Introduction to Data Center Network Architecture
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The document outlines data center network (DCN) architectures, including fat-tree and recursive designs, with a focus on design goals such as availability, scalability, and cost-effectiveness. It discusses various usage scenarios, including compute-intensive and data-intensive applications, and highlights challenges like reduced utilization and scalability issues. Additionally, it introduces the concept of modular data centers and virtualized DCNs, emphasizing their benefits in deployment efficiency and performance management.
![Conventional DCN Architecture
Rack 3 Rack 10Rack 1 Rack 2
Server 21
Server 100
Server 91
Server 30
Server 1
Server 20
Server 11
Server 10
ToR ToRToR ToR
AggrAggr Aggr
Core Core
Core
[10 GigE switches]
Aggregation
[10 GigE switches]
Edge
[Commodity
switches]
Internet
ETHERNET](https://image.slidesharecdn.com/dcnintroduction-141010054657-conversion-gate01/85/Introduction-to-Data-Center-Network-Architecture-4-320.jpg)
![References
• A. Kumar, S. V. Rao, and D. Goswami, “4-4, 1-4: Architecture for Data Center Network Based
on IP Address Hierarchy for Efficient Routing," in Parallel and Distributed Computing (ISPDC),
2012 11th International Symposium on, 2012, pp. 235-242.
• M. Al-Fares, A. Loukissas, and A. Vahdat, “A scalable, commodity data center network
architecture," in Proceedings of the ACM SIGCOMM 2008 conference on Data
communication, ser. SIGCOMM '08. New York, NY, USA: ACM, 2008, pp. 63-74.[Online].
Available: http://doi.acm.org/10.1145/1402958.1402967
• C. Guo, G. Lu, D. Li, H. Wu, X. Zhang, Y. Shi, C. Tian, Y. Zhang, and S. Lu, “Bcube:a high
performance, server-centric network architecture for modular data centers.“
• T. Benson, A. Anand, A. Akella, and M. Zhang, “Understanding data center trac
characteristics," SIGCOMM Comput. Commun. Rev., vol. 40, no. 1, pp. 92{99, Jan. 2010.
[Online]. Available: http://doi.acm.org/10.1145/1672308.1672325
• A. Greenberg, J. Hamilton, D. A. Maltz, and P. Patel. “The cost of a cloud: research problems
in data center networks.” SIGCOMM Comput. Commun. Rev.,39(1):68–73, 2009.](https://image.slidesharecdn.com/dcnintroduction-141010054657-conversion-gate01/85/Introduction-to-Data-Center-Network-Architecture-16-320.jpg)
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Introduction to Data Center Network Architecture
- 1. Data Center Network Architecture Presented by: Ankita Mahajan
- 2. Design Goals FAT-Tree DCN Recursive DCN Design MDCs Virtualized DCN DCN-Introduction
- 3. Data Center Network Data Center Networks are large clusters of servers interconnected by network switches. These servers are used to host applications which provide different concurrent services. Ex) • Web services like DNS, Web server, Mail server, gaming server, chat server. • Compute services like suggestion systems, indexing and scientific computing. DCN Usage Scenarios: • Compute Intensive: Heavily loaded servers, but low inter-server comm. Ex) HPC • Data Intensive: Huge intra-DCN data transfer, but low load at servers. Ex) Video and File Streaming • Balanced: Communication links and computing servers are proportionally loaded. Ex) Geographic Information System
- 4. Conventional DCN Architecture Rack 3 Rack 10Rack 1 Rack 2 Server 21 Server 100 Server 91 Server 30 Server 1 Server 20 Server 11 Server 10 ToR ToRToR ToR AggrAggr Aggr Core Core Core [10 GigE switches] Aggregation [10 GigE switches] Edge [Commodity switches] Internet ETHERNET
- 5. DCN Design Goals • Availability and Fault tolerance: Multiple paths and replicated servers. Graceful Degradation. Challenges: • Reduced Utilization
- 6. DCN Design Goals • Availability and Fault tolerance: Multiple paths and replicated servers. Graceful Degradation. • Scalability: Incrementally increase DCN size as and when needed. • Low Cost: Lower power and cooling costs. Challenges: • Reduced Utilization • Scale-out vs Scale-up: per-port cost, cabling and packaging complexity, scalable cooling. • Placement, Air-Flow and rack-density
- 7. DCN Design Goals • Availability and Fault tolerance: Multiple paths and replicated servers. Graceful Degradation. • Scalability: Incrementally increase DCN size as and when needed. • Low Cost: Lower power and cooling costs. • Throughput: The number of requests completed by the data center per unit of time. (Compute + Transmission+ Aggregation Time) • Economies of scale: Utilize the benefits of its huge size. • Scalable interconnect bandwidth: Host to host communication at full bisection bandwidth. • Load balancing: Avoid hot-spots, to fully utilize the multiple paths. Challenges: • Reduced Utilization • Scale-out vs Scale-up: per-port cost, cabling and packaging complexity, scalable cooling. • Placement, Air-Flow and rack-density • TCP Incast, Large Buffer switches • Resource fragmentation: VLANs • Manual Configuration • Oversubscription: 1:1 vs 1:240 • Flooding and Routing n/w overhead
- 8. Fat-Tree Based DC Architecture 1:1 Oversubscription ratio. Commodity Fat-tree with K=4 K-ary fat tree: three-layer topology (edge, aggregation and core) • each pod consists of (k/2)2 servers & 2 layers of k/2 k-port switches • each edge switch connects to k/2 servers & k/2 aggr. switches • each aggr. switch connects to k/2 edge & k/2 core switches • (k/2)2 core switches: each connects to k pods • i,e, (k/2)2 core switches for k2 pod switches and (k/2)2 servers.
- 9. Fat-Tree Based DC Architecture 1:1 Oversubscription ratio. Commodity Fat-tree with K=4 Advantages: •Full Bisection BW: 1:1 Oversubscription ratio •Low Cost: Commodity switches Disadvantage: •Scalability: Size of n/w dependent upon ports per switch.48 ports => maximum 27,648 hosts. •Agility and Performance Isolation: Not supported
- 10. Recursive DCN Architecture • A Level-0 subnet is the basic building block. It contains inter-connected servers. • Each level-k subnet has multiple level-(k-1) subnets. • Ex) DCell, BCube, 4-4 1-4, etc • Advantages: • Highly Scalable commodity n/w • Low CapEx and OpEx. • Disadvantage: • Cabling and packaging
- 11. Modular Data Centers (MDC) High density, shipping container based DCN. Should be Robust and provide Graceful Performance Degradation. Advantages:
- 12. Modular Data Centers (MDC) High density, shipping container based DCN. Should be Robust and provide Graceful Performance Degradation. Advantages: • Fast deployment • Lower costs • Increased efficiency • Easy scale-out
- 13. Virtualized DCN Added Issues: • Agility: Allocate any server to any service dynamically for performance isolation. • VM-migration across DCNs: No manual configuration. • Availability and Fault tolerance: Configuration of server IP addresses Solution: Separation of Location and Identity addresses. Ex) VL2, 4-4 1-4, etc Data Structure of Directory Packet tunneled through physical network using location-IP header
- 14. Typical Inter Server Communication in DC
- 15. Example: 4-4 1-4 DCN Fig: 4-4 1-4 Data Center • 4-4 1-4 is a location based forwarding architecture for DCN which utilizes IP-hierarchy. • Uses statically assigned, location based IP addresses for all network nodes. • Forwarding of packets is done by masking the destination IP address bits. • No routing or forwarding table maintained at switches • No convergence overhead of routing protocols. No. of physical machines in figure = 65,536
- 16. References • A. Kumar, S. V. Rao, and D. Goswami, “4-4, 1-4: Architecture for Data Center Network Based on IP Address Hierarchy for Efficient Routing," in Parallel and Distributed Computing (ISPDC), 2012 11th International Symposium on, 2012, pp. 235-242. • M. Al-Fares, A. Loukissas, and A. Vahdat, “A scalable, commodity data center network architecture," in Proceedings of the ACM SIGCOMM 2008 conference on Data communication, ser. SIGCOMM '08. New York, NY, USA: ACM, 2008, pp. 63-74.[Online]. Available: http://doi.acm.org/10.1145/1402958.1402967 • C. Guo, G. Lu, D. Li, H. Wu, X. Zhang, Y. Shi, C. Tian, Y. Zhang, and S. Lu, “Bcube:a high performance, server-centric network architecture for modular data centers.“ • T. Benson, A. Anand, A. Akella, and M. Zhang, “Understanding data center trac characteristics," SIGCOMM Comput. Commun. Rev., vol. 40, no. 1, pp. 92{99, Jan. 2010. [Online]. Available: http://doi.acm.org/10.1145/1672308.1672325 • A. Greenberg, J. Hamilton, D. A. Maltz, and P. Patel. “The cost of a cloud: research problems in data center networks.” SIGCOMM Comput. Commun. Rev.,39(1):68–73, 2009.