Abstract
In this paper, we have proposed the intimate environment of multiblockchain optimization algorithm using big data inquiry to mend the effectiveness of association query handling among numerous multihoming blockchains by implementing the big data system. This technique adds semantic evidences to the old-styled multiblockchain prototype and constructs a semantic model of multiblockchain that delivers a foundation for linking queries among the various blockchain multihoming system in big data. On the base of this model, distributed databases have index arrangement, and a linking index arrangement is proposed among the numerous blockchains, with several attributes linked to these blockchains employed to improve the efficacy of linking calculation. Besides, the communication cost is d for data communication. On this foundation, a multichain linking enquiry algorithm based on optimization is anticipated to progress the productivity of multiblockchain connection queries. To conclude, two genuine big data community sets of data are used to conduct experiments on. The associating index arrangement among blockchains is unchanging and is equated with the old-styled direct linking inquiry operation. The multiblockchain linking query method of optimization shortens the probe processing procedure. It acquires the query outcomes directly by retrieving the linking index, sinking the local calculating ability, system overhead, and illuminating query efficacy.