Journal of
Systemics, Cybernetics and Informatics
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ISSN: 1690-4524 (Online)


Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.

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Published by
The International Institute of Informatics and Cybernetics


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(A Community of about 40.000.000 Academics)


Honorary Editorial Advisory Board's Chair
William Lesso (1931-2015)

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

www.iiis.org
 

Editorial Advisory Board

Quality Assurance

Editors

Journal's Reviewers
Call for Special Articles
 

Description and Aims

Submission of Articles

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Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


Quantitative Endosurgery Process Analysis by Machine Learning Method
Bojan Nokovic, Andrew Lambe
(pages: 1-7)

Modelling Student Performance in a Structural Steel Graduate-Based Module: A Comparative Analysis Between K-Nearest Neighbor and Dummy Classifiers
Masengo Ilunga, Omphemetse Zimbili, Phahlani Mampilo, Agarwal Abhishek
(pages: 8-15)

Interoperable Digital Skills for Foreign Languages Education in the COVID-19 Paradigm
Rusudan Makhachashvili, Ivan Semenist, Iryna Vorotnykova
(pages: 16-20)

Education, Training and Informatics Go Hand in Hand in (Foreign) Higher Education Institutions (HEIs) – Case Studies From Live and Online Classrooms
Ekaterini Nikolarea
(pages: 21-29)

Enhancing Pedagogical and Digital Competencies Through Digital Tools: A Proposal for Semi-schooled Language Teaching Programs in Oaxaca, Mexico
José de Jesús Bautista Hernández, Eduardo Bustos Farías, Norma Patricia Maldonado Reynoso
(pages: 30-35)

Railway Track Degradation Modelling Using Finite Element Analysis: A Case Study in South Africa
Ntombela Lunga, Masengo Ilunga
(pages: 36-50)

Continuum of Academic Collaboration: Issues of Inconsistent Terminology in Multilingual Context
Cristo Leon, James Lipuma, Marcos O. Cabobianco, Maria B. Daizo
(pages: 51-62)

Peat Resource Management and Climate Change Mitigation Issues – Case of Latvia
Anita Titova, Natalja Lace
(pages: 63-70)

Using Geospatial Computation Intelligence for Mapping Temporal Evolution of Urban Built-up in Selected Areas of the Ekurhuleni Municipality, South Africa
Jo-Anne Correia, Masengo Ilunga
(pages: 71-80)

Cybernetics and Informatics of Generative AI for Transdisciplinary Communication in Education
Rusudan Makhachashvili, Ivan Semenist
(pages: 81-88)

Navigating Psychological Riptides: How Seafarers Cope and Seek Help for Mental Health Needs
Coleen Abadicio, Stella Louise Arenas, Rosette Renee Hahn, Angel Berry Maleriado, Ramon Miguel Mariano, Rodolfo Antonio Ma. Zabella, Genejane Adarlo
(pages: 89-98)


 

Abstracts

 


ABSTRACT


An Ad Hoc Adaptive Hashing Technique forNon-Uniformly Distributed IP Address Lookup in Computer Networks

Christopher Martinez, Wei-Ming Lin


Hashing algorithms long have been widely adopted to design a fast address look-up process which involves a search through a large database to find a record associated with a given key. Hashing algorithms involve transforming a key inside each target data to a hash value hoping that the hashing would render the database a uniform distribution with respect to this new hash value. The close the final distribution is to uniform, the less search time would be required when a query is made. When the database is already key-wise uniformly distributed, any regular hashing algorithm, such as bit-extraction, bit-group XOR, etc., would easily lead to a statistically perfect uniform distribution after the hashing. On the other hand, if records in the database are instead not uniformly distributed as in almost all known practical applications, then even different regular hash functions would lead to very different performance. When the target database has a key with a highly skewed distributed value, performance delivered by regular hashing algorithms usually becomes far from desirable. This paper aims at designing a hashing algorithm to achieve the highest probability in leading to a uniformly distributed hash result from a non-uniformly distributed database. An analytical pre-process on the original database is first performed to extract critical information that would significantly benefit the design of a better hashing algorithm. This process includes sorting on the bits of the key to prioritize the use of them in the XOR hashing sequence, or in simple bit extraction, or even a combination of both. Such an ad hoc hash design is critical to adapting to all real-time situations when there exists a changing (and/or expanding) database with an irregular non-uniform distribution. Significant improvement from simulation results is obtained in randomly generated data as well as real data.

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