Resource-Saving Multiobjective Task Distribution in the Fog- and Edge-Robotics

Abstract

In the current paper the question of the resource-saving tasks distribution is under consideration. As a wide range of computational tasks in robotics performs in a distributed manner in fog- and edge network layers, a lot of tasks are performed by devices with a relatively low computational complexity. At the same time, data preprocessing, machine learning, SLAM problems are computationally hard, and so the participants of the computational process can be overloaded, the latter causes the average residual life deterioration. In this paper a problem of resource-saving distribution task is formulated as structural-parametric multiobjective one, with paying attention to the workload of nodes, which transmit data. The general solution technique is proposed based on time constraints estimations and on the simulated annealing. Some selected experimental results are presented, and some comparisons with the previously conducted results are made.