Flow table is a fundamental and critical component in network data plane. Numerous algorithms and architectures have been devised for efficient flow table construction, lookup, and update. The diversity of flow tables and the difficulty to acquire real data sets make it challenging to give a fair and confident evaluation to a design. In the past, researchers rely on ClassBench and its improvements to synthesize flow tables, which become inadequate for today’s networks. In this paper, we present a new flow table benchmark tool, FlowBench. Based on a novel design methodology, FlowBench can generate large-scale flow tables with arbitrary combination of matching types and fields in a short time, and yet keep accurate characteristics to reveal the real performance of the algorithms under evaluation. The open-source tool facilitates researchers to evaluate both existing and future algorithms with unprecedented flexibility.

No abstract available.

The fast path, as the cache of exact-match rules in the slow path, is applied in software-based OpenFlow switches to improve the forwarding performance. A microflow in the fast path is the specification of its corresponding rules in the slow path, i.e., every field is explicit in a microflow. A rule can generate multiple microflows in the fast path, and a microflow can be generated from multiple rules since there are multiple flow tables in an OpenFlow switch. Due to the many-to-many mapping relationship between the microflows and the rules, the update consistency between the slow path and the fast path becomes a big challenge in software switches, e.g., Open vSwitch (OVS). In this paper, we propose a cache-based scheme (named FlowShadow) to achieve high update performance while keeping update consistency in OVS. In order to examine the reliability, validity, utility and scalability of FlowShadow, we implement FlowShadow on the OVS and conduct numerous experiments with different settings to measure the performance of FlowShadow. The experimental results demonstrate that FlowShadow achieves a lookup speed of 75 million packets per second on a commodity PC under the real backbone traces; the system with FlowShadow speeds up 3.4× times of the original OVS; and FlowShadow also shows high update performance and good scalability at different update speeds and with different numbers of flow tables.

As the network infrastructure has been consuming more and more power, various schemes have been proposed to improve the power efficiency of network devices. Many schemes put links to sleep when idle and wake them up when needed. A presumption in these schemes, though, is that router's line cards can be waken up very quickly. However, through systematic measurement of a major vendor's high-end routers, we find that it takes minutes to get a line card ready under the current design. To address this issue, we propose a new line card design that 1) keeps the host processor in a line card standby, which only consumes a small fraction of power but will save considerable wakeup time, and 2) downloads a slim slot of popular prefixes with higher priority, so that the line card will be ready for forwarding most of the traffic much earlier. We design algorithms as well as architecture that ensure fast and correct longest prefix match during prioritized routing prefix download. Experiments on an FPGA-based prototype show that the customized hardware can be ready to forward packets in 127.27 ms, which is 0.3% of the time the original design takes. This can better support numerous power-saving schemes based on the sleep/wakeup mechanism.

Updating rules in the flow tables of SDN switches are complex and time-consuming. Therefore, we propose a cache-based scheme (named FlowShadow) to improve the packet processing performance and keep continuous operating while updating rules in the flow tables. FlowShadow caches the microflows in the hash table to build a fast path for packet processing. By leveraging the Action Table, FlowShadow achieves update consistency and good update performance. In order to examine the reliability, validity, utility and scalability of FlowShadow, we implement FlowShadow on the Open VSwitch and conduct numerous experiments with different settings to measure the performance of FlowShadow. The experimental results demonstrate that FlowShadow achieves a lookup speed of 75 million packets per second on a commodity PC under the real backbone traces; the system with FlowShadow speeds up 3.4× times of the original Open VSwitch.

As the network infrastructure has been consuming more and more power, various schemes have been proposed to improve power efficiency of network devices. Many schemes put links to sleep when idle and wake them up when needed. A presumption in these schemes, though, is that router's line cards can be waken up quickly. However, through systematic measurement of a major vender's high-end router, we find that it takes minutes to get a line card ready under the current implementation. To address this issue, we propose a new line card design that (1) keeps the host processor in a line card always up, which only consumes a small fraction of power, and (2) downloads a slim slot of popular prefixes with higher priority, so that the line card will be ready for forwarding most of the traffic much earlier. We design algorithms that ensure fast and correct longest prefix match lookup during prioritized routing prefix download. Experiments on real hardware show that the wakeup time can be reduced to 127.27ms, which is 0.3% of the original line card wakeup time, well supporting many power-saving schemes.

Complex name constitution plus huge-sized name routing table makes wire speed name lookup a challenging task in Named Data Networking. To overcome this challenge, we propose two techniques to significantly speed up the lookup process. First, we look up name prefixes in an order based on the distribution of prefix length in the forwarding table, which can find the longest match much faster than the linear search of current prototype CCNx. The search order can be dynamically adjusted as the forwarding table changes. Second, we propose a new near-perfect hash table data structure that combines many small sparse perfect hash tables into a larger dense one while keeping the worst-case access time of O(1) and supporting fast update. Also the hash table stores the signature of a key instead of the key itself, which further improves lookup speed and reduces memory use.

Content-centric Networking (CCN) and the later proposed Named Data Networking (NDN) have attracted wide attention in both academia and industry, as the clean slate future Internet architecture. Wire speed name lookup for packet forwarding is one of the most challenging tasks in CCN/NDN. As a promising technology, its feasibilities including reachable speed, scalability, and update performance are imperative to be deeply evaluated. However, CCN/NDN is currently on its initial stage and no actual network is deployed, which means no real name routing tables and NDN traffic are available. In order to fulfill performance comparisons among various innovative name lookup solutions and facilitate future name lookup researches, we present NDNBench, a publicly available platform for evaluation, comparison and experiments with different name lookup approaches. NDNBench can generate various Forwarding Information Bases (FIBs), traces with structure and size diversity to conduct the tests thoroughly by adjusting the parameters. NDNBench provides a simulation package tool with flexibility to evaluate various name lookup approaches. Furthermore, in order to verify the effectiveness of NDNBench, we benchmark some existing name lookup schemes and the results are very supportive. NDNBench has been applied to recent work and is publicly available at the following site: http://s-router.cs.tsinghua.edu.cn/∼zhangting/.

In this paper we design, implement and evaluate NameFilter, a two-stage Bloom filter-based scheme for Named Data Networking name lookup, in which the first stage determines the length of a name prefix, and the second stage looks up the prefix in a narrowed group of Bloom filters based on the results from the first stage. Moreover, we optimize the hash value calculation of name strings, as well as the data structure to store multiple Bloom filters, which significantly reduces the memory access times compared with that of non-optimized Bloom filters. We conduct extensive experiments on a commodity server to test NameFilter's throughput, memory occupation, name update as well as scalability. Evaluation results on a name prefix table with 10M entries show that our proposed scheme achieves lookup throughput of 37 million searches per second at low memory cost of only 234.27 MB, which means 12 times speedup and 77% memory savings compared to the traditional character trie structure. The results also demonstrate that NameFilter can achieve 3M per second incremental updates and exhibit good scalability to large-scale prefix tables.

Different from the IP-based routers, Named Data Networking routers forward packets by content names, which consist of characters and have variable and unbounded length. This kind of complex name constitution plus the huge-sized name routing table makes wire speed name lookup an extremely challenging task. Greedy name lookup mechanism is proposed to speed up name lookup by dynamically adjusting the search path against the changes of the prefix table. Meanwhile, we elaborate a string-oriented perfect hash table to reduce memory consumption which stores the signature of the key in the entry instead of the key itself. Extensive experimental results on a commodity PC server with 3 million name prefix entries demonstrate that greedy name lookup mechanism achieves 57.14 million searches per second using only 72.95 MB memory.

The size of routing tables has been growing rapidly, while the link transmission speed of Internet backbone has increased up to 100Gbps commercially and towards 400Gbps Ethernet for laboratory experiments. In order to alleviate the pressure from both the huge large routing table and very high interface speed, ISPs are trying to find ways to compress the table while striving to design a more powerful lookup engine. To address this issue, we propose an algorithm, named Optimal Non-overlap Routing Table Constructor (ONRTC), to compute an equivalent routing table with a minimal number of prefixes under the constraint that all the prefixes are not overlapped. Experimental evaluations show that, for large backbone routing tables, the ONRTC algorithm requires only about 71% of the original number of prefixes. We release ONRTC's source code in [10].

With the fast development of Internet, the size of routing tables in the backbone routers keeps a rapid growth in recent years. An effective solution to control the memory occupation of the ever-increased huge routing table is the Forwarding Information Base (FIB) compression. Existing optimal FIB compression algorithm ORTC suffers from high computational complexity and poor update performance, due to the loss of essential structure information during its compression process. To address this problem, we present two suboptimal FIB compression algorithms — EAR-fast and EAR-slow, respectively, based on our proposed Election and Representative (EAR) algorithm which is an optimal FIB compression algorithm. The two suboptimal algorithms preserve the structure information, and support fast incremental updates while reducing computational complexity. Experiments on an 18-month real data set show that compared with ORTC, the proposed EAR-fast algorithm requires only 9.8% compression time and 37.7% memory space, but supports faster update while prolonging the recompression interval remarkably. All these performance advantages come at a cost of merely a 1.5% loss in compression ratio compared with the theoretical optimal ratio.