Review of the Complexity of Managing Big Data of the Internet of Things

Table 1

A representative set of ways and aspects of handling the complexity arising from the IoT, together with references to corresponding papers, categorized under the headings of three general approaches (local processing, edge computing and cloud computing) to carry out intensive data processing of Big Data.

Work	Main contributions
(A) Local processing
Smart sensing for IoT applications [21]	Discusses emerging trends of smart sensing.
Sensor Fusion and Smart Sensor in Sports and Biomedical Applications [24]	An overview of smart sensors and sensor fusion.
High-level modelling and synthesis of smart sensor networks for Industrial Internet of Things [27]	Efficient design process and methodology for complex industrial applications.
Smart Sensing Devices for Logistics Application [26]	Analysis of the logistics sector and Cyber Physical Systems (CPS) as smart connected solutions.
Intelligent Manufacturing in the Context of Industry 4.0: A Review [28]	Review of key technologies such as the IoT and cyber-physical systems.
(B) Edge computing
Edge Computing: Vision and Challenges [34]	Challenges and opportunities in the field of edge computing are described.
Collaborative Working Architecture for IoT-Based Applications [20]	Network design, which combines sensing and processing capabilities based on the MCC paradigm.
IoT-Based Computational Framework [25]	Distributed framework based on the IoT paradigm for real-time monitoring.
Edge Computing [35]	Analysis of the edge computing paradigm.
Fog Computing [48]	The Fog Computing framework.
Secure Multi-Tier Mobile Edge Computing Model [49]	Formal framework to handle the security level of edge computing environments.
Mobile Edge Computing [38]	Analysis of opportunities, solutions, and challenges of the MEC paradigm.
Cloudlets [39]	Introduction to the cloudlet concept for offloading computations.
Future Edge Cloud and Edge Computing for Internet of Things Applications [40]	Discussion of Edge Cloud and Edge Computing research efforts.
(C) Cloud computing
A Smart Sensing Architecture for Domestic Monitoring [50]	Integrated sensor network deployment with advanced Cloud Computing Data Mining algorithms.
IoT-as-a-Service [43]	Strategy for evaluating the information quality in delivering IoT-as-a-Service.
The shift to Cloud Computing [41]	This paper analyses the impact of the shift to the Cloud-based model.
Accessibility analysis in smart cities [46]	Comprehensive system for monitoring urban accessibility in smart cities.
Big data analytics framework for smart cities [47]	Smart City Data Analytics Panel for Big Data analytics.
Sensing and Actuation as a Service Delivery Model [44]	A novel system model for Sensing and Actuation as a Service (SAaaS).
User Quality-Of-Experience and Service Provider Profit in 5G [51]	The Quality-of-Experience (QoE) and the Profit-aware Resource Allocation problems are analysed.
Orchestrated Platform for Cyber-Physical Systems [45]	Discussion on the scalability of the sensor data back-end and the predictive simulation architecture for CPS.