Software Engineering and Information Systems
Narges Akhound; Sahar Adabi; Ali Rezaee; Amir masoud Rahmani
Articles in Press, Accepted Manuscript, Available Online from 27 September 2022
Abstract
The advent of the Internet of Things (IoT) technology has made it possible for different devices to be widely connected to the Internet and interact. It has led to the production of large amounts of heterogeneous data. On the other hand, cloud computing is a convenient and efficient processing model ...
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The advent of the Internet of Things (IoT) technology has made it possible for different devices to be widely connected to the Internet and interact. It has led to the production of large amounts of heterogeneous data. On the other hand, cloud computing is a convenient and efficient processing model for storing and processing data. Still, the increasing demand for real-time and delay-sensitive applications is increasing day by day. Due to network bandwidth limitations, these problems cannot be solved using cloud computing alone. A fog layer located between the IoT devices and the cloud computing layer has been proposed to overcome the problem of resource constraints in mobile devices. delay-sensitive applications run that require more volume and power resources. In this paper, end-to-end architecture for integrating IoT, fog, and cloud layers into a large-scale dispatched application is proposed to support high availability to make efficient use of fog-cloud resources and achieve the appropriate quality of service (QoS) in terms of delay and failure probability criteria. The mentioned architecture consists of three hierarchal layers: IoT devices, fog nodes, and cloud data centers. Depending on the processing power of each layer's resources, user requests may be executed on the same layer or sent to a higher layer. Then, quality characteristics such as availability, performance, and interoperability for the proposed architecture are evaluated by the ATAM scenario-based method. The basis of architectural evaluation and analysis in this method is the study of the requirements and the quality characteristics of the system architecture.
Computer Networks and Distributed Systems
Fatemeh Davami; Sahar Adabi; Ali Rezaee; Amir Masoud Rahamni
Volume 7, Issue 2 , May 2021, , Pages 126-136
Abstract
In the last ten years, the Cloud data centers have been manifested as the crucial computing architectures to enable extreme data workflows. Due to the complicatedness and diverse kinds of computational resources like Fog nodes and Cloud servers, workflow scheduling has been proposed to be the main challenge ...
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In the last ten years, the Cloud data centers have been manifested as the crucial computing architectures to enable extreme data workflows. Due to the complicatedness and diverse kinds of computational resources like Fog nodes and Cloud servers, workflow scheduling has been proposed to be the main challenge in Cloud and or Fog computing environments. For resolving this issue, the present study offers a scheduling algorithm according to the critical path extraction, referred to as the Critical Path Extraction Algorithm (CPEA). In fact, it is one of the new multi-criteria decision-making algorithms to extract the critical paths of multiple workflows because it is of high importance to find the critical path in the creation and control of the scheduling. Moreover, an extensive software simulation investigation has been performed to compare this new algorithm in the real work-loads and recent algorithm. We compare our algorithm with the GRP-HEFT algorithm. The experimental results confirm the proposed algorithm's superiority in fulfilling make-span and waiting time and that workflow scheduling based on CPEA further improves the workflow make-span and waiting time.