Abstract
Fog computing is a promising technology that leverages the resources to provide services for requests of IoT (Internet of Things) devices at the cloud edge. The high dynamic and heterogeneous nature of devices at the cloud edge causes failures to be a popular event and therefore fault tolerance became indispensable. Most early scheduling and fault-tolerant methods did not highly consider time-sensitive requests. This increases the possibility of latencies for serving these requests which causes unfavorable impacts. This paper proposes a fault-tolerant scheduling method (FTSM) for allocating services’ requests to the most sufficient devices in fog-cloud IoT-based environments. The main purpose of the proposed method is to reduce the latency and overheads of services and to increase the reliability and capacity of the cloud. The method depends on categorizing devices that can issue requests into three classes according to the type of service required. These classes are time-sensitive, time-tolerant and core. Each time-sensitive request is directly mapped to one or more edge devices using a pre-prepared executive list of devices. Each time-tolerant request may be assigned to one or more devices at the cloud edge or the cloud core. Core requests are assigned to resources at the cloud core. In order to achieve fault tolerance, the proposed method selects the most suitable fault-tolerant technique from replication, checkpointing and resubmission techniques for each request while most existing methods consider only one technique. The effectiveness of the proposed method is assessed using average service time, throughput, operation costs, success rate and capacity percentage as performance indicators.
Highlights
Cloud computing systems introduce inexpensive services to customers primarily in terms of storage and computing
Applications that depend on the Internet of Things (IoT), which represents the generation of networks, require real-time responses
There is a need for a computing model that distributes cloud services away from the cloud core to the cloud edge in order to avoid delays caused by moving data to the cloud core [1]
Summary
Cloud computing systems introduce inexpensive services to customers primarily in terms of storage and computing. The model acts as an interface that manages the virtual environment between the cloud core and the other resources located at the edge of the cloud. In IoT-based environments, as in fog-cloud computing, there is a great number of devices connected to the cloud at its edge. The occurrence of failures is popular because of the great dynamic and heterogeneity nature of the IoT devices and the interactions between them and the external environment [4] The effect of these failures ranges from minor influences resulting from delaying non-critical tasks which represent 70% of the cloud workload to major damages resulting from delaying critical tasks which represent about 30% of the cloud workload [5]. Some customers could not connect with their data or face a high latency to connect with it
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