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Chen et al., 2017 - Google Patents

A real-time scheduling strategy based on processing framework of Hadoop

Chen et al., 2017

Document ID
17441785624717147342
Author
Chen F
Liu J
Zhu Y
Publication year
Publication venue
2017 IEEE International Congress on Big Data (BigData Congress)

External Links

Snippet

Due to the batch processing capability and distributed storage, MapReduce and HDFS have always been the core parts of Hadoop. Nowadays, many studies still focus on improving and optimizing of the MapReduce task scheduling algorithms. However, in terms of real-time …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

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    • G06F9/46Multiprogramming arrangements
    • G06F9/48Programme initiating; Programme switching, e.g. by interrupt
    • G06F9/4806Task transfer initiation or dispatching
    • G06F9/4843Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • G06F9/4881Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
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    • G06F9/5005Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G06F9/505Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the load
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    • G06F9/5083Techniques for rebalancing the load in a distributed system
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    • G06F13/161Handling requests for interconnection or transfer for access to memory bus based on arbitration with latency improvement
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