Sundial

Yu, Xiangyao; Xia, Yu; Pavlo, Andrew; Sánchez, Daniel; Rudolph, Larry; Devadas, Srinivas

doi:10.14778/3231751.3231763

Cited by 26 publications

(2 citation statements)

References 44 publications

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“…Distributed systems suffer from two major bottlenecks related to ACP [32,62]. First, the long coordinator-side delay prolongs the latency of distributed transactions.…”

Section: Flac Ff For Failure-free Environmentmentioning

confidence: 99%

FLAC: Practical Failure-Aware Atomic Commit Protocol for Distributed Transactions

Pan¹,

Ta²,

Zhang³

et al. 2023

Preprint

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In distributed transaction processing, atomic commit protocol (ACP) is used to ensure database consistency. With the use of commodity compute nodes and networks, failures such as system crashes and network partitioning are common. It is therefore important for ACP to dynamically adapt to the operating condition for efficiency while ensuring the consistency of the database. Existing ACPs often assume stable operating conditions, hence, they are either nongeneralizable to different environments or slow in practice.In this paper, we propose a novel and practical ACP, called Failure-Aware Atomic Commit (FLAC). In essence, FLAC includes three protocols, which are specifically designed for three different environments: (i) no failure occurs, (ii) participant nodes might crash but there is no delayed connection, or (iii) both crashed nodes and delayed connection can occur. It models these environments as the failure-free, crash-failure, and network-failure robustness levels. During its operation, FLAC can monitor if any failure occurs and dynamically switch to operate the most suitable protocol, using a robustness level state machine, whose parameters are finetuned by reinforcement learning. Consequently, it improves both the response time and throughput, and effectively handles nodes distributed across the Internet where crash and network failures might occur. We implement FLAC in a distributed transactional keyvalue storage system based on Google Percolator and evaluate its performance with both a micro benchmark and a macro benchmark of real workload. The results show that FLAC achieves up to 2.22x throughput improvement and 2.82x latency speedup, compared to existing ACPs for high-contention workloads.

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“…Distributed systems suffer from two major bottlenecks related to ACP [32,62]. First, the long coordinator-side delay prolongs the latency of distributed transactions.…”

Section: Flac Ff For Failure-free Environmentmentioning

confidence: 99%

FLAC: Practical Failure-Aware Atomic Commit Protocol for Distributed Transactions

Pan¹,

Ta²,

Zhang³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Similarly to Zeus, many DSMs use cache coherence protocols, moving data to the accessing node, but, unlike Zeus, most focus on single-object consistency. A few support transactions (e.g., [11,73]) but relax consistency and/or forfeit availability for performance.…”

Section: Related Workmentioning

confidence: 99%

Zeus

Katsarakis

Tan

et al. 2021

Proceedings of the Sixteenth European Conference on Computer Systems

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State-of-the-art distributed in-memory datastores (FaRM, FaSST, DrTM) provide strongly-consistent distributed transactions with high performance and availability. Transactions in those systems are fully general; they can atomically manipulate any set of objects in the store, regardless of their location. To achieve this, these systems use complex distributed transactional protocols. Meanwhile, many workloads have a high degree of locality. For such workloads, distributed transactions are an overkill as most operations only access objects located on the same server -if sharded appropriately.In this paper, we show that for these workloads, a singlenode transactional protocol combined with dynamic object re-sharding and asynchronously pipelined replication can provide the same level of generality with better performance, simpler protocols, and lower developer effort. We present Zeus, an in-memory distributed datastore that provides general transactions by acquiring all objects involved in the transaction to the same server and executing a single-node transaction on them. Zeus is fault-tolerant and stronglyconsistent. At the heart of Zeus is a reliable dynamic object sharding protocol that can move 250K objects per second per server, allowing Zeus to process millions of transactions per second and outperform more traditional distributed transactions on a wide range of workloads that exhibit locality.

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Efficiency in the serverless cloud paradigm: A survey on the reusing and approximation aspects

Denninnart,

Chanikaphon,

Amini Salehi

2023

Softw Pract Exp

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SummaryServerless computing along with Function‐as‐a‐Service (FaaS) is forming a new computing paradigm that is anticipated to found the next generation of cloud systems. The popularity of this paradigm is due to offering a highly transparent infrastructure that enables user applications to scale in the granularity of their functions. Since these often small and single‐purpose functions are managed on shared computing resources behind the scene, a great potential for computational reuse and approximate computing emerges that if unleashed, can remarkably improve the efficiency of serverless cloud systems—both from the user's QoS and system's (energy consumption and incurred cost) perspectives. Accordingly, the goal of this survey study is to, first, unfold the internal mechanics of serverless computing and, second, explore the scope for efficiency within this paradigm via studying function reuse and approximation approaches and discussing the pros and cons of each one. Next, we outline potential future research directions within this paradigm that can either unlock new use cases or make the paradigm more efficient.

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Sundial

Cited by 26 publications

References 44 publications

FLAC: Practical Failure-Aware Atomic Commit Protocol for Distributed Transactions

FLAC: Practical Failure-Aware Atomic Commit Protocol for Distributed Transactions

Zeus

Efficiency in the serverless cloud paradigm: A survey on the reusing and approximation aspects

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