MIFAS: Medical Image File Accessing System in Co-allocation Data Grids

Yang, Chao‐Tung; Chen, Chiu-Hsiung; Yang, Ming-Feng; Chiang, Wen-Chung

doi:10.1109/apscc.2008.267

Cited by 7 publications

(2 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In our previous project, we built an integrated environment including a web portal composed of Ganglia and NWS services. Afterward, we started another project called Picture Archive and Communication System , and many experiments were performed on the same platform. The primary mission of Picture Archive and Communication System is to efficiently exchange medical images in a specific application developed by our team.…”

Section: Heuristic Qos Measurementmentioning

confidence: 99%

See 1 more Smart Citation

On construction of heuristic QoS bandwidth management in clouds

Yang

Liu

Ranjan

et al. 2013

Concurrency and Computation

Self Cite

View full text Add to dashboard Cite

In recent years, cloud computing has become popular and its applications widespread. Thus, there exists a common concern, that is, how to arrange and monitor various resources in the cloud computing environment. In the literature, Ganglia and Network Weather Service (NWS) were used to monitor and gather node status and network-related data, respectively. With supports of Ganglia and NWS, one can effectively administer available resources in the cloud computing environment. In order to achieve high performance of cloud computing, comprehensive monitoring and efficient management are critical. Ganglia is often used to gather status data of resources, such as live states of hosts, CPU or memory utilizations, and surely Ganglia is also capable of monitoring network-related information; however, instead of Ganglia, we used NWS services to gather network-related information such as end-to-end transmission control protocol/Internet protocol performance data. Compared with Ganglia, NWS services offer more selections and flexibility for measurement schemes. Besides, NWS services could be deployed with nonintruding manner that makes it easier and faster in deploying services to cloud nodes. The network-related information is acquired immediately after deployment. Although NWS services also provide measurements for CPU and memory utilizations, but less functionality is provided by them than Ganglia in these aspects. Therefore, we combine advantageous features of Ganglia and NWS to achieve the aims of effective monitoring and management of available resources in the cloud environment. Nevertheless, Ganglia and NWS services may not provide sufficient data in realistic situations due to diversified needs of users, especially application developers. For instance, users are not able to directly access utilizations or allocations of resources in the cloud environment via interfaces or channels of Ganglia or NWS. In addition, NWS services based on a domain-based network information model could greatly decrease overheads caused by unnecessary measurements. Hence, we propose a heuristic QoS measurement approach based on the domain-based information model. This measurement approach is capable of providing essential information to satisfy user requirements, and thus let users manage and monitor various resources in the cloud environment in a more efficient way.

show abstract

Section: Heuristic Qos Measurementmentioning

confidence: 99%

“…Smart Broker is the key component to evaluate QoS. Our previous work , provided users with an interface to tune up parameters, as shown in Figure . But most parameters used by the application, Cyber, must be set manually and it was very inconvenient for network administrators.…”

Section: Heuristic Qos Measurementmentioning

confidence: 99%