File Assignment in Parallel I/O Systems with Minimal Variance of Service Time
IEEE Transactions on Computers
Directed diffusion: a scalable and robust communication paradigm for sensor networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Identifying Dynamic Replication Strategies for a High-Performance Data Grid
GRID '01 Proceedings of the Second International Workshop on Grid Computing
Simulation of Dynamic Data Replication Strategies in Data Grids
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Content and service replication strategies in multi-hop wireless mesh networks
MSWiM '05 Proceedings of the 8th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems
Replica Placement Design with Static Optimality and Dynamic Maintainability
CCGRID '06 Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid
An on-line replication strategy to increase availability in Data Grids
Future Generation Computer Systems
A Secure and Scalable Update Protocol for P2P Data Grids
HASE '07 Proceedings of the 10th IEEE High Assurance Systems Engineering Symposium
Benefit-Based Data Caching in Ad Hoc Networks
IEEE Transactions on Mobile Computing
SEA: A Striping-Based Energy-Aware Strategy for Data Placement in RAID-Structured Storage Systems
IEEE Transactions on Computers
A dynamic data replication strategy using access-weights in data grids
The Journal of Supercomputing
Reliability in grid computing systems
Concurrency and Computation: Practice & Experience - A Special Issue from the Open Grid Forum
Future Generation Computer Systems
Dynamic cost-efficient replication in data clouds
ACDC '09 Proceedings of the 1st workshop on Automated control for datacenters and clouds
A file assignment strategy independent of workload characteristic assumptions
ACM Transactions on Storage (TOS)
CDRM: A Cost-Effective Dynamic Replication Management Scheme for Cloud Storage Cluster
CLUSTER '10 Proceedings of the 2010 IEEE International Conference on Cluster Computing
The Hadoop Distributed File System
MSST '10 Proceedings of the 2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)
Data Replication in Data Intensive Scientific Applications with Performance Guarantee
IEEE Transactions on Parallel and Distributed Systems
A Novel Cost-Effective Dynamic Data Replication Strategy for Reliability in Cloud Data Centres
DASC '11 Proceedings of the 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing
Dynamic hybrid replication effectively combining tree and grid topology
The Journal of Supercomputing
Evolutionary multiobjective optimization for green clouds
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
A Toolkit for Modeling and Simulating Cloud Data Storage: An Extension to CloudSim
ICCECT '12 Proceedings of the 2012 International Conference on Control Engineering and Communication Technology
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Effective data management is an important issue for a large-scale distributed environment such as data cloud. This can be achieved by using file replication, which efficiently reduces file service time and access latency, increases file availability and improves system load balancing. However, replication entails various costs such as storage and energy consumption for holding replicas. This article proposes a multi-objective offline optimization approach for replica management, in which we view the various factors influencing replication decisions such as mean file unavailability, mean service time, load variance, energy consumption and mean access latency as five objectives. It makes decisions of replication factor and replication layout with an improved artificial immune algorithm that evolves a set of solution candidates through clone, mutation and selection processes. The proposed algorithm named Multi-objective Optimized Replication Management (MORM) seeks the near optimal solutions by balancing the trade-offs among the five optimization objectives. The article reports a series of experiments that show the effectiveness of the MORM. Experimental results conclusively demonstrate that our MORM is energy effective and outperforms default replication management of HDFS (Hadoop Distributed File System) and MOE (Multi-objective Evolutionary) algorithm in terms of performance and load balancing for large-scale cloud storage cluster.