Abstract: Skyline query processing has recently received a lot of attention in database community. Most related works focus on the single processor environment. However, since skyline queries are CPU-sensitive and time costly, the existing methods have prodigious limitations in real applications. Motivated by the above fact, in this paper, we propose an efficient method for parallel processing of skyline queries, called parallel algorithm for processing skyline queries (PAPSQ). The PAPSQ algorithm seamlessly combines the speciality of multidimensional data objects and the implementary advantage of universal multiprocessor systems. Specially, the PAPSQ algorithm takes the partial order lattice of skyline queries as substrate structure, and utilizes the homeomorphism evaluation of multidimensional data objects and the weighted technology to markedly improve the performance of parallel processing of skyline queries. Furthermore, detailed theoretical analyses and extensive experiments are given to demonstrate that the algorithm is both efficient and effective.