HPS-HDS: High Performance Scheduling for Heterogeneous Distributed Systems

Florin Pop*, Alexandru Iosup, Radu Prodan

*Corresponding author for this work

Research output: Contribution to JournalEditorialAcademicpeer-review

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Heterogeneous Distributed Systems (HDS) are often characterized by a variety of resources that may or may not be coupled with specific platforms or environments. Such type of systems are Cluster Computing, Grid Computing, Peer-to-Peer Computing, Cloud Computing and Ubiquitous Computing all involving elements of heterogeneity, having a large variety of tools and software to manage them. As computing and data storage needs grow exponentially in HDS, increasing the size of data centers brings important diseconomies of scale. In this context, major solutions for scalability, mobility, reliability, fault tolerance and security are required to achieve high performance. More, HDS are highly dynamic in its structure, because the user requests must be respected as an agreement rule (SLA) and ensure QoS, so new algorithm for events and tasks scheduling and new methods for resource management should be designed to increase the performance of such systems. In this special issues, the accepted papers address the advance on scheduling algorithms, energy-aware models, self-organizing resource management, data-aware service allocation, Big Data management and processing, performance analysis and optimization.

Original languageEnglish
Pages (from-to)242-244
Number of pages3
JournalFuture Generation Computer Systems
Issue numberPart 1
Early online date20 Sept 2017
Publication statusPublished - Jan 2018


  • Big data
  • Fault tolerance
  • Heterogeneous distributed systems
  • Resource management
  • Scheduling algorithms


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