Abstract
ABSTRACTIn 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. © 2013 Wiley Periodicals, Inc.
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