Big Data and Cloud Computing: A Survey of the State-of-the-Art and Research Challenges

Author(s):  
Georgios Skourletopoulos ◽  
Constandinos X. Mavromoustakis ◽  
George Mastorakis ◽  
Jordi Mongay Batalla ◽  
Ciprian Dobre ◽  
...  
Author(s):  
Maria K. Krommyda ◽  
Verena Kantere

Large datasets pertaining to many scientific fields and everyday activities are becoming available at an increasing rate. Processing, analyzing, and understanding the information that they offer poses significant technical challenges. There are many efforts dedicated to the development of big data exploration, analysis, and visualization applications that will improve the value of the information extracted from these datasets. An analysis of the state-of-the-art in these applications is presented here along with open research challenges that have not yet been tackled sufficiently. Also, specific domains where big data applications are needed are presented, and unique challenges are identified.


2021 ◽  
Vol 16 (2) ◽  
pp. 111-135
Author(s):  
Emilio M. Sanfilippo

Information entities are used in ontologies to represent engineering technical specifications, health records, pictures or librarian data about, e.g., narrative fictions, among others. The literature in applied ontology lacks a comparison of the state of the art, and foundational questions on the nature of information entities remain open for research. The purpose of the paper is twofold. First, to compare existing ontologies with both each other and theories proposed in philosophy, semiotics, librarianship, and literary studies in order to understand how the ontologies conceive and model information entities. Second, to discuss some open research challenges that can lead to principled approaches for the treatment of information entities, possibly by getting into account the variety of information entity types found in the literature.


2018 ◽  
Vol 12 (02) ◽  
pp. 191-213
Author(s):  
Nan Zhu ◽  
Yangdi Lu ◽  
Wenbo He ◽  
Hua Yu ◽  
Jike Ge

The sheer volume of contents generated by today’s Internet services is stored in the cloud. The effective indexing method is important to provide the content to users on demand. The indexing method associating the user-generated metadata with the content is vulnerable to the inaccuracy caused by the low quality of the metadata. While the content-based indexing does not depend on the error-prone metadata, the state-of-the-art research focuses on developing descriptive features and misses the system-oriented considerations when incorporating these features into the practical cloud computing systems. We propose an Update-Efficient and Parallel-Friendly content-based indexing system, called Partitioned Hash Forest (PHF). The PHF system incorporates the state-of-the-art content-based indexing models and multiple system-oriented optimizations. PHF contains an approximate content-based index and leverages the hierarchical memory system to support the high volume of updates. Additionally, the content-aware data partitioning and lock-free concurrency management module enable the parallel processing of the concurrent user requests. We evaluate PHF in terms of indexing accuracy and system efficiency by comparing it with the state-of-the-art content-based indexing algorithm and its variances. We achieve the significantly better accuracy with less resource consumption, around 37% faster in update processing and up to 2.5[Formula: see text] throughput speedup in a multi-core platform comparing to other parallel-friendly designs.


Author(s):  
Rafal Cupek ◽  
Marek Drewniak ◽  
Marcin Fojcik ◽  
Erik Kyrkjebø ◽  
Jerry Chun-Wei Lin ◽  
...  

2015 ◽  
pp. 1933-1955
Author(s):  
Tolga Soyata ◽  
He Ba ◽  
Wendi Heinzelman ◽  
Minseok Kwon ◽  
Jiye Shi

With the recent advances in cloud computing and the capabilities of mobile devices, the state-of-the-art of mobile computing is at an inflection point, where compute-intensive applications can now run on today's mobile devices with limited computational capabilities. This is achieved by using the communications capabilities of mobile devices to establish high-speed connections to vast computational resources located in the cloud. While the execution scheme based on this mobile-cloud collaboration opens the door to many applications that can tolerate response times on the order of seconds and minutes, it proves to be an inadequate platform for running applications demanding real-time response within a fraction of a second. In this chapter, the authors describe the state-of-the-art in mobile-cloud computing as well as the challenges faced by traditional approaches in terms of their latency and energy efficiency. They also introduce the use of cloudlets as an approach for extending the utility of mobile-cloud computing by providing compute and storage resources accessible at the edge of the network, both for end processing of applications as well as for managing the distribution of applications to other distributed compute resources.


2018 ◽  
Vol 44 (4) ◽  
pp. 651-658
Author(s):  
Ralph Weischedel ◽  
Elizabeth Boschee

Though information extraction (IE) research has more than a 25-year history, F1 scores remain low. Thus, one could question continued investment in IE research. In this article, we present three applications where information extraction of entities, relations, and/or events has been used, and note the common features that seem to have led to success. We also identify key research challenges whose solution seems essential for broader successes. Because a few practical deployments already exist and because breakthroughs on particular challenges would greatly broaden the technology’s deployment, further R&D investments are justified.


2019 ◽  
Vol 18 (5) ◽  
pp. 3049-3082 ◽  
Author(s):  
Nelly Bencomo ◽  
Sebastian Götz ◽  
Hui Song

2012 ◽  
Vol 4 (1) ◽  
pp. 52-66 ◽  
Author(s):  
Junaid Arshad ◽  
Paul Townend ◽  
Jie Xu ◽  
Wei Jie

The evolution of modern computing systems has lead to the emergence of Cloud computing. Cloud computing facilitates on-demand establishment of dynamic, large scale, flexible, and highly scalable computing infrastructures. However, as with any other emerging technology, security underpins widespread adoption of Cloud computing. This paper presents the state-of-the-art about Cloud computing along with its different deployment models. The authors also describe various security challenges that can affect an organization’s decision to adopt Cloud computing. Finally, the authors list recommendations to mitigate with these challenges. Such review of state-of-the-art about Cloud computing security can serve as a useful barometer for an organization to make an informed decision about Cloud computing adoption.


2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Sabeen Masood ◽  
Fatima Khalique ◽  
Bushra Bashir Chaudhry ◽  
Abdul Rauf

Cloud computing has emerged as a powerful new technology. The processing and computation power embedded in the cloud technology is not only flexible but also infinitely scalable and cost effective. Service oriented architecture (SOA) is a perfect stage for cloud computing. SOA has allowed customers and organizations to achieve cloud computing and reap its benefits that would not have been possible through any other architecture. This paper discusses the concept and importance of service oriented cloud computing by highlighting possible architectures, their benefits and critical success factors.


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