交互式雲端應用的需求日益增加，其導致被運用在雲端應用的MapReduce框架即時性需求越來越被重視。有別於傳統應用程序，MapReduce為處理大數據，其具有數據區域性特徵且以不可搶占的方式執行。因此，MapReduce的實時調度問題必須要考慮非搶占執行造成的等待時間和未滿足數據區域性造成的數據傳輸時間。本論文提出了一種基於區域性感知的MapReduce即時調度框架，藉此保證交互式雲端應用程序的服務質量。本文提出的即時調度框架包括工作排程器、調度器與動態功耗管理，可縮短高優先權應用程序的等待時間、提升數據區域性的分配，並有效降低系統所需的能源消耗。本論文提出的方法藉由不同類型的工作負載進行評估，並與現存其他的調度演算法進行比較，顯示其可有效提高應用程序的可排程性與數據區域性。

MapReduce is widely used in cloud applications for large-scale data processing. The increasing number of interactive cloud applications has led to an increasing need for MapReduce real-time scheduling. Most MapReduce applications are data-oriented and nonpreemptively executed. Therefore, the problem of MapReduce real-time scheduling is complicated because of the trade-off between run-time blocking for nonpreemptive execution and data-locality. This paper proposes a data-locality-aware MapReduce real-time scheduling framework for guaranteeing quality of service for interactive MapReduce applications. A scheduler and dispatcher that can be used for scheduling two-phase MapReduce jobs and for assigning jobs to computing resources are presented, and the dispatcher enable the consideration of blocking and data-locality. Furthermore, dynamic power management for run-time energy saving is discussed. Finally, the proposed methodology is evaluated by considering synthetic workloads, and a comparative study of different scheduling algorithms is conducted.

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