Load rebalancing for Hadoop Distributed File System using distributed hash table

Nithya, M.; Maheshwari, Nitesh

doi:10.1109/iss1.2017.8389317

Cited by 6 publications

(2 citation statements)

References 10 publications

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“…For example, the successor of node 159 can be node 200 (there are no nodes with IDs between 159 and 200), which means that node 200 has a predecessor the node 159 [ 19 , 20 ].…”

Section: The Proposed Systemmentioning

confidence: 99%

A Blockchain-Based Verifiable User Data Access Control Policy for Secured Cloud Data Storage

2022

Computational Intelligence and Neuroscience

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Adding the adequate level of security of information systems dealing with sensitive data, privacy, or defense systems involves some form of access control. The audits performed are dealing with the determination of the allowed activities of the legal users, when attempting to access resources of the system. Usually, full access is provided after the user has been successfully authenticated through an authentication mechanism (e.g., password), while the corresponding authorization control is based on the confidentiality level of the respective resources and the authorization level assigned to each user. A very important diversification occurring in modern digital technologies is related to the identification based on blockchain technology, which is presented as a public, distributed data series, unable to modify its history and grouped in time-numbered blocks. In this work, a blockchain-based verifiable user data access control policy for secured cloud data storage is suggested for a version associated with big data in health care. It is an innovative system of applying classified access policies to secure resources in the cloud, which operates based on blockchain technology. System evaluation is carried out by studying a case in its resilience to Eclipse attack under different malicious user capabilities for routing table poisoning.

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“…For example, the successor of node 159 can be node 200 (there are no nodes with IDs between 159 and 200), which means that node 200 has a predecessor the node 159 [ 19 , 20 ].…”

Section: The Proposed Systemmentioning

confidence: 99%

A Blockchain-Based Verifiable User Data Access Control Policy for Secured Cloud Data Storage

2022

Computational Intelligence and Neuroscience

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“…D ISTRIBUTED networked control systems [1] have received significant attention with respect to their capabilities in field of communication networks, control and computer science. This system is based on distributed and parallel architecture, which is directly related to balance of the workload [2]. Moreover, critical impact in distributed systems is used to stabilize the system for redundancy and fault tolerance, [3].…”

Section: Introductionmentioning

confidence: 99%

Enhanced faulty node detection with interval weighting factor for distributed systems

2021

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This paper proposes an enhanced faulty node detection method using interval weighting factor, which monitors node behavior using pseudo-random Bose-Chaudhuri-Hocquenghem (BCH) code for distributed networked control systems. Master node collects the replacement of the cyclic redundancy check (CRC) codes by a single-bit BCH code of each slave node. However, BCH code can only obtain error position of the suspected faulty node without consideration of channel nodes. Hence, suspected error nodes are saved within the detected error interval and normalized using the weighting factor, which is carried out during sequential check, for interpretation. Fault judgement is carried out to adequately interpret the data, to guarantee detection accuracy of the detected error. The data is represented by statistical characteristic of the raw data and filtered data. This scheme can be applied to detect and prevent the severe damage by node failure. The simulation results prove the effectiveness of the interval faulty weighting factor, in obtaining raw data from the monitoring of the BCH code and filtered data, which are more accurate representation than the raw data. Moreover, the characteristics of the observed data were verified as the evaluation result of the suspected faulty node.

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DFS Response Time Prediction Using the Techniques of “Deep Learning”

Elomari

Hassouni

Maizate

2020

Artificial Intelligence and Industrial Applications

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Load rebalancing for Hadoop Distributed File System using distributed hash table

Cited by 6 publications

References 10 publications

A Blockchain-Based Verifiable User Data Access Control Policy for Secured Cloud Data Storage

A Blockchain-Based Verifiable User Data Access Control Policy for Secured Cloud Data Storage

Enhanced faulty node detection with interval weighting factor for distributed systems

DFS Response Time Prediction Using the Techniques of “Deep Learning”

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