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A User-Centric QoS-Aware Multi-Path Service Provisioning in Mobile Edge Computing

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A User-Centric QoS-Aware Multi-Path Service Provisioning in Mobile Edge Computing. / Malik, Saif U. R.; Kanwal, Tehsin; Khan, Samee U. et al.
In: IEEE Access, Vol. 9, 31.03.2021, p. 56020-56030.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Malik SUR, Kanwal T, Khan SU, Malik H, Pervaiz H. A User-Centric QoS-Aware Multi-Path Service Provisioning in Mobile Edge Computing. IEEE Access. 2021 Mar 31;9:56020-56030. doi: 10.1109/ACCESS.2021.3070104

Author

Malik, Saif U. R. ; Kanwal, Tehsin ; Khan, Samee U. et al. / A User-Centric QoS-Aware Multi-Path Service Provisioning in Mobile Edge Computing. In: IEEE Access. 2021 ; Vol. 9. pp. 56020-56030.

Bibtex

@article{cb6eb8e500ab4f6b9dd4a79c08f398e2,
title = "A User-Centric QoS-Aware Multi-Path Service Provisioning in Mobile Edge Computing",
abstract = "Recent development in modern wireless applications and services, such as augmented reality, image processing, and network gaming requires persistent computing on average commercial wireless devices to perform complex tasks with low latency. The traditional cloud systems are unable to meet those requirements solely. In the said perspective, Mobile Edge Computing (MEC) serves as a proxy between the things (devices) and the cloud, pushing the computations at the edge of the network. The MEC provides an effective solution to fulfill the demands of low-latency applications and services by executing most of the tasks within the proximity of users. The main challenge, however, is that too many simultaneous service requests created by wireless access produce severe interference, resulting in a decreased rate of data transmission. In this paper, we made an attempt to overcome the aforesaid limitation by proposing a user-centric QoS-aware multi-path service provisioning approach. A densely deployed base station MEC environment has overlapping coverage regions. We exploit such regions to distribute the service requests in a way that avoid hotspots and bottlenecks. Our approach is adaptive and can tune to different parameters based on service requirements. We performed several experiments to evaluate the effectiveness of our approach and compared it with the traditional Greedy approach. The results revealed that our approach improves the network state by 26.95% and average waiting time by 35.56% as compared to the Greedy approach. In addition, the QoS violations were also reduced by the fraction of 16.",
author = "Malik, {Saif U. R.} and Tehsin Kanwal and Khan, {Samee U.} and Hassan Malik and Haris Pervaiz",
year = "2021",
month = mar,
day = "31",
doi = "10.1109/ACCESS.2021.3070104",
language = "English",
volume = "9",
pages = "56020--56030",
journal = "IEEE Access",
issn = "2169-3536",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

RIS

TY - JOUR

T1 - A User-Centric QoS-Aware Multi-Path Service Provisioning in Mobile Edge Computing

AU - Malik, Saif U. R.

AU - Kanwal, Tehsin

AU - Khan, Samee U.

AU - Malik, Hassan

AU - Pervaiz, Haris

PY - 2021/3/31

Y1 - 2021/3/31

N2 - Recent development in modern wireless applications and services, such as augmented reality, image processing, and network gaming requires persistent computing on average commercial wireless devices to perform complex tasks with low latency. The traditional cloud systems are unable to meet those requirements solely. In the said perspective, Mobile Edge Computing (MEC) serves as a proxy between the things (devices) and the cloud, pushing the computations at the edge of the network. The MEC provides an effective solution to fulfill the demands of low-latency applications and services by executing most of the tasks within the proximity of users. The main challenge, however, is that too many simultaneous service requests created by wireless access produce severe interference, resulting in a decreased rate of data transmission. In this paper, we made an attempt to overcome the aforesaid limitation by proposing a user-centric QoS-aware multi-path service provisioning approach. A densely deployed base station MEC environment has overlapping coverage regions. We exploit such regions to distribute the service requests in a way that avoid hotspots and bottlenecks. Our approach is adaptive and can tune to different parameters based on service requirements. We performed several experiments to evaluate the effectiveness of our approach and compared it with the traditional Greedy approach. The results revealed that our approach improves the network state by 26.95% and average waiting time by 35.56% as compared to the Greedy approach. In addition, the QoS violations were also reduced by the fraction of 16.

AB - Recent development in modern wireless applications and services, such as augmented reality, image processing, and network gaming requires persistent computing on average commercial wireless devices to perform complex tasks with low latency. The traditional cloud systems are unable to meet those requirements solely. In the said perspective, Mobile Edge Computing (MEC) serves as a proxy between the things (devices) and the cloud, pushing the computations at the edge of the network. The MEC provides an effective solution to fulfill the demands of low-latency applications and services by executing most of the tasks within the proximity of users. The main challenge, however, is that too many simultaneous service requests created by wireless access produce severe interference, resulting in a decreased rate of data transmission. In this paper, we made an attempt to overcome the aforesaid limitation by proposing a user-centric QoS-aware multi-path service provisioning approach. A densely deployed base station MEC environment has overlapping coverage regions. We exploit such regions to distribute the service requests in a way that avoid hotspots and bottlenecks. Our approach is adaptive and can tune to different parameters based on service requirements. We performed several experiments to evaluate the effectiveness of our approach and compared it with the traditional Greedy approach. The results revealed that our approach improves the network state by 26.95% and average waiting time by 35.56% as compared to the Greedy approach. In addition, the QoS violations were also reduced by the fraction of 16.

U2 - 10.1109/ACCESS.2021.3070104

DO - 10.1109/ACCESS.2021.3070104

M3 - Journal article

VL - 9

SP - 56020

EP - 56030

JO - IEEE Access

JF - IEEE Access

SN - 2169-3536

ER -