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Jerome Tollet

dblp:203/0760 · DBLP profile ↗
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5ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0001-5659-9161ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 4 · 1 since 2021Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
2 papers
Internet architecture and protocols · 56% Routing and switching · 28% Datacenter networks · 17%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet architecture and protocols › packet processing
packet classification
0.412019
TupleMerge: Fast Software Packet Processing for Online Packet Classification · IEEE/ACM Trans. Netw. 2019
Internet architecture and protocols › packet processing › packet classification
tuple space search
0.412019
TupleMerge: Fast Software Packet Processing for Online Packet Classification · IEEE/ACM Trans. Netw. 2019
Internet architecture and protocols › overlay networks
application-aware routing
0.312018
6LB: Scalable and Application-Aware Load Balancing with Segment Routing · IEEE/ACM Trans. Netw. 2018
Datacenter networks
load balancing
0.312018
6LB: Scalable and Application-Aware Load Balancing with Segment Routing · IEEE/ACM Trans. Netw. 2018
Routing and switching › source routing
segment routing
0.312018
6LB: Scalable and Application-Aware Load Balancing with Segment Routing · IEEE/ACM Trans. Netw. 2018
Routing and switching › router architecture
software router
0.112019
TupleMerge: Fast Software Packet Processing for Online Packet Classification · IEEE/ACM Trans. Netw. 2019
Routing and switching
traffic engineering
0.112018
6LB: Scalable and Application-Aware Load Balancing with Segment Routing · IEEE/ACM Trans. Netw. 2018

Methods — techniques the papers use, named apart from their topics

tuple space search · 0.4hash table · 0.4segment routing · 0.3
YearPublicationVenuePosition
2021 FlowFight: High performance-low memory top-k spreader detection
Valerio Bruschi, Salvatore Pontarelli, Jerome Tollet, David Barach, Giuseppe Bianchi 0001
Comput. Networks3
2020 Multi-Cloud Chaining with Segment Routing
Francesco Spinelli, Luigi Iannone, Jerome Tollet
Networking3
2019 TupleMerge: Fast Software Packet Processing for Online Packet Classification
abstract
Packet classification is an important part of many networking devices, such as routers and firewalls. Software-defined networking (SDN) heavily relies on online packet classification which must efficiently process two different streams: incoming packets to classify and rules to update. This rules out many offline packet classification algorithms that do not support fast updates. We propose a novel online classification algorithm, TupleMerge (TM), derived from tuple space search (TSS), the packet classifier used by Open vSwitch (OVS). TM improves upon TSS by combining hash tables which contain rules with similar characteristics. This greatly reduces classification time preserving similar performance in updates. We validate the effectiveness of TM using both simulation and deployment in a full-fledged software router, specifically within the vector packet processor (VPP). In our simulation results, which focus solely on the efficiency of the classification algorithm, we demonstrate that TM outperforms all other state of the art methods, including TSS, PartitionSort (PS), and SAX-PAC. For example, TM is 34% faster at classifying packets and 30% faster at updating rules than PS. We then experimentally evaluate TM deployed within the VPP framework comparing TM against linear search and TSS, and also against TSS within the OVS framework. This validation of deployed implementations is important as SDN frameworks have several optimizations such as caches that may minimize the influence of a classification algorithm. Our experimental results clearly validate the effectiveness of TM. VPP TM classifies packets nearly two orders of magnitude faster than VPP TSS and at least one order of magnitude faster than OVS TSS.
James Daly, Valerio Bruschi, Leonardo Linguaglossa, Salvatore Pontarelli, Dario Rossi 0001, Jerome Tollet, Eric Torng, Andrew Yourtchenko
IEEE/ACM Trans. Netw.6
2018 6LB: Scalable and Application-Aware Load Balancing with Segment Routing
Yoann Desmouceaux, Pierre Pfister, Jerome Tollet, W. Mark Townsley, Thomas H. Clausen
IEEE/ACM Trans. Netw.3
2017 SRLB: The Power of Choices in Load Balancing with Segment Routing
abstract
Network load-balancers generally either do not take application state into account, or do so at the cost of a centralized monitoring system. This paper introduces a load-balancer running exclusively within the IP forwarding plane, i.e. in an application protocol agnostic fashion - yet which still provides application-awareness and makes real-time, decentralized decisions. To that end, IPv6 Segment Routing is used to direct data packets from a new flow through a chain of candidate servers, until one decides to accept the connection, based on its local state. This way, applications themselves naturally decide on how to share incoming connections, while incurring minimal network overhead, and no out-of-band signaling. Tests on different workloads - including realistic workloads such as replaying actual Wikipedia access traffic towards a set of replica Wikipedia instances - show significant performance benefits, in terms of shorter response times, when compared to a traditional random load-balancer.
Yoann Desmouceaux, Pierre Pfister, Jerome Tollet, W. Mark Townsley, Thomas H. Clausen
ICDCS3