Sunday, August 25, 2019
How Will Astronomy Archives Survive the Data Tsunami Case Study - 1
How Will Astronomy Archives Survive the Data Tsunami - Case Study Example Optimization techniques fail to create an efficient programmable dynamic query in case of astronomical data as data is present in bulk and is not usually centrally located. The disparate sources of data induce issue of network and bandwidth as well. When large chunks of data will be downloaded from disparate sources performance will be impacted as connections need to be established and maintained. Data is divided into different sources by a set criteria. This could be arranged date wise or could be based on specific type. The criteria even if incorporated in queries may not help much as the search that runs in dataset is time consuming. If data does not exist in data set time is required to load data from archives and search becomes intensive. There are various techniques used to provide better response times in such scenarios but the ever increasing data of astronomy that is stored in the database requires some special technique for data mining, machine learning and then update in t he systems (McLeod & Schell,Ã 2007, p.Ã 145). The requests made for specific data can be optimized by saving results of frequent query. Emerging researches will always produce new datasets which will take standard time. The infrastructure of archival data can be improved however the budget constraint of astronomical research hinders them from such an upgrade at the moment. Incompetent Archival Techniques: Modern day data is stored in a special environment that provides virtual drives hosted by third parties. This allows users to store data from different places online. This technology uses a web service that connects the client with the third party host systems. The customer has to depend on the reliability of the hosting party to provide reliability and security. In order to make systems available on cloud the whole time, third parties usually create redundant data on different virtual machines. If one machine is made unavailable due to a fault or network issue, other machines having the same data will be made available instantly. The astronomical data can be set on cloud to make it readily available. However, cloud computing has its own challenges as well. Such challenges include vulnerability of data attacks as the cloud is shared through a network and makes the data available through internet. The second issue is that of the third party supplier stability. The companies might lose down or merge with other companies resulting is partial or complete loss of data or other similar issues hence decreasing reliability of data on the cloud. There are a number of reasons why such a situation can arise. A supplier can go bankrupt, be bought by other large companies, it may expand and change the direction and interest of their business etc. Performance is again an issue in cloud as it is dependent on the available network bandwidth. Availability is impacted if a software failure occurs, network has a bottleneck or if a hardware fails. The last concern is cost of hosting a cloud platform. The budget constraints for an astronomical foundation may not allocate sufficient finances to meet the target of moving astronomical data on cloud. Emerging Technologies: The technologies currently in practice involve applying indexes on databases. These indexes are stored outside the database and increases the data access or recovery time. This does need advancement to a Peta byte level data management though. It is a challenge today to make efficient algorithms
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