Group-Based Neighbor Discovery in Low-Duty-Cycle Mobile Sensor Networks

Chen, Liangyin; Shu, Yuanchao; Gü, Yü; Guo, Shuang; He, Tian; Zhang, Fan; Chen, Jiming

doi:10.1109/tmc.2015.2476471

“…Quorum-based [21,22,29]; Prime-based: Disco [23], U-connect 2 [24]; Searchlight [7]; Unequal-sized Slot methods [7,25,26]; Block-based [8,27]; middleware methods WiFlock [13], Acc 3 [14], EQS 4 [9], Group [10] 1 prime-set-based algorithm; 2 unified connect; 3 on-demand accelerations; 4 extended quorum systems.…”

Section: Sub-categories Main Workmentioning

confidence: 99%

“…In recent years, more and more researchers have presented some neighbor discovery middleware, which use transitivity of neighbor relations to speed up neighbor discovery by sharing neighbor information, such as WiFlock [13], Acc [14], Group-based [10] and EQS (Extended Quorum Systems) [9]. In the WiFlock algorithm [13], all nodes in the range of one-hop are regarded as one group.…”

mentioning

confidence: 99%

“…In these scenarios, existing neighbor discovery methods fail to satisfy the requirements in terms of energy efficiency, communication traffic load, etc. To address this issue, this paper proposes a group-based fast neighbor discovery, i.e., GBFA (Group-based Fast Algorithm), based on the existing Group-based method [10], to highly efficiently speed up the discovery process.…”

mentioning

confidence: 99%

See 1 more Smart Citation

A Fast Neighbor Discovery Algorithm in WSNs

Wei¹,

Sun²,

Chen³

et al. 2018

Computer Supported Cooperative Work and Social Computing

Self Cite

1

0

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With the quick development of Internet of Things (IoT), one of its important supporting technologies, i.e., wireless sensor networks (WSNs), gets much more attention. Neighbor discovery is an indispensable procedure in WSNs. The existing deterministic neighbor discovery algorithms in WSNs ensure that successful discovery can be obtained within a given period of time, but the average discovery delay is long. It is difficult to meet the need for rapid discovery in mobile low duty cycle environments. In addition, with the rapid development of IoT, the node densities of many WSNs greatly increase. In such scenarios, existing neighbor discovery methods fail to satisfy the requirement in terms of discovery latency under the condition of the same energy consumption. This paper proposes a group-based fast neighbor discovery algorithm (GBFA) to address the issues. By carrying neighbor information in beacon packet, the node knows in advance some potential neighbors. It selects more energy efficient potential neighbors and proactively makes nodes wake up to verify whether these potential neighbors are true neighbors, thereby speeding up neighbor discovery, improving energy utilization efficiency and decreasing network communication load. The evaluation results indicate that, compared with other methods, GBFA decreases the average discovery latency up to 10.58% at the same energy budget.

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“…Asynchronous neighbor discovery mechanisms can be classi ed into two categories: i) direct, where nodes discover only the neighbors from which they receive a message [5] [6], and ii) indirect schemes, where nodes can learn the existence of neighbors from other nodes [7] [8] [9]. Indirect collaborative mechanisms are application-speci c and di cult to compare quantitatively, since nodes in geographical proximity, but not direct neighbors in the network, can be discovered by such schemes.…”

Section: Neighbor Discovery In a Nutshellmentioning

confidence: 99%

On the Energy Efficiency and Performance of Neighbor Discovery Schemes for Low Duty Cycle IoT Devices

Khan

¹

,

Pujol

²

,

Stanica

³

et al. 2017

Proceedings of the 14th ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, &Amp; Ubiquitous Networks

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0

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Mobile sensing and proximity-based applications require smart devices to nd other nodes in vicinity, though it is challenging for a device to nd neighbors in an energy e cient manner while running on low duty cycles. Neighbor discovery schemes allow nodes to follow a schedule to become active and send beacons or listen for other active nodes in order to discover each other with a bounded latency. However, a trade-o exists between the energy consumption and the time a node takes to discover neighbors using a given activity schedule. Moreover, energy consumption is not the only bo leneck, as theoretically perfect schedules can result in discovery failures in a real environment. In this paper, we provide an in-depth study on neighbor discovery, by rst de ning the relation between energy e ciency, discovery latency and the fraction of discovered neighbors. We evaluate existing mechanisms using extensive simulations for up to 100 nodes and testbed implementations for up to 15 nodes, with no synchronization between nodes and using duty cycles as low as 1% and 5%. Moreover, the literature assumes that multiple nodes active simultaneously always result in neighbor discovery, which is not true in practice as this can lead to collisions between the transmitted messages. Our ndings reveal such scalability issues in existing schemes, where discovery fails because of collisions between beacons from multiple nodes active at the same time. erefore, we show that energy e cient discovery schemes do not necessarily result in successful discovery of all neighbors, even when the activity schedules are computed in a deterministic manner.

show abstract

“…In addition, the neighbors of nodes change quickly in mobile WSNs. Neighbor discovery operation needs work continually in the entire lifetime of the network [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

A Fast Neighbor Discovery Algorithm in WSNs

Wei

¹

,

Sun

²

,

Chen

³

et al. 2018

Sensors

Self Cite

View full text Add to dashboard Cite

With the quick development of Internet of Things (IoT), one of its important supporting technologies, i.e., wireless sensor networks (WSNs), gets much more attention. Neighbor discovery is an indispensable procedure in WSNs. The existing deterministic neighbor discovery algorithms in WSNs ensure that successful discovery can be obtained within a given period of time, but the average discovery delay is long. It is difficult to meet the need for rapid discovery in mobile low duty cycle environments. In addition, with the rapid development of IoT, the node densities of many WSNs greatly increase. In such scenarios, existing neighbor discovery methods fail to satisfy the requirement in terms of discovery latency under the condition of the same energy consumption. This paper proposes a group-based fast neighbor discovery algorithm (GBFA) to address the issues. By carrying neighbor information in beacon packet, the node knows in advance some potential neighbors. It selects more energy efficient potential neighbors and proactively makes nodes wake up to verify whether these potential neighbors are true neighbors, thereby speeding up neighbor discovery, improving energy utilization efficiency and decreasing network communication load. The evaluation results indicate that, compared with other methods, GBFA decreases the average discovery latency up to 10.58% at the same energy budget.

show abstract

Group-Based Neighbor Discovery in Low-Duty-Cycle Mobile Sensor Networks

Cited by 38 publications

References 26 publications

A Fast Neighbor Discovery Algorithm in WSNs

A Fast Neighbor Discovery Algorithm in WSNs

On the Energy Efficiency and Performance of Neighbor Discovery Schemes for Low Duty Cycle IoT Devices

A Fast Neighbor Discovery Algorithm in WSNs

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