Minimum Latency Aggregation Scheduling in Internet of Things

An, Min Kyung; Cho, Hyuk; Zhou, Bing; Chen, Lei

doi:10.1109/iccnc.2019.8685660

Cited by 5 publications

(6 citation statements)

References 32 publications

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“…In [2], a hierarchical agglomerative aggregation scheduling method is proposed for minimizing the latency of data aggregation in directional WSNs with non-uniform power model. In [3], an approximation method is proposed in IoT (Internet of Things) networks such that the latency of reporting aggregated data is minimized. A break-and-join tree construction method is proposed in [33] to reconstruct and improve a given data aggregation tree such that the latency is minimized.…”

Section: Related Workmentioning

confidence: 99%

“…For minimizing the latency of reporting data to the sink, the studies in [2,3,44] address the problem of using minimum latency scheduling to aggregate data to the sink without data collisions in homogeneous or heterogenous WSNs. In addition, when several number of data can be aggregated into one packet, the problem of using minimum latency scheduling to report data to the sink without data collisions in WSNs is studied in [29ś31].…”

Section: Introductionmentioning

confidence: 99%

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Minimizing Latency for Data Aggregation in Wireless Sensor Networks: An Algorithm Approach

Pham

Nguyen

Liu

et al. 2022

ACM Trans. Sen. Netw.

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In wireless sensor networks (WSNs), especially in underwater sensor networks the problem of reporting data to the sink with minimum latency has been widely discussed in many research works. Many studies address on using data aggregation to report the same type of data to the sink without data collision in a short period of time. However, due to the rapid development of sensor technology in recent years, a sensor is allowed to have multiple sensing capabilities, that is, it can generate and collect different types of data. Because different types of data have different meanings and required aggregation functions, only the data that belong to the same type are allowed to be aggregated. In addition, due to the interference of the environment or the noise, the links in the WSNs are often not bidirectional. This motivates us to study the problem of using minimum latency scheduling to aggregate and report data to the sink without data collision in multiple-data-type WSNs having unidirectional links, which is shown to be NP-hard in the paper. In addition, the Relative-Collision-Graph-Based Scheduling Algorithm (RCGBSA) is therefore proposed accordingly. Simulations are conducted to demonstrate the performance of the RCGBSA.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Minimizing Latency for Data Aggregation in Wireless Sensor Networks: An Algorithm Approach

Pham

Nguyen

Liu

et al. 2022

ACM Trans. Sen. Netw.

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show abstract

“…To tide over these Due to the presence of intermediary nodes in a tree topology rooted at the BS, the transmission of aggregated data need to be carefully coordinated to avoid interference from other concurrent transmissions. The Minimum Latency Aggregation Scheduling (MLAS) algorithm aims to minimize the effect of wireless interferences and the number of time slots required to aggregate the data [71]. Several data aggregation scheduling algorithms have been developed using either Protocol or Physical Interference models or by using a combination of both, to address interference in WSN and IoTs [72].…”

Section: Lboa (Location Based Securementioning

confidence: 99%

“…The approach also presents schemes for scheduling of transmissions under Physical Interference model to attain optimized throughput. The MLAS problem in IoTs is addressed in [71]. A constantfactor approximation Aggregation Scheduling in IoTs (ASIoT) is developed to manage scheduling of heterogeneous devices.…”

Section: Review Of Data Aggregation Techniques To Addressmentioning

confidence: 99%

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A Survey of Data Aggregation Protocols for Energy Conservation in WSN and IoT

Begum

Nandury

2022

Wireless Communications and Mobile Computing

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Conservation of energy has been a major concern for Wireless Sensor Networks (WSNs) and IoT applications. Several strategies were devised, aimed at optimizing energy consumption in these applications, based on: (a) use of low-powered hardware devices, (b) deploying mobile/relay agents for data collection, (c) clustering, and (d) data aggregation. Amongst these, data aggregation is widely acknowledged as an important tool to conserve energy in WSN and IoTs. The paper provides a comprehensive survey of various data aggregation strategies, discusses the efficacy of these strategies in handling issues that are typical to WSN and IoT applications. These issues severely impact the performance metrics such as: energy efficiency, latency, fault-tolerance, network throughput, and network lifetime. Therefore, to optimize the data aggregation approach, an application developer needs to arrive at optimal tradeoffs between these parameters. A major contribution of the paper is to present a holistic review of data aggregation approaches emphasizing the effect of topology, security, mobility, interference, and fault-tolerance in WSN and IoTs. Based on gap areas in literature, we throw open few challenges and present them as “posers”, and put-forth suggestions for further research.

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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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Minimum Latency Aggregation Scheduling in Internet of Things

Cited by 5 publications

References 32 publications

Minimizing Latency for Data Aggregation in Wireless Sensor Networks: An Algorithm Approach

Minimizing Latency for Data Aggregation in Wireless Sensor Networks: An Algorithm Approach

A Survey of Data Aggregation Protocols for Energy Conservation in WSN and IoT

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

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