Abstract
The selection of resources and scheduling in the cloud are crucial due to the involvement of various features. Scheduling an appropriate resource onto the cloud is influenced by quality of service parameters. Providing a relevant resource to the user consists mainly of three steps: (1) finding the feasible set of resources, (2) selecting the most appropriate resource from the practical set of resources, and (3) scheduling the resource to the relevant processor. Selecting a relevant resource is modeled as a multi-criteria decision-making problem. Factors like availability, trust, cost, responsiveness, reliability, and capability have effects on the resource selection. In this chapter, an efficient workflow has been put into suggestion in consideration to make a selection of the most significant resource using PROMETHEE methodology, and scheduling is performed using a non-pre-emptive priority algorithm. The choice of the optimal resource is done pivoted on the value of information that is requested by the users for all the influencing factors. The outcome of the simulation proves that the suggested workflow decreases the response time, makespan, and cost, which also maximizes the quantity of resources utilized before the deadline.
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Abbreviations
- BaTS:
-
Budget constraint scheduling
- ELECTRE:
-
Elimination and choice expressing reality
- FCFS:
-
First come, first served
- IaaS:
-
Infrastructure-as-a-service
- MLBMPSO:
-
multi-objective load balancing mutation particle swarm optimization
- NBS:
-
Nash bargaining solution
- PaaS:
-
Platform-as-a-service
- PROMETHEE:
-
Preference ranking organization method for enrichment of evaluations
- RBS:
-
Raiffa bargaining solution
- SaaS:
-
Software-as-a-service
- SLA:
-
Service-level agreement
- VoI:
-
Value of information
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Ganvir, R.S., Silas, S., Rajsingh, E.B. (2020). Preferential Resource Selection and Scheduling of Cloud Resources Pivot on Value of Information. In: Kumar, L., Jayashree, L., Manimegalai, R. (eds) Proceedings of International Conference on Artificial Intelligence, Smart Grid and Smart City Applications. AISGSC 2019 2019. Springer, Cham. https://doi.org/10.1007/978-3-030-24051-6_57
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DOI: https://doi.org/10.1007/978-3-030-24051-6_57
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