scholarly journals Variants of the Low-Energy Adaptive Clustering Hierarchy Protocol: Survey, Issues and Challenges

Electronics ◽  
2018 ◽  
Vol 7 (8) ◽  
pp. 136 ◽  
Author(s):  
Mohammed Al-Shalabi ◽  
Mohammed Anbar ◽  
Tat-Chee Wan ◽  
Ahmad Khasawneh
Keyword(s):  
Power Consumption ◽  
Cluster Formation ◽  
Specific Area ◽  
Modern Technology ◽  
Low Energy ◽  
Future Research ◽  
Radio Communication ◽  
Adaptive Clustering ◽  
Research Guidelines ◽  
Current Survey

A wireless sensor network (WSN) is a modern technology in radio communication. A WSN comprises a number of sensors that are randomly spread in a specific area for sensing and monitoring physical attributes that are difficult to monitor by humans, such as temperature, humidity, and pressure. Many problems, including data routing, power consumption, clustering, and selecting cluster heads (CHs), may occur due to the nature of WSNs. Various protocols have been conducted to resolve these issues. One of the important hierarchical protocols that are used to reduce power consumption in WSNs is low-energy adaptive clustering hierarchy (LEACH). This paper presents a comprehensive study of clustering protocols for WSNs that are relevant to LEACH. This paper is the first to emphasis on cluster formation and CHs selection methods and their strengths and weaknesses. A new taxonomy is presented to discuss LEACH variants on the basis of different classes, and the current survey is compared with other existing surveys. A complete comparison of the location, energy, complexity, reliability, multi–hop path, and load balancing characteristics of LEACH variants is conducted. Future research guidelines for CHs selection and cluster formation in WSNs are also discussed.

scholarly journals Genetic algorithm based protocols to select cluster heads and find multi-hop path in wireless sensor networks: review

2018 ◽  
Vol 218 ◽  
pp. 03019 ◽  
Author(s):  
Mohammed Al-Shalabi ◽  
Mohammed Anbar ◽  
Tat-Chee Wan
Keyword(s):  
Genetic Algorithm ◽  
Optimization Technique ◽  
Specific Area ◽  
Modern Technology ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Path Finding ◽  
Radio Communication ◽  
Cluster Heads

A wireless sensor network (WSN) is a modern technology in radio communication. A WSN comprises a number of sensor nodes that are randomly spread in a specific area for sensing and monitoring physical attributes that are difficult to monitor by humans, such as temperature, fire, and pressure. Many problems, including data transmission, power consumption and selecting cluster heads, may occur due to the nature of WSNs. Various protocols have been conducted to resolve these issues. Most of the proposed protocols are based on the Genetic Algorithm as an optimization technique to select the Cluster Heads (CHs) or to find a multi-hop path for sending the data from the CHs to the Base Station (BS). This paper presents a comprehensive study of the protocols for WSNs that are proposed to come up with these issues. This study emphasises on CHs selection protocols and multi-hop path finding protocols and their strengths and weaknesses. A new taxonomy is presented to discuss these protocols on the basis of different classes. A complete comparison of the main features and behaviors of the protocols is conducted. This study will give basic guidelines for the researchers those have a motivation to develop a new CHs selection protocol or a multi-hop path finding protocol.

scholarly journals Computational Intelligence based Clustering Algorithms for Wireless Sensor Networks: Trends and Possible Solutions

2021 ◽  
Vol 12 (2) ◽  
pp. 2992-3002
Author(s):  
Nitin Mittal
Keyword(s):  
Computational Intelligence ◽  
Clustering Algorithms ◽  
Cluster Head ◽  
Low Energy ◽  
Wireless Sensor ◽  
Clustering Methods ◽  
Radio Communication ◽  
Adaptive Clustering ◽  
Ch Selection ◽  
Selection Of

A wireless sensor network (WSN) is a state-of-the-art technology for radio communication. A WSN includes several sensors that are arbitrarily distributed in a particular region to detect and track physical characteristics that are hard for humans to observe, like temperature, humidity, and pressure. Because of the nature of WSNs, many issues may arise, including information routing, power consumption, clustering, and cluster head (CH) selection.  Although there are still some difficulties in the WSN, owing to its versatility and robustness, it has gained considerable attention among scientists and technologists despite the shortcomings. Various protocols were designed to solve these problems. Low energy adaptive clustering hierarchy (LEACH) is one of the significant hierarchical protocols used to reduce energy consumption in WSNs. This article provides an extensive analysis of LEACH-variant clustering protocols for WSNs. Recent research on Machine Learning, Computational Intelligence, and WSNs has highlighted the optimized WSN clustering algorithms. However, the selection of a suitable paradigm for a clustering solution continues an issue owing to the diversity of WSN applications. In this paper, a comprehensive review of suggested optimized clustering alternatives has been conducted and a comparison of these optimized clustering methods has been suggested based on various performance parameters. The centralized clustering approaches based on the Swarm Intelligence paradigm are observed to be more suitable for the applications in which low energy is required, high information delivery rate, or elevated scalability than algorithms that are based on the other paradigms described.

scholarly journals Estimating the Financial Return to Education Between Fields of Study

SURG Journal ◽  
2019 ◽  
Vol 11 ◽  
Author(s):  
Jeffrey Alexander McRae
Keyword(s):  
Specific Area ◽  
Population Data ◽  
Return To Education ◽  
Future Research ◽  
Engineering Majors ◽  
Business Majors ◽  
Expected Return ◽  
Financial Return ◽  
Fields Of Study ◽  
Canadian Population

The Mincer regression equation was utilized to compute the expected financial return to education from additional years of education across the 2016 Canadian population. Data was taken from the 2016 Canadian Census of Population to create the populations of interest. Three sub populations were then derived from the collected data to represent Canadians with different major areas of study namely, business, humanities, and engineering. Mincerian regressions were run using these subsections to determine how the financial return to education differs between distinct majors. Additional multiple regressions included an interaction term between sex and years of schooling in an attempt to determine whether an individual’s sex affects their expected return to education given a specific area of study. The regression results indicated that business majors boast the largest average expected return to education while engineering majors boast the lowest. Subsequently, in relation to business majors, sex was not found to have an impact on expected financial returns. Future research may build off the findings of this paper by expanding the scope to include all areas of study in addition to deciphering whether the expected return to education for a given major is consistent throughout all major Canadian universities.

Giving negative feedback to Millennials

2016 ◽  
Vol 39 (6) ◽  
pp. 692-705 ◽  
Author(s):  
Emylee Anderson ◽  
Aaron A. Buchko ◽  
Kathleen J. Buchko
Keyword(s):  
Negative Feedback ◽  
Millennial Generation ◽  
Management Practice ◽  
Baby Boom ◽  
Demographic Data ◽  
Specific Area ◽  
Future Research ◽  
Content Type ◽  
Managerial Practices ◽  
New Generation

Purpose Demographic data indicate that the Millennial generation (those born between 1982 and the early 2000s) are entering the workforce and will become an increasingly significant component of the workforce in the near future. The Millennial generation appears to have significant differences in values, attitudes and expectations regarding work than prior generations. Design/methodology/approach The authors reviewed the literature on the “Millennial” generation (those born between 1982 and the early 2000s) and the research on giving negative feedback to identify issues that are significant with respect to the manner in which managers give negative information to this new generation of workers. Findings To be effective, negative feedback to Millennials needs to be consistent and ongoing. The feedback must be perceived by Millennials as benefitting them now or in the future. Managers must be assertive enough to make sure the employee understands the concerns, but sensitive to the fact that many Millennials have difficulty accepting such feedback. Research limitations/implications These findings offer suggestions for future research that needs to explicitly examine the differences in the new generation of workers and how these persons respond to current managerial practices. Practical implications Millennials are now entering the workforce in significant numbers. Managers will find increasing opportunities to address the organizational and individual needs of these workers. Managers must learn how to effectively direct and motivate this generation of workers, including how to provide constructive negative feedback. Social implications Demographic data indicate that the so-called “Baby Boom” generation will be leaving the workforce in large numbers over the next few years, and will be replaced by the Millennial generation. Originality/value To date, there has been little attempt by management researchers to address the organizational implications of the generational shift that is occurring. We seek to draw attention to one specific area of management practice – delivering negative feedback – and explore how the knowledge may be changing as a new generation of workers enter the workplace.

Auditing Defense Against XSS Worms in Online Social Network-Based Web Applications

2018 ◽  
pp. 879-909
Author(s):  
Pooja Chaudhary ◽  
Shashank Gupta ◽  
B. B. Gupta
Keyword(s):  
Social Network ◽  
Cyber Security ◽  
Web Applications ◽  
Online Social Network ◽  
Denial Of Service ◽  
Future Research ◽  
Ddos Attacks ◽  
Research Guidelines ◽  
High Level ◽  
Precise Interpretation

Nowadays, users of Online Social Network (OSN) are less familiar with cyber security threats that occur in such networks, comprising Cross-Site Scripting (XSS) worms, Distributed Denial of Service (DDoS) attacks, Phishing, etc. Numerous defensive methodologies exist for mitigating the effect of DDoS attacks and Phishing vulnerabilities from OSN. However, till now, no such robust defensive solution is proposed for the complete alleviation of XSS worms from such networks. This chapter discusses the detailed incidences of XSS attacks in the recent period on the platforms of OSN. A high level of taxonomy of XSS worms is illustrated in this article for the precise interpretation of its exploitation in multiple applications of OSN like Facebook, Twitter, LinkedIn, etc. We have also discussed the key contributions of current defensive solutions of XSS attacks on the existing platforms of OSN. Based on this study, we identified the current performance issues in these existing solutions and recommend future research guidelines.

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