arrow
Return

Incentive-Vacation Queueing for Edge Crowd Computing

delete2024-04-15
delete2
delete
OA
AI
S
Sherif B. Azmy
N
Nizar Zorba *
H
Hossam S. Hassanein
DOI:10.1109/JIOT.2023.3347442delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Edge computing aims to push services closer to endusers, greatly enhancing latency and scale. Yet, there's untapped potential beyond the network's last mile, on the extreme edge. Extreme edge computing (XEC) is a computing paradigm that exploits computational resources in the end-user's immediate vicinity. Edge crowd computing (ECC) is an orchestrated sharing economy model within XEC that uses idle resources on userowned devices for service provision, compensating owners. We analyze an orchestrated ECC where devices rent resources in exchange for incentives. Our incentive-vacation queueing (IVQ) model associates performance with incentive payments using vacation queueing, considering the multitenancy of devices through a server vacation dependent on incentives received. In this article, we offer a framework for analyzing any sharing economy system that can be modeled using IVQ. We discuss the relationship between incentives and vacations on performance, namely, the incentive-vacation or IVQ function. We examine two families of IVQ functions that can be adjusted to benefit either the orchestrator or the worker and introduce a performance metric for such preference. We derive analytical expressions for system performance that consider the random nature of worker devices' availability due to fluctuating incentives. The IVQ model explores commodifying user-owned resources in an ECC system, presenting a general approach for performance analysis in such environments.
Keywords:
Extreme edge computing (XEC)
Incentive
performance analysis
queueing
vacation

Journal

IEEE Internet of Things Journal cover
IEEE Internet of Things Journal
IF:
8.9
Papers:
1.4W
Citations:
7.8W

Organization

Q
queens university - canada
Scholars:
1.8W
Papers: 1.7W
Citations: 29
Q
Qatar University
Scholars:
8.9K
Papers: 9.0K
Citations: 16
Cited Papers

Cited Papers

End-to-end Characterization of Game Streaming Applications on Mobile Platforms
err2022-02-28
err10
PREAI
errBhuyan, Sandeepa; Zhao, Shulin; Ying, Ziyu; Kandemir, Mahmut T.; Das, Chita R.
errShare
errSave
Abnormal Child Psychology
err
IF0
err2008-08-29
err0
PREAI
errLinda Wilmshurst
errShare
errSave
err2000-01-01
err0
PREAI
errAsher Ben-Arieh
errShare
errSave
err
IF0
err
err0
PREAI
err
errShare
errSave
Incentives for Mobile Crowd Sensing: A Survey
err2016-01-01
err401
PREAI
errZhang, Xinglin; Yang, Zheng; Sun, Wei; Liu, Yunhao; Tang, Shaohua; Xing, Kai; Mao, Xufei
errShare
errSave
HIV/antiretroviral therapy–related lipodystrophy syndrome (HALS) is associated with higher RBP4 and lower omentin in plasma
err2015-07-01
err0
errOAAI
errJ. Peraire; M. López-Dupla; V. Alba; R. Beltrán-Debón; E. Martinez; P. Domingo; V. Asensi; M. Leal; C. Viladés; M.-I. Inza; X. Escoté; M. Arnedo; G. Mateo; E. Valle-Garay; S. Ferrando-Martinez; S. Veloso; J. Vendrell; J.Mª Gatell; F. Vidal
errShare
errSave
SCALABLE ON-CHAIN AND OFF-CHAIN BLOCKCHAIN FOR SHARING ECONOMY IN LARGE-SCALE WIRELESS NETWORKS
err2022-06-01
err13
PREAI
errCai, Ting; Chen, Wuhui; Psannis, Kostas L.; Goudos, Sotirios K.; Yu, Yang; Zheng, Zibin; Wan, Shaohua
errShare
errSave
Internet of Behaviors: A Survey
err2023-07-01
err16
errOAAI
errSun, Jiayi; Gan, Wensheng; Chao, Han-Chieh; Yu, Philip S.; Ding, Weiping
errShare
errSave
DOES CONTINGENT VALUATION MEASURE PREFERENCES?
err2015-03-08
err0
PREAI
errPETER A. DIAMOND; JERRY A. HAUSMAN; GREGORY K. LEONARD
errShare
errSave
researcher View more