scholarly journals Quality of Protection on WDM networks: A Recovery Probability based approach

2015 ◽  
Author(s):  
Marcelo Rodas-Brítez ◽  
Diego Pinto-Roa
Keyword(s):  
Genetic Algorithm ◽  
Optical Fibers ◽  
Wdm Networks ◽  
New Paradigm ◽  
Generic Level ◽  
Network Cost ◽  
Quality Of Protection ◽  
Resource Distributions ◽  
Probability Concept

WDM networks survivability needs a flexible quality of protection (QoP) due to the variety of existing connection demands, lack of fair resource distributions under traditional QoP and optimal resources assignment. Thus, this paper proposes a new paradigm of QoP based on generic levels of protection where the set of protection levels can be defined as the network administrator needs, i.e., a flexible QoP approach whose particular case is the traditional or non-flexible QoP approach. Essentially, the proposed generic level is based on the recovery probability concept which measures the grade of conflict among primary lightpaths that share backup lighpaths for link failure recovery. In order to study how this strategy impacts on the network cost, a Genetic Algorithm is proposed. It calculates the primary and backup lightpaths, considering a multi-objective optimization on the basis of lexicographical sorting approach. The Genetic Algorithm minimizes the number of blocked requests, the number of services without protection, the total differences between the requested QoP and the assigned QoP, and the network cost; all of which by considering the optical fibers used and subject to the wavelength usage as constraint. The experimental results indicate that the proposed approach –flexible QoP– is a promising strategy where the network cost, the number of requests and QoP levels are contradictory objective functions in environments with homogeneous and heterogeneous QoP requirements.

scholarly journals Preface to the December 2015 issue

2015 ◽  
Author(s):  
Héctor Cancela
Keyword(s):  
Distributed Computing ◽  
Computer Science ◽  
Optical Networks ◽  
Mobile Devices ◽  
Wdm Networks ◽  
Domain Name ◽  
Historical Climate ◽  
Quality Of Protection ◽  
Security Models

We are glad to present the last issue of 2015, completing Volume 18 of the CLEI Electronic Journal. This issue is comprised by the following regular papers.The first paper, “Quality of Protection on WDM networks: A Recovery Probability based approach”, by M. D. Rodas-Brítez and D. P. Pinto-Roa, features a proposal of a new quality of protection (QoP) paradigm for Wavelength Division Multiplexing optical networks. The new approach is flexible, allowing the network administrator to define and select a set of protection levels, based on recovery probabilities which measure the degree of conflict among primary lightpaths sharing backup lightpaths. To show the interest of the approach, a Genetic Algorithm is used to design a routing strategy by multi-objectiveoptimization, minimizing the number of blocked requests, the number of services without protection, the total differences between the requested QoP and the assigned QoP, and the network cost.The second paper, “Towards Scalability for Federated Identity Systems for Cloud-Based Environments”, by A.A. Pereira, J. B. M. Sobral and C. M. Westphall, addresses scalability issues in identity management for cloud computing environments. The authors propose an adapted sticky-session mechanism, as an alternative approach to the more common distributed memory approach, and discuss the implications in therms of computational resources, throughput and overall efficiency. The following work, “Formal Analysis of Security Models for Mobile Devices, Virtualization Platforms, and Domain Name Systems”, by G. Betarte and C. Luna,tackles security models for security-critical applications in three areas: mobile devices, virtualization platforms, and domain name systems. The authors develop formalizations using the Calculus of Inductive Constructions, to study different usual variants of security models in these platforms and their properties.The last paper of this issue is “Digi-Clima Grid: image processing and distributed computing for recovering historical climate data”, by authors S. Nesmachnow, G. Usera and F. Brasileiro. This paper reports an experience of implementing semi-automatic techniques for digitalizing and recovering historical climate records applying parallel computing techniques over distributed computing infrastructures, which was applied to Uruguayan historical climate data.As we complete now the eighteenth year of continued existence of CLEIej, we thank the regional community for its continued support, and we encourage researchers working in computer science and its applications to consider submitting their work to CLEIej, as the the leading electronic, open access journal in Computer Science in Latin America.

Task scheduling algorithm based on improved genetic algorithm in cloud computing environment

2020 ◽  
Vol 13 ◽  
Author(s):  
Ge Weiqing ◽  
Cui Yanru
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Task Completion ◽  
Improved Genetic Algorithm ◽  
Fitness Functions ◽  
Task Scheduling Algorithm ◽  
Simulation Results

Background: In order to make up for the shortcomings of the traditional algorithm, Min-Min and Max-Min algorithm are combined on the basis of the traditional genetic algorithm. Methods: In this paper, a new cloud computing task scheduling algorithm is proposed, which introduces Min-Min and Max-Min algorithm to generate initialization population, and selects task completion time and load balancing as double fitness functions, which improves the quality of initialization population, algorithm search ability and convergence speed. Results: The simulation results show that the algorithm is superior to the traditional genetic algorithm and is an effective cloud computing task scheduling algorithm. Conclusion: Finally, this paper proposes the possibility of the fusion of the two quadratively improved algorithms and completes the preliminary fusion of the algorithm, but the simulation results of the new algorithm are not ideal and need to be further studied.

scholarly journals Genetic Algorithm for the Retailers’ Shelf Space Allocation Profit Maximization Problem

2021 ◽  
Vol 11 (14) ◽  
pp. 6401
Author(s):  
Kateryna Czerniachowska ◽  
Karina Sachpazidu-Wójcicka ◽  
Piotr Sulikowski ◽  
Marcin Hernes ◽  
Artur Rot
Keyword(s):  
Genetic Algorithm ◽  
Profit Maximization ◽  
Allocation Rule ◽  
Maximization Problem ◽  
Shelf Space ◽  
Allocation Model ◽  
Space Allocation ◽  
Shelf Space Allocation ◽  
To Receive

This paper discusses the problem of retailers’ profit maximization regarding displaying products on the planogram shelves, which may have different dimensions in each store but allocate the same product sets. We develop a mathematical model and a genetic algorithm for solving the shelf space allocation problem with the criteria of retailers’ profit maximization. The implemented program executes in a reasonable time. The quality of the genetic algorithm has been evaluated using the CPLEX solver. We determine four groups of constraints for the products that should be allocated on a shelf: shelf constraints, shelf type constraints, product constraints, and virtual segment constraints. The validity of the developed genetic algorithm has been checked on 25 retailing test cases. Computational results prove that the proposed approach allows for obtaining efficient results in short running time, and the developed complex shelf space allocation model, which considers multiple attributes of a shelf, segment, and product, as well as product capping and nesting allocation rule, is of high practical relevance. The proposed approach allows retailers to receive higher store profits with regard to the actual merchandising rules.

scholarly journals Mobile Networks and Internet of Things Infrastructures to Characterize Smart Human Mobility

Smart Cities ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 894-918
Author(s):  
Luís Rosa ◽  
Fábio Silva ◽  
Cesar Analide
Keyword(s):  
Internet Of Things ◽  
Mobile Networks ◽  
Smart Cities ◽  
Human Mobility ◽  
Rapid Development ◽  
Disruptive Technology ◽  
New Paradigm ◽  
Design And Optimization ◽  
High Level

The evolution of Mobile Networks and Internet of Things (IoT) architectures allows one to rethink the way smart cities infrastructures are designed and managed, and solve a number of problems in terms of human mobility. The territories that adopt the sensoring era can take advantage of this disruptive technology to improve the quality of mobility of their citizens and the rationalization of their resources. However, with this rapid development of smart terminals and infrastructures, as well as the proliferation of diversified applications, even current networks may not be able to completely meet quickly rising human mobility demands. Thus, they are facing many challenges and to cope with these challenges, different standards and projects have been proposed so far. Accordingly, Artificial Intelligence (AI) has been utilized as a new paradigm for the design and optimization of mobile networks with a high level of intelligence. The objective of this work is to identify and discuss the challenges of mobile networks, alongside IoT and AI, to characterize smart human mobility and to discuss some workable solutions to these challenges. Finally, based on this discussion, we propose paths for future smart human mobility researches.

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