Cloud computing is a new computing model. The resource monitoring tools are immature compared to traditional distributed computing and grid computing. In order to better monitor the virtual resource in cloud computing...Cloud computing is a new computing model. The resource monitoring tools are immature compared to traditional distributed computing and grid computing. In order to better monitor the virtual resource in cloud computing, a periodically and event-driven push （PEP） monitoring model is proposed. Taking advantage of the push and event-driven mechanism, the model can provide comparatively adequate information about usage and status of the resources. It can simplify the communication between Master and Work Nodes without missing the important issues happened during the push interval. Besides, we develop ＂mon＂ to make up for the deficiency of Libvirt in monitoring of virtual CPU and memory.展开更多
With the vigorous development of mobile networks,the number of devices at the network edge is growing rapidly and the massive amount of data generated by the devices brings a huge challenge of response latency and com...With the vigorous development of mobile networks,the number of devices at the network edge is growing rapidly and the massive amount of data generated by the devices brings a huge challenge of response latency and communication burden.Existing resource monitoring systems are widely deployed in cloud data centers,but it is difficult for traditional resource monitoring solutions to handle the massive data generated by thousands of edge devices.To address these challenges,we propose a super resolution sensing(SRS)method for distributed resource monitoring,which can be used to recover reliable and accurate high‑frequency data from low‑frequency sampled resource monitoring data.Experiments based on the proposed SRS model are also conducted and the experimental results show that it can effectively reduce the errors generated when recovering low‑frequency monitoring data to high‑frequency data,and verify the effectiveness and practical value of applying SRS method for resource monitoring on edge clouds.展开更多
In the 21st century, the rapid development of global science and technology has directly promoted the popularization of information technology. All walks of life pay more and more attention to the application of infor...In the 21st century, the rapid development of global science and technology has directly promoted the popularization of information technology. All walks of life pay more and more attention to the application of information technology, and deeply understand and actively welcome the arrival of the information age. GPS technology is one of the advanced science and technology in the world, which consists of space part (GPS satellite), ground monitoring part and user part, and can provide users with high-efficiency and high-precision (up to millimeter level) rapid measurement service. In recent years, this technology has been widely used in hydrology and water resources monitoring. It can realize real-time monitoring of hydrology and water resources, and greatly shorten the surveying and mapping cycle of underwater topography, and plays a key role in hydrology and water resources monitoring. This paper mainly studies the basic principle and application advantages of GPS technology, discusses the specific application of GPS technology in hydrology and water resources monitoring, and provides reference for people to apply GPS technology to hydrology and water resources monitoring.展开更多
Water resource is an indispensable resource in peoples life and work. With the deepening of the concept of environmental protection, people have also deeply realized the importance of water environment protection, and...Water resource is an indispensable resource in peoples life and work. With the deepening of the concept of environmental protection, people have also deeply realized the importance of water environment protection, and actively carried out the development, utilization and protection of water resources, which can reduce waste while improving the efficiency of water resources. In recent years, the overall scale of global water resources has declined, which also has a certain impact on the sustainable development of social economy. After water resources monitoring, we can fully understand the distribution of water resources, water quality and other aspects, so that we can timely understand the problems and effectively control them. In order to better ensure the effect of hydrological and water resources monitoring, we should fully understand the actual situation of water environment, adopt reasonable hydrological and water resources monitoring technology and equipment, and establish a hydrological and water resources monitoring system, so as to ensure that hydrological and water resources monitoring can be carried out smoothly, improve the efficiency of water resources utilization, and better promote the development of water resources development.展开更多
To protect mining areas from electrical fire, it is very important to install electrical nre momtormg system to ensure safety in development of mineral resources and for buildings. In this paper, design for electrical...To protect mining areas from electrical fire, it is very important to install electrical nre momtormg system to ensure safety in development of mineral resources and for buildings. In this paper, design for electrical fire monitoring and detection system with optional sensor modules has been proposed. In addition, necessity and suitability of electrical fire monitoring and detection system with optional sensor modules in mining areas have been reviewed. The designed electrical fire monitoring and detection system suit- able for work environment of mining industry is composed by host-computer monitoring software and slave-computer detectors. Monitoring detectors are manufactured by using embedded technology. Exter- nal shells deployed have superior enclosure performances and explosion-proof properties. It is easy to install and maintain the system. In general, the system has reached, or even exceeded standards specified in national standards for performances and appearances of such devices. Test results show application of electrical fire monitoring and detection system can effectively enhance monitoring intensity over the mining areas and provide reliable guarantee to ensure orderly development of mineral resources and to protect physical and property safety of citizens in these areas.展开更多
With the rapid development of the economy in China, the seismic network has been changing rapidly, in that the capability of instruments, technological systems and network density are approaching those of developed co...With the rapid development of the economy in China, the seismic network has been changing rapidly, in that the capability of instruments, technological systems and network density are approaching those of developed countries and a large quantity of observation data has been accumulated. How to apply these resources to economic construction and public safety has become an important issue worth studying. In order to improve earthquake prediction and earthquake emergency response, it is suggested in this paper that extracting valuable precursor information, improving earthquake rapid reporting ability and extending rapid intensity reporting function are key issues. Integrating network resources, building unified standards and a multifunction seismic monitoring network are preconditions of establishing a public safety service platform and earthquake observation resources will contribute significantly to the fields of engineering, ocean, meteorology, and environmental protection. Thus, the future directions of the development of the seismic network are exploring monitoring resources, enhancing independent innovation, constructing a technological platform and enlarging the service field.展开更多
Cloud computing has recently emerged as a leading paradigm to allow customers to run their applications in virtualized large-scale data centers. Existing solutions for monitoring and management of these infrastructure...Cloud computing has recently emerged as a leading paradigm to allow customers to run their applications in virtualized large-scale data centers. Existing solutions for monitoring and management of these infrastructures consider virtual machines （VMs） as independent entities with their own characteristics. However, these approaches suffer from scalability issues due to the increasing number of VMs in modern cloud data centers. We claim that scalability issues can bc addressed by leveraging the similarity among VMs behavior in terms of resource usage patterns. In this paper we propose an automated methodology to cluster VMs starting from the usage of multiple resources, assuming no knowledge of the services executed on them. The innovative contribution of the proposed methodology is the use of the statistical technique known as principal component analysis （PCA） to automatically select the most relevant information to cluster similar VMs. We apply the methodology to two case studies, a virtualized testbed and a real enterprise data center. In both case studies, the automatic data selection based on PCA allows us to achieve high performance, with a percentage of correctly clustered VMs between 80% and 100% even for short time series （1 day） of monitored data. Furthermore, we estimate the potential reduction in the amount of collected data to demonstrate how our proposal may address the scalability issues related to monitoring and management in cloud computing data centers.展开更多
基金Project supported by the Shanghai Leading Academic Discipline Project(Grant No.J50103)the Ph D Programs Foundation of Ministry of Education of China(Grant No.200802800007)+1 种基金the Key Laboratory of Computer System and Architecture(Institute of Computing Technology,Chinese Academy of Sciences)the Innovation Project of Shanghai Municipal Education Commission(Grant No.11YZ09)
文摘Cloud computing is a new computing model. The resource monitoring tools are immature compared to traditional distributed computing and grid computing. In order to better monitor the virtual resource in cloud computing, a periodically and event-driven push （PEP） monitoring model is proposed. Taking advantage of the push and event-driven mechanism, the model can provide comparatively adequate information about usage and status of the resources. It can simplify the communication between Master and Work Nodes without missing the important issues happened during the push interval. Besides, we develop ＂mon＂ to make up for the deficiency of Libvirt in monitoring of virtual CPU and memory.
文摘With the vigorous development of mobile networks,the number of devices at the network edge is growing rapidly and the massive amount of data generated by the devices brings a huge challenge of response latency and communication burden.Existing resource monitoring systems are widely deployed in cloud data centers,but it is difficult for traditional resource monitoring solutions to handle the massive data generated by thousands of edge devices.To address these challenges,we propose a super resolution sensing(SRS)method for distributed resource monitoring,which can be used to recover reliable and accurate high‑frequency data from low‑frequency sampled resource monitoring data.Experiments based on the proposed SRS model are also conducted and the experimental results show that it can effectively reduce the errors generated when recovering low‑frequency monitoring data to high‑frequency data,and verify the effectiveness and practical value of applying SRS method for resource monitoring on edge clouds.
文摘In the 21st century, the rapid development of global science and technology has directly promoted the popularization of information technology. All walks of life pay more and more attention to the application of information technology, and deeply understand and actively welcome the arrival of the information age. GPS technology is one of the advanced science and technology in the world, which consists of space part (GPS satellite), ground monitoring part and user part, and can provide users with high-efficiency and high-precision (up to millimeter level) rapid measurement service. In recent years, this technology has been widely used in hydrology and water resources monitoring. It can realize real-time monitoring of hydrology and water resources, and greatly shorten the surveying and mapping cycle of underwater topography, and plays a key role in hydrology and water resources monitoring. This paper mainly studies the basic principle and application advantages of GPS technology, discusses the specific application of GPS technology in hydrology and water resources monitoring, and provides reference for people to apply GPS technology to hydrology and water resources monitoring.
文摘Water resource is an indispensable resource in peoples life and work. With the deepening of the concept of environmental protection, people have also deeply realized the importance of water environment protection, and actively carried out the development, utilization and protection of water resources, which can reduce waste while improving the efficiency of water resources. In recent years, the overall scale of global water resources has declined, which also has a certain impact on the sustainable development of social economy. After water resources monitoring, we can fully understand the distribution of water resources, water quality and other aspects, so that we can timely understand the problems and effectively control them. In order to better ensure the effect of hydrological and water resources monitoring, we should fully understand the actual situation of water environment, adopt reasonable hydrological and water resources monitoring technology and equipment, and establish a hydrological and water resources monitoring system, so as to ensure that hydrological and water resources monitoring can be carried out smoothly, improve the efficiency of water resources utilization, and better promote the development of water resources development.
基金the Science & Technology Research and Development Project of Langfang Municipal City for the Year 2013 (No.2013011048)Baoding GEEHO Electric Technology Development Co.,Ltd.for financial support and help in data acquisition and statistics during preparation of this paper
文摘To protect mining areas from electrical fire, it is very important to install electrical nre momtormg system to ensure safety in development of mineral resources and for buildings. In this paper, design for electrical fire monitoring and detection system with optional sensor modules has been proposed. In addition, necessity and suitability of electrical fire monitoring and detection system with optional sensor modules in mining areas have been reviewed. The designed electrical fire monitoring and detection system suit- able for work environment of mining industry is composed by host-computer monitoring software and slave-computer detectors. Monitoring detectors are manufactured by using embedded technology. Exter- nal shells deployed have superior enclosure performances and explosion-proof properties. It is easy to install and maintain the system. In general, the system has reached, or even exceeded standards specified in national standards for performances and appearances of such devices. Test results show application of electrical fire monitoring and detection system can effectively enhance monitoring intensity over the mining areas and provide reliable guarantee to ensure orderly development of mineral resources and to protect physical and property safety of citizens in these areas.
基金This project was sponsored by the National Natural Science Foundation of China (50378086)
文摘With the rapid development of the economy in China, the seismic network has been changing rapidly, in that the capability of instruments, technological systems and network density are approaching those of developed countries and a large quantity of observation data has been accumulated. How to apply these resources to economic construction and public safety has become an important issue worth studying. In order to improve earthquake prediction and earthquake emergency response, it is suggested in this paper that extracting valuable precursor information, improving earthquake rapid reporting ability and extending rapid intensity reporting function are key issues. Integrating network resources, building unified standards and a multifunction seismic monitoring network are preconditions of establishing a public safety service platform and earthquake observation resources will contribute significantly to the fields of engineering, ocean, meteorology, and environmental protection. Thus, the future directions of the development of the seismic network are exploring monitoring resources, enhancing independent innovation, constructing a technological platform and enlarging the service field.
文摘Cloud computing has recently emerged as a leading paradigm to allow customers to run their applications in virtualized large-scale data centers. Existing solutions for monitoring and management of these infrastructures consider virtual machines （VMs） as independent entities with their own characteristics. However, these approaches suffer from scalability issues due to the increasing number of VMs in modern cloud data centers. We claim that scalability issues can bc addressed by leveraging the similarity among VMs behavior in terms of resource usage patterns. In this paper we propose an automated methodology to cluster VMs starting from the usage of multiple resources, assuming no knowledge of the services executed on them. The innovative contribution of the proposed methodology is the use of the statistical technique known as principal component analysis （PCA） to automatically select the most relevant information to cluster similar VMs. We apply the methodology to two case studies, a virtualized testbed and a real enterprise data center. In both case studies, the automatic data selection based on PCA allows us to achieve high performance, with a percentage of correctly clustered VMs between 80% and 100% even for short time series （1 day） of monitored data. Furthermore, we estimate the potential reduction in the amount of collected data to demonstrate how our proposal may address the scalability issues related to monitoring and management in cloud computing data centers.
