Delay-aware tree construction and scheduling for data aggregation in duty-cycled wireless sensor networks

Abstract

Data aggregation is one of the most essential operations in wireless sensor networks (WSNs), in which data from all sensor nodes is collected at a sink node. A lot of studies have been conducted to assure collision-free data delivery to the sink node, with the goal of minimizing aggregation delay. The minimum delay data aggregation problem gets more complex when recent WSNs have adopted the duty cycle scheme to conserve energy and to extend the network lifetimes. The reason is that the duty cycle yields a notable increase of communication delay, beside a reduction of energy consumption, due to the periodic sleeping periods of sensor nodes. In this paper, we propose a novel data aggregation scheme that minimizes the data aggregation delay in duty-cycled WSNs. The proposed scheme takes the sleeping delay between sensor nodes into account to construct a connected dominating set (CDS) tree in the first phase. The CDS tree is used as a virtual backbone for efficient data aggregation scheduling in the second phase. The scheduling assigns the fastest available transmission time for every sensor node to deliver all data collision-free to the sink. The simulation results show that our proposed scheme reduces data aggregation delay by up to 72% compared to previous work. Thanks to data aggregation delay reduction, every sensor node has to work shorter and the network lifetime is prolonged.

Active Neighbor Exploitation for Fast Data Aggregation in IoT Sensor Networks

“…Data aggregation is the great technique to solve that problem. Immense studies have been investigating how to apply the data aggregation technique to sensor networks for energy efficiency [15]- [19] or time efficiency (Minimum Latency Aggregation Scheduling (MLAS)) [11], [13], [20]- [23]. With any of the above targets, at the end, the research helps the sensor network span their lifetime.…”

Hybrid Delay‐Minimization Scheduling Algorithm of FT and MPTS in WSN Data Aggregation

“…The research on optimizing the data aggregation delay can not only seek the approximate solutions, but also simplify the problem by assuming the parameters or modifying the system scale. For instance, Le et al [13] proposed a data aggregation delay scheme that minimized the duty cycle in WSN, examined the dormancy among the sensor nodes, and constructed the connection dominance set (CDS) tree in the first phase. In the second stage, CDS tree was used as the virtual backbone of effective data aggregation scheduling.…”

Adaptive dynamic duty cycle mechanism for energy efficient medium access control in wireless multimedia sensor networks

“…Le et al 21 Constructed tree based on the sleeping delay between sensor nodes is used as the virtual backbone for data aggregation Data aggregation schedule and tree construction increase the overhead and energy consumption OPEH 23 Optimization mechanism is designed for packet transmission scheme based on multistage relay. Duty cycle adjustment scheme based on ESN which is artificial intelligence algorithm Based on artificial intelligence algorithm which add complexity and energy prediction mechanism PHGWO 24 It proposed to finds a solution for the duty cycle design problem using the parallel and hybrid principles in high density environment…”

“…Le et al 21 proposed data aggregation mechanism to reduce delay duty cycled in WSNs. A connected demining set tree was constructed based on the sleeping delay between sensor nodes, where the constructed tree is used as the virtual backbone for data aggregation.…”

“…The queueing delay is the most dynamic delay components and it is indicative of bandwidth utilization and congestion level. The limitations of previous literature studies 6‐36 are summarized in Table 1. The main advantage of the proposed dynamic duty cycle is the ability to maintain a balance between energy and latency where the packet service time (PST), traffic priority and per hop delay requirements are considered.…”