Name
Abstract | ||
|---|---|---|
This paper proposes an efficient opportunistic forwarding algorithm in Delay Tolerant Networks (DTNs) using only local information: inter-meeting times collected locally. It tries to minimize delay with a controlled energy consumption through placing a limitation on the number of total copies per message. The proposed forwarding algorithm makes forwarding decisions based only on local information, which means that no information is needed to be exchanged among the nodes, except for the data to be transferred. The removal of information propagation is particularly important in large-scale DTNs with limited communication opportunities like vehicular communication networks. On the contrary, most existing algorithms either forward messages randomly without facilitating any information, or require the exchange of certain information to make wise forwarding decision. Extensive real trace-driven simulations are conducted, and the proposed algorithm significantly outperforms all of the compared localized algorithms in every simulation. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/MASS.2014.132 | MASS |
Keywords | Field | DocType |
mobile communication,trace-driven simulation,decision making,local forwarding decision,opportunistic forwarding algorithm,localized efficient forwarding algorithm,delay tolerant networks,large-scale delay tolerant networks, optimal stopping rule, local forwarding decision, trace-driven simulation,large-scale delay tolerant networks,vehicular communication networks,optimal stopping rule,dtn | Trace driven simulation,Telecommunications network,Computer science,Bidirectional Forwarding Detection,Algorithm,Computer network,Information propagation,Energy consumption,Optimal stopping rule,Distributed computing | Conference |
ISSN | Citations | PageRank |
2155-6806 | 1 | 0.35 |
References | Authors | |
10 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuxing He | 1 | 1 | 0.35 |
| Cong Liu | 2 | 586 | 30.47 |
| Yan Pan | 3 | 179 | 19.23 |
| Zhang Wei | 4 | 392 | 53.03 |
| Jie Wu | 5 | 8307 | 592.07 |
| Yaxiong Zhao | 6 | 115 | 7.18 |
| Shuhui Yang | 7 | 551 | 31.41 |
| Mingming Lu | 8 | 343 | 30.42 |