Strategic application placement in fog computing through multi-objective meta-heuristic algorithm
*Chintansinh ParmarCorresponding authorchintansinh191@gmail.comDepartment of Computer EngineeringSankalchand Patel College of EngineeringSankalchand Patel UniversityVisnagar, Gujarat, 384315, IndiaView full profile → , Ankur Goswamiajgoswami.ce@gmail.comDepartment of Computer EngineeringSankalchand Patel College of EngineeringSankalchand Patel UniversityVisnagar, Gujarat, 384315, IndiaView full profile → , Jinal Methajinalmehta1314@gmail.comDepartment of Computer EngineeringSankalchand Patel College of EngineeringSankalchand Patel UniversityVisnagar, Gujarat, 384315, IndiaView full profile → , Jayesh Mevadajmmevadace_spce@spu.ac.inDepartment of Computer EngineeringSankalchand Patel College of EngineeringSankalchand Patel UniversityVisnagar, Gujarat, 384315, IndiaView full profile → , Ochchhav Patelochchhav_ce@ldrp.ac.inDepartment of Computer EngineeringLDRP Institute of Technology & ResearchKadi Sarva VishwavidyalayaGandhinagar, Gujarat, 382015, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 01 Jun 2026
- Published Online:
- 30 Sep 2026
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-2440
- Pages:
- 3435–3444
Abstract
Fog computing has emerged as a promising paradigm for meeting the low-latency, high-bandwidth needs of Smart City applications close to data sources. However, existing placement strategies often struggle to jointly optimize timely task completion, efficient resource usage and reduced energy cost. This paper proposes a multi-objective PathFinder Algorithm (PFA) that balances makespan, Fog resource utilization and end-to-end latency in a unified framework. Extensive simulations in iFogSim2 use four baselines, Random, BF-SA, PEAPM and POAPM, evaluated on makespan, power consumption and task guarantee ratio (TGR). The results show that the PFA-based method outperforms the compared approaches across varying Fog network sizes, improving power conservation and overall performance.
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References
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