Overview of Cloud Computing Introduction Cloud evolution Cloud services Cloud projects Cloud challenges Concluding remarks Resource Scheduling for Cloud Computing Introduction Cloud service scheduling hierarchy Economic models for resource-allocation scheduling Heuristic models for task-execution scheduling Real-time scheduling in cloud computing Concluding remarks Game Theoretical Allocation in a Cloud Datacenter Introduction Game theory Cloud resource allocation model Nash equilibrium allocation algorithms Implementation in a cloud datacenter Concluding remarks Multidimensional Data Analysis in a Cloud Datacenter Introduction Pre-computing Data indexing Data partitioning Data replication Query processing parallelism Concluding remarks Data-Intensive Applications with MapReduce Introduction MapReduce: a new parallel computing model in cloud computing Distributed data storage underlying MapReduce Large-scale data analysis based on MapReduce SimMapReduce: a simulator for modeling MapReduce framework Concluding remarks Large-Scale Multidimensional Data Aggregation Introduction Data organization Choosing a right MapReduce framework Parallelizing single group-by query with MapReduce Parallelizing multiple group-by query with MapReduce Cost estimation Concluding remarks Multidimensional Data Analysis Optimization Introduction Data-locating-based job-scheduling Improvements by speed-up measurements Improvements by affecting factors Improvement by cost estimation Compressed data structures Concluding remarks Real-Time Scheduling with MapReduce Introduction A real-time scheduling problem Schedulability test in the cloud datacenter Utilization bounds for schedulability testing Real-time task scheduling with MapReduce Reliability indication methods Concluding remarks Future for Cloud Computing Bibliography Index RONG> Multidimensional Data Analysis in a Cloud Datacenter Introduction Pre-computing Data indexing Data partitioning Data replication Query processing parallelism Concluding remarks Data-Intensive Applications with MapReduce Introduction MapReduce: a new parallel computing model in cloud computing Distributed data storage underlying MapReduce Large-scale data analysis based on MapReduce SimMapReduce: a simulator for modeling MapReduce framework Concluding remarks Large-Scale Multidimensional Data Aggregation Introduction Data organization Choosing a right MapReduce framework Parallelizing single group-by query with MapReduce Parallelizing multiple group-by query with MapReduce Cost estimation Concluding remarks Multidimensional Data Analysis Optimization Introduction Data-locating-based job-scheduling Improvements by speed-up measurements Improvements by affecting factors Improvement by cost estimation Compressed data structures Concluding remarks Real-Time Scheduling with MapReduce Introduction A real-time scheduling problem Schedulability test in the cloud datacenter Utilization bounds for schedulability testing Real-time task scheduling with MapReduce Reliability indication methods Concluding remarks Future for Cloud Computing Bibliography Index p-by query with MapReduce Parallelizing multiple group-by query with MapReduce Cost estimation Concluding remarks Multidimensional Data Analysis Optimization Introduction Data-locating-based job-scheduling Improvements by speed-up measurements Improvements by affecting factors Improvement by cost estimation Compressed data structures Concluding remarks Real-Time Scheduling with MapReduce Introduction A real-time scheduling problem Schedulability test in the cloud datacenter Utilization bounds for schedulability testing Real-time task scheduling with MapReduce Reliability indication methods Concluding remarks Future for Cloud Computing Bibliography Index uting Bibliography Index.