Enhancement the video quality forwarding Using Receiver-Based Approach(URBA) in Vehicular Ad-Hoc Network

Hammood, Omar A.; Kahar, Mohd Nizam Mohmad; Mohammed, Muamer N.

doi:10.1109/icramet.2017.8253146

Cited by 11 publications

(11 citation statements)

References 15 publications

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“…Reliability in Could due to repeated on-off cycles in a utility model is also considered as a benefit of the energy savings received by switching the unused PMs off. A utility function model [29] RACE has been presented which considers the MTTF, thermal effects on hardware, the cost of VM migration, and PM state. The system mitigates SLA violations based on the allocated capacity being less than the required capacity.…”

Section: Reliability Considerations For Optimal Cloud Computingmentioning

confidence: 99%

HSO: A Hybrid Swarm Optimization Algorithm for Reducing Energy Consumption in the Cloudlets

et al. 2018

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Mobile Cloud Computing (MCC) is an emerging technology for the improvement of mobile service quality. MCC resources are dynamically allocated to the users who pay for the resources based on their needs. The drawback of this process is that it is prone to failure and demands a high energy input. Resource providers mainly focus on resource performance and utilization with more consideration on the constraints of service level agreement (SLA). Resource performance can be achieved through virtualization techniques which facilitates the sharing of resource providers' information between different virtual machines. To address these issues, this study sets forth a novel algorithm (HSO) that optimized energy efficiency resource management in the cloud; the process of the proposed method involves the use of the developed cost and runtime-effective model to create a minimum energy configuration of the cloud compute nodes while guaranteeing the maintenance of all minimum performances. The cost functions will cover energy, performance and reliability concerns. With the proposed model, the performance of the Hybrid swarm algorithm was significantly increased, as observed by optimizing the number of tasks through simulation, (power consumption was reduced by 42%). The simulation studies also showed a reduction in the number of required calculations by about 20% by the inclusion of the presented algorithms compared to the traditional static approach. There was also a decrease in the node loss which allowed the optimization algorithm to achieve a minimal overhead on cloud compute resources while still saving energy significantly. Conclusively, an energy-aware optimization model which describes the required system constraints was presented in this study, and a further proposal for techniques to determine the best overall solution was also made.

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Section: Reliability Considerations For Optimal Cloud Computingmentioning

confidence: 99%

HSO: A Hybrid Swarm Optimization Algorithm for Reducing Energy Consumption in the Cloudlets

et al. 2018

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“…Data flow algorithms handle data continuous stream to store past records with only limited ability. Online machine learning covers methods that update their models after observing a new event and can instantly make predictions based on the updated model [11][12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

A Review on Big Data Stream Processing Applications: Contributions, Benefits, and Limitations

Alwaisi

Abbood²,

Jalil

et al. 2021

JOIV : Int. J. Inform. Visualization

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The amount of data in our world has been rapidly keep growing from time to time. In the era of big data, the efficient processing and analysis of big data using machine learning algorithm is highly required, especially when the data comes in form of streams. There is no doubt that big data has become an important source of information and knowledge in making decision process. Nevertheless, dealing with this kind of data comes with great difficulties; thus, several techniques have been used in analyzing the data in the form of streams. Many techniques have been proposed and studied to handle big data and give decisions based on off-line batch analysis. Today, we need to make a constructive decision based on online streaming data analysis. Many researchers in recent years proposed some different kind of frameworks for processing the big data streaming. In this work, we explore and present in detail some of the recent achievements in big data streaming in term of contributions, benefits, and limitations. As well as some of recent platforms suitable to be used for big data streaming analytics. Moreover, we also highlight several issues that will be faced in big data stream processing. In conclusion, it is hoped that this study will assist the researchers in choosing the best and suitable framework for big data streaming projects.

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“…This method is helpful in medical field to recognize the identity of dead bodies [14][15][16][17][18]. Through this research we are going to prove the importance of this specific biometric, the ear authentication process in order to be used in other technological fields like in personal security process [19][20][21][22][23][24][25]. Ear structure is a distinctive organism of Man's body structure which has many different unique characteristics like form, skin, pose, and others [26][27][28][29][30][31][32][33][34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Ear biometric verification approach based on morphological and geometric invariants

Jbara

2020

IJEECS

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<p>Biometric verification based on ear features is modern filed for scientific research. As known, there are many biometric identifiers that can identify people such as fingerprints, iris and speech. In this paper, the focus is placed on the ear biometric model in order to verifying the identity of persons. The main idea is based on used the moments as ear feature extractors. The proposed approach included some operations as follow: image capturing, edge detection, erosion, feature extraction, and matching. The proposed approach has been tested using many images of the ears with different states. Experimental results using several trails verified that the proposed approach is achieved high accuracy level over a wide variety of ear images. Also, the verification process will be completed by matching query ear image with ear images that kept in database during real time.</p>

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Enhancement the video quality forwarding Using Receiver-Based Approach(URBA) in Vehicular Ad-Hoc Network

Cited by 11 publications

References 15 publications

HSO: A Hybrid Swarm Optimization Algorithm for Reducing Energy Consumption in the Cloudlets

HSO: A Hybrid Swarm Optimization Algorithm for Reducing Energy Consumption in the Cloudlets

A Review on Big Data Stream Processing Applications: Contributions, Benefits, and Limitations

Ear biometric verification approach based on morphological and geometric invariants

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