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Agent-based fuzzy constraint-directed negotiation for service level agreements in cloud computing

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Abstract

Establishing a service level agreement (SLA) between a cloud provider and a cloud consumer is becoming increasingly critical: consumers expect a specified quality of service (QoS) for their cloud applications, and providers must be able to guarantee that the agreed-upon QoS will be maintained. These concepts require the SLA negotiation to be performed in a manner whereby a provider and a consumer can effectively bargain on various QoS preferences, such as price, response time and service level. This paper presents a novel agent-based fuzzy constraint-directed negotiation (AFCN) model for SLA negotiation. It provides a framework for integrating time, resource (market) and behavioral factors into the decision making process for service level agreements and cloud load balancing. The proposed AFCN model supports an iterative many-to-many bargaining negotiation infrastructure that is a fully distributed and autonomous approach and that does not require a broker to coordinate the negotiation process. The novelty of the proposed model is that it uses the concept of a fuzzy membership function to represent imprecise QoS preferences. This added information sharing is critical for the effectiveness of distributed coordination. It can not only speed up the convergence but also enforce global consistency through iterative exchanges of offers and counter-offers with limited information sharing and without privacy breaches. To consider the behavior of different agents, the AFCN model can also flexibly adopt different negotiation strategies such as the competitive, win-win, and collaborative strategies in different cloud computing environments. The experimental results demonstrate that the proposed model consistently outperforms other agent-based SLA negotiation models in terms of the degree of satisfaction, the ratio of successful negotiation, the buying price of the consumer agent (CA), the revenue of the provider agent (PA), and the convergence speed. Consequently, the proposed AFCN is both flexible and useful for fully distributed SLA negotiations.

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Acknowledgements

This study was partially supported by the Taiwan Ministry of Science and Technology Grants MOST 104-2221-E-155-013, MOST 104-3115-E-155-002, MOST 105-2118-E-155-010,and MOST 106-2118-E-155-007, and by Grant 2016Y0079 from the Natural Science Foundation of Fujian Province, China.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Yuan Ze University, Chungli, Taiwan

    Lin Li & K. Robert Lai

  2. Department of Information Management, Yuan Ze University, Chungli, Taiwan

    Chia-Yu Hsu & Liang-Chih Yu

  3. Innovation Center for Big Data and Digital Convergence, Yuan Ze University, Chungli, Taiwan

    Chia-Yu Hsu, Liang-Chih Yu & K. Robert Lai

  4. School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China

    Lin Li

  5. School of Science and Technology, Singapore University of Social Sciences, Singapore, Singapore

    Chee Shin Yeo

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  1. Lin Li
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  2. Chee Shin Yeo
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Correspondence to K. Robert Lai.

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Li, L., Yeo, C.S., Hsu, CY. et al. Agent-based fuzzy constraint-directed negotiation for service level agreements in cloud computing. Cluster Comput 21, 1349–1363 (2018). https://doi.org/10.1007/s10586-017-1248-y

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  • DOI: https://doi.org/10.1007/s10586-017-1248-y

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