scholarly journals Hybrid Invasive Weed Optimization with Greedy Algorithm for an Energy and Deadline Aware Scheduling in Cloud Computing

2019 ◽  
Vol 8 (12) ◽  
pp. 1354-1359
Keyword(s):  
Cloud Computing ◽  
Greedy Algorithm ◽  
Greedy Algorithms ◽  
Population Based ◽  
Task Completion ◽  
Network Access ◽  
Invasive Weed Optimization ◽  
Invasive Weed ◽  
Resource Pooling ◽  
The Greedy Algorithm

Cloud computing is being envisioned to be the computing paradigm of the next generation primarily for its advantages of on-demand services, risk transference, resource pooling that is independent of location and ubiquitous network access. Service quality is allocated using various resources in the scheduling process. The deadline refers to the time period from task submission until task completion. An algorithm that has good scheduling attempts at keeping the task executed inside the constraint of the deadline. The Genetic Algorithm (GA) is a common metaheuristic that is used often in literature for procuring solutions that are either optimal or near-optimal. The Invasive Weed Optimization (IWO) is an evolutionary algorithm that is population-based with certain interesting specifications like creations of offspring that are based on the levels of fitness of the parents which increases the size of the population and generates new population by making use of the best among parents and the best among off-springs. The Greedy Algorithms will construct an object that is globally best by means of continuously choosing the option that is locally the best. In this work, a hybrid GA with the Greedy Algorithm and a Hybrid IWO with the Greedy Algorithm that has been proposed for the energy and the deadline-aware scheduling in cloud computing.

An Overview of Cloud and Edge Computing Architecture and Its Current Issues and Challenges

2021 ◽  
pp. 2340-2370
Author(s):  
Guru Prasad Bhandari ◽  
Ratneshwer Gupta
Keyword(s):  
Cloud Computing ◽  
Edge Computing ◽  
Network Access ◽  
Computing Systems ◽  
Computing Architecture ◽  
Resource Pooling ◽  
Cloud Architecture ◽  
On Demand ◽  
Emerging Issues ◽  
Self Service

Edge computing is a technique of optimizing cloud computing systems by performing data processing at the edge of the network, near the source of the data in the systems. And, cloud computing is a service that delivers on-demand self-service, broad network access, resource pooling, rapid elasticity or expansion, which is trending in today's technology-driven world. With the advantage of flexibility, storage, sharing, and easy accessibility, cloud is being used by major players in IT (information technology). This chapter highlights cloud/edge computing architecture and its current issues and challenges from technological and organizational aspects. A brief introduction of edge computing architecture with similar technologies along with its service models is discussed. A few counterexamples of cloud computing architecture are showed. Organizational aspects of cloud computing architecture, as well as IBM and Oracle reference cloud architecture, are briefly presented. Some emerging issues and challenges associated with cloud/edge computing on its utilization are also elaborated.

scholarly journals Cloud Computing Services for Improving Efficiency In Omani Small and Medium Enterprises Sector

2017 ◽  
Author(s):  
Mohammed Soud Al Rawahi ◽  
Shaik Asif Hussain
Keyword(s):  
Economic Growth ◽  
Cloud Computing ◽  
New Technologies ◽  
Small And Medium Enterprises ◽  
Economic Recession ◽  
Professional Staff ◽  
Cloud Services ◽  
Network Access ◽  
Resource Pooling ◽  
Advantages And Disadvantages

Small and medium sized enterprises (SMEs) assure economic growth in Oman. Generally, many SMEs are struggling to survive in an ongoing global recession and are often reluctant to use research results and new technologies for business and learning. Cloud Computing offers many opportunities and could help companies to improve their business and use technology more efficiently. Small and medium sized enterprises (SMEs) assure economic growth in Oman, but the last financial crisis and the economic recession have hit SMEs hard in Omani SMEe and some of them have difficulties to survive and less resource to invest in new technologies. Cloud Computing offers many opportunities and can help companies to improve their business and use technology more efficiently. Some features i.e. on-demand services, broad network access, resource pooling, rapid elasticity and measured service distinguish Cloud from other computer networking models. According to the analyst firm IDC in 2012 more than 1.7 million cloud computing jobs have remained unoccupied and the trend should lead to more than seven million cloud-related vacancies worldwide. In this research, cloud computing advantages and disadvantages of cloud technology are reflected in the context of Omani SME sector. The project IN-Cloud is analyzed considering Omani SME project to understand the effectiveness of efforts in this direction. The general objective of the project IN-CLOUD are to study the framework of use of cloud computing in SME sector. Survey results of Cloud Computing and advantages for SMEs are presented in paper within the context of Omani SME sector. The results show that 70% of SMEs have adopted or used some of features of Cloud services but they indicated the need n for awareness, safety and training, qualified professional staff in this field.

Cloud Technologies and Services

2021 ◽  
pp. 3-26
Author(s):  
W Kuan Hon ◽  
Christopher Millard ◽  
Jatinder Singh
Keyword(s):  
Cloud Computing ◽  
Business Models ◽  
Cloud Service ◽  
Network Access ◽  
Resource Pooling ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Self Service ◽  
Definition Of ◽  
Cloud Technologies

This chapter defines what cloud computing is. The National Institute of Standards and Technology (NIST) has set out a commonly used definition of cloud computing. Under this definition, a 'computing capacity' will qualify as a 'cloud service' if it has the following five characteristics: on-demand self-service; broad network access; resource pooling; rapid elasticity; and measured service. In terms of business models, cloud computing resources are typically offered 'as a Service'. Traditionally, cloud computing services were typically described as falling into one or more of the following three service categories or models: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). The chapter then looks at the key concepts of the cloud supply chain.

Hands-On Xen

2018 ◽  
pp. 221-232
Author(s):  
Khaleel Ahmad ◽  
Masroor Ansari ◽  
Afsar Kamal
Keyword(s):  
Cloud Computing ◽  
Distributed System ◽  
Operating Systems ◽  
Cost Effective ◽  
Easy Access ◽  
Cloud Base ◽  
Network Access ◽  
Resource Pooling ◽  
Hands On ◽  
The World

Xen is an open source virtualization framework in distributed system based on rapid elasticity on broad network access. It is a cost-effective platform for resource pooling and allows easy access to run any code any time from everywhere by any user. It is a hypervisor using a microkernel design, provides services that allow multiple operating systems to execute on the same computer concurrently. In other words, the hypervisor was made accessible to the world directly from any location, anticipating a fully virtualized cloud base environment, which is turned into cloud computing.

scholarly journals The Hybrid Invasive Weed Optimization-Shuffled Frog-leaping Algorithm Applied to Optimal Design of Frame Structures

2019 ◽  
Author(s):  
Ali Kaveh ◽  
Siamak Talatahari ◽  
Nima Khodadadi
Keyword(s):  
Optimization Algorithm ◽  
Optimal Solution ◽  
Optimization Methods ◽  
Optimization Method ◽  
Population Based ◽  
Frame Structures ◽  
Invasive Weed Optimization ◽  
Shuffled Frog Leaping Algorithm ◽  
Invasive Weed ◽  
Shuffled Frog Leaping

In this article, an efficient hybrid optimization algorithm based on invasive weed optimization algorithm and shuffled frog-leaping algorithm is utilized for optimum design of skeletal frame structures. The shuffled frog-leaping algorithm is a population-based cooperative search metaphor inspired by natural memetic, and the invasive weed optimization algorithm is an optimization method based on dynamic growth of weeds colony. In the proposed algorithm, shuffled frog-leaping algorithm works to find optimal solution region rapidly, and invasive weed optimization performs the global search. Different benchmark frame structures are optimized using the new hybrid algorithm. Three design examples are tested using the new method. This algorithm converges to better or at least the same solutions compared the utilized methods with a smaller number of analyses. The outcomes are compared to those obtained previously using other recently developed meta-heuristic optimization methods.

scholarly journals A Review of Assured Data Deletion Mechanism in Cloud Computing

2018 ◽  
Vol 7 (4.5) ◽  
pp. 329
Author(s):  
Sultan Ahmad ◽  
Dr. Mohammad Mazhar Afza
Keyword(s):  
Cloud Computing ◽  
Cloud Storage ◽  
Main Concern ◽  
Network Access ◽  
Resource Pooling ◽  
Security Issues ◽  
Huge Data ◽  
Efficient Access ◽  
Self Service ◽  
Cloud User

As Cloud Computing has become a new way to store information remotely. It makes possible for many companies to become paperless. IT people and companies can outsource their huge data by using this emerging technology. The major important characteristics of cloud computing are on-demand self-service, broad network access, resource pooling, rapid elasticity and measured services. These cloud computing characteristics are helpful for organizations to become agile. Also there are few serious problems like security, scalability, availability and interoperability which are associated with the above cloud computing characteristics. Providing a secure and efficient access and retrieval of the valuable data is a main concern of cloud computing technologies. It is very important to protect data and credentials of cloud client on the internet. Apart from these security issues of data, the deletion of data on cloud storage is also a very serious issue nowadays.  Once a cloud user wants to delete his data, it must be sure that data actually deleted from all cloud storage sources and there should not be remain any copy of data exist at anywhere in cloud storage anyway. In this paper, different existing data deletion and retrieval methods are studied, observed and analyzed. The importance and related challenges to assured data deletion on the cloud storage are explored.  

scholarly journals Sufficient conditions for the optimality of the greedy algorithm in greedoids

2021 ◽  
Author(s):  
Dávid Szeszlér
Keyword(s):  
Greedy Algorithm ◽  
Greedy Algorithms ◽  
General Theorem ◽  
Sufficient Conditions ◽  
Theoretical Background ◽  
Theoretical Computer Science ◽  
Special Cases ◽  
Original Works ◽  
Optimum Solution ◽  
The Greedy Algorithm

AbstractGreedy algorithms are among the most elementary ones in theoretical computer science and understanding the conditions under which they yield an optimum solution is a widely studied problem. Greedoids were introduced by Korte and Lovász at the beginning of the 1980s as a generalization of matroids. One of the basic motivations of the notion was to extend the theoretical background behind greedy algorithms beyond the well-known results on matroids. Indeed, many well-known algorithms of a greedy nature that cannot be interpreted in a matroid-theoretical context are special cases of the greedy algorithm on greedoids. Although this algorithm turns out to be optimal in surprisingly many cases, no general theorem is known that explains this phenomenon in all these cases. Furthermore, certain claims regarding this question that were made in the original works of Korte and Lovász turned out to be false only most recently. The aim of this paper is to revisit and straighten out this question: we summarize recent progress and we also prove new results in this field. In particular, we generalize a result of Korte and Lovász and thus we obtain a sufficient condition for the optimality of the greedy algorithm that covers a much wider range of known applications than the original one.

scholarly journals Matroids And Greedy Algorithms. A Deeper Justification of Using Greedy Approach To Find A Maximal set of a Matroid

2017 ◽  
Vol 16 (2) ◽  
pp. 48
Author(s):  
Syed Aqib Haider
Keyword(s):  
Greedy Algorithm ◽  
Local Level ◽  
Greedy Algorithms ◽  
Optimal Solution ◽  
Independent Set ◽  
Computation Time ◽  
Optimal Choice ◽  
Greedy Approach ◽  
The Greedy Algorithm ◽  
Selection Of

<p>Greedy algorithms are used in solving a diverse set of problems in small computation time. However, for solving problems using greedy approach, it must be proved that the greedy strategy applies. The greedy approach relies on selection of optimal choice at a local level reducing the problem to a single sub problem, which actually leads to a globally optimal solution. Finding a maximal set from the independent set of a matroid M(S, I) also uses greedy approach and justification is also provided in standard literature (e.g. Introduction to Algorithms by Cormen et .al.). However, the justification does not clearly explain the equivalence of using greedy algorithm and contraction of M by the selected element. This paper thus attempts to give a lucid explanation of the fact that the greedy algorithm is equivalent to reducing the Matroid into its contraction by selected element. This approach also provides motivation for research on the selection of the test used in algorithm which might lead to smaller computation time of the algorithm.</p>

scholarly journals PENJADWALAN MATAKULIAH MENGGUNAKAN ALGORITMA GREEDY (STUDI KASUS PENJADWALAN SEMESTER GANJIL 2017-2018 INFORMATIKA ITENAS)

2018 ◽  
Vol 4 (3) ◽  
Author(s):  
Yasmin Math Khader ◽  
Youllia Indrawaty Nurhasanah ◽  
Afriyanti Dwi Kartika
Keyword(s):  
College Student ◽  
Greedy Algorithm ◽  
Computational Algorithm ◽  
Greedy Algorithms ◽  
Computational Algorithms ◽  
Shortest Distance ◽  
College Subject ◽  
The Greedy Algorithm

Arranging college subject becomes one of the problem for the institute. Limited of class rooms, lecturer time that should be adjusted, many courses should be attended by college student cause arranging college subject should carefully arranged. Making manual schedule need more time and obstructing lectures. The purpose of this study is to implement greedy algorithms so that the results of scheduling lectures that have no clash, class capacity and number of students can adjust. Greedy algorithm is a computational algorithm to find the shortest distance, from the theory then diadposi into computational algorithms to find the lowest value in the combination of scheduling a class. By applying the greedy algorithm to the system, the system can generate class schedules without clashes, class capacity and number of students can adjust. The output of this system is the course schedule stored in the calendar.

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