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We consider a distributed server system consisting of a large number of servers, each with limited capacity on multiple resources (CPU, memory, etc.). Jobs with different rewards arrive over time and require certain amounts of resources for the duration of their service. When a job arrives, the system must decide whether to admit it or reject it, and if admitted, in which server to schedule it. The objective is to maximize the expected total reward received by the system. This problem is motivated by control of cloud computing clusters, in which jobs are requests for virtual machines (VMs) or containers that reserve resources for various services, and rewards represent service priority of requests or price paid per time unit of service. We study this problem in an asymptotic regime where the number of servers and jobs’ arrival rates scale by a factor L, as L becomes large. We propose a resource reservation policy that asymptotically achieves at least 1/2, and under certain monotone property on jobs’ rewards and resources, at least [Formula: see text] of the optimal expected reward. The policy automatically scales the number of VM slots for each job type as the demand changes and decides in which servers the slots should be created in advance, without the knowledge of traffic rates.
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Reducing Faulty Jobs by Job Submission Verifier in Grid Engine
Grid Engine is a Distributed Resource Manager (DRM), that manages the resources of distributed systems (such as Grid, HPC, or Cloud systems) and executes designated jobs which have requested to occupy or consume those resources. Grid Engine applies scheduling policies to allocate resources for jobs while simultaneously attempting to maintain optimal utilization of all machines in the distributed system. However, due to the complexity of Grid Engine's job submission commands and complicated resource management policies, the number of faulty job submissions in data centers increases with the number of jobs being submitted. To combat the increase in faulty jobs, Grid Engine allows administrators to design and implement Job Submission Verifiers (JSV) to verify jobs before they enter into Grid Engine. In this paper, we will discuss a Job Submission Verifier that was designed and implemented for Univa Grid Engine, a commercial version of Grid Engine, and thoroughly evaluated at the High Performance Computing Center of Texas Tech University. Our newly developed JSV communicates with Univa Grid Engine (UGE) components to verify whether a submitted job should be accepted as is, or modified then accepted, or rejected due to improper requests for resources. It had a substantial positive impact on reducing the number of faulty jobs submitted to UGE by far. For instance, it corrected 28.6% of job submissions and rejected 0.3% of total jobs from September 2018 to February 2019, that may otherwise lead to long or infinite waiting time in the job queue.
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- Award ID(s):
- 1835892
- PAR ID:
- 10123133
- Date Published:
- Journal Name:
- ACM Practice and Experience in Advanced Research Computing (PEARC'19)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/https://doi.org/10.1145/3332186.3338408
