Study on Secure Dynamic Covering Algorithm for E-Logistics Information in a Cloud Computing Platform

Abstract

For traditional coverage method, local adaptive weighted search is adopted for subspace reconstruction of e-logistics information, which requires significant iterative computations and leads to large coverage errors and unsatisfactory results. This paper proposes a secure dynamic covering algorithm for e-logistics information based on the basis of directional clustering for the envelope of optimization solution vectors. A data network distribution model of e-logistics information on a cloud computing platform is constructed to extract features of e-logistics information and to construct time series of information flows. The directional clustering algorithm for the envelope of optimization solution vectors is introduced to schedule features of e-logistics information. The experimental results show that the proposed algorithm has higher coverage rate, smaller error, and increases performance of e-logistics information transmission and higher application value on a cloud computing platform.