| 1. |
- Abdi, Somayeh, et al.
(author)
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Cognitive and Time Predictable Task Scheduling in Edge-cloud Federation
- 2022
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In: IEEE International Conference on Emerging Technologies and Factory Automation, ETFA. - : Institute of Electrical and Electronics Engineers Inc.. - 9781665499965
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Conference paper (peer-reviewed)abstract
- In this paper, we present a hierarchical model for time predictable task scheduling in edge-cloud computing architecture for industrial cyber-physical systems. Regarding the scheduling problem, we also investigate the common problem-solving approaches and discuss our preliminary plan to realize the proposed architecture. Furthermore, an Integer linear programming (ILP) model is proposed for task scheduling problem in the cloud layer. The model considers timing and security requirements of applications and the objective is to minimize the financial cost of their execution.
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| 2. |
- Abdi, Somayeh, et al.
(author)
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Cost-aware workflow offloading in edge-cloud computing using a genetic algorithm
- 2024
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In: Journal of Supercomputing. - : Springer. - 0920-8542 .- 1573-0484.
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Journal article (peer-reviewed)abstract
- The edge-cloud computing continuum effectively uses fog and cloud servers to meet the quality of service (QoS) requirements of tasks when edge devices cannot meet those requirements. This paper focuses on the workflow offloading problem in edge-cloud computing and formulates this problem as a nonlinear mathematical programming model. The objective function is to minimize the monetary cost of executing a workflow while satisfying constraints related to data dependency among tasks and QoS requirements, including security and deadlines. Additionally, it presents a genetic algorithm for the workflow offloading problem to find near-optimal solutions with the cost minimization objective. The performance of the proposed mathematical model and genetic algorithm is evaluated on several real-world workflows. Experimental results demonstrate that the proposed genetic algorithm can find admissible solutions comparable to the mathematical model and outperforms particle swarm optimization, bee life algorithm, and a hybrid heuristic-genetic algorithm in terms of workflow execution costs.
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| 3. |
- Abdi, Somayeh, et al.
(author)
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Deadline-constrained security-aware workflow scheduling in hybrid cloud architecture
- 2025
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In: Future Generation Computer Systems. - : Elsevier B.V.. - 0167-739X .- 1872-7115. ; 162
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Journal article (peer-reviewed)abstract
- A hybrid cloud is an efficient solution to deal with the problem of insufficient resources of a private cloud when computing demands increase beyond its resource capacities. Cost-efficient workflow scheduling, considering security requirements and data dependency among tasks, is a prominent issue in the hybrid cloud. To address this problem, we propose a mathematical model that minimizes the monetary cost of executing a workflow and satisfies the security requirements of tasks under a deadline. The proposed model fulfills data dependency among tasks, and data transmission time is formulated with exact mathematical expressions. The derived model is a Mixed-integer linear programming problem. We evaluate the proposed model with real-world workflows over changes in the input variables of the model, such as the deadline and security requirements. This paper also presents a post-optimality analysis that investigates the stability of the assignment problem. The experimental results show that the proposed model minimizes the cost by decreasing inter-cloud communications for dependent tasks. However, the optimal solutions are affected by the limitations that are imposed by the problem constraints.
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| 4. |
- Abdi, Somayeh, et al.
(author)
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Task Offloading in Edge-cloud Computing using a Q-Learning Algorithm
- 2024
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In: International Conference on Cloud Computing and Services Science, CLOSER - Proceedings. - : Science and Technology Publications, Lda. - 9789897587016 ; , s. 159-166
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Conference paper (other academic/artistic)abstract
- Task offloading is a prominent problem in edge−cloud computing, as it aims to utilize the limited capacityof fog servers and cloud resources to satisfy the QoS requirements of tasks, such as meeting their deadlines.This paper formulates the task offloading problem as a nonlinear mathematical programming model to maximizethe number of independent IoT tasks that meet their deadlines and to minimize the deadline violationtime of tasks that cannot meet their deadlines. This paper proposes two Q-learning algorithms to solve theformulated problem. The performance of the proposed algorithms is experimentally evaluated with respect toseveral algorithms. The evaluation results demonstrate that the proposed Q-learning algorithms perform wellin meeting task deadlines and reducing the total deadline violation time.
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| 5. |
- Alvarez Vadillo, Ines, et al.
(author)
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Centralised Architecture for the Automatic Self-Configuration of Industrial Networks
- 2023
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In: IEEE Int. Conf. Emerging Technol. Factory Autom., ETFA. - : Institute of Electrical and Electronics Engineers Inc.. - 9798350339918
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Conference paper (peer-reviewed)abstract
- Novel production paradigms aim at increasing the efficiency and flexibility of production systems. Nonetheless, traditional industrial infrastructures lack the mechanisms needed to support these new paradigms. One of the main limiting factors is the architecture, which follows the automation pyramid in which subsystems are divided in layers depending on their functionalities. This allowed to meet the timing and dependability requirements of the production subsystems, however at the cost of limiting the exchange of information required to provide increased flexibility to the system. For this reason, in this paper we propose a new industrial architecture with a single network infrastructure to connect all the devices that conform to the industrial systems. On top of that, we design an Automatic Network Configurator to support the automatic configuration of the system. To assess the feasibility of our design and evaluate its performance, we implement the first instance of the architecture capable of supporting changes in the traffic requirements during run-time, i.e., without stopping or disrupting the system's operation. Furthermore, we use the implemented instance to measure the time required for reconfigurations.
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| 6. |
- Alvarez Vadillo, Ines, et al.
(author)
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Implementing a First CNC for Scheduling and Configuring TSN Networks
- 2022
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In: IEEE International Conference on Emerging Technologies and Factory Automation, ETFA. - : Institute of Electrical and Electronics Engineers Inc.. - 9781665499965
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Conference paper (peer-reviewed)abstract
- Novel industrial applications are leading to important changes in industrial systems. One of the most important changes is the need for systems that are capable to adapt to changes in the environment or the system itself. Because of their nature many of these applications are distributed, and their network infrastructure is key to guarantee the correct operation of the overall system. Furthermore, in order for a distributed system to be able to adapt, its network must be flexible enough to support changes in the traffic during runtime. The Time-Sensitive Networking (TSN) Task Group has proposed a series of standards that aim at providing deterministic real-time communications over Ethernet. TSN also provides centralised online configuration and control architectures which enable the online configuration of the network. A key part in TSN's centralised architectures is the Centralised Network Configuration element (CNC). In this work we present a first implementation of a CNC capable of scheduling time-triggered traffic and deploying such configuration in the network using the Network Configuration (NETCONF) protocol. We also assess the correctness of our implementation using an industrial use case provided by Volvo Construction Equipment.
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| 9. |
- Ashjaei, Mohammad, et al.
(author)
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End-to-end Resource Reservations in Distributed Embedded Systems
- 2016
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In: Proceedings - 2016 IEEE 22nd International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2016. ; , s. 1-11
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Conference paper (peer-reviewed)abstract
- The resource reservation techniques provide effective means to lower the software complexity, ensure predictability and allow flexibility during the development and execution of complex distributed embedded systems. In this paper we propose a new end-to-end resource reservation model for distributed embedded systems. The model is comprehensive in such a way that it supports end-to-end resource reservations on distributed transactions with various activation patterns that are commonly used in industrial control systems. The model allows resource reservations on processors and real-time network protocols. We also present timing analysis for the distributed embedded systems that are developed using the proposed model. The timing analysis computes the end-to-end response times as well as delays such as data age and reaction delays. The presented analysis also supports real-time networks that can autonomously initiate transmissions. Such networks are not supported by the existing analyses. We also include a case study to show the usability of the model and end-to-end timing analysis with resource reservations.
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