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Wireless Communications and Mobile Computing
Volume 2017 (2017), Article ID 6128437, 11 pages
Research Article

Scalable and Soundness Verifiable Outsourcing Computation in Marine Mobile Computing

1Department of Computer Science and Technology, East China Normal University, Shanghai, China
2The State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an, China
3College of Information Technology, Shanghai Ocean University, Shanghai, China
4Westone Cryptologic Research Center, Beijing, China

Correspondence should be addressed to Haifeng Qian

Received 29 June 2017; Accepted 13 September 2017; Published 10 December 2017

Academic Editor: Zhipeng Cai

Copyright © 2017 Kai Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Outsourcing computation with verifiability is a merging notion in cloud computing, which enables lightweight clients to outsource costly computation tasks to the cloud and efficiently check the correctness of the result in the end. This advanced notion is more important in marine mobile computing since the oceangoing vessels are usually constrained with less storage and computation resources. In such a scenario, vessels always firstly outsource data set and perform a function computing over them or at first outsource computing functions and input data set into them. However, vessels may choose which delegation computation type to outsource, which generally depends on the actual circumstances. Hence, we propose a scalable verifiable outsourcing computation protocol () in marine cloud computing at first and extract a single-mode version of it (), where both protocols allow anyone who holds verification tokens to efficiently verify the computed result returned from cloud. In this way, the introduced “scalable” property lets vessels adjust the protocol to cope with different delegation situations in practice. We additionally prove both and achieving selective soundness in the random oracle model and evaluate their performance in the end.