomly
NSDI'12 Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation
Computer Networks: The International Journal of Computer and Telecommunications Networking
Incrementally upgradable data center architecture using hyperbolic tessellations
Computer Networks: The International Journal of Computer and Telecommunications Networking
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Data centers have a crucial role in current Internet architecture supporting content-centric networking. State-of-the-art data centers have different architectures like fat-tree, DCell, or BCube. However, their architectures share a common property: symmetry. Due to their symmetric nature, a tricky point with these architectures is that they are hard to be extended in small quantities. Contrary to state-of-the-art data center architectures, we propose an asymmetric data center topology generation method called Scafida inspired by scale-free networks; these data centers have not only small diameters and high fault tolerance, inherited by scale-free networks, but can also be scaled in smaller and less homogenous increments. We extend the original scale-free network generation algorithm of Barabasi and Albert to meet the physical constraints of switches and routers. Despite the fact that our method artificially limits the node degrees in the network, our data center architectures keep the preferable properties of scale-free networks. Based on extensive simulations we present preliminary results that are promising regarding the error tolerance, scalability, and flexibility of the architecture.