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  Browse All Reviews > Software (D) > Operating Systems (D.4) > Process Management (D.4.1) > Scheduling (D.4.1...)  
  1-10 of 133 Reviews about "Scheduling (D.4.1...)": Date Reviewed
  Joint online coflow routing and scheduling in data center networks
Tan H., Jiang S., Li Y., Li X., Zhang C., Han Z., Lau F.  IEEE/ACM Transactions on Networking 27(5): 1771-1786, 2019. Type: Article

With the proliferation of big data initiatives across corporations and academia, the importance of distributed computing frameworks has created many research opportunities related to routing and scheduling the multiple groups of parallel flows gen...

Sep 3 2020
  Package-aware scheduling of FaaS functions
Abad C., Boza E., van Eyk E.  ICPE 2018 (Companion of the 2018 ACM/SPEC International Conference on Performance Engineering, Berlin, Germany,  Apr 9-13, 2018) 101-106, 2018. Type: Proceedings

This paper applies the longstanding notion of caching to the new field of serverless computing. Moving computation to the data, that is, functions to the nodes where libraries are cached, is advantageous to function-as-a-service (FaaS) functions t...

Mar 22 2019
  Scheduling distributed clusters of parallel machines: primal-dual and LP-based approximation algorithms
Murray R., Khuller S., Chao M.  Algorithmica 80(10): 2777-2798, 2018. Type: Article

As large amounts of data continue to accumulate at never-before-seen rates, it becomes uneconomical to store it at a single location, not to mention storing copies at different locations. One solution is to partition the data and store it in group...

Aug 17 2018
  Mixed-criticality federated scheduling for parallel real-time tasks
Li J., Ferry D., Ahuja S., Agrawal K., Gill C., Lu C.  Real-Time Systems 53(5): 760-811, 2017. Type: Article

In mixed-criticality systems, the same computing platform is used to execute a workload consisting of safety-critical tasks and non-safety-critical ones. Whereas the former class of tasks exposes stringent timing and performance requirements that ...

Nov 29 2017
  An efficient schedulability analysis for optimizing systems with adaptive mixed-criticality scheduling
Zhao Y., Zeng H.  Real-Time Systems 53(4): 467-525, 2017. Type: Article

Mixed-criticality (MC) systems are of particular interest today. The adaptive scheduling of tasks on such systems attracts a lot of attention because of the complexity of the activity due to the high number of parameters and constraints and the ne...

Oct 16 2017
  Improving resource efficiency at scale with Heracles
Lo D., Cheng L., Govindaraju R., Ranganathan P., Kozyrakis C.  ACM Transactions on Computer Systems 34(2): Article No. 6, 2016. Type: Article

Most of the paper’s authors are connected to Google, and their work centers on Google workload performance improvement. They’ve developed runtime controller software, Heracles, that uses real-time feedback and static modeling rules to ...

Sep 6 2017
  A survey on resource scheduling in cloud computing: issues and challenges
Singh S., Chana I.  Journal of Grid Computing 14(2): 217-264, 2016. Type: Article, Reviews: (2 of 2)

This is one of the best survey papers I have ever come across. It provides a thorough review of resource scheduling algorithms (RSAs) with a particular focus on cloud computing. While the paper does not excel as a survey of RSAs, it does excel in ...

Jun 14 2017
  MRCP-RM: a technique for resource allocation and scheduling of MapReduce jobs with deadlines
Lim N., Majumdar S., Ashwood-Smith P.  IEEE Transactions on Parallel and Distributed Systems 28(5): 1375-1389, 2017. Type: Article

In this paper, the authors discuss issues in scheduling (that is, match making) of job streams with end-to-end service-level agreements (SLAs) with agreed-upon quality of service (QoS) and allocation of resources in a distributed cloud environment...

Jun 9 2017
  A survey on resource scheduling in cloud computing: issues and challenges
Singh S., Chana I.  Journal of Grid Computing 14(2): 217-264, 2016. Type: Article, Reviews: (1 of 2)

When a cloud provider doesn’t properly schedule workloads, performance usually degrades. If the degradation is not caught in time, a cloud outage can occur. A couple of minutes of downtime is too long for many enterprise users to wait for th...

May 9 2017
  A constraint programming scheduler for heterogeneous high-performance computing machines
Bridi T., Bartolini A., Lombardi M., Milano M., Benini L.  IEEE Transactions on Parallel and Distributed Systems 27(10): 2781-2794, 2016. Type: Article

If you have managed high-performance computing (HPC) facilities, you will be aware of the difficulties that can arise in job scheduling. Nineteen nodes in your large-memory queue become available; you have one user who wants 20 nodes for an hour t...

Mar 23 2017
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