A Novel Evolutionary Algorithm for Solving Static Data Allocation Problem in Distributed Database Systems

Mamaghani, Ali Safari; Mahi, Mostafa; Meybodi, Mohammad Reza; Moghaddam, Mohammad Hosseinzadeh

doi:10.1109/netapps.2010.10

Cited by 13 publications

(6 citation statements)

References 8 publications

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“…Distributed Database system which is a configuration of distributed system where a set of independent databases are running on multiple nodes simultaneously so that users can access stored data from any node irrespective of were the data was stored [12,30,32]. Distributed database system is illustrated in Figure 4.…”

Section: Distributed Databaasesmentioning

confidence: 99%

Security in Distributed System: A Review Perspective

Obasi¹,

Ikharo²,

Oisamoje³

2022

IJLTEMAS

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Computer over the years has grown from single user to multi-user systems and then presently to distributed system, implying that computing resources can be distributed to different host and can be access by multiple users. This scenario is required for horizontally scaling of systems’ requirement against vertical scaling now known as distributed systems, which cannot be improved beyond certain threshold. Security in such a heterogeneous system becomes a paramount issue of concern. This paper looks at distributed system, while highlighting the security challenges inherent in such system and reviewing the various progress in providing solution to the security challenges.

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Section: Distributed Databaasesmentioning

confidence: 99%

Security in Distributed System: A Review Perspective

Obasi¹,

Ikharo²,

Oisamoje³

2022

IJLTEMAS

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“…The execution time is minimized while the stability of this DAP algorithm is also significant. Mamaghani et al 2010, [23] employed two techniques of genetic algorithm and learning automata (GA-LA) synchronically for examining the states space of problem. This approach is efficient in solving DAP; the quality of generated solutions has been accelerated.…”

Section: Related Workmentioning

confidence: 99%

Data Allocation in Distributed Database based on CSO

Thalij¹

2022

Tikrit J. Pure Sci.

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Distributed databases (DDBs) provide smart processing of large databases, the problems of fragmentation and allocation are vital design problems in addition to the centralized design. The majority of performance degradation in DDBs is due to the communication cost by query remote access and retrieval of data. This can be optimized through an efficient data allocation approach that will provide flexible retrieval of a query by low cost accessible sites. In this paper, a novel high performance data allocation approach is designed using Chicken Swarm Optimization (CSO) algorithm. Data allocation problem (DAP) is a NP-Hard problem modelled as optimization problem. The proposed data allocation approach initially characterizes the DAP into optimal problem of choosing the appropriate and minimal communication cost provoking sites for the data fragments. Then the CSO algorithm optimally chooses the sites for each of the data fragments without creating much overhead and data route diversions. This enhances the overall distributed database design and subsequently ensures quality replication. The experimental results illustrate that the proposed CSO based intelligent data fragment allocation approach has better performance than most existing approaches and thus signifies the impact of efficient data allocation in DDBs.

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“…Adl and Rankoohi [2] proposed three different versions of ACO based heuristic methods for data allocation. Mamaghani et al [29] proposed a hybrid evolutionary approach for data allocation. Hybrid approach is combination of object migration learning automata and genetic algorithm.…”

Section: Related Workmentioning

confidence: 99%

SBBO Based Replicated Data Allocation Approach for Distributed Database Design

Singh¹

2020

International Journal of Engineering Research and Technology

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In the current scenario, when the demand of cloud based services and IoT devices is increasing day by day, designing distributed databases have become more challenging task. The performance of any distributed database is heavily dependent on its proper design. Moreover, data allocation is an important part of distributed database design after data fragmentation. A new replicated data allocation approach has been proposed in this paper. Simplified biogeography-based optimization (SBBO) is used for developing the proposed approach. SBBO based approach helps in minimizing total processing cost of a query and also increasing the overall performance of the system. Results obtained from the SBBO based approach are evaluated against the performance of BBO and GA based approaches. The SBBO based approach provides quality solutions as compared to other two algorithms.

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A Novel Evolutionary Algorithm for Solving Static Data Allocation Problem in Distributed Database Systems

Cited by 13 publications

References 8 publications

Security in Distributed System: A Review Perspective

Security in Distributed System: A Review Perspective

Data Allocation in Distributed Database based on CSO

SBBO Based Replicated Data Allocation Approach for Distributed Database Design

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