{"title":"雾计算环境下的服务布局","authors":"H. K. Apat, B. Sahoo, P. Maiti","doi":"10.1109/ICIT.2018.00062","DOIUrl":null,"url":null,"abstract":"Due to the advent of Internet of Things(IoT) plethora of services has been emerged and to perpetuate all these services using cloud computing paradigm is really tiresome. A new promising service provider called as Fog computing came into the picture where the distance between Iot and edge device is small to provide the services efficiently to the end users. There are different considerable factors like service response time, and expected QoS must met without violating other resource constraints. In this paper we try to layout an architecture which is based on the combination of cloud and fog by introducing a middleware called as cloud fog control middleware, which manages the service request according to some constraints. By using this architecture we can maximize the advantages of next generation computer system, however the architecture require new strategies to manage the mapping of services to resources. Despite several Heuristic and Meta Heuristic techniques has been proposed by different authors to solve the service placement in fog computing with considering different parameters like quality of service(QoS), Latency, etc. In this paper we are trying to minimize the energy consumption in fog computing paradigm by formulating the service placement plan in order to utilize the resources efficiently by considering the Active and Idle state of machine. First we calculate the energy consumption by the application(number of tasks) requesting for a particular service. Undoubtedly the service placement problem is a combinatorial optimization problem. The optimal solution obtained distribute the load to some other fog node by appropriate placement of service which leads to reduce the over heat generated by a particular fog node. In this way we can achieve energy minimization in fog computing.","PeriodicalId":221269,"journal":{"name":"2018 International Conference on Information Technology (ICIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Service Placement in Fog Computing Environment\",\"authors\":\"H. K. Apat, B. Sahoo, P. Maiti\",\"doi\":\"10.1109/ICIT.2018.00062\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the advent of Internet of Things(IoT) plethora of services has been emerged and to perpetuate all these services using cloud computing paradigm is really tiresome. 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引用次数: 7
摘要
由于物联网(IoT)的出现,出现了大量的服务,使用云计算范式来延续所有这些服务确实令人厌烦。一种名为“雾计算”的新型服务提供商出现了,它可以将物联网与边缘设备之间的距离缩小,从而有效地为最终用户提供服务。有不同的重要因素,如服务响应时间,预期的QoS必须在不违反其他资源约束的情况下满足。本文通过引入云雾控制中间件(cloud fog control middleware),根据一定的约束条件对服务请求进行管理,尝试构建一个基于云雾结合的体系结构。通过使用这种体系结构,我们可以最大限度地发挥下一代计算机系统的优势,但是这种体系结构需要新的策略来管理服务到资源的映射。尽管不同的作者提出了几种启发式和元启发式技术来解决雾计算中的服务放置问题,并考虑了不同的参数,如服务质量(QoS)、延迟等。在雾计算范式中,我们考虑到机器的活动和空闲状态,通过制定服务放置计划来有效地利用资源,从而尽量减少能量消耗。首先,我们计算请求特定服务的应用程序(任务数)的能耗。服务配置问题无疑是一个组合优化问题。所得到的最优解通过适当的服务布局将负载分配到其他雾节点,从而减少特定雾节点产生的过热。通过这种方法,我们可以在雾计算中实现能量最小化。
Due to the advent of Internet of Things(IoT) plethora of services has been emerged and to perpetuate all these services using cloud computing paradigm is really tiresome. A new promising service provider called as Fog computing came into the picture where the distance between Iot and edge device is small to provide the services efficiently to the end users. There are different considerable factors like service response time, and expected QoS must met without violating other resource constraints. In this paper we try to layout an architecture which is based on the combination of cloud and fog by introducing a middleware called as cloud fog control middleware, which manages the service request according to some constraints. By using this architecture we can maximize the advantages of next generation computer system, however the architecture require new strategies to manage the mapping of services to resources. Despite several Heuristic and Meta Heuristic techniques has been proposed by different authors to solve the service placement in fog computing with considering different parameters like quality of service(QoS), Latency, etc. In this paper we are trying to minimize the energy consumption in fog computing paradigm by formulating the service placement plan in order to utilize the resources efficiently by considering the Active and Idle state of machine. First we calculate the energy consumption by the application(number of tasks) requesting for a particular service. Undoubtedly the service placement problem is a combinatorial optimization problem. The optimal solution obtained distribute the load to some other fog node by appropriate placement of service which leads to reduce the over heat generated by a particular fog node. In this way we can achieve energy minimization in fog computing.