Replication management using the state-machine approach
Distributed systems (2nd Ed.)
The Byzantine Generals Problem
ACM Transactions on Programming Languages and Systems (TOPLAS)
Delta Four: A Generic Architecture for Dependable Distributed Computing
Delta Four: A Generic Architecture for Dependable Distributed Computing
The failure and recovery problem for replicated databases
PODC '83 Proceedings of the second annual ACM symposium on Principles of distributed computing
Distributed Systems: Concepts and Design (4th Edition) (International Computer Science)
Distributed Systems: Concepts and Design (4th Edition) (International Computer Science)
Energy-Efficient Computation Models for Distributed Systems
NBIS '09 Proceedings of the 2009 International Conference on Network-Based Information Systems
Algorithms for Reducing the Total Power Consumption in Data Communication-Based Applications
AINA '10 Proceedings of the 2010 24th IEEE International Conference on Advanced Information Networking and Applications
Power Consumption-Based Server Selection Algorithms for Communication-Based Systems
NBIS '10 Proceedings of the 2010 13th International Conference on Network-Based Information Systems
A Power Consumption Model for Storage-based Applications
CISIS '11 Proceedings of the 2011 International Conference on Complex, Intelligent, and Software Intensive Systems
A Power Consumption Model of a Storage Server
NBIS '11 Proceedings of the 2011 14th International Conference on Network-Based Information Systems
An Extended Power Consumption Model for Distributed Applications
AINA '12 Proceedings of the 2012 IEEE 26th International Conference on Advanced Information Networking and Applications
AINA '12 Proceedings of the 2012 IEEE 26th International Conference on Advanced Information Networking and Applications
Energy-Aware Distributed Systems for Computation and Storage-Based Applications
CISIS '12 Proceedings of the 2012 Sixth International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)
An Energy-Efficient Redundant Execution Algorithm by Terminating Meaningless Redundant Processes
AINA '13 Proceedings of the 2013 IEEE 27th International Conference on Advanced Information Networking and Applications
A Dynamic Energy-Aware Server Selection Algorithm
AINA '13 Proceedings of the 2013 IEEE 27th International Conference on Advanced Information Networking and Applications
Group Communication Protocols for Scalable Groups of Peers
WAINA '13 Proceedings of the 2013 27th International Conference on Advanced Information Networking and Applications Workshops
CISIS '13 Proceedings of the 2013 Seventh International Conference on Complex, Intelligent, and Software Intensive Systems
Hi-index | 0.00 |
In information systems, processes requested by clients have to be performed on servers so that not only QoS (quality of service) requirements like response time are satisfied but also the total electric power consumed by servers to perform processes has to be reduced. Furthermore, each process has to be reliably performed in the presence of server faults. In our approach to reliably performing processes, each process is redundantly performed on multiple servers. The more number of servers a process is performed on, the more reliably the process can be performed but the more amount of electric power is consumed by the servers. Hence, it is critical to discuss how to reliably and energy-efficiently perform processes on multiple servers. In this paper, we discuss how to reduce the total electric power consumed by servers in a cluster where each request process is passively replicated on multiple servers. Here, a process is performed on only one primary server while taking checkpoints and sending the checkpoints to secondary servers. If the primary server is faulty, one of the secondary servers takes over the faulty primary server and the process is performed from the check point on the new primary server. We evaluate the energy-aware passive replication scheme of a process in terms of total power consumption and average execution time and response time of each process in presence of server fault.