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Author:

Lu, Shuaibing (Lu, Shuaibing.) | Wu, Jie (Wu, Jie.) | Duan, Yubin (Duan, Yubin.) | Wang, Ning (Wang, Ning.) | Fang, Juan (Fang, Juan.) (Scholars:方娟)

Indexed by:

EI Scopus SCIE

Abstract:

Fog computing is an emerging paradigm that brings computing capabilities closer to distributed IoT devices, which provides networking services between end devices and traditional cloud data centers. One important mission is to further reduce the monetary cost of fog resources while meeting the ever-growing demands of multiple users. In this paper, we focus on minimizing the total cost for multiple mobile users to provide an efficient resource provisioning scheme in fog computing. The total cost includes two aspects: the replication cost and the transmission cost. We consider three cases for the resource provision problem by focusing on different cost models. First, one simple case where users can only upload one replication is discussed, and an optimal solution is proposed by converting the original problem into a bipartite graph matching. Then we consider a more complicated case in which each user can upload multiple replications on fog nodes in the resource provisioning. Specifically, two models are discussed: the 0-1 transmission cost model and the different transmission cost model. For the 0-1 transmission cost model, each user can upload multiple replications with a constant transmission cost, and one optimal greedy solution is proposed. For the different transmission cost model, the transmission cost is related to the distance of each pair of fog nodes. This problem is proven to be NP-hard. We first propose a non-adaptive algorithm which is proved to be bounded by2/3W + 1/3OPT. Another 3 + is an element of-approximation algorithm is proposed based on local search, which has better performance with higher complexity. Extensive simulations also prove the efficiency of our schemes. (C) 2020 Elsevier Inc. All rights reserved.

Keyword:

Resource provision Fog computing Mobility Cost-efficiency Multiple users

Author Community:

  • [ 1 ] [Lu, Shuaibing]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
  • [ 2 ] [Fang, Juan]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
  • [ 3 ] [Lu, Shuaibing]Temple Univ, Ctr Networked Comp, Philadelphia, PA 19122 USA
  • [ 4 ] [Wu, Jie]Temple Univ, Ctr Networked Comp, Philadelphia, PA 19122 USA
  • [ 5 ] [Duan, Yubin]Temple Univ, Ctr Networked Comp, Philadelphia, PA 19122 USA
  • [ 6 ] [Wang, Ning]Rowan Univ, Dept Comp Sci, Glassboro, NJ USA

Reprint Author's Address:

  • 方娟

    [Fang, Juan]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China

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Source :

JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING

ISSN: 0743-7315

Year: 2020

Volume: 146

Page: 96-106

3 . 8 0 0

JCR@2022

ESI Discipline: COMPUTER SCIENCE;

ESI HC Threshold:132

Cited Count:

WoS CC Cited Count: 15

SCOPUS Cited Count: 17

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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