Edge-computing-driven Internet of Things: A Survey

Abstract

The Internet of Things (IoT) is impacting the world’s connectivity landscape. More and more IoT devices are connected, bringing many benefits to our daily lives. However, the influx of IoT devices poses non-trivial challenges for the existing cloud-based computing paradigm. In the cloud-based architecture, a large amount of IoT data is transferred to the cloud for data management, analysis, and decision making. It could not only cause a heavy workload on the cloud but also result in unacceptable network latency, ultimately undermining the benefits of cloud-based computing. To address these challenges, researchers are looking for new computing models for the IoT. Edge computing, a new decentralized computing model, is valued by more and more researchers in academia and industry. The main idea of edge computing is placing data processing in near-edge devices instead of remote cloud servers. It is promising to build more scalable, low-latency IoT systems. Many studies have been proposed on edge computing and IoT, but a comprehensive survey of this crossover area is still lacking. In this survey, we firstly introduce the impact of edge computing on the development of IoT and point out why edge computing is more suitable for IoT than other computing paradigms. Then, we analyze the necessity of systematical investigation on the edge-computing-driven IoT (ECDriven-IoT) and summarize new challenges occurred in ECDriven-IoT. We categorize recent advances from bottom to top, covering six aspects of ECDriven-IoT. Finally, we conclude lessons learned and propose some challenging and worthwhile research directions.

Enabling Artificial Intelligent Virtual Sensors in an IoT Environment

“…A continuous transfer of large amounts of IoT data and from multiple devices to the cloud burdens the network’s bandwidth and incurs privacy and security issues. Recent studies show that edge computing is more suitable for IoT than other computing paradigms [ 9 ]. Nevertheless, the edge incurs storage and processing limitations.…”

“…However, there are some serious challenges that need to be addressed, so that the full potential of IoT can be understood. For instance, the increasing number of IoT devices and the necessity of processing a significant amount of data have the disadvantage of increasing (i) the number of transmitted packets [ 9 ], (ii) the resource requirements, and (iii) the total overhead of device deployment and synchronization [ 10 ]. This growing trend in the demand of IoT devices imposes limitations, regardless of the computing layer it runs, i.e., Cloud, Edge, or Fog [ 11 ].…”

AI-Powered Edge Computing Evolution for Beyond 5G Communication Networks

“…However, more targeted solutions are required in order to fully leverage the massive parallelism capabilities of the HW-accelerated platforms, which is fundamental in order to deliver the Key Performance Indicators (KPIs) for ultra-low latency processing required by computational-intensive B5G and 6G applications. On the other hand, the complexity of parallel programming techniques for such heterogeneous scenarios can be daunting [5], stressing the need for programming models capable of providing the right level and granularity of abstraction to express the performance capabilities of the underlying HW platforms, with the lowest possible overhead.…”

“…Hence, the synergy between B5G and edge computing can provide computing and storage capabilities for applications residing at the boundary of operators' networks [4]. Nevertheless, many open challenges must be addressed in order to achieve an open, secure and distributed edge architecture that can be seamlessly integrated into an edge-cloud compute continuum, further boosting B5G capabilities enabling innovative next generation services [5].…”

Analysis of Latency and Bandwidth for Edge-Based Short Length in Edge Computing Devices for Short Ranges and Long Ranges

“…Edge computing reduces the delay by executing the computing process close to the data source (1) . It also discussed the need for systematic research on edge computing-driven Internet of Things (ECDriven-IoT) and listed recent developments in this field (2) . MobileEdge Computing-enabled video streaming offers extraordinary improvement to support unique use cases.…”