Complexity of Data Collection, Aggregation, and Selection for Wireless Sensor Networks

Li, Xiangyang; Wang, Yajun; Wang, Weichao

doi:10.1109/tc.2010.50

Cited by 67 publications

(7 citation statements)

References 27 publications

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“…We finally turn to a comparison of the amount of the involved control messages for the different clustering schemes. For this, we count the number of transmissions of control messages as metric, 33 without distinguishing broadcast or unicast control messages. As to ROSS, in the first phase, the maximal number of broadcasts is N according to 2.…”

Section: Figure 12mentioning

confidence: 99%

Robust clustering for ad hoc cognitive radio network

Fang

Gross

2018

Trans Emerging Tel Tech

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Cluster structure in cognitive radio (CR) networks facilitates cooperative spectrum sensing, routing, and other functionalities. Unlicensed channels, which are temporally available for a group of CR users in one area, consolidate the group into a cluster. More available unlicensed channels in a cluster make the cluster more likely to uphold against the licensed users' influence, making clusters more robust. This paper analyzes the problem of how to form robust clusters in a CR network such that CR systems benefit from collaboration within clusters despite intense primary user activity. We give a formal description of the robust clustering problem, prove it to be NP‐hard, and propose both centralized and distributed solutions. The congestion game model is adopted to analyze the process of cluster formation, which not only contributes to the design of the distributed clustering scheme but also provides a guarantee on the convergence to a Nash equilibrium and the convergence speed. The proposed distributed clustering scheme outperforms state‐of‐the‐art in terms of cluster robustness, convergence speed, and overhead. Extensive simulations are presented supporting the theoretical claims.

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Section: Figure 12mentioning

confidence: 99%

Robust clustering for ad hoc cognitive radio network

Fang

Gross

2018

Trans Emerging Tel Tech

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“…A great deal of work has been devoted to this field [16,17,18,19,20,21]. Li et al [22] studied the time complexity, message complexity, and energy cost complexity of some data collection, data aggregation, and queries for a multi-hop wireless sensor network of n nodes. Network delay and reliable communication have an important influence on WSN applications and need to be considered in many WSN studies.…”

Section: Related Workmentioning

confidence: 99%

A Delay-Aware and Reliable Data Aggregation for Cyber-Physical Sensing

Zhang

Long

Zhang

et al. 2017

Sensors

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Physical information sensed by various sensors in a cyber-physical system should be collected for further operation. In many applications, data aggregation should take reliability and delay into consideration. To address these problems, a novel Tiered Structure Routing-based Delay-Aware and Reliable Data Aggregation scheme named TSR-DARDA for spherical physical objects is proposed. By dividing the spherical network constructed by dispersed sensor nodes into circular tiers with specifically designed widths and cells, TSTR-DARDA tries to enable as many nodes as possible to transmit data simultaneously. In order to ensure transmission reliability, lost packets are retransmitted. Moreover, to minimize the latency while maintaining reliability for data collection, in-network aggregation and broadcast techniques are adopted to deal with the transmission between data collecting nodes in the outer layer and their parent data collecting nodes in the inner layer. Thus, the optimization problem is transformed to minimize the delay under reliability constraints by controlling the system parameters. To demonstrate the effectiveness of the proposed scheme, we have conducted extensive theoretical analysis and comparisons to evaluate the performance of TSR-DARDA. The analysis and simulations show that TSR-DARDA leads to lower delay with reliability satisfaction.

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“…Several communication protocols such as ASLEEP [Anastasi et al 2009], S-MAC [Ye et al 2004], B-MAC [Polastre et al 2004] and DS-MAC [Peng et al 2004] allow duty cycling of the wireless radio in order to reduce the energy consumption. On the other hand, in-network data processing techniques such as data compression or data aggregation [Mo et al 2011] and energy efficient communication data routing mechanisms as in [Junyoung et al 2009] help to reduce the energy consumption of the wireless radio. Power supply module.…”

Section: Architecture Of a Wsnmentioning

confidence: 99%

On Battery Recovery Effect in Wireless Sensor Nodes

Narayanaswamy¹,

Schlueter²,

Steinhorst³

et al. 2016

ACM Trans. Des. Autom. Electron. Syst.

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With the perennial demand for longer runtime of battery-powered Wireless Sensor Nodes (WSNs), several techniques have been proposed to increase the battery runtime. One such class of techniques exploiting the battery recovery effect phenomenon claims that performing an intermittent discharge instead of a continuous discharge will increase the usable battery capacity. Several works in the areas of embedded systems and wireless sensor networks have assumed the existence of this recovery effect and proposed different power management techniques in the form of power supply architectures (multiple battery setup) and communication protocols (burst mode transmission) in order to exploit it. However, until now, a systematic experimental evaluation of the recovery effect has not been performed with real battery cells, using high-accuracy battery testers to confirm the existence of this recovery phenomenon. In this article, a systematic evaluation procedure is developed to verify the existence of this battery recovery effect. Using our evaluation procedure, we investigated Alkaline, Nickel-Metal Hydride (NiMH), and Lithium-Ion (Li-Ion) battery chemistries, which are commonly used as power supplies for Wireless Sensor Node (WSN) applications. Our experimental results do not show any evidence of the aforementioned recovery effect in these battery chemistries. In particular, our results show a significant deviation from the stochastic battery models, which were used by many power management techniques. Therefore, the existing power management approaches that rely on this recovery effect do not hold in practice. Instead of a battery recovery effect, our experimental results show the existence of the rate capacity effect , which is the reduction of usable battery capacity with higher discharge power, to be the dominant electrochemical phenomenon that should be considered for maximizing the runtime of WSN applications. We outline power management techniques that minimize the rate capacity effect in order to obtain a higher energy output from the battery.

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Complexity of Data Collection, Aggregation, and Selection for Wireless Sensor Networks

Cited by 67 publications

References 27 publications

Robust clustering for ad hoc cognitive radio network

Robust clustering for ad hoc cognitive radio network

A Delay-Aware and Reliable Data Aggregation for Cyber-Physical Sensing

On Battery Recovery Effect in Wireless Sensor Nodes

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