Special issue on recent advances in mobile service computing and applications
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GUEST EDITORIAL
Special issue on recent advances in mobile service computing and applications Honghao Gao1 • Yuyu Yin2 • Yucong Duan3
Ó Springer Science+Business Media, LLC, part of Springer Nature 2019
With the development of 5G technology and edge computing, the mobile application has greatly facilitated in our daily life. As core problems, how to make mobile service computing smart and trust and how to provide high-quality services for mobile applications are increasing attention from both the industry and academia. This special issue aims to present the state-of-the-art research on mobile service computing, as well as to organize a forum for experts to disseminate their recent advances and views on future perspectives in the field of mobility, limited capability, restricted power, unguaranteed security. After strict review, this special issue features six selected papers with high quality. The first paper titled Local community detection for multi-layer mobile network based on the trust relation proposes a local community detection algorithm for multilayer complicated network based on the trust relation (MTLCD) to constrain the node tensor. They compare the performance of the proposed algorithm with other classic network clustering algorithms, such as GL, LART. Their algorithm can be used to effectively identify the local community. The second paper titled Distributed Machine Learning Load Balancing Strategy in Cloud Computing Services implements an A-DSP model based on AdaptFR load
& Honghao Gao [email protected] Yuyu Yin [email protected] Yucong Duan [email protected] 1
Computing Center, Shanghai University, Shanghai, China
2
College of Computer, Hangzhou Dianzi University, Hangzhou, China
3
College of Information Science and Technology, Hainan University, Haikou, China
balancing strategy. The method can dynamically adjust the communication strategy between the computing node and the parameter server according to the performance of the cluster nodes. Thus, this model improves the training speed. The third paper titled Computation Offloading for Multimedia Workflows with Deadline Constraints in Cloudlet-Based Mobile Cloud proposes a multimedia workflow offloading method in the cloudlet-based MCC environment. They first discuss how to model multimedia applications and analyze the model from two aspects of time and energy consumption. And then, they use the NSDE algorithm to optimize the model and minimize the energy consumption with the constraints of meeting the deadline of each multimedia workflow. The fourth paper titled Privacy Preserving Semantic Trajectory Data Publishing for Mobile Location-based Services considers the POI information and the users’ motion modes such as walking, running, driving. The semantic trajectory anonymizing based on the k-anonymity model is proposed. It can form sensitive areas containing k-1 POI points that are similar to the sensitive points. Then, trajectory ambiguity is executed based on the motion modes, road ne
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