scholarly journals Moving towards Smart Cities: A Selection of Middleware for Fog-to-Cloud Services

2018 ◽  
Vol 8 (11) ◽  
pp. 2220 ◽  
Author(s):  
Hind Bangui ◽  
Said Rakrak ◽  
Said Raghay ◽  
Barbora Buhnova
Keyword(s):  
Selection Process ◽  
Smart Cities ◽  
Cloud Model ◽  
Research Question ◽  
Edge Computing ◽  
Cloud Services ◽  
Fuzzy Similarity ◽  
Customer Services ◽  
Topsis Technique ◽  
Selection Of

Smart cities aim at integrating various IoT (Internet of Things) technologies by providing many opportunities for the development, governance, and management of user services. One of the ways to support this idea is to use cloud and edge computing techniques to reduce costs, manage resource consumption, enhance performance, and connect the IoT devices more effectively. However, the selection of services remains a significant research question since there are currently different strategies towards cloud computing, including services for central remote computing (traditional cloud model) as well as distributed local computing (edge computing). In this paper, we offer an integrated view of these two directions and the selection among the edge technologies based on MCDA (Multiple Criteria Decision Analysis) algorithms. To this end, we propose a foglet as a middleware that aims at achieving satisfactory levels of customer services by using fuzzy similarity and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) to facilitate the rating and selection of services in the fog-to-cloud environment. Then, we describe the selection process with a numerical example, and conclude our work with an outline of future perspectives.

scholarly journals Supplier selection using different metric functions

2015 ◽  
Vol 25 (3) ◽  
pp. 413-423 ◽  
Author(s):  
S.E. Omosigho ◽  
Dickson Omorogbe
Keyword(s):  
Supplier Selection ◽  
Selection Process ◽  
Fuzzy Topsis ◽  
Ideal Solution ◽  
Order Preference ◽  
Metric Functions ◽  
Metric Function ◽  
Topsis Technique ◽  
Intuitionistic Fuzzy Topsis ◽  
Selection Of

Supplier selection is an important component of supply chain management in today?s global competitive environment. Hence, the evaluation and selection of suppliers have received considerable attention in the literature. Many attributes of suppliers, other than cost, are considered in the evaluation and selection process. Therefore, the process of evaluation and selection of suppliers is a multi-criteria decision making process. The methodology adopted to solve the supplier selection problem is intuitionistic fuzzy TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution). Generally, TOPSIS is based on the concept of minimum distance from the positive ideal solution and maximum distance from the negative ideal solution. We examine the deficiencies of using only one metric function in TOPSIS and propose the use of spherical metric function in addition to the commonly used metric functions. For empirical supplier selection problems, more than one metric function should be used.

A TOPSIS-Based Multi-Criteria Approach to Faculty Recruitment: A Case Study

2013 ◽  
Vol 415 ◽  
pp. 741-744
Author(s):  
D.K. Behera ◽  
Asis Sarkar
Keyword(s):  
Decision Making ◽  
Selection Process ◽  
Real Life ◽  
Fuzzy Topsis ◽  
Educational Background ◽  
Strategic Decision ◽  
Success Factor ◽  
Strategy Formulation ◽  
Topsis Technique ◽  
Selection Of

Selection of qualified faculty is a key success factor for any university. The aim of this paper is to support adequately the decision making process for those connected with the faculty selection process. The steps of fuzzy TOPSIS technique are considered, incorporating a new concept for the ranking of the alternative candidates. The candidates are judged on the following criterias such as strategy formulation/strategic decision making capability, change management /change adaptability, communication/interpersonal skill, leadership, risk/crisis management, knowledge of software/software tools , professional experience , and educational background. Five candidates with different skills are taken for the judgment of their fate. They were asked to answer a set of questionnaires made by the experts and after that they were evaluated by the experts board. The real life application on the selection of any executive member/post shows the practical utility of this method.

scholarly journals Efficient of Floading Approach for Resource Allocation and Optimization in Mobile Edge Computing Environment

2021 ◽  
Vol 12 (6) ◽  
pp. 2581-2593
Author(s):  
C. Anuradha, M. Ponnavaikko
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Smart Cities ◽  
Edge Computing ◽  
Cloud Services ◽  
Security And Privacy ◽  
The Internet ◽  
Mobile Edge Computing ◽  
Major Barrier

Cloud computing provides a platform for services and resources over the internet for users. The large pool of data resources and services has enabled the emergence of several novel applications such as smart grids, smart environments, and virtual reality. However, the state-of-the-art of cloud computing faces a delay constraint, which becomes a major barrier for reliable cloud services. This constraint is mostly highlighted in the case of smart cities (SC) and the Internet of Things (IoT). Therefore, the recent cloud computing paradigm has poor performance and cannot meet the low delay, navigation, and mobility support requirements.Machine-to-machine (M2M) connectivity has drawn considerable interest from both academia and industry with a growing number of machine-type communication devices (MTCDs). The data links with M2M communications are usually small but high bandwidth, unlike conventional networking networks, demanding performance management of both energy consumption and computing. The main challenges faced in mobile edge computing are task offloading, congestion control, Resource allocation, security and privacy issue, mobility and standardization .Our work mainly focus on offloading based resource allocation and security issues by analyzing the network parameters like reduction of latency and improvisation of bandwidth involved in cloud environment. The cloudsim simulation tool has been utilized to implement the offload balancing mechanism to decrease the energy consumption and optimize the computing resource allocation as well as improve computing capability.

scholarly journals Number of Financial Indicators as a Factor of Multi-Criteria Analysis via the TOPSIS Technique: A Municipal Case Study

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 64 ◽  
Author(s):  
Roman Vavrek ◽  
Jiří Bečica ◽  
Viera Papcunová ◽  
Petra Gundová ◽  
Jana Mitríková
Keyword(s):  
Assessment Tool ◽  
Selection Process ◽  
Financial Health ◽  
Efficiency Assessment ◽  
Private And Public ◽  
Multi Criteria Analysis ◽  
Topsis Technique ◽  
Key Indicators ◽  
Selection Of

Multi-criteria analysis is a decision-making and efficiency assessment tool for application in both the private and public sectors. Its application is preceded by the selection of suitable indicators and a homogenous set of variants, as well as suitable methods based on the nature of the input data. The goal of the submitted research is to highlight the importance of selecting suitable indicators using a case study assessment of the financial health of a municipality—more precisely, the efficiency of management of this municipality. Four key indicators, thirty-two homogenous subjects, and one multi-criteria analysis method were identified in this study based on the theoretical foundations of the specific issue. These elements were processed into a total of 14 variants depending on the number of assessed indicators. Then, these results were subjected to statistical verification alongside verification using the Jaccard index. Based on the acquired results, we highlight the need for correct and expert identification of the relevant sets of alternatives (the criteria matrix) and expert discussion, which should precede the selection of the assessed indicators and objectify this selection process as much as possible. Assessment based on a low number of indicators was shown to be insufficient, highly variable, and diverse, and these differences were partially eliminated as the number of assessed indicators increased.

scholarly journals Indicators to Choose a Suitable Marketing Automation Platform

2018 ◽  
Vol 4 (3) ◽  
pp. 52-60
Author(s):  
Florian Berghofer ◽  
Günter Hofbauer ◽  
Anita Sangl
Keyword(s):  
Selection Process ◽  
Research Question ◽  
Selection Procedure ◽  
Marketing Automation ◽  
Marketing Technology ◽  
Customer Information ◽  
Academic Discussion ◽  
Key Aspects ◽  
Critical Literature ◽  
Selection Of

Marketing automation platforms are an efficient tool for the collection, analysis and the processing of customer information. As a consequence, they are a highly relevant aspect of modern marketing, both for the practical and academic discussion. The rising demand implicates a more complex vendor landscape, whereby the comparison and selection of marketing technology are getting increasingly difficult. This article is an analytical and conceptual paper. The research question deals with the identification of indicators regarding the selection of a suitable marketing automation platform. Initially, the increasing necessity of marketing technology is pointed out. A general understanding of marketing automation as relevant subarea of marketing technology will be enabled. For this reason, a definition, relevant features as well as chances and risks are presented on the basis of a critical literature research. A holistic decision model for choosing a marketing automation solution complements the basic information and shows a selection procedure as well as the most essential selection and evaluation indicators. The specific contribution for academic discussion is twofold: Firstly, the key aspects of marketing automation are presented, and its basics are introduced. Secondly, this paper describes a framework that serves as recommendation and orientation for the selection process of marketing automation platforms and marketing technology.

Spatial Autocorrelation in the Study of Neighbourhoods towards Smart Cities: Empirical Evidence from Kerman, Iran

2012 ◽  
Vol 9 (2) ◽  
pp. 1
Author(s):  
Asra Hosseini
Keyword(s):  
Spatial Autocorrelation ◽  
Urban Areas ◽  
Smart Cities ◽  
Moran’S I ◽  
Moran's I ◽  
Urban Planner ◽  
Universal Feature ◽  
Autocorrelation Method ◽  
Selection Of

From earliest cities to the present, spatial division into residential zones and neighbourhoods is the universal feature of urban areas. This study explored issue of measuring neighbourhoods through spatial autocorrelation method based on Moran's I index in respect of achieving to best neighbourhoods' model for forming cities smarter. The research carried out by selection of 35 neighbourhoods only within central part of traditional city of Kerman in Iran. The results illustrate, 75% of neighbourhoods' area in the inner city of Kerman had clustered pattern, and it shows reduction in Moran's index is associated with disproportional distribution of density and increasing in Moran's I and Z-score have monotonic relation with more dense areas and clustered pattern. It may be more efficient for urban planner to focus on spatial autocorrelation to foster neighbourhood cohesion rather than emphasis on suburban area. It is recommended characteristics of historic neighbourhoods can be successfully linked to redevelopment plans toward making city smarter, and also people's quality of life can be related to the way that neighbourhoods' patterns are defined. 

Spatial Autocorrelation in the Study of Neighbourhoods towards Smart Cities: Empirical Evidence from Kerman, Iran

2012 ◽  
Vol 9 (2) ◽  
pp. 1
Author(s):  
Asra Hosseini
Keyword(s):  
Spatial Autocorrelation ◽  
Smart Cities ◽  
Moran’S I ◽  
Moran's I ◽  
Urban Planner ◽  
Universal Feature ◽  
Autocorrelation Method ◽  
Selection Of ◽  
Monotonic Relation

From earliest cities to the present, spatial division into residential zones and neighbourhoods is the universal feature ofurban areas. This study explored issue ofmeasuring neighbourhoods through spatial autocorrelation method based on Moran's I index in respect of achieving to best neighbourhoods' model for forming cities smarter. The research carried out by selection of 35 neighbourhoods only within central part of traditional city of Kerman in Iran. The results illustrate, 75% ofneighbourhoods, area in the inner city of Kerman had clustered pattern, and it shows reduction in Moran's index is associated with disproportional distribution of density and increasing in Moran's I and Z-score have monotonic relation with more dense areas and clustered pattern. It may be more efficient for urban planner to focus on spatial autocorrelation to foster neighbourhood cohesion rather than emphasis on suburban area. It is recommended characteristics of historic neighbourhoods can be successfully linked to redevelopment plans toward making city smarter, and also people's quality of life can be related to the way that neighbourhoods' patterns are defined.

IMPLEMENTASI PENENTUAN ARSITEKTUR MASJID MODERN DI ACEH MENGGUNAKAN PEMODELAN SISTEM CERDAS

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Soraya Masthura Hasan ◽  
T Iqbal Faridiansyah
Keyword(s):  
Fuzzy Inference System ◽  
Architectural Design ◽  
Fuzzy Inference ◽  
Intelligent System ◽  
Selection Process ◽  
System Modeling ◽  
Inference System ◽  
Normal Limits ◽  
Roof Structure ◽  
Selection Of

Mosque architectural design is based on Islamic culture as an approach to objects and products from the Islamic community by looking at their suitability and values and basic principles of Islam that explore more creative and innovative ideas. The purpose of this system is to help the team and the community in seeing the best mosque in the top order so that the system can be used as a reference for the team and the community. The variables used in the selection of modern mosques include facilities and infrastructure, building structure, roof structure, mosque area, level of security and facilities. The system model used is a fuzzy promethee model that is used for the modern mosque selection process. Fuzzy inference assessment is used to determine the value of each variable so that the value remains at normal limits. Fuzzy values will then be included in promethee assessment aspects. The highest promethee ranking results will be made a priority for the best mosque ranking. This fuzzy inference system and promethee system can help the management team and the community in determining the selection of modern mosques in aceh in accordance with modern mosque architecture. Intelligent System Modeling System In Determining Modern Mosque Architecture in the City of Aceh, this building will be web based so that all elements of society can see the best mosque in Aceh by being assessed by all elements of modern mosque architecture.Keywords: Fuzzy inference system, Promethe, Option of  Masjid

Love Your Enemy: A Christian Response to Embrace Others

2020 ◽  
Author(s):  
Hanna Dewi Aritonang ◽  
Bestian Simangunsong ◽  
Adiani Hulu
Keyword(s):  
Jesus Christ ◽  
Research Question ◽  
Theological Reflection ◽  
Religious Communities ◽  
Religious People ◽  
Lifestyle Choice ◽  
Sustainable Peace ◽  
Research Problems ◽  
Selection Of

This article addresses the issue of conflict between religious communities that cause enmity amid society. Hostilities must be overcome and resolved in accordance with the call of Christianity to live in love and peace. The study used the qualitative paradigm as the method of the research and the descriptive-analyses as the writing method by describing the research problems based on data collected from related publications.One of the powerful messages of Jesus's teaching is "Love your enemies." It’s one of the greatest challenges in life. Jesus Christ gave an important doctrine about loving the enemy because love is more powerful than evil, hurtful deeds. Loving the enemy means canceling hostilities and violence, but instead, it promises acceptance of each other. The title of this study is "love your enemies": A Christian Response to Embrace Others. As the title of this study is "love your enemies," the reason for the selection of this article is because the author sees that "loving the enemy is a commandment from God that must be obeyed. This research question emphasizes how to realize "loving the enemy" amid hostility. This paper argues that Jesus's command to love the enemy is a proper Christian lifestyle choice in the midst of hostility. We use CS Song thoughts, which elaborated with other scholars' views on theology, loving, and embracing others. The purpose of the research was to gain understanding and build a theological reflection on Jesus' commandment to love the enemy. In this article, we first briefly discuss the portrait of life among religious people in Indonesia. Secondly, we discuss the conflict between religious people in Indonesia. Finally, we apply the command of Jesus to love our enemy as a Christian lifestyle in the midst of hostility to construct harmony amid hostility. We propose the command of Jesus to ‘love your enemy’ as a response to establishing sustainable peace by embrace others. Finally, the Christians must become a loving community because God so loved us, and we also ought to love and embrace others.

scholarly journals A novel two-phase cycle algorithm for effective cyber intrusion detection in edge computing

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yiguang Gong ◽  
Yunping Liu ◽  
Chuanyang Yin
Keyword(s):  
Intrusion Detection ◽  
Optimal Parameter ◽  
Edge Computing ◽  
Cloud Services ◽  
Second Phase ◽  
Pareto Optimal ◽  
Two Phase ◽  
Multi Objective ◽  
Phase Cycle ◽  
Positive Rate

AbstractEdge computing extends traditional cloud services to the edge of the network, closer to users, and is suitable for network services with low latency requirements. With the rise of edge computing, its security issues have also received increasing attention. In this paper, a novel two-phase cycle algorithm is proposed for effective cyber intrusion detection in edge computing based on a multi-objective genetic algorithm (MOGA) and modified back-propagation neural network (MBPNN), namely TPC-MOGA-MBPNN. In the first phase, the MOGA is employed to build a multi-objective optimization model that tries to find the Pareto optimal parameter set for MBPNN. The Pareto optimal parameter set is applied for simultaneous minimization of the average false positive rate (Avg FPR), mean squared error (MSE) and negative average true positive rate (Avg TPR) in the dataset. In the second phase, some MBPNNs are created based on the parameter set obtained by MOGA and are trained to search for a more optimal parameter set locally. The parameter set obtained in the second phase is used as the input of the first phase, and the training process is repeated until the termination criteria are reached. A benchmark dataset, KDD cup 1999, is used to demonstrate and validate the performance of the proposed approach for intrusion detection. The proposed approach can discover a pool of MBPNN-based solutions. Combining these MBPNN solutions can significantly improve detection performance, and a GA is used to find the optimal MBPNN combination. The results show that the proposed approach achieves an accuracy of 98.81% and a detection rate of 98.23% and outperform most systems of previous works found in the literature. In addition, the proposed approach is a generalized classification approach that is applicable to the problem of any field having multiple conflicting objectives.

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