{"title":"Towards Policy-based Task Self-Reallocation in Dynamic Edge Computing Systems","authors":"Victor Pazmino Betancourt, Bo Liu, Jürgen Becker","doi":"10.1109/INDIN45523.2021.9557374","DOIUrl":null,"url":null,"abstract":"Innovations and novel applications in the area of the Industrial Internet of Things (IIoT) are driven by the technical possibilities of digitalization and edge computing. This leads to rapid advancements and enormous time pressure in the development and operation of new functionalities. Edge computing systems with self-x functionalities are able to react independently to changes in operation and thus mitigate this time pressure problem. The autonomous response during the operation of the self-x system must nevertheless remain compliant with the original system design requirements. A distributed edge computing system has complex requirements in different components and at different levels of the system. This leads to a major challenge when describing these requirements and constraints in such a way that they can be automatically checked and fulfilled during operation. This paper proposes a model-based description of policies that is used as a basis for reallocation of services during operation. The approach was tested and evaluated using an IIoT use case of a camera-based monitoring system for smart construction sites. Our results show that, based on the policy description, it is possible to automatically compute the reallocation when changes occur in the system, without any intervention from the developer. With this self-x capability, the system can remain in operation longer. Overall, this helps to reduce time pressure in the development, deployment and maintenance of new innovations and applications in the field of the Industrial Internet of Things.","PeriodicalId":370921,"journal":{"name":"2021 IEEE 19th International Conference on Industrial Informatics (INDIN)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 19th International Conference on Industrial Informatics (INDIN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDIN45523.2021.9557374","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Innovations and novel applications in the area of the Industrial Internet of Things (IIoT) are driven by the technical possibilities of digitalization and edge computing. This leads to rapid advancements and enormous time pressure in the development and operation of new functionalities. Edge computing systems with self-x functionalities are able to react independently to changes in operation and thus mitigate this time pressure problem. The autonomous response during the operation of the self-x system must nevertheless remain compliant with the original system design requirements. A distributed edge computing system has complex requirements in different components and at different levels of the system. This leads to a major challenge when describing these requirements and constraints in such a way that they can be automatically checked and fulfilled during operation. This paper proposes a model-based description of policies that is used as a basis for reallocation of services during operation. The approach was tested and evaluated using an IIoT use case of a camera-based monitoring system for smart construction sites. Our results show that, based on the policy description, it is possible to automatically compute the reallocation when changes occur in the system, without any intervention from the developer. With this self-x capability, the system can remain in operation longer. Overall, this helps to reduce time pressure in the development, deployment and maintenance of new innovations and applications in the field of the Industrial Internet of Things.