Big Data and Internet of Things: A Roadmap for Smart Environments

By N. Bessis, C. Dobre. Big Data and Internet of Things, 2014

429 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/afefe35db68dabf33fa548ab818b46c47c860e08

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Information Systems

Citations in the corpus

Smart Cities: A Survey on Data Management, Security, and Enabling Technologies (2017, methodology): “Bessis and Dobre [284] provide a taxonomy and analysis of data dissemination techniques in the context of IoT.”
Smart Water Management Platform: IoT-Based Precision Irrigation for Agriculture (2019, background): “Fog computing is a fairly new paradigm aimed at dealing with challenges related to the huge amount of data that will be generated with the increasing utilization of IoT-based systems [15].”
A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications (2017, background): “At last, we discuss the advantages of mobile edge networks.”
A survey on Internet of Things architectures (2016, positive): “8 (see Left) presents multi tenant IoT-Fog architecture (Bonomi et al., 2014) with suitable applications A and B.”
Optimal Workload Allocation in Fog-Cloud Computing Toward Balanced Delay and Power Consumption (2016, background): “For example, Bonomi et al. [10] defined the characteristics of fog computing which make it an appropriate platform for a number of critical services and applications in Internet of Things and big data analytics.”
iFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments (2016, methodology): “Fog computing [3] extends cloud services to the edge of networks, which results in latency reduction through geographical distribution of IoT application components, and increased scalability for handling large scale deployments.”
Mobile Edge Computing via a UAV-Mounted Cloudlet: Optimization of Bit Allocation and Path Planning (2016, neutral): “J. Kang is with the Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291, Daehak-ro, Yuseong-gu, Daejeon 34141, Korea (e-mail: jhkang@ee.kaist.ac.kr).”
Fog Computing in Healthcare Internet of Things: A Case Study on ECG Feature Extraction (2015, neutral): “2.”
Big Data Analytics for Dynamic Energy Management in Smart Grids (2015, background): “Keywords: Big data, Smart grids, Dynamic energy management, Predictive analytics, Artificial intelligence, high performance computing.”
Edge-computing-driven Internet of Things: A Survey (2022, background): “introduced a general hardware architecture that meets the needs of most IoT scenarios [23].”
The role of big data analytics in Internet of Things (2017, background): “This section explains the role of big data and analytics in different IoT applications, including smart grids, smart healthcare, smart transportation, and smart inventory systems [44], [54], [55].”
Federated Learning in Edge Computing: A Systematic Survey (2022, background): “There are many new concepts aiming to operate on the edge of the network in the evolution of EC, including Micro Data Centers (MDCs) [26], Cloudlets [27], mobile edge computing [28] (also called multi-access edge computing [29]), and fog computing [30,31].”
Internet of Things (IoT) Security Intelligence: A Comprehensive Overview, Machine Learning Solutions and Research Directions (2022, neutral): “proved performance and faster response times [35].”