Scheduling problems in interference-aware wireless sensor networks

Lam, Nhat X.; An, Min Kyung; Huynh, Dung T.; Nguyen, Trac N.

doi:10.1109/iccnc.2013.6504188

Cited by 7 publications

(3 citation statements)

References 18 publications

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“…Wang and Baras 20 designed a distributed algorithm achieving the time-latency bound of O ( Λ ) , where Λ is the logarithm of the ratio between the lengths of longest and shortest links in the network. Later, Lam et al 21 proposed an approximate algorithm using O ( R + Λ ) time-slots at most to complete the aggregation task, where R is the network radius. Recently, Li et al 22 presented a distributed algorithm whose latency is bounded by O ( Λ ) and a centralized algorithm with a latency bounded by O ( log 3 n ) , where n is the number of nodes.…”

Section: Related Workmentioning

confidence: 99%

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Minimum-latency data aggregation scheduling based on multi-path routing structures under physical interference model

Liu

Yang

Chen

2018

International Journal of Distributed Sensor Networks

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Minimum-Latency Aggregation Scheduling is a significant problem in wireless sensor networks. The key challenge is to find an effective solution to aggregate data from all sensors to the sink with minimum aggregation latency. In this article, we propose a novel data aggregation scheduling algorithm under the physical interference model. First, the algorithm partitions the network into square cells according to the communication range of a sensor. Second, a node is selected randomly as the aggregated node to receive the data from the other nodes in the same cell. Finally, a data aggregation tree, which consists of multiple disjoint paths, is constructed to aggregate data from all aggregated nodes to the sink. We empirically proved that the delay of the aggregation schedule generated by our algorithm is (K + 1) 2 D2K21 + 2l time-slots at most, where K is a constant depending on the sensors transmitting power, the signal-to-interference-plusnoise-ratio threshold, and the path-loss exponent; D represents the maximal number of nodes in a cell; and l denotes the number of cells at a row/column in a square network area. Simulation results also show that our algorithm achieves lower average latency than the previous works.

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Section: Related Workmentioning

confidence: 99%

“…In contrast, the physical interference model 14 is more realistic and captures the cumulative interference between links more accurately. Due to the challenge of handling the cumulative interference effect, only a few previous works [15][16][17][18][19][20][21][22] studied the MLAS problem under the physical interference model.…”

Section: Introductionmentioning

confidence: 99%

Minimum-latency data aggregation scheduling based on multi-path routing structures under physical interference model

Liu

Yang

Chen

2018

International Journal of Distributed Sensor Networks

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“…In [20], Wang et al designed a new approximation algorithm for MWLS with constant approximation bound regardless of the value of the ambient noise, when the ratio of the maximum power level to the minimum power level or the number of power levels is bounded by a constant. In [21], Lam et al presented a constant approximation algorithm for MWLS with power control under the SINR model.…”

Section: Related Workmentioning

confidence: 99%

Heuristic Algorithms for One-Slot Link Scheduling in Wireless Sensor Networks under SINR

Deng

et al. 2015

International Journal of Distributed Sensor Networks

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One-slot link scheduling is important for enhancing the throughput capacity of wireless sensor networks. It includes two aspects: maximum links scheduling (MLS) and maximum weighted links scheduling (MWLS). In this paper we propose two heuristic algorithms for the two NP-hard problems with obvious power assignments under the SINR (signal-to-interferenceplus-noise-ratio) model. For MLS, we propose an algorithm MTMA (maximum tolerance and minimum affectance), which improves the currently best approximation algorithm by 28%-62% on average. For MWLS, we give an effective heuristic algorithm MWMA (maximum weighted and minimum affectance), which performs better on improving the throughput and reducing the running time. The correctness and performance of our algorithms are confirmed through theoretical analysis and comprehensive simulations.

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Data aggregation protocols for WSN and IoT applications – A comprehensive survey

Begum

Nandury

2023

Journal of King Saud University - Computer and Information Scie

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Scheduling problems in interference-aware wireless sensor networks

Cited by 7 publications

References 18 publications

Minimum-latency data aggregation scheduling based on multi-path routing structures under physical interference model

Minimum-latency data aggregation scheduling based on multi-path routing structures under physical interference model

Heuristic Algorithms for One-Slot Link Scheduling in Wireless Sensor Networks under SINR

Data aggregation protocols for WSN and IoT applications – A comprehensive survey

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