Multi-agent system-based fuzzy constraints offer negotiation of workflow scheduling in Fog-Cloud environment

This paper presents the multi-agent system fuzzy-constraints offer negotiation of Workflow Scheduling in Fog-Cloud environment, called (Fuzzy-Cone) approach, to solve the workflow scheduling problem with conflicting constraints in Fog-Cloud IT infrastructures. A client agent and a supplier agent are created to represent the client and supplier sides respectively, with a win–win strategy based on negotiation. The novelty of this approach is the design of a multi-agent system with agents supervised by a strategy based on a fuzzy inference system modeling all possible cases, thus facilitating decision-making. The workflow scheduling problem is treated as a set of fuzzy constraint satisfaction problems (FCSP). Each agent has an FCSP modeling a set of fuzzy constraints based on the negotiation with other agents by proposing offers or counter-offers. The proposed negotiation approach is implemented to respect all the imposed restrictions and represent the imprecise preferences of the approach entities by pre-defining the fuzzy constraints and optimizing the workflow scheduling solution in terms of time and cost. of compiling. The proposed approach has been tested with different experiments and compared with state-of-the-art algorithms. The experimental results show that the negotiation between the solutions, of mutually satisfactory scheduling, considerably improved the values of time and cost of compilation, while respecting the set of the imposed constraints. The proposed approach achieves a workflow scheduling scheme that reduces compilation time by 37% and increases cost by 6% compared to state-of-the-art algorithms. The different solutions we have proposed respect the constraints of time and budget by executing workflows of different sizes in reasonable time and cost.