دانلود رایگان مقاله انگلیسی کلان داده برای اینترنت اشیا - الزویر 2018

Abstract

With the rapid development of the Internet of Things (IoT), Big Data technologies have emerged as a critical data analytics tool to bring the knowledge within IoT infrastructures to better meet the purpose of the IoT systems and support critical decision making. Although the topic of Big Data analytics itself is extensively researched, the disparity between IoT domains (such as healthcare, energy, transportation and others) has isolated the evolution of Big Data approaches in each domain. Thus, the mutual understanding across IoT domains can possibly advance the evolution of Big Data research in IoT. In this work, we therefore conduct a survey on Big Data technologies in different IoT domains to facilitate and stimulate knowledge sharing across the IoT domains. Based on our review, this paper discusses the similarities and differences among Big Data technologies used in different IoT domains, suggests how certain Big Data technology used in one IoT domain can be re-used in another IoT domain, and develops a conceptual framework to outline the critical Big Data technologies across all the reviewed IoT domains.

Conclusion

In this paper, we have conducted an extensive survey on the papers bridging the IoT and Big Data communities. Based on the review of IoT papers, we have selected a set of typical IoT domains and described the features in each domain. By reviewing the Big Data papers, we have derived four important aspects from the Big Data process analysis. After specifying the IoT domains and important Big Data aspects, we have focused on the literature review across the IoT and Big Data research. The related papers have been classified based on the IoT domain that the paper belongs to, which Big Data techniques are used in this IoT domain and how Big Data techniques are applied in certain IoT domain. Furthermore, we have extracted, summarized and organized the keywords from reviewed papers to indicate which Big Data elements are used in each IoT domain. As such, we are able to conclude mutual understandings and interpretations across IoT domains in terms of Big Data, whereby suggest which state-of-theart Big Data technologies can be possibly used for which IoT domain, as well as outline the Big Data research opportunities in different IoT domains. We have further analyzed the Big Data research across IoT domains, for example, the pros and cons of Big Data technologies and their applications in certain IoT domain. Based on these results, we have proposed a conceptual framework to guide researchers and practitioners to select the Big Data technologies that are prevalently used in certain IoT domain. This also provides practical implications on how we can possibly improve or complement certain IoT domain by using the widely accepted Big Data technologies from other domains.