文献类型：期刊文献

英文题名：A Set-Associated Bin Packing Algorithm with Multiple Objectives in the Cloud

作者：Luo, Fei[1]; Gu, Chunhua[1]

机构：[1] School of Information and Engineering, East China University of Science and Technology, Shanghai, China

年份：2018

卷号：10971 LNCS

起止页码：3

外文期刊名：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

收录：EI(收录号：20182805525333)

语种：英文

摘要：The bin packing problem (BPP) is NP-hard and it is widely studied due to its various applications, where the initial sole object is to find a minimum number of bins for the items. This paper applies the BPP in the cloud, and tries to attain multiple objectives, such as minimum used bins, minimum packing time and load balance for the bins. Therefore, a set-associative bin packing algorithm is proposed, where the item set is first divided into two sets with descending order, and then a two-way set-associative mapping process is used to combine the elements in divided sets and pack them into a suitable bin. The packing process is iterated until all the items are resolved. With different performance indicators, experiments and analysis are carried out by the comparison with the traditional typical packing algorithms, which verifies the efficiency of the algorithm. ? 2018, Springer International Publishing AG, part of Springer Nature.