Verifiable outsourcing of constrained nonlinear programming by particle swarm optimization in cloud

• Published in: Soft computing (Berlin, Germany) Vol. 22; no. 10; pp. 3343 - 3355
• Main Authors: Xiang, Tao, Zhang, Weimin, Zhong, Shigang, Yang, Jiyun
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2018; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Cheating; Cloud computing; Computational Intelligence; Control; Convex analysis; Cryptography; Engineering; Linear programming; Mathematical Logic and Foundations; Mechatronics; Methodologies and Application; Nonlinear programming; Optimization; Outsourcing; Particle swarm optimization; Protocol; Robotics; Verification; Verifiable outsourcing; Approximate KKT conditions; Nonlinear programming; Particle swarm optimization
• ISSN: 1432-7643; 1433-7479
• DOI: 10.1007/s00500-017-2569-8

In this paper, we explore the verification problem of outsourcing constrained nonlinear programming (NLP) when it is required to be solved by particle swarm optimization (PSO) algorithm, i.e., making sure that the cloud runs PSO algorithm faithfully and returns an acceptable solution. An efficient verification scheme without any cryptographic tool is proposed. The proposed scheme involves approximate KKT conditions with the ε -KKT point in verifying the optimality of the result returned by PSO algorithm. Extensive experiments on PSO benchmarks and NLP test problems demonstrate that our proposed scheme is effective and efficient at verifying the cloud’s honesty.