Lihat Juga

• A Cuckoo-based Workflow Scheduling Algorithm to Reduce Cost and Increase Load Balance in the Cloud Environment
  oleh: Ghasemi, Shahin, et al.
  Terbitan: (2019)
• Optimization of ARIMA Forecasting Model using Firefly Algorithm
  oleh: unggara, Ilham, et al.
  Terbitan: (2019)
• Optimal Power Flow using Fuzzy-Firefly Algorithm
  oleh: Lastomo, Dwi; Institut Teknologi Sepuluh Nopember Surabaya, et al.
  Terbitan: (2019)
• A Firefly Algorithm for Portfolio Optimization
  oleh: Lazulfa, Indana
  Terbitan: (2019)
• Workflow Scheduling Techniques and Algorithms in IaaS Cloud: A Survey
  oleh: In the modern era, workflows are adopted as a powerful and attractive paradigm for expressing/solving a variety of applications like scientific, data intensive computing, and big data applications such as MapReduce and Hadoop. These complex applications are described using high-level representations in workflow methods. With the emerging model of cloud computing technology, scheduling in the cloud becomes the important research topic. Consequently, workflow scheduling problem has been studied extensively over the past few years, from homogeneous clusters, grids to the most recent paradigm, cloud computing. The challenges that need to be addressed lies in task-resource mapping, QoS requirements, resource provisioning, performance fluctuation, failure handling, resource scheduling, and data storage. This work focuses on the complete study of the resource provisioning and scheduling algorithms in cloud environment focusing on Infrastructure as a service (IaaS). We provided a comprehensive understanding of existing scheduling techniques and provided an insight into research challenges that will be a possible future direction to the researchers., et al.
  Terbitan: (2018)