A Case for Rigorous Workload Classification

Modern web applications are deployed in cloud computing systems because they support unlimited storage and computing power. One of the main back-end storage components of this cloud computing system is the distributed file system which allows massive amounts of data to be stored and accessed. In most web applications deployed in such systems, read operations are performed more frequently than write operations. Consequently, increasing the efficiency of read operations in distributed file systems is a challenging and important research problem. The two main procedures used in distributed file systems to improve the performance of read operations are prefetching and caching. In this paper, we proposed novel prefetching and multi-level caching algorithms based on the Access-Frequency and Access-Recency ranking of file blocks that were previously accessed by client application programs. We also proposed new augmented ranking algorithms for prefetching file blocks by combining the Access-Frequency and Access-Recency ranking of the file blocks. We used rank-based replacement algorithms to replace file blocks in the cache. The simulation results show that, the proposed algorithms improve the performance of read operations on distributed file systems by 29% to 77% in comparison to algorithms proposed in the literature.

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“…The Access-Frequency rank(AF_rank) for each fid(bid) stored in local FFBs list and global FFBs list is calculated as shown in Equation (5).…”

Section: Ccn _support(f Id) =mentioning

confidence: 99%

“…If q blocks have the same support value, they are ordered according to their access time while assigning the position. After assigning the position to the FFBs in both lists, the Access-Frequency rank for each FFB is calculated using Equation (5). The procedure for local and global ranking of FFBs is described in Algorithm 1.…”

Section: ) Afpmc Ranking Algorithmmentioning

confidence: 99%

Efficient Prefetching and Client-Side Caching Algorithms for Improving the Performance of Read Operations in Distributed File Systems

2022

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“…Previous studies have analyzed storage system behavior under different workloads, including both archival and high intensity workloads [5], [8], [9]. The challenge of rigorously characterizing storage system workloads does not outweigh the importance of using workload characteristics to understand how best to model and design storage systems [10].…”

Section: Archive Parametersmentioning

confidence: 99%

Using Simulation to Design Scalable and Cost-Efficient Archival Storage Systems

Byron

Long

Miller

2018

2018 IEEE 26th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS

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The need for reliable and cost-effective data storage grows as digital information becomes increasingly ubiquitous. Archival systems must store valuable data for years while adapting to changing user needs, capacity, and performance requirements. Storage devices differ in terms of performance, capacity, reliability, acquisition cost, power consumption, and the rates at which their features change over time. As a result, choosing the best storage technology to use for an archive has become increasingly challenging with the proliferation of new technologies alongside existing ones.We have designed a simulator that models the capacity, performance, acquisition cost, and power cost of an archival system using the characteristics of the drives and media that comprise it. We simulate and compare four storage technologies that exhibit different cost and performance characteristics: tape, optical disc, hard disk, and NAND flash SSD. We evaluate the total cost of ownership for each storage technology within an archival system, and we explore the effect that prospective technological advancements and growth rates over time may have on the relative cost and viability of each storage technology for archival systems. We show that the lifecycle and upgrade cost of drives are significant cost factors for removable media archives. We observe that increasing performance requires adding more drives to an archival system, and the cost of each drive dominates the cost to increase performance. We compare trends in storage technologies to suggest developments that could minimize the long-term total cost of ownership for archival systems. We show that hard disks and flash could become cost-competitive with tape-based archives by adopting new designs to minimize infrastructure and electricity costs.

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“…Cloud computing platforms are commonly used to deploy data-intensive applications due to their enormous storage and processing capacities. The users of such data-intensive applications that are deployed in the cloud perform read access requests (read requests) more frequently when compared to write requests [1,2]. Therefore improving the performance of read operations carried out on the DFS is a significant and challenging research problem.…”

Section: Introductionmentioning

confidence: 99%

HRFP: Highly Relevant Frequent Patterns-Based Prefetching and Caching Algorithms for Distributed File Systems

et al. 2023

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Data-intensive applications are generating massive amounts of data which is stored on cloud computing platforms where distributed file systems are utilized for storage at the back end. Most users of those applications deployed on cloud computing systems read data more often than they write. Hence, enhancing the performance of read operations is an important research issue. Prefetching and caching are used as important techniques in the context of distributed file systems to improve the performance of read operations. In this research, we introduced a novel highly relevant frequent patterns (HRFP)-based algorithm that prefetches content from the distributed file system environment and stores it in the client-side caches that are present in the same environment. We have also introduced a new replacement policy and an efficient migration technique for moving the patterns from the main memory caches to the caches present in the solid-state devices based on a new metric namely the relevancy of the patterns. According to the simulation results, the proposed approach outperformed other algorithms that have been suggested in the literature by a minimum of 15% and a maximum of 53%.

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A Case for Rigorous Workload Classification

Cited by 5 publications

References 11 publications

Efficient Prefetching and Client-Side Caching Algorithms for Improving the Performance of Read Operations in Distributed File Systems

Efficient Prefetching and Client-Side Caching Algorithms for Improving the Performance of Read Operations in Distributed File Systems

Using Simulation to Design Scalable and Cost-Efficient Archival Storage Systems

HRFP: Highly Relevant Frequent Patterns-Based Prefetching and Caching Algorithms for Distributed File Systems

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