Gossip-based Hybrid Multi-attribute Overlay for Resource Discovery in Federated Clouds

Federated clouds establish a model for independent cloud providers to cooperate and share resource to cope with unforeseen demand loads. One of the challenges in federated clouds is how to find suitable virtual machines to locate resource requests, with constrains of multiple resource attributes. This paper proposes a Gossip-based Hybrid Multi-attribute Overlay (GHMO) for effective resource discovery in federated clouds. GHMO enhances structured overlay with gossip protocol, expanding possible routing ranges to improve the efficiency multi-attribute search. A weight overlay is introduced in the case of routing costs among federated clouds, and an improved neighbor selection strategy is raised to reduce routing costs in process of multi-attribute search. Experimental evaluations show that the performance of the proposed approach is acceptable and stable, and the routing hop and cost is reduced compared with other multi-attribute search methods.