Data Centre Optimisation – Scalable Infrastructure for Big Data

@article{9130915,
title = {High-Accuracy Packet Pacing on Commodity Servers for Constant-Rate Flows},
author = {Mohammed Hawari and Juan Antonio Cordero and Thomas Clausen},
url = {https://www.thomasclausen.net/wp-content/uploads/2020/08/2020-IEEE-TNET-High-Accuracy-Packet-Pacing-on-Commodity-Servers-for-Constant-Rate-Flows.pdf},
doi = {10.1109/TNET.2020.3001672},
issn = {1558-2566},
year = {2020},
date = {2020-01-01},
journal = {IEEE/ACM Transactions on Networking},
pages = {1-15},
abstract = {This addresses the problem of high-quality packet pacing for constant-rate packet consumption systems, with strict buffering limitations. A mostly-software pacing architecture is developed, which has minimal hardware requirements, satisfied by commodity servers - rendering the proposed solution easily deployable in existing (data-centre) infrastructures. Two algorithms (free-running and frequency-controlled pacing, for explicitly and implicitly indicated target rates, respectively) are specified, and formally analysed. The proposed solution, including both algorithms, is implemented, and is tested on real hardware and under real conditions. The performance of these implementations is experimentally evaluated and compared to existing mechanisms, available in general-purpose hardware. Results of both exhaustive experiments, and of an analytical modeling, indicate that the proposed approach is able to perform low-jitter packet pacing on commodity hardware, being thus suitable for constant rate transmission and consumption in media production scenarios.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Desmouceaux2018a,
title = {Flow-Aware Workload Migration in Data Centers},
author = {Yoann Desmouceaux and Sonia Toubaline and Thomas Clausen},
url = {https://link.springer.com/epdf/10.1007/s10922-018-9452-5?author_access_token=qm_40d91CsNLlZ_vZ0tZFPe4RwlQNchNByi7wbcMAY4xSrvbLplDMLQ3AN9vWEoUIxtZAIdnOGAzJH5W3YOrbGteOLvaEXsEE1xFv66lVxTKlL40BAS25fsaLf8w1RJAvY69owHWqhJkTmAZpvdCkQ%3D%3D
https://www.epizeuxis.net/wp-content/uploads/2018/03/jons-2018.pdf},
doi = {10.1007/s10922-018-9452-5},
year = {2018},
date = {2018-03-10},
journal = {Springer - Journal of Network and Systems Management (JONS)},
abstract = {In data centers, subject to workloads with heterogeneous (and sometimes short) lifetimes, workload migration is a way of attaining a more efficient utilization of the underlying physical machines.
To not introduce performance degradation, such workload migration must take into account not only machine resources, and per-task resource requirements, but also application dependencies in terms of network communication.

This articleformat presents a workload migration model capturing all of these constraints.
A linear programming framework is developed allowing accurate representation of per-task resources requirements and inter-task network demands. Using this, a multi-objective problem is formulated to compute a re-allocation of tasks that (i) maximizes the total inter-task throughput, while (ii) minimizing the cost incurred by migration and (iii) allocating the maximum number of new tasks.

A baseline algorithm, solving this multi-objective problem using the $epsilon$-constraint method is proposed, in order to generate the set of Pareto-optimal solutions. As this algorithm is compute-intensive for large topologies, a heuristic, which computes an approximation of the Pareto front, is then developed, and evaluated on different topologies and with different machine load factors. These evaluations show that the heuristic can provide close-to-optimal solutions, while reducing the solving time by one to two order of magnitudes.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Desmouceaux2018,
title = {6LB: Scalable and Application-Aware Load Balancing with Segment Routing},
author = {Yoann Desmouceaux and Pierre Pfister and Jérôme Tollet and W. Mark Townsley and Thomas Clausen},
url = {http://www.thomasclausen.net/wp-content/uploads/2018/02/2018-IEEE-Transactions-on-Networking-6LB-Scalable-and-Application-Aware-Load-Balancing-with-Segment-Routing.pdf},
doi = {10.1109/TNET.2018.2799242},
issn = {1063-6692},
year = {2018},
date = {2018-02-15},
journal = {IEEE/ACM Transactions on Networking},
volume = {26},
number = {2},
pages = {819-834},
abstract = {Network load-balancers generally either do not take application state into account, or do so at the cost of a central- ized 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 deci- sions. 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 solely on its local state. This way, applications themselves naturally decide on how to fairly share incoming connections, while incurring minimal network overhead, and no out-of-band signaling. A consistent hashing algorithm, as well as an in-band stickiness protocol, allow for the proposed solution to be able to be reliably distributed across a large number of instances.
Performance evaluation by means of an analytical model and actual tests on different workloads (including a Wikipedia replay as a realistic workload) show significant performance benefits in terms of shorter response times, when compared to a traditional random load-balancer. In addition, this paper introduces and compares kernel bypass high-performance implementations of both 6LB and a state-of-the-art load-balancer, showing that the significant system-level benefits of 6LB are achievable with a negligible data-path CPU overhead.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}