Improved Utilization and Responsiveness with Gang Scheduling
IPPS '97 Proceedings of the Job Scheduling Strategies for Parallel Processing
Overhead Analysis of Preemptive Gang Scheduling
IPPS/SPDP '98 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Metrics for Parallel Job Scheduling and Their Convergence
JSSPP '01 Revised Papers from the 7th International Workshop on Job Scheduling Strategies for Parallel Processing
An Integrated Approach to Parallel Scheduling Using Gang-Scheduling, Backfilling, and Migration
JSSPP '01 Revised Papers from the 7th International Workshop on Job Scheduling Strategies for Parallel Processing
Job-Length Estimation and Performance in Backfilling Schedulers
HPDC '99 Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computing
IEEE Transactions on Parallel and Distributed Systems
Combining batch execution and leasing using virtual machines
HPDC '08 Proceedings of the 17th international symposium on High performance distributed computing
SnowFlock: rapid virtual machine cloning for cloud computing
Proceedings of the 4th ACM European conference on Computer systems
Evaluating the cost-benefit of using cloud computing to extend the capacity of clusters
Proceedings of the 18th ACM international symposium on High performance distributed computing
Resource Leasing and the Art of Suspending Virtual Machines
HPCC '09 Proceedings of the 2009 11th IEEE International Conference on High Performance Computing and Communications
Performance evaluation of gang scheduling in a two-cluster system with migrations
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
An Analysis of Provisioning and Allocation Policies for Infrastructure-as-a-Service Clouds
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
Multi-Criteria Job Scheduling in Grid Using an Accelerated Genetic Algorithm
Journal of Grid Computing
Failure-aware resource provisioning for hybrid Cloud infrastructure
Journal of Parallel and Distributed Computing
Enhancing performance of failure-prone clusters by adaptive provisioning of cloud resources
The Journal of Supercomputing
Cost-effective cloud HPC resource provisioning by building semi-elastic virtual clusters
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
The Journal of Supercomputing
Virtual Machine Allocation in Cloud Computing Environment
International Journal of Cloud Applications and Computing
The Journal of Supercomputing
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
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Cloud Computing refers to the notion of outsourcing on-site available services, computational facilities, or data storage to an off-site, location-transparent centralized facility or "Cloud." Gang Scheduling is an efficient job scheduling algorithm for time sharing, already applied in parallel and distributed systems. This paper studies the performance of a distributed Cloud Computing model, based on the Amazon Elastic Compute Cloud (EC2) architecture that implements a Gang Scheduling scheme. Our model utilizes the concept of Virtual Machines (or VMs) which act as the computational units of the system. Initially, the system includes no VMs, but depending on the computational needs of the jobs being serviced new VMs can be leased and later released dynamically. A simulation of the aforementioned model is used to study, analyze, and evaluate both the performance and the overall cost of two major gang scheduling algorithms. Results reveal that Gang Scheduling can be effectively applied in a Cloud Computing environment both performance-wise and cost-wise.