Delay-Aware and User-Adaptive Offloading of Computation-Intensive Applications with Per-Task Delay in Mobile Edge Computing Networks

Chanyour, Tarik; Hmimz, Youssef; El, Mohamed; Oucamah, Mohammed

doi:10.14569/ijacsa.2020.0110190

Cited by 7 publications

(4 citation statements)

References 17 publications

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“…• Edge Processing: Mobile devices are constrained by their computing resources, which are often not enough to process heavy tasks. Therefore, computation offloading comes in useful with the possibility to delegate the tasks to the edge, thus in this case, additionally to the processing time on the Mobile Edge Computing server, a transmission delay is also calculated, it represents both time cost for uploading the input data and downloading the output results, the latter is rarely taken in consideration by researchers assuming that the obtained output data size is insignificant when compared to the input data size [11], [24]- [27].…”

Section: Computation Offloadingmentioning

confidence: 99%

Optimal Task Processing and Energy Consumption Using Intelligent Offloading in Mobile Edge Computing

Maftah

Ghmary

Bouabidi

et al. 2022

Int. J. Interact. Mob. Technol.

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The appearance of Edge Computing with the possibility to bring powerful computation servers near the mobile device is a major stepping stone towards better user experience and resource consumption optimization. Due to the Internet of Things invasion that led to the constant demand for communication and computation resources, many issues were imposed in order to deliver a seamless service within an optimized cost of time and energy, since most of the applications nowadays require real response time and rely on a limited battery resource. Therefore, Mobile Edge Computing is the new reliable paradigm in terms of communication and computation consumption by the mobile devices. Mobile Edge Computing rely on computation offloading to surpass cloud-based technologies issues and break the limitations of mobile devices such as computing, storage and battery resources. However, computation offloading is not always the optimal choice to adopt, which makes the offloading decision a crucial part in which many parameters should be taken in consideration such as delegating the heavy tasks to the appropriate machine within the network by migrating the high-resource node to an edge server and lend these capabilities to the low-resources one. In this paper, we use an Edge Computing simulator to see how network delay can impact the delivery of a certain result, we also experiment computation offloading using a two-tier with Edge Orchestration architecture, which turns out to be efficient in terms of processing time.

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Section: Computation Offloadingmentioning

confidence: 99%

Optimal Task Processing and Energy Consumption Using Intelligent Offloading in Mobile Edge Computing

Maftah

Ghmary

Bouabidi

et al. 2022

Int. J. Interact. Mob. Technol.

View full text Add to dashboard Cite

show abstract

“…A scenario where users receive the list of computation tasks to be offloaded. Each task must be handled by the MEC server within a fixed time frame [12]. The proposed optimization problems aim at the reduction of energy usage, the total processing delays as well as the insatiable processing workload.…”

Section: Related Workmentioning

confidence: 99%

Multi-Task Multi-User Offloading in Mobile Edge Computing

Moussammi¹,

Ghmary²,

Idrissi³

2022

IJACSA

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Mobile Edge Computing (MEC) is a new method to overcome the resource limitations of mobile devices by enabling Computation Offloading (CO) with low latency. This paper proposes a multi-user multi-task effective system to offload computations for MEC that guarantees in terms of energy, latency for MEC. To begin, radio and computation resources are integrated to ensure the efficient utilization of shared resources when there are multiple users. The energy consumed is positively correlated with the power of transmission and the local CPU frequency. The values can be adjusted to accommodate multi-tasking in order to minimize the amount of energy consumed. The current methods for offloading aren't appropriate when multiple tasks and multiple users have high computing density. Additionally, this paper proposes a multi-user system that includes multiple tasks and high-density computing that is efficient. Simulations have confirmed the Multi-User Multi-Task Offloading Algorithm (MUMTOD). The results in terms of execution time and energy consumption are extremely positive. This improves the effectiveness of offloading as well as reducing energy consumption.

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“…Since the birth of online optimization of animation art design user virtual perception, its function has been used for film special effects [23]. With the development of decades, digital virtual scenes, virtual cameras, virtual roles, motion capture, cluster animation, and other advanced digital image technologies have been widely applied in modern film creation and digital technology has gradually risen to the leading position from its the initial function of assisting film and television special effects [24]. Animation art design user virtual online optimization with its own modern digital technology advantages constantly improves the visual expression of film art.…”

Section: Related Workmentioning

confidence: 99%

Online Optimization of Animation Art Design User Virtual Perception in Mobile Edge Computing Environment

Guo-zhu

Tsai

2022

Scientific Programming

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Animation art design is widely used in all levels of social life and has become an important part of modern social visual culture. Driven by new technologies, it is integrated with relevant application fields, resulting in new media forms and art categories. The development course of animation art design is sorted out, focusing on the analysis of the technical basis of animation art design and art form, social function and cultural form, creative practice, and theoretical research. This paper puts forward the concept of dimension composition of animation art design and analyzes and studies the dimensions of technology and art, cognition and experience, economy, and culture in animation art design and artistic creation based on this concept. The modeling of edge devices and services is proposed to abstract resources and provide a unified formal description of user virtual perception for animation art design of various sensing types. All related attributes are described uniformly, and the device model and task model are given. Users can customize services based on predefined attributes. According to the development demand of multiuser shared virtual environments, the characteristics and limitations of the previous perception management scheme are analyzed and a two-layer perception management scheme is designed to adapt to the development of new multiuser shared virtual environment of animation art design.

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Delay-Aware and User-Adaptive Offloading of Computation-Intensive Applications with Per-Task Delay in Mobile Edge Computing Networks

Cited by 7 publications

References 17 publications

Optimal Task Processing and Energy Consumption Using Intelligent Offloading in Mobile Edge Computing

Optimal Task Processing and Energy Consumption Using Intelligent Offloading in Mobile Edge Computing

Multi-Task Multi-User Offloading in Mobile Edge Computing

Online Optimization of Animation Art Design User Virtual Perception in Mobile Edge Computing Environment

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