Forwarding Information Base Aggregation Research Articles

On the aggregation of FIBs at ICN routers using routing strategy

Utilizing in-network caching is essential for the current communication network. In the last decade, ICN (Information-Centric Networking) has been under the spotlight as a network that mainly focuses on transmitted and received data rather than on hosts that transmit and receive data. In ICNs, to appropriately forward request packets, a router maintains a routing table called FIB (Forwarding Information Base). However, it is unsuitable for us to assume that FIB can store entries of all contents within a network. This is mainly because the FIB memory is not large enough to store the prefix of all contents. Thus, for realizing global-scale ICNs, it is crucial to develop an effective technique to reduce the size of FIB. In this paper, to tackle the reduction in the FIB size with the aggregation, we propose a routing strategy called constrained shortest-path tree (CSPT) routing. The fundamental idea of our CSPT routing is to combine shortest-paths on the network and that on a shortest-path tree of the network, which is intended to enhance the effect of FIB aggregation. Furthermore, we extensively investigate the relationship, i.e., trade-off, between the FIB aggregation and the communication performance of ICN using CSPT routing. Consequently, we reveal that our CSPT routing can dramatically reduce the number of FIB entries while suppressing the increase in the number of hops required to deliver request packets.

VeriTable: Fast equivalence verification of multiple large forwarding tables

Due to network practices such as traffic engineering and multi-homing, the number of routes, also known as IP prefixes, in the global forwarding tables has been increasing significantly in the last decade and continues growing in a super linear trend. One of the most promising solutions is to use Forwarding Information Base (FIB) aggregation algorithms with incremental handling of BGP updates. FIB aggregation compresses the forwarding tables by reducing the number of prefixes in an FIB. Obviously, FIB aggregation should preserve the forwarding behavior of the data plane, i.e., packets must be forwarded in the same directions as if the original FIB is applied. Failures at the control plane or an incorrect algorithm may violate this rule. Thus we pose a research question, how can we efficiently verify that the original table achieves the same forwarding behavior for a router as the aggregated one? This paper proposes VeriTable, an algorithm that addresses the problem of verification of the equivalence of forwarding tables and the challenges caused by the Longest Prefix Matching (LPM) lookups. VeriTable employs a single tree traversal to quickly check if multiple forwarding tables are equivalent, as well as if they result in network ”black-holes”. VeriTable algorithm significantly outperforms the state-of-the-art work for both IPv4 and IPv6 tables in terms of the total running time, memory access times and memory consumption.

Scale the Internet routing table by generalized next hops of strict partial order

The Internet routing tables have been expanding at a dramatic and increasing rate. Although the latest high-performance routers provide enough capacities, Internet Service Providers (ISPs) cannot afford to upgrade their routers at the pace of routing table growth. Shrinking the routing table, especially the TCAM-based Forwarding Information Base (FIB), is more feasible. In this paper, we propose a scheme to aggregate the FIB based on generalized next hops of strict partial order (SPO). We first use generalized SPO next hops to construct the Nexthop-Selectable FIB (NSFIB), where each prefix has multiple next hops. Our NSFIB aggregation avoids the aggregation performance degrading with the network density increasing, which is one main defect of the traditional single-nexthop FIB aggregation. We then design different levels of aggregation algorithms to aggregate the NSFIB. Besides, we control the path stretch by setting an upper limit to filter bad next hops. We also introduce routing protection by the pre-computed SPO next hops. According to our simulation, our aggregation algorithms shrink the FIB to 5–15%, compared with 20–60% of single-nexthop FIB aggregation algorithms; our method works very well in controlling the path stretch; and SPO next hops protect 50–95% (topology-related) failure-affected packets.

N-FIB: Scalable, memory efficient name-based forwarding

Named Data Networking (NDN) is a promising future Internet which retrieves the content using their names. Content names composed of strings separated by ‘/’ are stored in the NDN Forwarding Information Base (FIB) to forward the incoming packets further. Though NDN has several benefits over traditional IP-based Internet, storing names instead of IP addresses has two major bottlenecks. While it consumes significantly large memory, it incurs higher search and update time. Another issue is the fast growth of routing table size through which FIB will not fit in existing routers’ line-card memory. Moreover, frequent updates to the FIB can degrade the packet delivery performance. In this paper, we propose a scalable and memory efficient Patricia trie based name forwarding scheme (called, N-FIB) for FIB. N-FIB supports FIB aggregation to significantly minimize the impact of large FIB size and high FIB update cost. Extensive experiment results show that the N-FIB scheme can reduce memory consumption by 68.18% compared to the BP scheme for 29 million named dataset. Moreover, N-FIB is reducing routers’ computation and memory overhead, while supporting strong forwarding correctness.

Nexthop-Selectable FIB aggregation: An instant approach for internet routing scalability

Recently, the core net routing table is growing at an alarming speed which has become a major concern to Internet Service Providers. One effective solution is Forwarding Information Base (FIB) aggregation. All the previous studies assume every prefix has only one next hop. In this paper, we argue that a packet can be delivered to its destination by multiple selectable next hops. Based on this observation, we propose Nexthop-Selectable FIB aggregation. Prefixes, including those which originally have different next hops, are aggregated if they share one common next hop.We provide a systematic study on this Nexthop-Selectable FIB aggregation problem. We present several practical choices to build selectable next hops for prefixes. We propose a non-trivial O(N) algorithm to optimally solve the problem. We then study a generalized problem where we assign weights for different next hops to bound path stretch. We further develop an optimal incremental updating algorithm with constant running time. We evaluate our algorithms through a comprehensive set of simulations with BRITE and real world topologies. Our evaluation shows that the aggregated FIB is one order of magnitude smaller than the original one.

Catching popular prefixes at AS border routers with a prediction based method

Modern Internet routers require powerful forwarding facilities to cope with extremely high rate Forwarding Information Base (FIB) lookups. In general, the FIB is constrained to a small highly efficient but expensive memory. Unfortunately, the BGP route table (RIB) keeps increasing, and this subsequently results in severe FIB inflation at BGP routers. What if we only load a small portion of the RIB into the FIB? Recently the route caching mechanism has been revisited. With such a route caching mechanism, the optimal method is to load in a FIB with popular prefixes which contribute major traffic loads. We propose a prediction based method to catch those popular prefixes with a limited cache size. In this paper, the dynamics of popular prefixes has been studied based on real traffic traces from different ISPs. On applying a GM(1,1) model which is widely applied in grey system control and prediction, we propose a traffic prediction-based route caching method which attempts to bias the cache dump strategy with a range of history to ameliorate the effects of bursts from non-popular prefixes. We also suggest applying FIB aggregation techniques, e.g. Optimal Routing Table Constructor (ORTC) algorithm, to suppress the number of non-popular sub-prefixes of the popular prefixes on route updates. The evaluation of our method is based on simulation over real traffic traces. The simulation shows our prediction-based cache replacement strategy outperforms other cache strategies and matches Internet traffic dynamics very well.