A web-based system architecture for ontology-based data integration in the domain of IT benchmarking

Pfaff, Matthias; Krcmar, Helmut

doi:10.1080/17517575.2017.1329552

Cited by 10 publications

(1 citation statement)

References 40 publications

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“…Finally, the ordinary nodes are synchronized to the consensus nodes to update the entire network blockchain. Experiments show that CRaft has better throughput and lower latency than the commonly used consortium chain consensus algorithm PBFT (Practical Byzantine Fault Tolerance) [5]. It is of practical significance to study the enterprise distributed system based on Raft algorithm [6][7].…”

Section: Introductionmentioning

confidence: 99%

Enterprise Distributed System Based on Raft Algorithm

2020

DPS

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With the development of the network from the initial simple form to the Internet era, especially when the development of several enterprises requires huge and complex data, in order to solve the problem of data consistency on different computing nodes, it is inseparable from the distributed Research on the key topic of data consistency in the field. The purpose of this paper is to study the analysis and design of enterprise distributed system based on Raft algorithm. The consistency and Raft algorithm of distributed storage system are introduced. In the network layer, the ROUTER-DEALER mode based on the ZMQ message queue technology is used to realize the message communication between each node of the distributed architecture. In the application layer, the idea based on the Raft consensus algorithm is used to realize the public business module. The allocation of the public business logic load balancing designates the public server, which ensures the consistency of the related interactive business logic data of the public server node, and can quickly switch and recover after the node stops working. In the data layer, the data cache function based on RedisCluster cluster technology is used to reduce the redundant operation of the database. The experimental results show that the fast data reading and writing ability of the enterprise distributed system is improved.

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Section: Introductionmentioning

confidence: 99%

Enterprise Distributed System Based on Raft Algorithm

2020

DPS

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Ontology for Semantic Data Integration in the Domain of IT Benchmarking

2017

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A domain-specific ontology for IT benchmarking has been developed to bridge the gap between a systematic characterization of IT services and their data-based valuation. Since information is generally collected during a benchmark exercise using questionnaires on a broad range of topics, such as employee costs, software licensing costs, and quantities of hardware, it is commonly stored as natural language text; thus, this information is stored in an intrinsically unstructured form. Although these data form the basis for identifying potentials for IT cost reductions, neither a uniform description of any measured parameters nor the relationship between such parameters exists. Hence, this work proposes an ontology for the domain of IT benchmarking, available at https://w3id.org/bmontology. The design of this ontology is based on requirements mainly elicited from a domain analysis, which considers analyzing documents and interviews with representatives from Small- and Medium-Sized Enterprises and Information and Communications Technology companies over the last eight years. The development of the ontology and its main concepts is described in detail (i.e., the conceptualization of benchmarking events, questionnaires, IT services, indicators and their values) together with its alignment with the DOLCE-UltraLite foundational ontology.

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