Mind the Gap

Humphries, Jack Tigar; Kaffes, Kostis; Mazières, David; Kozyrakis, Christos

doi:10.1145/3365609.3365856

Cited by 18 publications

(2 citation statements)

References 14 publications

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“…Beyond our algorithm in Section 5, there exist many methods for DC-internal traffic steering, such as [27,30,35,37]. As a solution for Internet traffic steering, the solution in [31] was designed for service function chaining scenarios but can be applied for ingress-based scheduling, very much like the work in [40], although the former merely applies site-local load balancing, while the latter requires regular metric signalling to ingress points, incurring significant routing costs.…”

Section: Related Workmentioning

confidence: 99%

On-path vs off-path traffic steering, that is the question

Khandaker

Trossen

Yang

et al. 2022

Proceedings of the ACM SIGCOMM Workshop on Future of Internet Routing &Amp; Addressing

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Service-level traffic steering in the Internet has been using an indirection-based model for decades now, using the DNS to resolve a name to a locator, often complemented with load balancing techniques. Contrasting this off-path realization, service information as part of the data packet itself may determine the one of possibly many communication endpoints on-path while traversing the network. This paper compares both design choices regardless of the specific decision mechanism used. For this, we assume a compute-aware traffic steering mechanism for both approaches and determine latency penalties through off-path resolution steps as well as distributing scheduling decisions to on-path network ingress points. Lastly, we investigate latency variances and resilience in an AR/VR scenario.

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Section: Related Workmentioning

confidence: 99%

On-path vs off-path traffic steering, that is the question

Khandaker

Trossen

Yang

et al. 2022

Proceedings of the ACM SIGCOMM Workshop on Future of Internet Routing &Amp; Addressing

View full text Add to dashboard Cite

show abstract

“…Although we implement C-4 over the NeBuLa architecture, our design could be implemented over a variety of baselines (e.g., NanoPU [39], FlexNIC [52], or NICA [26]). Due to the unique challenges of µs-scale RPCs that characterize KVS, several proposals pursue synchronization-free RPC load balancing [17,38,45,54,62,77,83,93]. C-4 is orthogonal to these works because none of them can relax the restrictions that writes impose on load balancing.…”

Section: Concurrency and Synchronizationmentioning

confidence: 99%

Cooperative Concurrency Control for Write-Intensive Key-Value Workloads

Sutherland

Falsafi

Daglis

2022

Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems,

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Key-Value Stores (KVS) are foundational infrastructure components for online services. Due to their latency-critical nature, today's best-performing KVS contain a plethora of full-stack optimizations commonly targeting read-mostly, popularity-skewed workloads. Motivated by production studies showing the increased prevalence of write-intensive workloads, we break down the KVS workload space into four distinct classes, and argue that current designs are only sufficient for two of them. The reason is that KVS concurrency control protocols expose a fundamental tradeoff: avoiding synchronization by partitioning writes across threads is mandatory for high throughput, but necessarily creates load imbalance that grows with core count and write fraction. We break this tradeoff with C-4, a codesign between NIC hardware and KVS software that judiciously separates write requests into two classes: independent ones that can be balanced across threads, and dependent ones which must be queued. C-4 dynamically partitions independent writes with the NIC to increase the load balancing flexibility of current KVS designs, and adds a software layer to the KVS to compact dependent writes into batches. Our evaluation shows that for write-intensive workloads, C-4 reduces 99th% tail latency by 1.3 − 5× and improves throughput by up to 1.7×. CCS CONCEPTS• Hardware → Networking hardware; • Computer systems organization → Multicore architectures; Client-server architectures; • Networks → Network servers.

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Differentiating Network Flows for Priority-Aware Scheduling of Incoming Packets in Real-Time IoT Systems

Blumschein

Behnke

Thamsen

et al. 2022

2022 IEEE 25th International Symposium on Real-Time Distributed Computing (ISORC)

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When IP-packet processing is unconditionally carried out on behalf of an Operating System kernel thread, processing systems can experience overload in high incoming traffic scenarios. This is especially worrying for embedded realtime devices controlling their physical environment in industrial IoT scenarios and automotive systems.We propose an embedded real-time aware IP stack adaption with an early demultiplexing scheme for incoming packets and subsequent per-flow aperiodic scheduling. By instrumenting existing embedded IP stacks, rigid prioritization with minimal latency is deployed without the need of further task resources. Simple mitigation techniques can be applied to individual flows, causing hardly measurable overhead while at the same time protecting the system from overload conditions. Our IP stack adaption is able to reduce the low-priority packet processing time by over 86% compared to an unmodified stack. The network subsystem can thereby remain active at a 7x higher general traffic load before disabling the receive IRQ as a last resort to assure deadlines.Index Terms-embedded systems, real-time operating systems, embedded IP stack, internet of things, cyber-physical systems• Protection against network-induced system overloads, facilitating real-time systems. • Optimal processing latency for well-behaved High Priority flows. • Best-effort performance for Low Priority flows. The paper also introduces a prototypical implementation modifying a popular network stack and presents a set of experiments that evaluate basic performance properties.

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Mind the Gap

Cited by 18 publications

References 14 publications

On-path vs off-path traffic steering, that is the question

On-path vs off-path traffic steering, that is the question

Cooperative Concurrency Control for Write-Intensive Key-Value Workloads

Differentiating Network Flows for Priority-Aware Scheduling of Incoming Packets in Real-Time IoT Systems

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