Caesar: high-speed and memory-efficient forwarding engine for future internet architecture

Moradi, Mehrdad; Qian, Feng; Xu, Qiang; Mao, Z. Morley; Bethea, Darrell; Reiter, Michael K.

doi:10.1109/ancs.2015.7110130

Cited by 13 publications

(7 citation statements)

References 27 publications

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“…If two network functions obviously rely on similar data structures, it is a natural decision for a consolidated design. For example, BUFFALO [44] and CAESAR [34] use Bloom filters for packet forwarding and Bloom filters are also key building blocks of the bSketch [50]. A co-located data structure based on Bloom filters can be designed similar to LuCS presented in Section 3.…”

Section: Systematical Design Methodologiesmentioning

confidence: 99%

“…These data structures include variants of cardinality-estimation sketches [4,6,19] and frequency-estimation sketches [9,12]. Meanwhile we have also noticed a line of research of applying other space-compact algorithms and data structures for network forwarding information base (FIB) [13,20,26,34,38,44,46,48,49] and load balancing [14,32,47]. These data structures include variants of Bloom filters [7], cuckoo hashing [36], Bloomier filters [10,11], and a recent design called Ludo hashing [38].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Don't Work on Individual Data Plane Algorithms. Put Them Together!

Qian

Shi

et al. 2020

Proceedings of the 19th ACM Workshop on Hot Topics in Networks

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Algorithms and data structures for data plane network functions have been extensively studied in the literature. Recently various compact data structures and algorithms have been used in data plane to achieve less memory cost and higher throughput. However, most of these studies only focus on individual network functions, such as packet forwarding information base (FIB), traffic measurement, and load balancing. To our knowledge, no study has been conducted to design compact data structures and algorithms for multiple and co-located network functions. We argue that there is a huge space of optimization if we design algorithms and data structures considering multiple co-located network functions, compared to designing them individually. It is because many of them share similar design goals and building blocks. We use two recently published methods as examples and present a new memory-compact design that serves both FIB and traffic measurement functions by a novel integration of the two methods. The preliminary results show that the new design can achieve almost 2x throughput compared to running them individually while achieving a higher accuracy of measurement using the same memory. In addition, we will discuss potential research directions and challenges. CCS CONCEPTS • Theory of computation → Sketching and sampling; Bloom filters and hashing; • Networks → Data path algorithms.

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Section: Systematical Design Methodologiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Don't Work on Individual Data Plane Algorithms. Put Them Together!

Qian

Shi

et al. 2020

Proceedings of the 19th ACM Workshop on Hot Topics in Networks

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“…3) Concise guarantees to return the correct forwarding actions for valid names. It is not probabilistic like those using Bloom filters [34], [22].…”

Section: ) Compared To Existing Fib Designs For Name Switchingmentioning

confidence: 99%

Memory-efficient and Ultra-fast Network Lookup and Forwarding using Othello Hashing

Belazzougui

Qian

et al. 2016

Preprint

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Network algorithms always prefer low memory cost and fast packet processing speed. Forwarding information base (FIB), as a typical network processing component, requires a scalable and memory-efficient algorithm to support fast lookups. In this paper, we present a new network algorithm, Othello Hashing, and its application of a FIB design called Concise, which uses very little memory to support ultra-fast lookups of network names. Othello Hashing and Concise make use of minimal perfect hashing and relies on the programmable network framework to support dynamic updates. Our conceptual contribution of Concise is to optimize the memory efficiency and query speed in the data plane and move the relatively complex construction and update components to the resource-rich control plane. We implemented Concise on three platforms. Experimental results show that Concise uses significantly smaller memory to achieve much faster query speed compared to existing solutions of network name lookups.

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“…The migration to IPv6 is not expected to mitigate the address space disaggregation problem [7]. The increasing memory requirement comes at a significant cost for ISPs [31], as this memory is expensive and power-hungry [21].…”

Section: Introductionmentioning

confidence: 99%

Online Aggregation of the Forwarding Information Base: Accounting for Locality and Churn

Bieńkowski

Sarrar

Schmid

et al. 2018

IEEE/ACM Trans. Networking

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This paper studies the problem of compressing the Forwarding Information Base (FIB), but taking a wider perspective. Indeed, FIB compression goes beyond sheer compression, as the gain in memory use obtained from the compression has consequences on the updates that will have to be applied to the compressed FIB. We are interested in the situation where forwarding rules can change over time, e.g., due to BGP route updates. Accordingly, we frame FIB compression as an online problem, and design competitive online algorithms to solve it. In contrast to prior work which mostly focused on static optimizations, we study an online variant of the problem where routes can change over time, and where the number of updates to the FIB are taken into account explicitly. The reason to consider this version of the problem is that leveraging temporal locality while accounting for the number of FIB updates helps to keep routers CPU load low and reduces the number of FIB updates to be transferred, e.g., from the network-attached Software-Defined Network (SDN) controller to a remote switch. This paper introduces a formal model which is an interesting generalization of several classic online aggregation problems. Our main contribution is an O(w)-competitive algorithm, where w is the length of an IP address. We also derive a lower bound which shows that our result is asymptotically optimal within a natural class of algorithms, based on so-called sticks.

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Caesar: high-speed and memory-efficient forwarding engine for future internet architecture

Cited by 13 publications

References 27 publications

Don't Work on Individual Data Plane Algorithms. Put Them Together!

Don't Work on Individual Data Plane Algorithms. Put Them Together!

Memory-efficient and Ultra-fast Network Lookup and Forwarding using Othello Hashing

Online Aggregation of the Forwarding Information Base: Accounting for Locality and Churn

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