A green, energy, and trust-aware multi-objective cloud coalition formation approach

摘要

The workload of cloud providers is often uncertain due to the dynamic and varied client demands, thus presenting a significant challenge. If cloud providers fail to meet changing demands during peak hours, they may experience service requests' delays and rejections, damaging both their reputation and their profit margin. The idea of cloud federations is contemplated as a solution to this challenge by allowing a group of cloud providers to combine their resources, as and when required, to satisfy client requests dynamically. Despite the merits of the existing cloud federation approaches, they suffer from several limitations, such as performance issues, the inability to converge to a solution in complex scenarios, the lack of consideration of SLA requirements during the federation formation phase, and the lack of flexibility offered to clients to prioritize specific objectives during the formation of the cloud federation. This work addresses these deficiencies by presenting a green, practical, and customizable SLA-based approach to cloud federation formation. Inspired by social gaming, the proposed approach can rapidly form a stable coalition of cloud providers able to fulfill client requests, while ensuring the satisfaction of SLA requirements in terms of performance, energy consumption, CO_2 emissions, and providers' trustfulness. At the heart of this approach lies a new coalition formation algorithm, dubbed the "multi-criterion coalition formation algorithm (MCCF)." Unlike existing collation formation algorithms, the MCCF algorithm offers clients the flexibility to prioritize the objectives used for cloud federation formation. Based on those preferences, the MCCF algorithm generates stable SLA-aware groups of cloud providers that dynamically adapt to network changes using a self-healing process. The MCCF algorithm has been implemented and extensively tested using a wide range of scenarios, and its performance was compared with that of two state of the art approaches: The optimal approach and the split-and-merge approach. The results show that the MCCF algorithm outperforms the optimal and the split-and-merge approaches in terms of coalition size, individual providers' payoff, and mistrust cost. Moreover, the proposed approach yields a zero % request rejection rate and an execution time that is 8 to 16 times faster than the split-and-merge and optimal approaches, while enabling a reduction of the Carbon footprint of the cloud coalition operations. Owing to these advantages and its ability to offer a flexible and customizable solution to clients, the MCCF algorithm represents a promising and environmentally conscious cloud collation formation approach that is ideal for real-time applications and practical cloud deployments.