Searcharxiv⌕ Search

arXiv subjects

Seyed Esmaeil Mirvakili

Publications and source records attributed to Seyed Esmaeil Mirvakili.

2 recordsLinked to original sources

Managing Bufferbloat in Cloud Storage Systems

Today, companies and data centers are moving towards cloud and serverless storage systems instead of traditional file systems. As a result of such a transition, allocating sufficient resources to users and parties to satisfy their service level demands has become crucial in cloud storage. In cloud storage, the schedulability of system components and requests is of great importance to achieving QoS goals. However, the bufferbloat phenomenon in storage backends impacts the schedulability of the system. In a storage server, bufferbloat happens when the server submits all requests immediately to the storage backend due to a large buffer in the backend. In recent decades, many studies have focused on the bufferbloat as a latency problem. Nevertheless, none of these works investigate the impact of bufferbloat on the schedulability of the system. In this paper, we demonstrate that the bufferbloat impacts scheduling and performance isolation and identify utilizing admission control in the storage backend as an easy-to-adopt solution to mitigate bufferbloat. Moreover, we show that traditional static admission controls are inadequate in the face of dynamic workloads in cloud environments. Finally, we propose SlowFast CoDel, an adaptive admission control, as a starting point for developing adaptive admission control mechanisms to mitigate bufferbloat in cloud storage.

cs.DC↗

Reactive Liquid: Optimized Liquid Architecture for Elastic and Resilient Distributed Data Processing

Today's most prominent IT companies are built on the extraction of insight from data, and data processing has become crucial in data-intensive businesses. Nevertheless, the size of data which should be processed is growing significantly fast. The pace of the data growing has changed the nature of data processing. Today, data-intensive industries demand highly scalable and fault tolerant data processing architectures which can handle the massive amount of data. In this paper, we presented a distributed architecture for elastic and resilient data processing based on the Liquid which is a nearline and offline big data architecture. We used the Reactive Manifesto to design the architecture highly reactive to workload changes and failures. We evaluate our architecture by drawing some numerical comparisons between our architecture prototype and the Liquid prototype. The performed evaluation shows that our architecture can be more scalable against workload and more resilient against failures than the Liquid architecture is.

cs.DC↗