List of Articles محاسبات مه

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  1 - Priority based Deployment of IoT Applications in Fog
  Masomeh Azimzadeh Ali Rezaee Somayyeh  Jafarali Jassbi MohammadMahdi Esnaashari
  Fog computing technology has emerged to respond to the need for modern IoT applications for low latency, high security, etc. On the other hand, the limitations of fog computing such as heterogeneity, distribution, and resource constraints make service management in this More

  Fog computing technology has emerged to respond to the need for modern IoT applications for low latency, high security, etc. On the other hand, the limitations of fog computing such as heterogeneity, distribution, and resource constraints make service management in this environment challenging. Intelligent service placement means placing application services on fog nodes to ensure their QoS and effective use of resources. Using communities to organize nodes for service placement is one of the approaches in this area, where communities are mainly created based on the connection density of nodes, and applications are placed based on a single-criteria prioritization approach. This leads to the creation of unbalanced communities and inefficient placement of applications. This paper presents a priority-based method for deploying applications in the fog environment. To this end, balanced communities are created and applications are placed in balanced communities based on a multi-criteria prioritization approach. This leads to optimal use of network capacities and increases in QoS. The simulation results show that the proposed method improves deadline by up to 22%, increases availability by about 12%, and increases resource utilization by up to 10%. Manuscript profile
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  2 - Improving IoT resource management using fog calculations and ant lion optimization algorithm
  payam shams Seyedeh Leili Mirtaheri reza shahbazian ehsan arianyan
  20.1001.1.27170411.1402.15.57.16.1
  In this paper, a model based on meta-heuristic algorithms for optimal allocation of IoT resources based on fog calculations is proposed. In the proposed model, the user request is first given to the system as a workflow; For each request, the resource requirements (proc More

  In this paper, a model based on meta-heuristic algorithms for optimal allocation of IoT resources based on fog calculations is proposed. In the proposed model, the user request is first given to the system as a workflow; For each request, the resource requirements (processing power, storage memory, and bandwidth) are first extracted. This component determines the requested traffic status of the application in terms of real-time. If the application is not real-time and is somewhat resistant to latency, the request will be referred to the cloud environment, but if the application needs to respond promptly and is sensitive to latency, it will be dealt with as a fog calculation. It will be written to one of the Cloudletes. In this step, in order to select the best solution in allocating resources to serve the users of the IoT environment, the ant milk optimization algorithm was used. The proposed method is simulated in MATLAB software environment and to evaluate its performance, five indicators of fog cells energy consumption, response time, fog cell imbalance, latency and bandwidth have been used. The results show that the proposed method reduces the energy consumption, latency rate in fog cells, bandwidth consumption rate, load balance rate and response time compared to the base design (ROUTER) 22, 18, 12, 22 and 47, respectively. Percentage has improved. Manuscript profile
• Open Access Article
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  3 - Community-Based Multi-Criteria Placement of Applications in the Fog Environment
  Masomeh Azimzadeh Ali Rezaee Somayyeh  Jafarali Jassbi MohammadMahdi Esnaashari
  Fog computing technology has emerged to respond to the need for modern IoT applications for low latency, high security, etc. On the other hand, the limitations of fog computing such as heterogeneity, distribution, and resource constraints make service management in this More

  Fog computing technology has emerged to respond to the need for modern IoT applications for low latency, high security, etc. On the other hand, the limitations of fog computing such as heterogeneity, distribution, and resource constraints make service management in this environment challenging. Intelligent service placement means placing application services on fog nodes to ensure their QoS and effective use of resources. Using communities to organize nodes for service placement is one of the approaches in this area, where communities are mainly created based on the connection density of nodes, and applications are placed based on a single-criteria prioritization approach. This leads to the creation of unbalanced communities and inefficient placement of applications. This paper presents a priority-based method for deploying applications in the fog environment. To this end, balanced communities are created and applications are placed in balanced communities based on a multi-criteria prioritization approach. This leads to optimal use of network capacities and increases in QoS. The simulation results show that the proposed method improves deadline by up to 22%, increases availability by about 12%, and increases resource utilization by up to 10%. Manuscript profile