IEEE Transactions on Cloud Computing

From the April-June 2015 issue

FastRAQ: A Fast Approach to Range-Aggregate Queries in Big Data Environments

By Xiaochun Yun, Guangjun Wu, Guangyan Zhang, Keqin Li, and Shupeng Wang

Featured article thumbnail imageRange-aggregate queries are to apply a certain aggregate function on all tuples within given query ranges. Existing approaches to range-aggregate queries are insufficient to quickly provide accurate results in big data environments. In this paper, we propose FastRAQ—a fast approach to range-aggregate queries in big data environments. FastRAQ first divides big data into independent partitions with a balanced partitioning algorithm, and then generates a local estimation sketch for each partition. When a range-aggregate query request arrives, FastRAQ obtains the result directly by summarizing local estimates from all partitions. FastRAQ has $O(1)$ time complexity for data updates and $O(\frac{N}{P\times {B}})$ time complexity for range-aggregate queries, where $N$ is the number of distinct tuples for all dimensions, $P$ is the partition number, and $B$ is the bucket number in the histogram. We implement the FastRAQ approach on the Linux platform, and evaluate its performance with about 10 billions data records. Experimental results demonstrate that FastRAQ provides range-aggregate query results within a time period two orders of magnitude lower than that of Hive, while the relative error is less than 3 percent within the given confidence interval.

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Call for Papers

Special Issue on Advances of Multimedia Big Data on the Cloud

Submission deadline: January 31, 2016. View PDF.

Today’s multimedia big data is becoming a part of daily life in our society, industry and academia to access different multimedia systems, services and applications in terms of internet search, social media stream, internet-of-things-based streams, video stream in surveillance, medical image or video stream, mobile phone photos or video stream, business transactions, to name a few. However, due to the challenge of managing Exabyte of such multimedia big data in terms of computations, communications, storage, and sharing, there is a growing demand of an infrastructure to have on-demand access to a shared pool of configurable computing resources (e.g., networks, storages, processing, applications and services) to collect, store, preserve, manage, analyze, and share huge quantities of multimedia data. Cloud computing is such an infrastructure providing scalability, flexibility, agility, and ubiquity in terms of massive scale multimedia data processing, storage, access and communications.

The potential of this emergent research on multimedia big data is huge because of the major challenges in dealing with uncertainty, unpredictability (e.g., data volume, velocity and heterogeneity or variety) and massiveness with regards to real-time cross-media integration, multi-scale analysis and processing, where media is originated from multiple heterogeneous media sources with a variety of modality as well as context. Moreover, provisioning of Cloud resources for multimedia big data applications further enhances many technical challenges with regards to capturing, storage, searching, correlating, transferring, sharing, analysis, and visualization of multimedia.

Special Issue on Advances of Utility and Cloud Computing Technologies and Services

Submission deadline: January 31, 2016. View PDF.

Computing is rapidly moving towards a model where it is provided as services that are delivered in a manner similar to traditional utilities such as water, electricity, gas, and telephony. In such a model, users access services according to their requirements, without regard to where the services are hosted or how they are delivered. Several computing architectures have evolved to realize this utility computing vision, including Grid computing, Service-Oriented Architecture (SOA) and Cloud computing, which has recently shifted into the center of attention in the ICT industry. Increasing numbers of IT vendors are promising to offer applications, storage and computation hosting services with conforming Service-Level Agreements (SLA) to ensure Quality of Services (QoS) and performance. Considering many of these services are hosted in traditional data centers, there is significant complexity involved in ensuring the scalability, availability, manageability and accessibility of applications, services and data, as the scale of the systems as well as the users grows. As a result, it is becoming important to investigate the use of cloud computing techniques and its interoperability with utility computing. This special issue focuses on principles, paradigms and applications of "Utility computing" and its practical realization especially in the context of Cloud Computing.

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