Abstract
To provide a better quality of service (QoS), cloud computing paradigm in Internet of Things (IoT) networks has shifted toward the edge. Fog-aided IoT networks deploy fog nodes, which are equipped with computing and storage resources, at the network edge to take over the deadline-driven computing tasks from IoT devices. In the fog node, where multiple virtual machines (VMs) can be rented to process the tasks, fog provisioning is to determine which VM should be rented and how to distribute different tasks to VMs in order to minimize the system cost (i.e., VM rentals). On the other hand, VMs may fail and lead to QoS degradation. Hence, reliability of VMs should also be considered when addressing the fog resource provisioning problem. To improve reliability, more VMs should be rented to satisfy the QoS requirement; this leads to higher system cost. Therefore, there is a tradeoff between reliability and the system cost. In this paper, we investigate the tradeoff of maximizing the reliability and minimizing the system cost for fog resource provisioning in IoT networks. An integer linear programming (ILP) problem is formulated but suffers from a high computational complexity. We then design an alternative algorithm to achieve suboptimal solutions with better time efficiency. The simulation results demonstrate the performances of our proposed algorithm.
Original language | English (US) |
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Article number | 8735844 |
Pages (from-to) | 8262-8269 |
Number of pages | 8 |
Journal | IEEE Internet of Things Journal |
Volume | 6 |
Issue number | 5 |
DOIs | |
State | Published - Oct 2019 |
All Science Journal Classification (ASJC) codes
- Signal Processing
- Information Systems
- Hardware and Architecture
- Computer Science Applications
- Computer Networks and Communications
Keywords
- Fog computing
- Internet of Things (IoT)
- multiobjective optimization
- quality of service (QoS)
- reliability
- resource provisioning