On Maximizing the Lifetime of Wireless Sensor Networks Using Virtual Backbone Scheduling

Zhao, Yaxiong; Wu, Jie; Feng, Li; Lu, Sanglu

doi:10.1109/tpds.2011.305

Cited by 89 publications

(61 citation statements)

References 12 publications

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“…Jing He et al have proposed a load balanced CDS, in which workload is shared between nodes and the number of dependents of particular tree node is load balanced [3]. Zhao et al maximize the overall network lifetime by constructing virtual backbone through rules 1, 2 and k and have implemented virtual backbone through iterative local replacement [4].…”

Section: Related Workmentioning

confidence: 99%

Virtual Backbone Trees for Most Minimal Energy Consumption and Increasing Network Lifetime in WSNS

Saibharath¹,

Aarthi²

2014

IJCNC

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Section: Related Workmentioning

confidence: 99%

Virtual Backbone Trees for Most Minimal Energy Consumption and Increasing Network Lifetime in WSNS

Saibharath¹,

Aarthi²

2014

IJCNC

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“…Some works aim at improving energy efficiency for data collection with TDMA scheduling [7,[25][26][27][28][29]. Zhao and Tang [7] propose an energy-efficient TDMA schedule to accommodate periodic data collection with dynamic traffic patterns.…”

Section: Related Workmentioning

confidence: 99%

A Negotiation-Based TDMA Scheduling with Consecutive Slots Assignment for Wireless Sensor Networks

Zeng

Yang

Liu

2014

International Journal of Distributed Sensor Networks

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TDMA protocols are recognized to save energy consumption by avoiding unnecessary idle listening and communication collision. As sensor nodes are usually equipped with limited resource supply, they are thus desirable to improve network capacity and energy efficiency by adopting TDMA scheduling for wireless sensor networks (WSNs). This paper proposes a TDMA scheduling approach, which reuses time slots among sensor nodes, for WSNs. Specifically, with the idea of consecutive slots assignment, our approach can reduce both the time and energy cost of establishing nodes' schedule. Furthermore, the energy of node's switching is also reduced. To avoid the transmission of a node's result interference to all irrelevant receivers within its interference range, we develop a slot negotiation mechanism for slot assignment. We perform extensive simulations in NS-2 to evaluate our proposed approach. The results show that our approach outperforms existing TDMA scheduling in terms of time and energy overhead.

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“…This trend gives birth to many emerging technologies (e.g., OFDMA, network coding, and cognitive radio [1][2][3]). To realize the IoT, a key job is how to optimize the allocation of existing wireless communication resources (e.g., link scheduling, channel allocation, and power allocation [4,5]), improve the communication bandwidth, and reduce the communication power consumption. Aside from the traditional usage of data transmission, recent research efforts even extend the usage of the wireless signal in IoT to perform localization [6] and activity recognition [7].…”

Section: Introductionmentioning

confidence: 99%

Compressed RSS Measurement for Communication and Sensing in the Internet of Things

Zhao

et al. 2017

Wireless Communications and Mobile Computing

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The receiving signal strength (RSS) is crucial for the Internet of Things (IoT), as it is the key foundation for communication resource allocation, localization, interference management, sensing, and so on. Aside from its significance, the measurement process could be tedious, time consuming, inaccurate, and involving human operations. The state-of-the-art works usually applied the fashion of "measure a few, predict many," which use measurement calibrated models to generate the RSS for the whole networks. However, this kind of methods still cannot provide accurate results in a short duration with low measurement cost. In addition, they also require careful scheduling of the measurement which is vulnerable to measurement conflict. In this paper, we propose a compressive sensing-(CS-) based RSS measurement solution, which is conflict-tolerant, time-efficient, and accuracyguaranteed without any model-calibrate operation. The CS-based solution takes advantage of compressive sensing theory to enable simultaneous measurement in the same channel, which reduces the time cost to the level of O(log ) (where is the network size) and works well for sparse networks. Extensive experiments based on real data trace are conducted to show the efficiency of the proposed solutions.

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On Maximizing the Lifetime of Wireless Sensor Networks Using Virtual Backbone Scheduling

Cited by 89 publications

References 12 publications

Virtual Backbone Trees for Most Minimal Energy Consumption and Increasing Network Lifetime in WSNS

Virtual Backbone Trees for Most Minimal Energy Consumption and Increasing Network Lifetime in WSNS

A Negotiation-Based TDMA Scheduling with Consecutive Slots Assignment for Wireless Sensor Networks

Compressed RSS Measurement for Communication and Sensing in the Internet of Things

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