TY - JOUR
T1 - HPS-HDS
T2 - High Performance Scheduling for Heterogeneous Distributed Systems
AU - Pop, Florin
AU - Iosup, Alexandru
AU - Prodan, Radu
PY - 2018/1
Y1 - 2018/1
N2 - 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.
AB - 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.
KW - Big data
KW - Fault tolerance
KW - Heterogeneous distributed systems
KW - Resource management
KW - Scheduling algorithms
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U2 - 10.1016/j.future.2017.09.012
DO - 10.1016/j.future.2017.09.012
M3 - Editorial
AN - SCOPUS:85029745754
SN - 0167-739X
VL - 78
SP - 242
EP - 244
JO - Future Generation Computer Systems
JF - Future Generation Computer Systems
IS - Part 1
ER -