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In a multi-view application, view synthesis is required to synthesize unavailable views using texture and depth information of the given views. In this paper, a compensation algorithm based on template matching for partial recovery of disocclusion regions is proposed. The shape of a template is dynamically adjusted, and a new reference mode which mimics pushing dominoes is also proposed. To find an...
MapReduce has been widely used as a Big Data processing platform. As it gets popular, its scheduling becomes increasingly important. In particular, since many MapReduce applications require real-time data processing, scheduling real time applications in MapReduce environments has become a significant problem. In this paper, we create a novel real-time scheduler for MapReduce, which overcomes the deficiencies...
MapReduce is a powerful platform for large-scale data processing. To achieve good performance, a MapReduce scheduler must avoid unnecessary data transmission by enhancing the data locality (placing tasks on nodes that contain their input data). This paper develops a new MapReduce scheduling technique to enhance map task's data locality. We have integrated this technique into Hadoop default FIFO scheduler...
With growing cost of electricity, the power management of server clusters has become an important problem. Most existing research, however, either do not apply to virtualized environments or do not focus on power-efficient workload distribution. To fill in this research gap, we propose a workload distribution algorithm for virtualized server clusters to reduce their power consumptions and provide...
Providing QoS and performance guarantees to arbitrarily divisible loads has become a significant problem for many cluster-based research computing facilities. While progress is being made in scheduling arbitrarily divisible loads, current approaches are not efficient and do not scale well. In this paper, we propose a linear algorithm for real-time divisible load scheduling. Unlike existing approaches,...
With growing cost of electricity, the power management (PM) of server clusters has become an important problem. However, most previous researchers only address the challenge in homogeneous environments. Considering the increasing popularity of heterogeneous systems, this paper proposes an efficient algorithm for PM of heterogeneous soft real-time clusters. It is built on simple but effective mathematical...
Data grids provide geographically distributed storage and computing resources for large data-intensive applications. To support fast data access and processing, effective data management is essential. In this paper, we propose two novel algorithms on data placement and data replication. We evaluate the algorithms through intensive simulations. Results show that the new algorithms achieve significant...
Existing 3D clustering algorithms on gene times sample times time expression data do not consider the time lags between correlated gene expression patterns. Besides, they either ignore the correlation on time subseries, or disregard the continuity of the time series, or only validate pure shifting or pure scaling coherent patterns instead of the general shifting and-scaling patterns. In this paper,...
With growing cost of electricity, the power management of server clusters has become an important problem. However, most previous researchers only address the challenge in homogeneous environments. Considering the increasing popularity of heterogeneous systems, this paper proposes an efficient algorithm for power management of heterogeneous soft real-time clusters. It is built on simple but effective...
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