Related papers: An Experimental and Comparative Benchmark Study Ex…
Distributed data processing frameworks (e.g., Hadoop, Spark, and Flink) are widely used to distribute data among computing nodes of a cloud. Recently, there have been increasing efforts aimed at evaluating the performance of distributed…
We present a framework for performance optimization in serverless edge-cloud platforms using dynamic task placement. We focus on applications for smart edge devices, for example, smart cameras or speakers, that need to perform processing…
This case study illustrates the potential benefits and risks associated with the migration of an IT system in the oil & gas industry from an in-house data center to Amazon EC2 from a broad variety of stakeholder perspectives across the…
Modern cloud computing advances have been pressing application modernization in the last 15 years, stressing the need for application redesign towards the use of more distributed and ephemeral resources. From the initial IaaS and PaaS…
In recent years, much research has focused on how to optimize Hadoop jobs. Their approaches are diverse, ranging from improving HDFS and Hadoop job scheduler to optimizing parameters in Hadoop configurations. Despite their success in…
Hadoop MapReduce is now a popular choice for performing large-scale data analytics. This technical report describes a detailed set of mathematical performance models for describing the execution of a MapReduce job on Hadoop. The models…
The need for Linux system administrators to do performance management has returned with a vengeance. Why? The cloud. Resource consumption in the cloud is all about pay-as-you-go. This article shows you how performance models can find the…
We investigate a hierarchically organized cloud infrastructure and compare distributed hierarchical control based on resource monitoring with market mechanisms for resource management. The latter do not require a model of the system, incur…
Edge computing has emerged as a popular paradigm for running latency-sensitive applications due to its ability to offer lower network latencies to end-users. In this paper, we argue that despite its lower network latency, the…
Understanding and predicting the performance of big data applications running in the cloud or on-premises could help minimise the overall cost of operations and provide opportunities in efforts to identify performance bottlenecks. The…
Increased adoption of scientific workflows in the community has urged for the development of multi-tenant platforms that provide these workflow executions as a service. As a result, Workflow-as-a-Service (WaaS) concept has been created by…
Abstract The cloud computing is a key computing approach adopted by many organizations in order to share resources. It provides Everything As-A-Service (XaaS). Software-As-A-Service is an important resource on the cloud computing…
With the proliferation of the Internet of Things (IoT) and the wide penetration of wireless networks, the surging demand for data communications and computing calls for the emerging edge computing paradigm. By moving the services and…
Edge computing is the next Internet frontier that will leverage computing resources located near users, sensors, and data stores to provide more responsive services. Therefore, it is envisioned that a large-scale, geographically dispersed,…
Blockchain is increasingly offered as blockchain-as-a-service (BaaS) by cloud service providers. However, configuring BaaS appropriately for optimal performance and reliability resorts to try-and-error. A key challenge is that BaaS is often…
The great prosperity of big data systems such as Hadoop in recent years makes the benchmarking of these systems become crucial for both research and industry communities. The complexity, diversity, and rapid evolution of big data systems…
Serverless computing is transforming cloud application development, but the performance-cost trade-offs of control plane designs remain poorly understood due to a lack of open, cross-platform benchmarks and detailed system analyses. In this…
In this paper, we demonstrate that a server running a single latency-sensitive application can be treated as a black box to reduce energy consumption while meeting an SLA target. We find that when the mean offered load is stable, one can…
Data centers have become ubiquitous for today's businesses. From banks to startups, they rely on cloud infrastructure to deploy user applications. In this context, it is vital to provide users with application performance guarantees.…
Function-as-a-service (FaaS) is a popular serverless computing paradigm for developing event-driven functions that elastically scale on public clouds. FaaS workflows, such as AWS Step Functions and Azure Durable Functions, are composed from…