A Novel Range Search Scheme Based on Frequent Computing for Edge-Cloud Collaborative Computing in CPSS

Abstract

Due to the rapid advances of Information and Communication Technologies (ICT), especially 5G and Artificial Intelligence (AI), the Internet of Everything is gradually becoming a reality, and human beings living environments are becoming smarter and smarter. Every day there will be generated large amounts of data in Humans-Machines-Things hybrid space, which is also called Cyber-Physical-Social Systems (CPSSs). Today, the city we live in has become a data-driven society. However, how to effectively mine valuable information from these massive data to provide proactive and personalized services for human beings is a challenging problem. Thus, top-k search remains an important topic of ongoing research. In this paper, we focus on a basic problem of geo-tagged data: find the top-k frequent terms among the geo-tagged data in a specific region from the cloud. We first construct a Region Tree Index (RTI) for geo-tagged data. Then the list storage structure is proposed to Store Sorted Terms and Weights (SSTW) in RTI. And then an efficient kTermsSearch algorithm is presented to compute top-k frequent terms in a given region. Finally, extensive experiments verify the validity of the proposed scheme. INDEX TERMS Cyber-physical-social system (CPSS), frequent computing, top-k search, edge-cloud collaborative computing.

Privacy‐Guarding Optimal Route Finding with Support for Semantic Search on Encrypted Graph in Cloud Computing Scenario

“…But the server on CCP is not completely honest and trustworthy, the privacy and security issues of the outsourcing graph data need to be considered and handled. Encrypting the outsourcing graph data is an effective and commonly used method before they are outsourced to CCP [8]. However, it is not easy for data customers to manipulate and further use the encrypted outsourcing graph data.…”