A Hybrid Framework for TCP Incast Congestion Control in Data Center Networks
K. Arun Selvi1, K. Kumar2, K. Ramalakshmi3, A. Sathiya4
1Ms. K. Arun Selvi is Currently Working as an Assistant Professor With the Computer Science and Engineering Department, National Engineering College, Kovilpatti-628 503, (Tamil Nadu), India.
2Dr. K. Kumar is Currently Working as an Assistant Professor with the Computer Science and Engineering Department, Government College of Technology, Coimbatore-641 013, (Tamil Nadu), India.
3Ms.K. Ramalakshmi is Currently Working as an Assistant Professor With the Computer Science and Engineering Department, National Engineering College, Kovilpatti-628 503, (Tamil Nadu), India.
4Ms. A. Sathiya is Currently Working as an Assistant Professor With the Computer Science and Engineering Department, National Engineering College, Kovilpatti-628 503, (Tamil Nadu), India.
Manuscript received on 16 March 2019 | Revised Manuscript received on 21 March 2019 | Manuscript published on 30 July 2019 | PP: 798-806 | Volume-8 Issue-2, July 2019 | Retrieval Number: F2701037619/19©BEIESP | DOI: 10.35940/ijrte.F2701.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Cloud data centers with large bandwidth and low latency networks experiences many-to-one traffic pattern called TCP-incast. It occurs in the partition-aggregate architecture and causes emergence congestion at the network wharfconnected to the parent server, overcoming the port emergence buffer. The ending packet loss requires nodes to encounter loss, retransmit data and slowly rise up throughput per definitive TCP behavior. This paper proposes Receiver-oriented Congestion Control with Edge computing approach (RCCE) for enhancing the speed, nature and firmness of traffic performance. Receiver-oriented Congestion Control (RCC) combines both closed and open loop congestion controls at receiverwhereas edge computing involves localization of traffic management in the middle-tier aggregator for reducing Flow Completion Times (FCT) and latency for the entire application processing deployments. In addition, the centralized controller at the edge balances the load during incast by using spanning trees in a well-made manner by implementing multi-stage Clos networks. The entire prototype is implemented in ns3 and simulation results demonstrates that RCCE has an average decrease of 60.2 % in the 99th percentage latency and 50.4 % of mean queue size in the heavy traffic over TCP.
Index Terms: Edge Computing, Data Center Networks, Incast, Receiver-Oriented Congestion Control, TCP.
Scope of the Article: Data Mining