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Hadoop is a famous distributed computing framework that is applied to process large-scale data. "Straggling tasks" have a serious impact on Hadoop performance due to imbalance of slow tasks distribution. Speculative execution (SE) presents a way to deal with Straggling tasks by monitoring the real-time progress of running tasks and replicating potential "Stragglers" on another...
Cloud hosted NoSQL data stores are for economic reasons often shared amongst multiple tenants simultaneously. The NoSQL provider consolidates multiple tenants access into a shared NoSQL instance and provides a dedicated view for each tenant. This multi-tenancy has tenants' data and workloads coexisting in the same node, which under certain conditions can lead to performance degradation of one tenant...
To analyze data distributed across the world, one can use distributed computing power to take advantage of data locality and achieve higher throughput. The multi-cloud model, a composition of multiple clouds, can provide cost-effective computing resources to process such distributed data. As multicolour becomes more and more accessible from cloud users, the use of MapReduce/Hadoop over multi-cloud...
The need for low latency analysis over high-velocity data streams motivates the need for distributed continuous dataflow systems. Contemporary stream processing systems use simple techniques to scale on elastic cloud resources to handle variable data rates. However, application QoS is also impacted by variability in resource performance exhibited by clouds and hence necessitates autonomic methods...
Energy efficiency is an important issue in radio cellular network planning due to the increasing awareness of environmental protection and cost-efficiency. Heterogenous cloud computing technology is introduced to cellular networks in recent years, which can improve energy utilization by employing lower power cells to reduce the distance between users and base stations, as well as simplifying the system...
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