Reducing router forwarding table size using aggregation and caching.

详细信息   

• 作者：Liu ; Yaoqing.
• 学历：Doctor
• 年：2013
• 毕业院校：The University of Memphis
• Department：Computer Science.
• ISBN：9781303825910
• CBH：3586725
• Country：USA
• 语种：English
• FileSize：3771799
• Pages：126

文摘

The fast growth of global routing table size has been causing concerns that the Forwarding Information Base FIB) will not be able to fit in existing routers expensive line-card memory,and upgrades will lead to a higher cost for network operators and customers. FIB Aggregation,a technique that merges multiple FIB entries into one,is probably the most practical solution since it is a software solution local to a router,and does not require any changes to routing protocols or network operations. While previous work on FIB aggregation mostly focuses on reducing table size,this work focuses on algorithms that can update compressed FIBs quickly and incrementally. Quick updates are critical to routers because they have very limited time to process routing updates without impacting packet delivery performance. We have designed three algorithms: FIFA-S for the smallest table size,FIFA-T for the shortest running time,and FIFA-H for both small tables and short running time,and operators can use the one best suited to their needs. These algorithms significantly improve over existing work in terms of reducing routers computation overhead and limiting impact on the forwarding plane while maintaining a good compression ratio. Another potential solution is to install only the most popular FIB entries into the fast memory i.e.,an FIB cache),while storing the complete FIB in slow memory. In this paper,we propose an effective FIB caching scheme that achieves a considerably higher hit ratio than previous approaches while preventing the cache-hiding problem. Our experimental results using data traffic from a regional network show that with only 20K prefixes in the cache 5.36% of the actual FIB size),the hit ratio of our scheme is higher than 99.95%. Our scheme can also efficiently handle cache misses,cache replacement and routing updates.