scholarly journals Cloudification of Virtual Reality Gliding Simulation Game

Information ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 293 ◽  
Author(s):  
Rytis Buzys ◽  
Rytis Maskeliūnas ◽  
Robertas Damaševičius ◽  
Tatjana Sidekerskienė ◽  
Marcin Woźniak ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Video Quality ◽  
Computation Offloading ◽  
Perceptual Quality ◽  
Simulation Game ◽  
Proof Of Concept ◽  
Game Logic ◽  
Cloud Server ◽  
Computationally Intensive ◽  
Cloud Servers

Cloud gaming provides cloud computing-based game as a service. In this paper we describe the development of a virtual reality base gliding game as a proof-of-concept. In the cloud, a cloud gaming platform is hosted on cloud servers with two principal components: game logic engaged in the implementation of game mechanics and game interactions, and video renderer that generates the game frames in real-time. The virtual gliding game was realized in the Unity gaming engine. To ensure smooth playability, and access for remote players, the computationally-intensive parts of the game were offloaded to a physically remote cloud server. To analyze the efficiency of the client-cloud interaction, three cloud servers were setup. The results of cloudification were evaluated by measuring and comparing computation offloading performance, network traffic, the probability of service drop, perceptual quality and video quality.

scholarly journals The effect of parallel execution on multi-site computation offloading in mobile cloud computing

2021 ◽  
Author(s):  
Muhammad Ismail Sheikh
Keyword(s):  
Mobile Cloud Computing ◽  
Optimal Solution ◽  
Pareto Optimal Solution ◽  
Parallel Execution ◽  
Computation Offloading ◽  
Mobile Cloud ◽  
Cloud Server ◽  
Cloud Servers ◽  
Smart Mobile ◽  
Multi Server

The demand for running complex applications on smart mobile devices is rapidly increasing. However, the limitations of resources are restricting the development of intensive applications on these devices. The restrictions can be overcome by offloading the computation of an application in the powerful cloud servers. The objective of the computation offloading is to offload the parts of an application to the cloud server to minimize the response time, energy consumption and monetary cost of the application. Unlike prior work in computation offloading, this work considers the effect of parallel execution—on different devices (external parallelism) and on the different cores of a single device (internal parallelism). This work models each device as a multi-server queueing station. It uses genetic algorithm to determine the near-optimal offloading allocation. The results show that considering the effect of parallel execution yields better pareto-optimal solution for the allocation problem compared to excluding parallelism.

Efficient Computation Offloading in Mobile Cloud Computing with Nature-Inspired Algorithms

2019 ◽  
Vol 18 (04) ◽  
pp. 1950023 ◽  
Author(s):  
Shikha Mehta ◽  
Parmeet Kaur
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Optimal Solution ◽  
Computation Offloading ◽  
Efficient Computation ◽  
Shuffled Frog Leaping ◽  
Computationally Intensive ◽  
Nature Inspired Algorithms ◽  
Cloud Servers ◽  
Ubiquitous Presence

The ubiquitous presence of smart phones and other hand-held computing devices has resulted in a growing feasibility to utilize them as computing resources. However, these mobile devices are constrained in battery and may not possess adequate capability for computationally intensive tasks. Cloud computing allows mobile devices to address their inherent challenges by making it possible to offload computation, completely or partially, to powerful cloud servers. This enables mobile devices to act as compute resources; though, it also results in cost of using cloud servers as well as communication cost involved in offloading. The paper models the computation offloading problem as an optimization problem and makes use of nature-inspired algorithms for deciding whether a task should be executed locally on a mobile device or offloaded to the cloud. The study was performed over four algorithms, namely Genetic Algorithm (GA), Differential Evolution (DE), Particle Swarm Optimization (PSO) and Shuffled Frog Leaping Algorithm (SFLA). Experimental analysis revealed that these algorithms outperform exhaustive search technique by providing a near optimal solution in a reasonable time even for large workflows. Results also establish that GA outperforms DE, PSO and SFLA by around 45%, 65% and 42%, respectively by reducing an application’s overall execution cost.

scholarly journals The effect of parallel execution on multi-site computation offloading in mobile cloud computing

2021 ◽  
Author(s):  
Muhammad Ismail Sheikh
Keyword(s):  
Mobile Cloud Computing ◽  
Optimal Solution ◽  
Pareto Optimal Solution ◽  
Parallel Execution ◽  
Computation Offloading ◽  
Mobile Cloud ◽  
Cloud Server ◽  
Cloud Servers ◽  
Smart Mobile ◽  
Multi Server

The demand for running complex applications on smart mobile devices is rapidly increasing. However, the limitations of resources are restricting the development of intensive applications on these devices. The restrictions can be overcome by offloading the computation of an application in the powerful cloud servers. The objective of the computation offloading is to offload the parts of an application to the cloud server to minimize the response time, energy consumption and monetary cost of the application. Unlike prior work in computation offloading, this work considers the effect of parallel execution—on different devices (external parallelism) and on the different cores of a single device (internal parallelism). This work models each device as a multi-server queueing station. It uses genetic algorithm to determine the near-optimal offloading allocation. The results show that considering the effect of parallel execution yields better pareto-optimal solution for the allocation problem compared to excluding parallelism.

scholarly journals Enhancing the Optical Efficiency of Near-Eye Displays with Liquid Crystal Optics

Crystals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 107
Author(s):  
Tao Zhan ◽  
En-Lin Hsiang ◽  
Kun Li ◽  
Shin-Tson Wu
Keyword(s):  
Virtual Reality ◽  
Liquid Crystal ◽  
High Efficiency ◽  
Berry Phase ◽  
Optical Element ◽  
Liquid Crystal Polymer ◽  
Proof Of Concept ◽  
Optical Efficiency ◽  
Crystal Polymer ◽  
Light Efficiency

We demonstrate a light efficient virtual reality (VR) near-eye display (NED) design based on a directional display panel and a diffractive deflection film (DDF). The DDF was essentially a high-efficiency Pancharatnam-Berry phase optical element made of liquid crystal polymer. The essence of this design is directing most of the display light into the eyebox. The proposed method is applicable for both catadioptric and dioptric VR lenses. A proof-of-concept experiment was conducted with off-the-shelf optical parts, where the light efficiency was enhanced by more than 2 times.

Joint Optimization Offloading Strategy of Execution Time and Energy Consumption of Mobile Edge Computing

2021 ◽  
Vol 18 (5) ◽  
Author(s):  
Qingzhu Wang ◽  
Xiaoyun Cui
Keyword(s):  
Energy Consumption ◽  
Mobile Devices ◽  
Execution Time ◽  
Optimal Solution ◽  
Computation Offloading ◽  
Joint Optimization ◽  
Random Strategy ◽  
Fitness Value ◽  
Cloud Server ◽  
Time And Energy

As mobile devices become more and more powerful, applications generate a large number of computing tasks, and mobile devices themselves cannot meet the needs of users. This article proposes a computation offloading model in which execution units including mobile devices, edge server, and cloud server. Previous studies on joint optimization only considered tasks execution time and the energy consumption of mobile devices, and ignored the energy consumption of edge and cloud server. However, edge server and cloud server energy consumption have a significant impact on the final offloading decision. This paper comprehensively considers execution time and energy consumption of three execution units, and formulates task offloading decision as a single-objective optimization problem. Genetic algorithm with elitism preservation and random strategy is adopted to obtain optimal solution of the problem. At last, simulation experiments show that the proposed computation offloading model has lower fitness value compared with other computation offloading models.

The Perceptual Quality of the Oculus Rift for Immersive Virtual Reality

2016 ◽  
Vol 34 (1) ◽  
pp. 51-82 ◽  
Author(s):  
Manuela Chessa ◽  
Guido Maiello ◽  
Alessia Borsari ◽  
Peter J. Bex
Keyword(s):  
Virtual Reality ◽  
Perceptual Quality ◽  
Immersive Virtual Reality ◽  
Oculus Rift

Machine Learning-Based Subjective Quality Estimation for Video Streaming Over Wireless Networks

2019 ◽  
pp. 235-254
Author(s):  
Monalisa Ghosh ◽  
Chetna Singhal
Keyword(s):  
Machine Learning ◽  
Wireless Networks ◽  
Video Streaming ◽  
Video Transmission ◽  
Video Quality ◽  
Subjective Quality ◽  
Perceptual Quality ◽  
Support Vector ◽  
Machine Learning Model

Video streaming services top the internet traffic surging forward a competitive environment to impart best quality of experience (QoE) to the users. The standard codecs utilized in video transmission systems eliminate the spatiotemporal redundancies in order to decrease the bandwidth requirement. This may adversely affect the perceptual quality of videos. To rate a video quality both subjective and objective parameters can be used. So, it is essential to construct frameworks which will measure integrity of video just like humans. This chapter focuses on application of machine learning to evaluate the QoE without requiring human efforts with higher accuracy of 86% and 91% employing the linear and support vector regression respectively. Machine learning model is developed to forecast the subjective quality of H.264 videos obtained after streaming through wireless networks from the subjective scores.

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