scholarly journals An Ant Colony Inspired Cache Allocation Mechanism for Heterogeneous Information Centric Network

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 55485-55496
Author(s):  
Ping Zhou ◽  
Jianhui Lv ◽  
Lianbo Ma ◽  
Yidan Chen ◽  
Shujun Yang
2012 ◽  
Author(s):  
Earth B. Ugat ◽  
Jennifer Joyce M. Montemayor ◽  
Mark Anthony N. Manlimos ◽  
Dante D. Dinawanao

2012 ◽  
Vol 3 (3) ◽  
pp. 122-125
Author(s):  
THAHASSIN C THAHASSIN C ◽  
◽  
A. GEETHA A. GEETHA ◽  
RASEEK C RASEEK C

2015 ◽  
Vol 9 ◽  
pp. 193-203
Author(s):  
Mirzakhmet SYZDYKOV ◽  
◽  
Madi UZBEKOV ◽  

Author(s):  
Achmad Fanany Onnilita Gaffar ◽  
Agusma Wajiansyah ◽  
Supriadi Supriadi

The shortest path problem is one of the optimization problems where the optimization value is a distance. In general, solving the problem of the shortest route search can be done using two methods, namely conventional methods and heuristic methods. The Ant Colony Optimization (ACO) is the one of the optimization algorithm based on heuristic method. ACO is adopted from the behavior of ant colonies which naturally able to find the shortest route on the way from the nest to the food sources. In this study, ACO is used to determine the shortest route from Bumi Senyiur Hotel (origin point) to East Kalimantan Governor's Office (destination point). The selection of the origin and destination points is based on a large number of possible major roads connecting the two points. The data source used is the base map of Samarinda City which is cropped on certain coordinates by using Google Earth app which covers the origin and destination points selected. The data pre-processing is performed on the base map image of the acquisition results to obtain its numerical data. ACO is implemented on the data to obtain the shortest path from the origin and destination point that has been determined. From the study results obtained that the number of ants that have been used has an effect on the increase of possible solutions to optimal. The number of tours effect on the number of pheromones that are left on each edge passed ant. With the global pheromone update on each tour then there is a possibility that the path that has passed the ant will run out of pheromone at the end of the tour. This causes the possibility of inconsistent results when using the number of ants smaller than the number of tours.


2013 ◽  
Vol 61 (3) ◽  
pp. 569-579 ◽  
Author(s):  
A. Poniszewska-Marańda

Abstract Nowadays, the growth and complexity of functionalities of current information systems, especially dynamic, distributed and heterogeneous information systems, makes the design and creation of such systems a difficult task and at the same time, strategic for businesses. A very important stage of data protection in an information system is the creation of a high level model, independent of the software, satisfying the needs of system protection and security. The process of role engineering, i.e. the identification of roles and setting up in an organization is a complex task. The paper presents the modeling and design stages in the process of role engineering in the aspect of security schema development for information systems, in particular for dynamic, distributed information systems, based on the role concept and the usage concept. Such a schema is created first of all during the design phase of a system. Two actors should cooperate with each other in this creation process, the application developer and the security administrator, to determine the minimal set of user’s roles in agreement with the security constraints that guarantee the global security coherence of the system.


2020 ◽  
Vol 26 (11) ◽  
pp. 2427-2447
Author(s):  
S.N. Yashin ◽  
E.V. Koshelev ◽  
S.A. Borisov

Subject. This article discusses the issues related to the creation of a technology of modeling and optimization of economic, financial, information, and logistics cluster-cluster cooperation within a federal district. Objectives. The article aims to propose a model for determining the optimal center of industrial agglomeration for innovation and industry clusters located in a federal district. Methods. For the study, we used the ant colony optimization algorithm. Results. The article proposes an original model of cluster-cluster cooperation, showing the best version of industrial agglomeration, the cities of Samara, Ulyanovsk, and Dimitrovgrad, for the Volga Federal District as a case study. Conclusions. If the industrial agglomeration center is located in these three cities, the cutting of the overall transportation costs and natural population decline in the Volga Federal District will make it possible to qualitatively improve the foresight of evolution of the large innovation system of the district under study.


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