标题：Optimizing Routing Rules Space through Traffic Engineering Based on Ant Colony Algorithm in Software Defined Network
作者：Gao, Chuangen; Wang, Hua; Zhai, Linbo; Yi, Shanwen; Yao, Xibo
作者机构：[Gao, Chuangen; Wang, Hua; Zhai, Linbo; Yi, Shanwen; Yao, Xibo] Shandong Univ, Sch Comp Sci & Technol, Jinan, Peoples R China.
会议名称：28th IEEE International Conference on Tools with Artificial Intelligence (ICTAI)
会议日期：NOV 06-08, 2016
来源：2016 IEEE 28TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2016)
关键词：routing rule; traffic engineering; ant colony optimization; software; defined network
摘要：Software Defined Network (SDN) has been envisioned as the next generation network infrastructure, which simplify network management by decoupling the control plane and data plane. It is becoming the leading technology behind many traffic engineering solutions, since it allows a central controller to globally plan the paths of the flows. However, Ternary Content Addressable Memory (TCAM), as a critical hardware storing rules in SDN-enabled devices, can be supplied to each device with very limited quantity because it is expensive and energy-consuming. To efficiently use TCAM resources, we address the routing rule space occupation problem for multiple unicast sessions with Quality-of-Service (QoS) constraints. To our best knowledge, this is the first work to joint routing rule optimization with traffic engineering for multipath flows. We formulate the problem using Mixed Integer Linear Programing (MILP) and propose an approach based on ant colony algorithm to solve it. Finally, we evaluate the expected performance of our proposed algorithm through a simulation study.