Abstract
The Internet of Things (IoT) has recently become a popular technology that can play increasingly important roles in every aspect of our daily life. For collaboration between IoT devices and edge cloud servers, edge server nodes provide the computation and storage capabilities for IoT devices through the task offloading process for accelerating tasks with large resource requests. However, the quantitative impact of different offloading architectures and policies on IoT applications’ performance remains far from clear, especially with a dynamic and unpredictable range of connected physical and virtual devices. To this end, this work models the performance impact by exploiting a potential latency that exhibits within the environment of edge cloud. Also, it investigates and compares the effects of loosely-coupled (LC) and orchestrator-enabled (OE) architecture. The LC scheme can smoothly address task redistribution with less time consumption for the offloading sceneries with small scale and small task requests. Moreover, the OE scheme not only outperforms the LC scheme in the large-scale tasks requests and offloading occurs but also reduces the overall time by 28.19%. Finally, to achieve optimized solutions for optimal offloading placement with different constraints, orchestration is important.
Highlights
In this digitized era, the number of sensor-enabled objects and devices connected to the network has significantly increased, where this number was doubled five years ago [1]
This work models the performance impact by exploiting a potential latency that exhibits within the environment of edge cloud
In this study, we investigate the effectiveness of various architectures of edge cloud offloading on the total Internet of Things (IoT) service time throughout the process of task offloading and study how the demands of various application parameters, such as communication and computation, can influence on the holistic efficiency
Summary
The number of sensor-enabled objects and devices connected to the network has significantly increased, where this number was doubled five years ago (i.e., between 2014 and 2019) [1]. This revolution has led to a new era of technology called the Internet of Things (IoT), that has gained well consideration from both industry and academia. The identities and attributes of physical and virtual IoT things are capable to use intelligent interfaces and can be integrated as a network of information” [2]. Through the IoT technology, physical objects, such as vehicles, buildings, and sensors, are interconnected and created a virtual environment, which leads to increase the integration of cyber-physical objects.
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