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Current Infrastructure-as-a-Service (IaaS) clouds offer both on-demand and reservation instance purchasing options. Users can combine these two options dynamically to serve time-varying demands while minimizing their instance acquisition costs. However, when future demands are unknown, it is far from trivial for cloud users to make optimal instance purchasing decisions. To deal with this problem,...
Parallel application jobs account for a large population in current domain of cloud computing and Big Data processing services, whose execution time can be varied greatly with different runtime configurations. For efficiently scheduling resources and services to run parallel jobs, the ability to quickly and accurately estimate the performance of parallel applications is critical. Analytic predictive...
Intelligent Transportation System (ITS) is a significant part of smart city, and short-term traffic flow prediction plays an important role in intelligent transportation management and route guidance. A number of models and algorithms based on time series prediction and machine learning were applied to short-term traffic flow prediction and achieved good results. However, most of the models require...
Trust in Online Social Networks is an increasing popular issue in the field of social computing. It has been widely used in scenarios such as e-commerce, friend recommendation and trust-based access control system. Several trust computing methods have been proposed from different perspectives, however, most of them just quantify certain trust related factors and integrate them into a trust value by...
The problem of prediction is an important task in network analysis, which has attracted more attention from computer science communities. In this paper, prediction in signed heterogeneous networks is addressed, which contains two aspects, link prediction and sign prediction. Most of previous studies focus on non-signed networks that have only positive links or homogeneous networks that have only one...
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