Mobile Edge Computing: Cost-Efficient Content Delivery in Resource-Constrained Mobile Computing Environment

@article{Mahenge2019MobileEC,
  title={Mobile Edge Computing: Cost-Efficient Content Delivery in Resource-Constrained Mobile Computing Environment},
  author={Michael P. J. Mahenge and Chunlin Li and Camilius A. Sanga},
  journal={Int. J. Mob. Comput. Multim. Commun.},
  year={2019},
  volume={10},
  pages={23-46}
}
The overwhelming growth of resource-intensive and latency-sensitive applications trigger challenges in legacy systems of mobile cloud computing (MCC) architecture. Such challenges include congestion in the backhaul link, high latency, inefficient bandwidth usage, insufficient performance, and quality of service (QoS) metrics. The objective of this study was to find out the cost-efficient design that maximizes resource utilization at the edge of the mobile network which in return minimizes the… Expand
3 Citations
Adaptive Edge Process Migration for IoT in Heterogeneous Fog and Edge Computing Environments
TLDR
The paper proposes a resource-aware edge process migration (REM) scheme that is capable of optimising the process migration decision and develops a framework called edge process-enabled internet of thing (EPIoT) host, which is implemented and evaluated and shown to be capable of enhancing the performance of the process Migration in heterogeneous FEC environment. Expand
Optimal path strategy for the web computing under deep reinforcement learning
TLDR
An intelligent routing algorithm for the network congestion caused by the explosive growth of data volume in the future of the big data era is proposed, which can significantly reduce the probability of data congestion and increase network throughput. Expand
Intelligent Early Warning of Internet Financial Risks Based on Mobile Computing
  • Mu Sheng Dong
  • Computer Science
  • Int. J. Mob. Comput. Multim. Commun.
  • 2020
TLDR
K-means algorithm improved by quantum evolutionary is used in this paper to divide risk early-warning interval by combining with the given initial value and the value-at-risk measured by China's well-known internet finance company. Expand

References

SHOWING 1-10 OF 45 REFERENCES
Collaborative Mobile Edge and Cloud Computing: Tasks Unloading for Improving Users’ Quality of Experience in Resource-Intensive Mobile Applications
TLDR
This study proposes an architecture that considers unloading resource-intensive tasks from clients’ devices to more resourceful edge servers which exploit cooperative approach for tasks processing and results show that the proposed approach through unloading, it reduces response time and energy usage. Expand
Energy-Efficient Joint Offloading and Wireless Resource Allocation Strategy in Multi-MEC Server Systems
TLDR
This paper considers an Orthogonal Frequency-Division Multiplexing Access (OFDMA) based multi-user and multi-MEC-server system, where the task offloading strategies and wireless resources allocation are jointly investigated, and proposes the joint offloading and resource allocation strategy for latency- critical applications. Expand
Joint Subcarrier and CPU Time Allocation for Mobile Edge Computing
TLDR
This paper considers a cloudlet in an Orthogonal Frequency-Division Multiplexing Access (OFDMA) system with multiple mobile devices, where the proposed algorithm significantly outperforms per- resource optimization, accommodating more offloading requests while achieving salient energy saving. Expand
Mobile Edge Computing: A Survey on Architecture and Computation Offloading
TLDR
This paper describes major use cases and reference scenarios where the mobile edge computing (MEC) is applicable and surveys existing concepts integrating MEC functionalities to the mobile networks and discusses current advancement in standardization of the MEC. Expand
Task Offloading with Execution Cost Minimization in Heterogeneous Mobile Cloud Computing
TLDR
This paper proposes a system framework for adaptive partitioning and dynamic selective offloading, and designs an optimal cloud selection algorithm with execution cost minimization which consists of offloading judgement and cloud selection. Expand
A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications
TLDR
This survey makes an exhaustive review on the state-of-the-art research efforts on mobile edge networks, including definition, architecture, and advantages, and presents a comprehensive survey of issues on computing, caching, and communication techniques at the network edge. Expand
Collaborative cache allocation and computation offloading in mobile edge computing
TLDR
This work proposes collaborative cache allocation and computation offloading, where the MEC servers collaborate for executing computation tasks and data caching, and formulate an optimization problem that aims at maximizing the resource utilization. Expand
A dynamic programming offloading algorithm for mobile cloud computing
TLDR
Performance evaluation shows that the proposed DPH algorithm can achieve near minimal energy while meeting an application's execution time constraints, and it can find a nearly optimal offloading decision within a few iterations. Expand
Multiuser Joint Task Offloading and Resource Optimization in Proximate Clouds
TLDR
This paper proposes a heuristic offloading decision algorithm (HODA), which is semidistributed and jointly optimizes the offload decision, and communication and computation resources to maximize system utility, a measure of quality of experience based on task completion time and energy consumption of a mobile device. Expand
Edge Computing in the Industrial Internet of Things Environment: Software-Defined-Networks-Based Edge-Cloud Interplay
TLDR
An SDN-based edge-cloud interplay is presented to handle streaming big data in IIoT environment, wherein SDN provides an efficient middleware support and a multi-objective evolutionary algorithm using Tchebycheff decomposition for flow scheduling and routing in SDN is presented. Expand
...
1
2
3
4
5
...