{"title":"智慧城市物联网应用服务资源发放","authors":"José Santos, T. Wauters, B. Volckaert, F. Turck","doi":"10.23919/CNSM.2017.8255974","DOIUrl":null,"url":null,"abstract":"In the last years, traffic over wireless networks has been increasing exponentially, due to the impact of Internet of Things (IoT) and Smart Cities. Current networks must adapt to and cope with the specific requirements of IoT applications since resources can be requested on-demand simultaneously by multiple devices on different locations. One of these requirements is low latency, since even a small delay for an IoT application such as health monitoring or emergency service can drastically impact their performance. To deal with this limitation, the Fog computing paradigm has been introduced, placing cloud resources on the edges of the network to decrease the latency. However, deciding which edge cloud location and which physical hardware will be used to allocate a specific resource related to an IoT application is not an easy task. Therefore, in this paper, an Integer Linear Programming (ILP) formulation for the IoT application service placement problem is proposed, which considers multiple optimization objectives such as low latency and energy efficiency. Solutions for the resource provisioning of IoT applications within the scope of Antwerp's City of Things testbed have been obtained. The result of this work can serve as a benchmark in future research related to placement issues of IoT application services in Fog Computing environments since the model approach is generic and applies to a wide range of IoT use cases.","PeriodicalId":211611,"journal":{"name":"2017 13th International Conference on Network and Service Management (CNSM)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"51","resultStr":"{\"title\":\"Resource provisioning for IoT application services in smart cities\",\"authors\":\"José Santos, T. Wauters, B. Volckaert, F. Turck\",\"doi\":\"10.23919/CNSM.2017.8255974\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the last years, traffic over wireless networks has been increasing exponentially, due to the impact of Internet of Things (IoT) and Smart Cities. Current networks must adapt to and cope with the specific requirements of IoT applications since resources can be requested on-demand simultaneously by multiple devices on different locations. One of these requirements is low latency, since even a small delay for an IoT application such as health monitoring or emergency service can drastically impact their performance. To deal with this limitation, the Fog computing paradigm has been introduced, placing cloud resources on the edges of the network to decrease the latency. However, deciding which edge cloud location and which physical hardware will be used to allocate a specific resource related to an IoT application is not an easy task. Therefore, in this paper, an Integer Linear Programming (ILP) formulation for the IoT application service placement problem is proposed, which considers multiple optimization objectives such as low latency and energy efficiency. Solutions for the resource provisioning of IoT applications within the scope of Antwerp's City of Things testbed have been obtained. The result of this work can serve as a benchmark in future research related to placement issues of IoT application services in Fog Computing environments since the model approach is generic and applies to a wide range of IoT use cases.\",\"PeriodicalId\":211611,\"journal\":{\"name\":\"2017 13th International Conference on Network and Service Management (CNSM)\",\"volume\":\"111 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"51\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 13th International Conference on Network and Service Management (CNSM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/CNSM.2017.8255974\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 13th International Conference on Network and Service Management (CNSM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/CNSM.2017.8255974","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Resource provisioning for IoT application services in smart cities
In the last years, traffic over wireless networks has been increasing exponentially, due to the impact of Internet of Things (IoT) and Smart Cities. Current networks must adapt to and cope with the specific requirements of IoT applications since resources can be requested on-demand simultaneously by multiple devices on different locations. One of these requirements is low latency, since even a small delay for an IoT application such as health monitoring or emergency service can drastically impact their performance. To deal with this limitation, the Fog computing paradigm has been introduced, placing cloud resources on the edges of the network to decrease the latency. However, deciding which edge cloud location and which physical hardware will be used to allocate a specific resource related to an IoT application is not an easy task. Therefore, in this paper, an Integer Linear Programming (ILP) formulation for the IoT application service placement problem is proposed, which considers multiple optimization objectives such as low latency and energy efficiency. Solutions for the resource provisioning of IoT applications within the scope of Antwerp's City of Things testbed have been obtained. The result of this work can serve as a benchmark in future research related to placement issues of IoT application services in Fog Computing environments since the model approach is generic and applies to a wide range of IoT use cases.