TTSA: An Effective Scheduling Approach for Delay Bounded Tasks in Hybrid Clouds

Haitao Yuan, Jing Bi, Wei Tan, Meng Chu Zhou, Bo Hu Li, Jianqiang Li

Research output: Contribution to journalArticlepeer-review

181 Scopus citations


The economy of scale provided by cloud attracts a growing number of organizations and industrial companies to deploy their applications in cloud data centers (CDCs) and to provide services to users around the world. The uncertainty of arriving tasks makes it a big challenge for private CDC to cost-effectively schedule delay bounded tasks without exceeding their delay bounds. Unlike previous studies, this paper takes into account the cost minimization problem for private CDC in hybrid clouds, where the energy price of private CDC and execution price of public clouds both show the temporal diversity. Then, this paper proposes a temporal task scheduling algorithm (TTSA) to effectively dispatch all arriving tasks to private CDC and public clouds. In each iteration of TTSA, the cost minimization problem is modeled as a mixed integer linear program and solved by a hybrid simulated-annealing particle-swarm-optimization. The experimental results demonstrate that compared with the existing methods, the optimal or suboptimal scheduling strategy produced by TTSA can efficiently increase the throughput and reduce the cost of private CDC while meeting the delay bounds of all the tasks.

Original languageEnglish (US)
Article number7508444
Pages (from-to)3658-3668
Number of pages11
JournalIEEE Transactions on Cybernetics
Issue number11
StatePublished - Nov 2017

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


  • Cloud computing
  • cloud data center
  • cost minimization
  • delay bounded tasks
  • hybrid clouds
  • metaheuristic
  • resource provisioning
  • task scheduling


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