Abstract
Fog computing is one of the promising technologies for realizing global-scale Internet of Things (IoT) applications as it allows moving compute and storage resources closer to IoT devices, where data is generated, in order to solve the limitations in cloud-based technologies such as communication delay, network load, energy consumption, and operational cost. However, this technology is still in its infancy stage containing essential research challenges. For instance, what is a suitable fog computing scheme where effective service provision models can be deployed is still an open question. This paper proposes a novel multitier fog computing architecture that supports IoT service provisioning. Concretely, a solid service placement mechanism that optimizes service decentralization on fog landscape leveraging context-aware information such as location, response time, and resource consumption of services has been devised. The proposed approach optimally utilizes virtual resources available on the network edges to improve the performance of IoT services in terms of response time, energy, and cost reduction. The experimental results from both simulated data and use cases from service deployments in real-world applications, namely, the intelligent transportation system (ITS) in Ho Chi Minh City, show the effectiveness of the proposed solution in terms of maximizing fog device utilization while reducing latency, energy consumption, network load, and operational cost. The results confirm the robustness of the proposed scheme revealing its capability to maximize the IoT potential.
Highlights
The Internet of Things (IoT) has emerged as a revolutionary technology that offers a fully connected “smart” world that accelerates the 4th industrial revolution where thousands or millions of things in the physical world are connected with each other
If every IoT captured data pattern is transferred to data centers (DCs) on the cloud for processing and storage, and another large amount of information is returned to users or to actuators on the physical world, a huge volume of traffic is pumped into the network making it congested or malfunctioned
Energy consumption reduction, fog device utilization, and cost saving as functions of application complexities and network topologies have been thoroughly evaluated through experiments on general scenarios and real world applications
Summary
The Internet of Things (IoT) has emerged as a revolutionary technology that offers a fully connected “smart” world that accelerates the 4th industrial revolution where thousands or millions of things in the physical world are connected with each other. Realization of IoT services in a large scale, is hindered due to the constraints of IoT devices (embedded on everyday objects such as consumer goods, enduring products, vehicles, utility components, sensors, and other physical devices) in terms of computing resources, memory capacity, energy, and bandwidth limitations Many of these issues could be resolved by employing the Cloud-Assisted Internet of Things or Cloud-of-Things (CoT) technology as it offers large-scaled and on-demand networked computing resources to manage, store, process, and share IoT data and services [1]. If every IoT captured data pattern is transferred to data centers (DCs) on the cloud for processing and storage, and another large amount of information is returned to users or to actuators on the physical world, a huge volume of traffic is pumped into the network making it congested or malfunctioned This process challenges systems’ performance and robustness in terms of ensuring low latency
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