Abstract
Opportunistic mobile networks consisting of intermittently connected mobile devices have been exploited for various applications, such as computational offloading and mitigating cellular traffic load. In contrast to existing work, in this paper, we focus on cooperatively offloading data among mobile devices to maximally improve the probability of data delivery from a mobile device to intermittently connected infrastructure within a given time constraint, which is referred to as the cooperative offloading problem. Unfortunately, the estimation of data delivery probability over an opportunistic path is difficult and cooperative offloading is NP-hard. To this end, we first propose a probabilistic framework that provides the estimation of such probability. Based on the proposed probabilistic framework, we design a heuristic algorithm to solve cooperative offloading at a low computation cost. Due to the lack of global information, a distributed algorithm is further proposed. The performance of the proposed approaches is evaluated based on both synthetic networks and real traces. Experimental results show that the probabilistic framework can accurately estimate the data delivery probability, cooperative offloading greatly improves the delivery probability, the heuristic algorithm approximates the optimum, and the performance of both the heuristic algorithm and distributed algorithm outperforms other approaches.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 3382-3395 |
| Number of pages | 14 |
| Journal | IEEE/ACM Transactions on Networking |
| Volume | 25 |
| Issue number | 6 |
| DOIs | |
| State | Published - Dec 2017 |
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All Science Journal Classification (ASJC) codes
- Software
- Computer Science Applications
- Computer Networks and Communications
- Electrical and Electronic Engineering
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Cooperative Data Offload in Opportunistic Networks : From Mobile Devices to Infrastructure. / Lu, Zongqing; Sun, Xiao; La Porta, Thomas.
In: IEEE/ACM Transactions on Networking, Vol. 25, No. 6, 12.2017, p. 3382-3395.Research output: Contribution to journal › Article
TY - JOUR
T1 - Cooperative Data Offload in Opportunistic Networks
T2 - From Mobile Devices to Infrastructure
AU - Lu, Zongqing
AU - Sun, Xiao
AU - La Porta, Thomas
PY - 2017/12
Y1 - 2017/12
N2 - Opportunistic mobile networks consisting of intermittently connected mobile devices have been exploited for various applications, such as computational offloading and mitigating cellular traffic load. In contrast to existing work, in this paper, we focus on cooperatively offloading data among mobile devices to maximally improve the probability of data delivery from a mobile device to intermittently connected infrastructure within a given time constraint, which is referred to as the cooperative offloading problem. Unfortunately, the estimation of data delivery probability over an opportunistic path is difficult and cooperative offloading is NP-hard. To this end, we first propose a probabilistic framework that provides the estimation of such probability. Based on the proposed probabilistic framework, we design a heuristic algorithm to solve cooperative offloading at a low computation cost. Due to the lack of global information, a distributed algorithm is further proposed. The performance of the proposed approaches is evaluated based on both synthetic networks and real traces. Experimental results show that the probabilistic framework can accurately estimate the data delivery probability, cooperative offloading greatly improves the delivery probability, the heuristic algorithm approximates the optimum, and the performance of both the heuristic algorithm and distributed algorithm outperforms other approaches.
AB - Opportunistic mobile networks consisting of intermittently connected mobile devices have been exploited for various applications, such as computational offloading and mitigating cellular traffic load. In contrast to existing work, in this paper, we focus on cooperatively offloading data among mobile devices to maximally improve the probability of data delivery from a mobile device to intermittently connected infrastructure within a given time constraint, which is referred to as the cooperative offloading problem. Unfortunately, the estimation of data delivery probability over an opportunistic path is difficult and cooperative offloading is NP-hard. To this end, we first propose a probabilistic framework that provides the estimation of such probability. Based on the proposed probabilistic framework, we design a heuristic algorithm to solve cooperative offloading at a low computation cost. Due to the lack of global information, a distributed algorithm is further proposed. The performance of the proposed approaches is evaluated based on both synthetic networks and real traces. Experimental results show that the probabilistic framework can accurately estimate the data delivery probability, cooperative offloading greatly improves the delivery probability, the heuristic algorithm approximates the optimum, and the performance of both the heuristic algorithm and distributed algorithm outperforms other approaches.
UR - http://www.scopus.com/inward/record.url?scp=85030633857&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85030633857&partnerID=8YFLogxK
U2 - 10.1109/TNET.2017.2747621
DO - 10.1109/TNET.2017.2747621
M3 - Article
AN - SCOPUS:85030633857
VL - 25
SP - 3382
EP - 3395
JO - IEEE/ACM Transactions on Networking
JF - IEEE/ACM Transactions on Networking
SN - 1063-6692
IS - 6
ER -