scholarly journals Dynamic Service Migration in Ultra-Dense Multi-Access Edge Computing network for High Mobility Scenarios

2020 ◽  
Author(s):  
Haowei Lin ◽  
Xiaolong Xu ◽  
Juan Zhao ◽  
Xinheng Wang
Keyword(s):  
Cloud Computing ◽  
Mobile Applications ◽  
High Mobility ◽  
Edge Computing ◽  
The Other ◽  
Mobile Users ◽  
Computing Power ◽  
Service Migration ◽  
The Stability ◽  
Multi Access

Abstract The Multi-Access Edge Computing (MEC) has higher computing power than user equipment and lower latency than remote cloud computing, making new types of services and mobile applications keep emerging. However, the movement of users could induce service migration or interruption in the MEC network. Especially for highly mobile users, they accelerate the frequency of services' migration and handover, impacting on the stability of the total MEC network. In this paper, we propose a hierarchical multi-access edge computing architecture, setting up the Infrastructure for dynamic service migration in the ultra-dense MEC networks. Moreover, we propose a new mechanism for users with high mobility in the ultra-dense MEC network, efficiently arranging service migrations for users with high mobility and ordinary users together. Then, we propose an algorithm for evaluating migrated services to contribute to choose the suitable MEC servers for migrated services. The results show that the proposed mechanism can efficiently arrange service migrations and more quickly restore the services even in the blockage. On the other hand, the proposed algorithm is able to make a supplement to the existing algorithms for selecting MEC servers because it can better reflect the capability of migrated services.

scholarly journals Dynamic service migration in ultra-dense multi-access edge computing network for high-mobility scenarios

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Haowei Lin ◽  
Xiaolong Xu ◽  
Juan Zhao ◽  
Xinheng Wang
Keyword(s):  
Cloud Computing ◽  
Mobile Application ◽  
High Mobility ◽  
Edge Computing ◽  
The Other ◽  
Mobile Users ◽  
Computing Power ◽  
Service Migration ◽  
The Stability ◽  
Multi Access

Abstract The multi-access edge computing (MEC) has higher computing power and lower latency than user equipment and remote cloud computing, enabling the continuing emergence of new types of services and mobile application. However, the movement of users could induce service migration or interruption in the MEC network. Especially for highly mobile users, they accelerate the frequency of services’ migration and handover, impacting on the stability of the total MEC network. In this paper, we propose a hierarchical multi-access edge computing architecture, setting up the infrastructure for dynamic service migration in the ultra-dense MEC networks. Moreover, we propose a new mechanism for users with high mobility in the ultra-dense MEC network, efficiently arranging service migrations for users with high-mobility and ordinary users together. Then, we propose an algorithm for evaluating migrated services to contribute to choose the suitable MEC servers for migrated services. The results show that the proposed mechanism can efficiently arrange service migrations and more quickly restore the services even in the blockage. On the other hand, the proposed algorithm is able to make a supplement to the existing algorithms for selecting MEC servers because it can better reflect the capability of migrated services.

scholarly journals ZONE-Based Multi-Access Edge Computing Scheme for User Device Mobility Management

2019 ◽  
Vol 9 (11) ◽  
pp. 2308 ◽  
Author(s):  
Juyong Lee ◽  
Daeyoub Kim ◽  
Jihoon Lee
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Mobility Management ◽  
Mobile Network ◽  
Edge Computing ◽  
Mobile Users ◽  
Long Distance ◽  
Cloud Server ◽  
Multi Access ◽  
User Device

Recently, new mobile applications and services have appeared thanks to the rapid development of mobile devices and mobile network technology. Cloud computing has played an important role over the past decades, providing powerful computing capabilities and high-capacity storage space to efficiently deliver these mobile services to mobile users. Nevertheless, existing cloud computing delegates computing to a cloud server located at a relatively long distance, resulting in significant delays due to additional time to return processing results from a cloud server. These unnecessary delays are inconvenient for mobile users because they are not suitable for applications that require a real-time service environment. To cope with these problems, a new computing concept called Multi-Access Edge Computing (MEC) has emerged. Instead of sending all requests to the central cloud to handle mobile users’ requests, the MEC brings computing power and storage resources to the edge of the mobile network. It enables the mobile user device to run the real-time applications that are sensitive to latency to meet the strict requirements. However, there is a lack of research on the efficient utilization of computing resources and mobility support when mobile users move in the MEC environment. In this paper, we propose the MEC-based mobility management scheme that arranges MEC server (MECS) as the concept of Zone so that mobile users can continue to receive content and use server resources efficiently even when they move. The results show that the proposed scheme reduce the average service delay compared to the existing MEC scheme. In addition, the proposed scheme outperforms the existing MEC scheme because mobile users can continuously receive services, even when they move frequently.

scholarly journals Video Pre-Caching Joint Hand-Off and Content Delivery in Multi-Access Edge Computing Based EONs

2021 ◽  
Author(s):  
Yutong Chai ◽  
Shan Yin ◽  
Lihao Liu ◽  
Liyou Jiang ◽  
Shanguo Huang
Keyword(s):  
Quality Of Service ◽  
High Mobility ◽  
Content Delivery ◽  
Edge Computing ◽  
The Other ◽  
Latency Time ◽  
Hand Off ◽  
Simulation Results ◽  
Multi Access

Multi-access Edge Computing (MEC) performs as a feasible solution when it comes to content delivery, for it can bring contents much closer to users. However, the hand-off (HO) and latency that occur in user movement reduce the users’ quality of service. In this work, we consider the problem of high mobility handoff and content delivery of video streaming in the MEC based EONs. We propose a video pre-caching algorithm considering handoff and content delivery. The algorithm firstly selects the content delivery method and chunks the video accordingly using a preset threshold. Secondly, the algorithm chooses the shortest transmission path and calculates the latency time using Dijkstra method. Simulation results show that our algorithm significantly reduces the latency time and balances the server load compared to the other two baselines.

Next Generation Multi-Access Edge-Computing Fiber-Wireless-Enhanced HetNets for Low-Latency Immersive Applications

2020 ◽  
pp. 40-68
Author(s):  
Amin Ebrahimzadeh ◽  
Martin Maier
Keyword(s):  
Edge Computing ◽  
Computation Offloading ◽  
Mobile Users ◽  
Low Latency ◽  
Next Generation ◽  
End User ◽  
Multi Access ◽  
Smart Mobile ◽  
Time And Energy

Next generation optical access networks have to cope with the contradiction between the intense computation and ultra-low latency requirements of the immersive applications and limited resources of smart mobile devices. In this chapter, after presenting a brief overview of the related work on multi-access edge computing (MEC), the authors explore the potential of full and partial decentralization of computation by leveraging mobile end-user equipment in an MEC-enabled FiWi-enhanced LTE-A HetNet, by designing a two-tier hierarchical MEC-enabled FiWi-enhanced HetNet-based architecture for computation offloading, which leverages both local (i.e., on-device) and nonlocal (i.e., MEC/cloud-assisted) computing resources to achieve low response time and energy consumption for mobile users. They also propose a simple yet efficient task offloading mechanism to achieve an improved quality of experience (QoE) for mobile users.

scholarly journals An efficient fog computing for comprising approach to avoid data theft attack

2018 ◽  
Vol 7 (2.8) ◽  
pp. 680
Author(s):  
T Pavan Kumar ◽  
B Eswar ◽  
P Ayyappa Reddy ◽  
D Sindhu Bhargavi
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Paradigm Shift ◽  
Fog Computing ◽  
Edge Computing ◽  
New Paradigm ◽  
Computing Power ◽  
Data Theft

Cloud computing has become a new paradigm shift in the IT world because of its revolutionary model of computing. It provides flexibility, scalability, and reliability and decreased operational and support expenses for an organization. The Enterprise edition software’s are very costly and maintaining a separate IT team and maintaining their own servers is very expensive and that’s the reason why most of the companies are opting for Cloud computing over enterprise edition of the software. However, few organization cloud customers are not willing to step to cloud computing up on a big scale because of the safety problems present in cloud computing. One more disadvantage of Cloud is it’s not suitable for another revolutionary technology i.e.IoT(Internet of things)In this paper we are going to present the Advantages of Fog Computing and Decoy technology to address the security in cloud computing by extending it into fog computing.Fog Computing is a new paradigm in which the computing power moves to the edge of the network. So, it’s also called as Edge Computing.

Cloud resource optimization based on poisson linear deep gradient learning for mobile cloud computing

2021 ◽  
Vol 40 (1) ◽  
pp. 787-797
Author(s):  
G. Saravanan ◽  
N. Yuvaraj
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Mobile Applications ◽  
Mobile Cloud Computing ◽  
Service Providers ◽  
Mobile User ◽  
Mobile Users ◽  
Mobile Cloud ◽  
Queuing Model ◽  
Gradient Learning

Mobile Cloud Computing (MCC) addresses the drawbacks of Mobile Users (MU) where the in-depth evaluation of mobile applications is transferred to a centralized cloud via a wireless medium to reduce load, therefore optimizing resources. In this paper, we consider the resource (i.e., bandwidth and memory) allocation problem to support mobile applications in a MCC environment. In such an environment, Mobile Cloud Service Providers (MCSPs) form a coalition to create a resource pool to share their resources with the Mobile Cloud Users. To enhance the welfare of the MCSPs, a method for optimal resource allocation to the mobile users called, Poisson Linear Deep Resource Allocation (PL-DRA) is designed. For resource allocation between mobile users, we formulate and solve optimization models to acquire an optimal number of application instances while meeting the requirements of mobile users. For optimal application instances, the Poisson Distributed Queuing model is designed. The distributed resource management is designed as a multithreaded model where parallel computation is provided. Next, a Linear Gradient Deep Resource Allocation (LG-DRA) model is designed based on the constraints, bandwidth, and memory to allocate mobile user instances. This model combines the advantage of both decision making (i.e. Linear Programming) and perception ability (i.e. Deep Resource Allocation). Besides, a Stochastic Gradient Learning is utilized to address mobile user scalability. The simulation results show that the Poisson queuing strategy based on the improved Deep Learning algorithm has better performance in response time, response overhead, and energy consumption than other algorithms.

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