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Cloud computing is a general term that involves delivering hosted services over the Internet. With the accelerated growth of the volume of data used by applications, many organizations have moved their data into cloud servers to provide…
A model of cloud services is emerging whereby a few trusted providers manage the underlying hardware and communications whereas many companies build on this infrastructure to offer higher level, cloud-hosted PaaS services and/or SaaS…
Cyber-physical systems increasingly rely on distributed computing platforms where sensing, computing, actuation, and communication resources are shared by a multitude of applications. Such `cyber-physical cloud computing platforms' present…
Users of MapReduce often run into performance problems when they scale up their workloads. Many of the problems they encounter can be overcome by applying techniques learned from over three decades of research on parallel DBMSs. However,…
This article introduces a general processing framework to effectively utilize waveform data stored on modern cloud platforms. The focus is hybrid processing schemes where a local system drives processing. We show that downloading files and…
High performance computing (HPC) and cloud have traditionally been separate, and presented in an adversarial light. The conflict arises from disparate beginnings that led to two drastically different cultures, incentive structures, and…
Cloud computing delivers value to users by facilitating their access to computing capacity in periods when their need arises. An approach is to provide both on-demand and spot services on shared servers. The former allows users to access…
This paper presents an accelerated spherical K-means clustering algorithm for large-scale and high-dimensional sparse document data sets. We design an algorithm working in an architecture-friendly manner (AFM), which is a procedure of…
Performance modeling can help to improve the resource efficiency of clusters and distributed dataflow applications, yet the available modeling data is often limited. Collaborative approaches to performance modeling, characterized by the…
Cloud computing, thanks to the pervasiveness of information technologies, provides a foundational environment for developing IT applications, offering organizations virtually unlimited and flexible computing resources on a pay-per-use…
Data processing systems impose multiple views on data as it is processed by the system. These views include spreadsheets, databases, matrices, and graphs. There are a wide variety of technologies that can be used to store and process data…
Distributed dataflow systems like Apache Spark and Apache Hadoop enable data-parallel processing of large datasets on clusters. Yet, selecting appropriate computational resources for dataflow jobs -- that neither lead to bottlenecks nor to…
The rapid growth of data generated from Internet of Things (IoTs) such as smart phones and smart home devices presents new challenges to cloud computing in transferring, storing, and processing the data. With increasingly more powerful edge…
Top-tier parallel computing clusters continue to accumulate more and more computational power with more and better CPUs and Networks. This allows, especially for environmental simulations, computations with larger domain sizes and better…
This report evaluates the new analytical capabilities of DataStax Enterprise (DSE) [1] through the use of standard Hadoop workloads. In particular, we run experiments with CPU and I/O bound micro-benchmarks as well as OLAP-style analytical…
The performance of cluster computing depends on how concurrent jobs share multiple data center resource types like CPU, RAM and disk storage. Recent research has discussed efficiency and fairness requirements and identified a number of…
A hybrid mobile/fixed device cloud that harnesses sensing, computing, communication, and storage capabilities of mobile and fixed devices in the field as well as those of computing and storage servers in remote datacenters is envisioned.…
In this report we investigate the performance of Hadoop clusters, deployed with separated storage and compute layers, on top of a hypervisor managing a single physical host. We have analyzed and evaluated the different Hadoop cluster…
In the cloud computing application area of accomplish, we find the fact that cloud computing covers a lot of areas are its main asset. At a top level, it is an approach to IT where many users, some even from different companies get access…
Cloud infrastructures enable the efficient parallel execution of data-intensive tasks such as entity resolution on large datasets. We investigate challenges and possible solutions of using the MapReduce programming model for parallel entity…