Coalescing and Deduplicating Incremental Checkpoint Files for Restore-Express Multi-Level Checkpointing

Sigdel, Purushottam; Tzeng, Nian-Feng

doi:10.1109/tpds.2018.2844210

Cited by 9 publications

(2 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The solid-state drive (SSD) has become an alternative storage device even in datacenters where failures cannot be avoided [70], due to its far speedier reads and writes. To demonstrate the advantage of COMEX over a counterpart server with its swap partition served by an SSD (of SATA Transcend 64GB SSD340), we conducted benchmark evaluation under M = 8GB, with normalized execution time results shown in Fig.…”

Section: Execution Results With Ssd As Swap Partitionmentioning

confidence: 99%

Cooperative Memory Expansion via OS Kernel Support for Networked Computing Systems

Srinuan

Yuan

Tzeng

2020

IEEE Trans. Parallel Distrib. Syst.

Self Cite

View full text Add to dashboard Cite

The growing popularity of in-memory computing for bigdata analytics often causes performance bottlenecks to memory subsystem resided in operating systems (OS). This article purposes cooperative memory expansion (COMEX), an OS kernel extension. COMEX establishes a stable pool of memory collectively across nodes in a cluster and enhances OS's memory subsystem for memory aggregation from connected machines by allowing process's page table to track remote memory page frames without programmer effort or modifications to application codes. COMEX employs Remote Direct Memory Access (RDMA) for low-latency data transfer with destination kernel bypassed and does not rely on an old design of the I/O block subsystem usually adopted by all known remote paging. COMEX fits soundly in the emerging system design approach of resource disaggregation which breaks hard walls between server-centric machines into a new design paradigm of separated resource pools. The new architecture facilitates both system scaling-up and scaling-out, also eliminates imbalance resources existing in datacenters. We have implemented COMEX based on Linux kernel 3.10.87 and deployed on our 32 networked servers. Performance evaluation results under ten applications from two benchmark suites reveal the speedup of up to 170 times when application execution footprints are 10 times larger than available system memory. Index Terms-I/O block devices, memory management, networked computer systems, operating systems (OS), page tables, remote direct memory access (RDMA).

show abstract

Section: Execution Results With Ssd As Swap Partitionmentioning

confidence: 99%

Cooperative Memory Expansion via OS Kernel Support for Networked Computing Systems

Srinuan

Yuan

Tzeng

2020

IEEE Trans. Parallel Distrib. Syst.

Self Cite

View full text Add to dashboard Cite

show abstract

“…In the context of data protection, a typical technique is checkpointing, which is an efficient method for saving re-execution time in the presence of faults [11] through saving current data in the main memory to secondary storage. Checkpointing is easy to conduct and has been widely studied for decades [12][13][14][15][16]. For example, Fukumoto et al [12], and Dohi et al [13] introduced different checkpointing schemes for database systems, and Ranganathan and Upadhyaya [14] considered the temporal behavior related to database system states from a macroscopic viewpoint.…”

Section: Introductionmentioning

confidence: 99%

Availability Analysis of Software Systems with Rejuvenation and Checkpointing

Zheng

Okamura

2021

Mathematics

View full text Add to dashboard Cite

In software reliability engineering, software-rejuvenation and -checkpointing techniques are widely used for enhancing system reliability and strengthening data protection. In this paper, a stochastic framework composed of a composite stochastic Petri reward net and its resulting non-Markovian availability model is presented to capture the dynamic behavior of an operational software system in which time-based software rejuvenation and checkpointing are both aperiodically conducted. In particular, apart from the software-aging problem that may cause the system to fail, human-error factors (i.e., a system operator’s misoperations) during checkpointing are also considered. To solve the stationary solution of the non-Markovian availability model, which is derived on the basis of the reachability graph of stochastic Petri reward nets and is actually not one of the trivial stochastic models such as the semi-Markov process and the Markov regenerative process, the phase-expansion approach is considered. In numerical experiments, we illustrate steady-state system availability and find optimal software-rejuvenation policies that maximize steady-state system availability. The effects of human-error factors on both steady-state system availability and the optimal software-rejuvenation trigger timing are also evaluated. Numerical results showed that human errors during checkpointing both decreased system availability and brought a significant effect on the optimal rejuvenation-trigger timing, so that it should not be overlooked during system modeling.

show abstract

Computation algorithms for workload-dependent optimal checkpoint placement

Okamura

Qian

2022

Int J Syst Assur Eng Manag

View full text Add to dashboard Cite

Coalescing and Deduplicating Incremental Checkpoint Files for Restore-Express Multi-Level Checkpointing

Cited by 9 publications

References 28 publications

Cooperative Memory Expansion via OS Kernel Support for Networked Computing Systems

Cooperative Memory Expansion via OS Kernel Support for Networked Computing Systems

Availability Analysis of Software Systems with Rejuvenation and Checkpointing

Computation algorithms for workload-dependent optimal checkpoint placement

Contact Info

Product

Resources

About