Nearly Constant Approximation for Data Aggregation Scheduling in Wireless Sensor Networks

Huang, Scott C.-H.; Wan, Peng‐Jun; Vu, Chinh; Li, Yingshu; Yao, Fei

doi:10.1109/infcom.2007.50

Cited by 193 publications

(191 citation statements)

References 18 publications

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“…However, designing an effective data aggregation approach is still a matter of challenge. This data aggregation issue is called convergecast [42][43][44] issue. In convergecast, each node generates only one data packet in a round.…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

“…That is, node only receives data in data collection stage, and once data is sent in transmission stage, the node no longer receives data, and no matter how many data packets are received, they are aggregated into one. Several convergecast algorithms proposed for wireless networks can be used for WSNs [42][43][44]. In convergecast, generally adopt the TDMA way, and divide the time into the slot of equal length.…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

“…Therefore, the data collection operation is transformed into how to arrange the operation time slots of each node to minimize the number of slots required for data collection, that is, the minimum data collection delay. Huang et al [42] proposed a centralized scheduling algorithm with the delay bound of 23 +Δ+18 time slots, where is the network radius and Δ is the maximum node degree. Park et al [43] proposed a distributed scheduling method for generating collision-free schedules with delay at most 24 + 6Δ + 16 time slots, where is the network diameter.…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

“…However, a node receiving packets and aggregating them and then transmitting data consumes less energy. Convergecast [42] is the method used when a node can no longer receive data before sending data. However, less data generated by this method will take longer to reach the sink, making it less suitable for delay-sensitive applications.…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

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Adaptive Transmission Power Control for Reliable Data Forwarding in Sensor Based Networks

Teng

Liu

et al. 2018

Wireless Communications and Mobile Computing

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In wireless sensor networks (WSNs), many applications require a high reliability for the sensing data forwarding to sink. Due to the lossy nature of wireless channels, achieving reliable communication through multihop forwarding can be very challenging. Broadcast technology is an effective way to improve the communication reliability so that the data can be received by multiple receiver nodes. As long as the data of any one of the receiver nodes is transmitted to the sink, the data can be transmitted successfully. In this paper, a cross-layer optimization protocol named Adaptive transmission Power control based Reliable data Forwarding (APRF) scheme by using broadcast technology is proposed to improve the reliability of network and reduce communication delay. The main contributions of this paper are as follows: (1) for general data aggregation sensor networks, through the theoretical analysis, the energy consumption characteristics of the network are obtained. (2) According to the case that the energy consumption of nearsink area is high and that in far-sink area is low, a cross-layer optimization method is adopted, which can effectively improve the data communication by increasing the transmission power of the remaining energy nodes. (3) Since the reliability of communication is improved by increasing the transmission power of the node, the number of retransmissions of the data packet is reduced, so that the delay of the packet reaching the sink node is reduced. The theoretical and experimental results show that, applying APRF scheme under initial transmission power of 0 dBm, although the lifetime dropped by 13.77%, delay could be reduced by 40.37%, network reliability could be reduced by 10.08%, and volume of data arriving at sink increased by 10.08% compared with retransmission-only mechanism.

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Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive Transmission Power Control for Reliable Data Forwarding in Sensor Based Networks

Teng

Liu

et al. 2018

Wireless Communications and Mobile Computing

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“…Data Aggregation/Collection Scheduling with minimum delay has been proven to be NP-hard [2] and well studied in [10,16,[18][19][20].…”

Section: Related Workmentioning

confidence: 99%

Fast Group Communication Scheduling in Duty-Cycled Multihop Wireless Sensor Networks

Cao

Wan

2012

Wireless Algorithms, Systems, and Applications

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Abstract. We study group communication scheduling in duty-cycled multi-hop wireless sensor networks. Assume that time is divided into time-slots and we group multiple consecutive time-slots into periods. Each node can transmit data at any time-slot while it only wakes up at its active time-slot of every period and thus be allowed to receive data. Under the protocol interference model, we investigate four group communication patterns, i.e., broadcast, data aggregation, data gathering, and gossiping. For each pattern, we develop a delay efficient scheduling algorithm which greatly improve the current state-of-the-art algorithm. Additionally, we propose a novel and efficient design to coherently couple the wireless interference requirement and duty cycle requirement.

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Energy‐efficient and localized lossy data aggregation in asynchronous sensor networks

Zhang

Shen

Zeng

et al. 2012

Int J Communication

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SUMMARYIn wireless sensor networks, most data aggregation scheduling methods let all nodes aggregate data in every time instance. It is not energy efficient and practical because of link unreliability and data redundancy. This paper proposes a lossy data aggregation (LDA) scheme to reduce traffic and save energy. LDA selects partial child nodes to sample data at partial time slots and allows estimated aggregation at parent nodes or a root in a network. We firstly consider that all nodes sample data synchronously and find that the error between the real value of a physical parameter and that measured by LDA is bounded respectively with and without link unreliability. Detailed analysis is given on error bound when a confidence level is previously assigned to the root by a newly designed algorithm. Thus, each parent can determine the minimum number of child nodes needed to achieve its assigned confidence level. We then analyze a probability to bound the error with a confidence level previously assigned to the root when all nodes sample data asynchronously. An algorithm then is designed to implement our data aggregation under asynchronization. Finally, we implement our experiment on the basis of real test‐beds to prove that the scheme can save more energy than an existing algorithm for node selection, Distributive Online Greedy (DOG). Copyright © 2012 John Wiley & Sons, Ltd.

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Nearly Constant Approximation for Data Aggregation Scheduling in Wireless Sensor Networks

Cited by 193 publications

References 18 publications

Adaptive Transmission Power Control for Reliable Data Forwarding in Sensor Based Networks

Adaptive Transmission Power Control for Reliable Data Forwarding in Sensor Based Networks

Fast Group Communication Scheduling in Duty-Cycled Multihop Wireless Sensor Networks

Energy‐efficient and localized lossy data aggregation in asynchronous sensor networks

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