Genetic optimization–based scheduling in maritime cyber physical systems
In this article, we attempt to solve the issue of optimal scheduling for vessels monitoring video data uploading in maritime cyber physical systems, during the period of sailing from the origin port to destination port. We consider the terrestrial infrastructure-based networking, delivering video pa...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2017-07-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147717717163 |
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| _version_ | 1832556791971446784 |
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| author | Tingting Yang Hailong Feng Jian Zhao Ruilong Deng Ying Wang Zhou Su |
| author_facet | Tingting Yang Hailong Feng Jian Zhao Ruilong Deng Ying Wang Zhou Su |
| author_sort | Tingting Yang |
| collection | DOAJ |
| description | In this article, we attempt to solve the issue of optimal scheduling for vessels monitoring video data uploading in maritime cyber physical systems, during the period of sailing from the origin port to destination port. We consider the terrestrial infrastructure-based networking, delivering video packets assisted by the shoreside infostations to the authorities on land. Each video packet has respective elements (i.e. release time, deadline, processing time, and weight) to describe, in which deadline is utilized to demonstrate the time domain limitation before that to upload it successfully. In order to cope with the computation complexity of traditional scheduling algorithms in intermittent infostations scenario, time-capacity mapping method is exploited to transfer it to a continue scenario when classic scheduling algorithms could be utilized with lower time complexity. An ingenious mathematic job-machine scheduling formulation is indicated with the goal of minimizing the total penalties of tardiness of uploaded video packets, taking into account the tardiness and the weights of jobs simultaneously. A genetic based algorithm, as well as an improved genetic algorithm–based optimization scheme, is proposed to target this optimization formulation. Specially, the genetic based algorithm as well as the improved genetic based algorithm are described in detail, including a novel chromosome representation, a heuristic initialization procedure, as well as a modified crossover and mutation process. The effectiveness of the proposed schemes is verified by the simulation results. |
| format | Article |
| id | doaj-art-ff5716a00b1a403fbbe5be85ef82280f |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2017-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-ff5716a00b1a403fbbe5be85ef82280f2025-02-03T05:44:33ZengWileyInternational Journal of Distributed Sensor Networks1550-14772017-07-011310.1177/1550147717717163Genetic optimization–based scheduling in maritime cyber physical systemsTingting Yang0Hailong Feng1Jian Zhao2Ruilong Deng3Ying Wang4Zhou Su5Navigation College, Dalian Maritime University, Dalian, ChinaNavigation College, Dalian Maritime University, Dalian, ChinaNavigation College, Dalian Maritime University, Dalian, ChinaDepartment of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, CanadaInstitute of Information Science and Technology, Dalian Maritime University, Dalian, ChinaSchool of Mechatronic Engineering and Automation, Shanghai University, Shanghai, ChinaIn this article, we attempt to solve the issue of optimal scheduling for vessels monitoring video data uploading in maritime cyber physical systems, during the period of sailing from the origin port to destination port. We consider the terrestrial infrastructure-based networking, delivering video packets assisted by the shoreside infostations to the authorities on land. Each video packet has respective elements (i.e. release time, deadline, processing time, and weight) to describe, in which deadline is utilized to demonstrate the time domain limitation before that to upload it successfully. In order to cope with the computation complexity of traditional scheduling algorithms in intermittent infostations scenario, time-capacity mapping method is exploited to transfer it to a continue scenario when classic scheduling algorithms could be utilized with lower time complexity. An ingenious mathematic job-machine scheduling formulation is indicated with the goal of minimizing the total penalties of tardiness of uploaded video packets, taking into account the tardiness and the weights of jobs simultaneously. A genetic based algorithm, as well as an improved genetic algorithm–based optimization scheme, is proposed to target this optimization formulation. Specially, the genetic based algorithm as well as the improved genetic based algorithm are described in detail, including a novel chromosome representation, a heuristic initialization procedure, as well as a modified crossover and mutation process. The effectiveness of the proposed schemes is verified by the simulation results.https://doi.org/10.1177/1550147717717163 |
| spellingShingle | Tingting Yang Hailong Feng Jian Zhao Ruilong Deng Ying Wang Zhou Su Genetic optimization–based scheduling in maritime cyber physical systems International Journal of Distributed Sensor Networks |
| title | Genetic optimization–based scheduling in maritime cyber physical systems |
| title_full | Genetic optimization–based scheduling in maritime cyber physical systems |
| title_fullStr | Genetic optimization–based scheduling in maritime cyber physical systems |
| title_full_unstemmed | Genetic optimization–based scheduling in maritime cyber physical systems |
| title_short | Genetic optimization–based scheduling in maritime cyber physical systems |
| title_sort | genetic optimization based scheduling in maritime cyber physical systems |
| url | https://doi.org/10.1177/1550147717717163 |
| work_keys_str_mv | AT tingtingyang geneticoptimizationbasedschedulinginmaritimecyberphysicalsystems AT hailongfeng geneticoptimizationbasedschedulinginmaritimecyberphysicalsystems AT jianzhao geneticoptimizationbasedschedulinginmaritimecyberphysicalsystems AT ruilongdeng geneticoptimizationbasedschedulinginmaritimecyberphysicalsystems AT yingwang geneticoptimizationbasedschedulinginmaritimecyberphysicalsystems AT zhousu geneticoptimizationbasedschedulinginmaritimecyberphysicalsystems |