IoT Service Placement Optimization in Fog Computing using LinearProgramming: A Comparative Study

Optimizing IoT service placement in fog computing using linear programmingfocuses on optimizing IoT service placement in fog computing environments usinglinear programming techniques. Fog computing, as a decentralized computinginfrastructure, aims to reduce latency and improve quality of service (QoS) forreal-time IoT applications by providing storage and computing space adjacent toIoT devices. The abstract discusses the challenges of deploying IoT services in fognodes and the need for optimization to balance various objectives such asbandwidth cost, energy consumption, delay minimization, load balancing, QoS,and security. The use of linear programming models, such as mixed integer linearprogramming (MILP) and integer linear programming (ILP), highlights thesechallenges. The abstract also emphasizes the comparative study of different linearprogramming approaches and their effectiveness in optimizing the deployment ofIoT services in fog computing environments, taking into account criteria such aslatency, energy consumption and cost efficiency[۲,۳,۴,۵,۷].

کلیدواژه ها:

Fog Computing ، linear programming ، IoT service placementIntroduction: