A Bees Life Algorithm for Cloud Computing Services Selection

2012 ◽  
pp. 31-46
Author(s):  
Salim Bitam ◽  
Mohamed Batouche ◽  
El-Ghazali Talbi
Keyword(s):  
Cloud Computing ◽  
Optimization Problems ◽  
Population Based ◽  
Computational Time ◽  
Future Research ◽  
Bee Colony ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Future Research Directions ◽  
Population Based Algorithm

In recent years, the scientific community has begun to model and solve complex optimization problems using bio-inspired methods. Such problems cannot be solved exactly by traditional methods within a reasonable complexity in terms of computer capacities or computational times. However, bio-inspired methods provide near optimal solutions in realist conditions such as cost, capacity, and computational time. In this chapter, the authors propose a new population-based algorithm called the Bees Life Algorithm (BLA). It is applied to solve the cloud computing services selection with quality of service (QoS) requirements. It is considered as swarm-based algorithm, which closely imitates the life of the bee colony. It follows the two important behaviors in the nature of bees, reproduction and food foraging. Bees life algorithm can be applied to the combinatorial optimization problems as well as to the functional optimization problems. An experimental study has been conducted in order to demonstrate the performance and the efficiency of the proposal and its robustness. After comparisons with genetic algorithm (GA) as referential algorithm in this field, the obtained results showed the BLA performance and effectiveness. Finally, promising future research directions are examined to show the BLA usefulness for research in the cloud computing and computational intelligence areas.

Applying CI in Biology through PSO

2020 ◽  
pp. 502-527
Author(s):  
Rojalina Priyadarshini ◽  
Nilamadhab Dash ◽  
Brojo Kishore Mishra ◽  
Rachita Misra
Keyword(s):  
Optimization Problems ◽  
Real Life ◽  
Population Based ◽  
Computing Methods ◽  
Future Research ◽  
Natural Systems ◽  
Solution Methods ◽  
Working Together ◽  
Future Research Directions ◽  
Population Based Algorithm

Conventional computing methods face challenges dealing with real world problems, which are characterised by noisy or incomplete data. To find solutions for such problems, natural systems have evolved over the years and on analysis it has been found these contain many simple elements when working together to solve real life complex problems. Swarm Intelligence (SI) is one of the techniques which is inspired by nature and is a population based algorithm motivated by the collective behaviour of a group of social insects. Particle swarm optimization (PSO) is one of the techniques belonging to this group, used to solve some optimization problems. This chapter will discuss some of the problems existing in computational biology, their contemporary solution methods followed by the use of PSO to address those problems. Along with this several applications of PSO are discussed in few of the relevant fields are discussed having some future research directions on this field.

Meta-Heuristic and Non-Meta-Heuristic Energy-Efficient Load Balancing Algorithms in Cloud Computing

2020 ◽  
pp. 203-222
Author(s):  
Rojalina Priyadarshini ◽  
Rabindra Kumar Barik ◽  
Brojo Kishore Mishra
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Energy Efficient ◽  
Future Research ◽  
Computing Paradigm ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Future Research Directions ◽  
Cloud Environments ◽  
Power And Energy

The number of users of cloud computing services is drastically increasing, thereby increasing the size of data centers across the globe. In virtue of it, the consumption of power and energy is a major concern for system designers and developers. Their goal is now to develop power and energy-efficient products at the same time maintaining the quality and cost of products and services. For managing the power and efficiency, several aspects are taken into consideration in cloud computing paradigm. Load balancing, task scheduling, task migration, resource allocation are some of the techniques, which need to be efficiently employed to minimize the energy consumption. This chapter represents the detailed survey of the existing solutions and approaches for energy-efficient load balancing algorithms used in cloud environments. The research challenges as well as future research directions are also discussed in this chapter.

Applying CI in Biology through PSO

2016 ◽  
pp. 119-143
Author(s):  
Rojalina Priyadarshini ◽  
Nilamadhab Dash ◽  
Brojo Kishore Mishra ◽  
Rachita Misra
Keyword(s):  
Optimization Problems ◽  
Real Life ◽  
Population Based ◽  
Computing Methods ◽  
Future Research ◽  
Natural Systems ◽  
Solution Methods ◽  
Working Together ◽  
Future Research Directions ◽  
Population Based Algorithm

Conventional computing methods face challenges dealing with real world problems, which are characterised by noisy or incomplete data. To find solutions for such problems, natural systems have evolved over the years and on analysis it has been found these contain many simple elements when working together to solve real life complex problems. Swarm Intelligence (SI) is one of the techniques which is inspired by nature and is a population based algorithm motivated by the collective behaviour of a group of social insects. Particle swarm optimization (PSO) is one of the techniques belonging to this group, used to solve some optimization problems. This chapter will discuss some of the problems existing in computational biology, their contemporary solution methods followed by the use of PSO to address those problems. Along with this several applications of PSO are discussed in few of the relevant fields are discussed having some future research directions on this field.

Managing the Cloud for Information Systems Agility

2015 ◽  
pp. 1877-1899
Author(s):  
Haibo Yang ◽  
Sid Huff ◽  
Mary Tate
Keyword(s):  
Cloud Computing ◽  
Information Systems ◽  
Literature Review ◽  
Rapid Development ◽  
Major Change ◽  
Future Research ◽  
Turbulent Environment ◽  
Computing Services ◽  
Modern Business ◽  
Cloud Computing Services

Change is endemic in modern business competition. In an age of globalization, with the rapid development of Internet technologies, changes occur at a much faster pace, and are also more unpredictable. Being agile in a turbulent environment has been ranked highly by executives in surveys of business issues conducted in past five years. Today nearly all organizations rely on information systems (IS) to operate. Agility in IS is critical in achieving overall agility in business. However, despite the interest from the practitioner community, IS agility (sometimes termed IT agility) in academia has received limited recognition and represents an under-researched area. The recent adoption of cloud computing services has presented a major change in the way IS are delivered, in the hope of creating more agile and responsive IS. However, whether or not cloud computing, as promised by the providers, increases IS agility, is still unclear. This research aims at providing a conceptualization of IS agility based on research to date, and examining how cloud computing might facilitate such agility. Based on a literature review, cloud computing services (IaaS, PaaS, and SaaS) are analyzed against multiple aspects of IS agility. Only IaaS is found to have the potential providing consistent agility, whereas agility at PaaS and SaaS levels is more determined by human/organization factors. Lastly, suggestions for businesses and directions to future research are proposed.

Managing the Cloud for Information Systems Agility

2012 ◽  
pp. 70-93 ◽  
Author(s):  
Haibo Yang ◽  
Sid L. Huff ◽  
Mary Tate
Keyword(s):  
Cloud Computing ◽  
Information Systems ◽  
Literature Review ◽  
Rapid Development ◽  
Major Change ◽  
Future Research ◽  
Turbulent Environment ◽  
Computing Services ◽  
Modern Business ◽  
Cloud Computing Services

Change is endemic in modern business competition. In an age of globalization, with the rapid development of Internet technologies, changes occur at a much faster pace, and are also more unpredictable. Being agile in a turbulent environment has been ranked highly by executives in surveys of business issues conducted in past five years. Today nearly all organizations rely on information systems (IS) to operate. Agility in IS is critical in achieving overall agility in business. However, despite the interest from the practitioner community, IS agility (sometimes termed IT agility) in academia has received limited recognition and represents an under-researched area. The recent adoption of cloud computing services has presented a major change in the way IS are delivered, in the hope of creating more agile and responsive IS. However, whether or not cloud computing, as promised by the providers, increases IS agility, is still unclear. This research aims at providing a conceptualization of IS agility based on research to date, and examining how cloud computing might facilitate such agility. Based on a literature review, cloud computing services (IaaS, PaaS, and SaaS) are analyzed against multiple aspects of IS agility. Only IaaS is found to have the potential providing consistent agility, whereas agility at PaaS and SaaS levels is more determined by human/organization factors. Lastly, suggestions for businesses and directions to future research are proposed.

An Entrepreneurial Approach to Cloud Computing Design and Application

2018 ◽  
pp. 190-203
Author(s):  
Vanessa Ratten
Keyword(s):  
Cloud Computing ◽  
Technological Innovation ◽  
Future Research ◽  
Technological Innovations ◽  
Computing Services ◽  
Innovative System ◽  
Cloud Computing Services ◽  
The Government ◽  
Design And Application

The design and application of cloud computing services is inherently entrepreneurial as it is constantly evolving as a result of technological innovation. This chapter focuses on providing an entrepreneurial approach to understanding change in the cloud computing context by highlighting the importance of innovative system usage. The chapter discusses how cloud computing services are creating a ecosystem of mobile commerce applications that is changing the way consumers, businesses and the government collects, disseminates and stores information. These changes have given way to entrepreneurial service innovations in the cloud domain that are a result of consumer demand for more current and relevant technological innovations. This chapter addresses the role of entrepreneurship in technological innovations by focusing on marketing and learning applications that are unique to cloud computing services. The future research suggestions from this chapter stress the importance nature of being entrepreneurial to encourage technological innovation in the cloud computing context.

Behavioral Intentions to Adopt Technological Innovations

2014 ◽  
Vol 10 (3) ◽  
pp. 1-12 ◽  
Author(s):  
Vanessa Ratten
Keyword(s):  
Cloud Computing ◽  
Technology Acceptance ◽  
Cognitive Theory ◽  
Perceived Usefulness ◽  
Future Research ◽  
Technological Innovations ◽  
Chinese Consumers ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Acceptance Model

Cloud computing services are a prominent innovation that has changed consumer behaviours towards adopting new technological services. Despite the popularity of this technological innovation the underlying factors that contribute to a consumer's intention to adopt cloud computing services has not been well researched. This paper builds upon the well-known behavioural intention theories of the technology acceptance model and social cognitive theory to develop and test a number of hypotheses designed to understand the factors influencing intention to use cloud computing services. The research hypotheses in the paper propose that perceived usefulness, consumer innovation attitude, social norms, performance expectancy and trust influence behavioural intentions of consumers towards cloud computing services. The hypotheses are tested in a sample of United States and Chinese consumers to understand whether there are differences in behavioural attitudes towards technological innovations. The paper identifies research limitations, practical implications and future research suggestions.

scholarly journals A taxonomy of : The reviews on Cloud Computing Direction (CCD)

2015 ◽  
Vol 4 (1) ◽  
pp. 204
Author(s):  
Alla Talal Yassin ◽  
Ban Kassim Alnidawy
Keyword(s):  
Cloud Computing ◽  
Manufacturing Industry ◽  
High Reliability ◽  
Future Research ◽  
Educational Materials ◽  
Computing Services ◽  
On Line ◽  
Major Transformation ◽  
Future Research Directions ◽  
Smart Technologies

<p>The manufacturing industry is undergoing a major transformation enabled by IT and related smart technologies. The main thrust of Cloud computing is to provide on-demand computing services with high reliability, scalability and availability in a distributed environment. This paper summarizes our taxonomy of the CC review direction. The goals of this taxonomy were (i) clarify the needs and the directions of the use of the CC, (ii) define the academic and practical issues involved in CC , (iii) learn the state of the directions on methodologies of the CC , (iv) identify future research directions, which benefit the short and long terms. The taxonomy has concluded that (i) CC is advantageous in dealing with changes and uncertainties in the every-changing environment. (ii)It has been found that few existing CC can achieve the objective of security. (iii) The obstacles of the development of CC include the difficulties to identify and generalize the requirement of CC security, the lake of effective technologies that can be used to support the clouding use, and no international origination that serves for standardizing the modular components for cloud computing processes. In this paper, we use the IVSL(The Iraq Virtual Science Library) to select the free, full-text access to papers from major publishers as well as a large collection of on-line educational materials.</p>

scholarly journals Cloud Computing Services

2012 ◽  
Vol 2 (2) ◽  
pp. 48-58 ◽  
Author(s):  
Vanessa Ratten
Keyword(s):  
Cloud Computing ◽  
Cognitive Theory ◽  
Theoretical Perspective ◽  
Security And Privacy ◽  
Future Research ◽  
Marketing Capability ◽  
Ethical Guidelines ◽  
Computing Services ◽  
Cloud Computing Services

Cloud computing is an emerging service technology that has ethical and entrepreneurial implications. Due to technological innovations increasing the attention placed on cloud computing services, more people are focusing on the security and privacy issues determined by ethical guidelines and how the technology is evolving as an entrepreneurial service innovation. This paper presents a theoretical perspective on how a person adopts cloud computing. The literature on technology innovation and adoption behaviour is examined with a focus on social cognitive theory. A theoretical framework is then presented, which indicates a number of propositions to describe the intention of a person to adopt cloud computing services. The role of technology marketing capability, sustained learning and outcome expectancy are included in helping to understand the role of cloud computing applications. Suggestions for future research and practical implications are stated.

scholarly journals Rethinking the Meaning of Cloud Computing for Health Care: A Taxonomic Perspective and Future Research Directions (Preprint)

2018 ◽  
Author(s):  
Fangjian Gao ◽  
Scott Thiebes ◽  
Ali Sunyaev
Keyword(s):  
Health Care ◽  
Cloud Computing ◽  
Conceptual Understanding ◽  
Health Care Organizations ◽  
Future Research ◽  
Health It ◽  
Computing Services ◽  
Traditional Health ◽  
Cloud Computing Services ◽  
Stage 1

BACKGROUND Cloud computing is an innovative paradigm that provides users with on-demand access to a shared pool of configurable computing resources such as servers, storage, and applications. Researchers claim that information technology (IT) services delivered via the cloud computing paradigm (ie, cloud computing services) provide major benefits for health care. However, due to a mismatch between our conceptual understanding of cloud computing for health care and the actual phenomenon in practice, the meaningful use of it for the health care industry cannot always be ensured. Although some studies have tried to conceptualize cloud computing or interpret this phenomenon for health care settings, they have mainly relied on its interpretation in a common context or have been heavily based on a general understanding of traditional health IT artifacts, leading to an insufficient or unspecific conceptual understanding of cloud computing for health care. OBJECTIVE We aim to generate insights into the concept of cloud computing for health IT research. We propose a taxonomy that can serve as a fundamental mechanism for organizing knowledge about cloud computing services in health care organizations to gain a deepened, specific understanding of cloud computing in health care. With the taxonomy, we focus on conceptualizing the relevant properties of cloud computing for service delivery to health care organizations and highlighting their specific meanings for health care. METHODS We employed a 2-stage approach in developing a taxonomy of cloud computing services for health care organizations. We conducted a structured literature review and 24 semistructured expert interviews in stage 1, drawing on data from theory and practice. In stage 2, we applied a systematic approach and relied on data from stage 1 to develop and evaluate the taxonomy using 14 iterations. RESULTS Our taxonomy is composed of 8 dimensions and 28 characteristics that are relevant for cloud computing services in health care organizations. By applying the taxonomy to classify existing cloud computing services identified from the literature and expert interviews, which also serves as a part of the taxonomy, we identified 7 specificities of cloud computing in health care. These specificities challenge what we have learned about cloud computing in general contexts or in traditional health IT from the previous literature. The summarized specificities suggest research opportunities and exemplary research questions for future health IT research on cloud computing. CONCLUSIONS By relying on perspectives from a taxonomy for cloud computing services for health care organizations, this study provides a solid conceptual cornerstone for cloud computing in health care. Moreover, the identified specificities of cloud computing and the related future research opportunities will serve as a valuable roadmap to facilitate more research into cloud computing in health care.

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