Energy-efficiency of load-balancing routing for wireless convergecast networks: Centralized versus distributed implementation

Di, Xin; Zhang, Zhaoyu; Chen, Ao; Tian, Junfang; Ozaki, Kazuyuki; Wen, Yingyou; Fujita, Hiroshi

doi:10.1109/iwcmc.2015.7289107

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…Furthermore, the centralized and distributed methods can be complementary to each other. In cases where the MS is down, these events are detected by the base station, and SNs close to the base station could be triggered to perform distributed routings, as introduced by the other works [44]- [47].…”

Section: A Signaling and Task Assignmentmentioning

confidence: 99%

Fuzzy Logic-Based Path Planning for Data Gathering Mobile Sinks in WSNs

et al. 2021

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Mobile sinks (MSs) are capable of collecting data along specified paths in wireless sensor networks (WSNs). They are deployed as a popular alternative for data loggers, to which all nodes have to send sensory data. If MSs' paths (or cycles) are not well determined, it might take a relatively long time for the MSs to make a round trip. Recent research works have proposed methods to determine rendezvous points (RPs) that the MSs must pass by to collect data, with the aim of reducing the data-collection time. Determination of the number of RPs is important, and it is challenging to make ensure that there are sufficient RPs widely located throughout a sensor network, forming a circle along which the MSs can spend limited time traveling. This research presents a method for designing paths and pinpointing RPs for MSs to collect data, as well as determining the next hop to relay data for each sensor node. Instead of reducing the MSs' travel time, the focus of this research is to preserve the energy of all sensor nodes in WSNs. Our method determines the maximum number of RPs such that the MSs can run through each RP's communication range (within a time constraint) without depleting their own energy. The method comprises three main steps. First, we calculate the number of RPs and design the MS path. Second, the exact datacollection points are determined. The last step is to specify the path along which sensory data are relayed to the MS. In our experiments, we simulate two WSNs of different sizes. The results show that our method outperforms the others by 70%-80% in terms of the sensor node uptime, power consumption, MS traveling time and the number of RPs.

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Section: A Signaling and Task Assignmentmentioning

confidence: 99%

Fuzzy Logic-Based Path Planning for Data Gathering Mobile Sinks in WSNs

et al. 2021

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“…To overcome this drawback, Refs. [21][22][23][24] further studied power allocation and relay loading balance in an OFDMAbased RA network. References [25][26][27] adopted game theory to adjust the loading of the heterogeneous network.…”

Section: Introductionmentioning

confidence: 99%

Loading-balance relay-selective strategy based on stochastic dynamic program

Zhao

et al. 2018

Tinshhua Sci. Technol.

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A Relay-Assisted (RA) network with relay selection is considered as a type of effective technology to improve the spectrum and energy efficiency of a cellular network. However, loading balance of the assisted relay node becomes an inevitable bottleneck in RA network development because users do not follow uniform distribution. Furthermore, the time-varying channel condition of wireless communication is also a major challenge for the RA network with relay selection. To solve these problems and improve the practicability of the RA network, a Loading Balance-Relay Selective (LBRS) strategy is proposed for the RA network in this paper. The proposed LBRS strategy formulates the relay selection of the RA network under imperfect channel state information assumption as a Multistage Decision (MD) problem. An optimal algorithm is also investigated to solve the proposed MD problem based on stochastic dynamic program. Numerical results show that the performance of the LBRS strategy is better than that of traditional greedy algorithm and the former is effective as an exhaustive search-based method.

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Energy-efficiency of load-balancing routing for wireless convergecast networks: Centralized versus distributed implementation

Cited by 2 publications

References 8 publications

Fuzzy Logic-Based Path Planning for Data Gathering Mobile Sinks in WSNs

Fuzzy Logic-Based Path Planning for Data Gathering Mobile Sinks in WSNs

Loading-balance relay-selective strategy based on stochastic dynamic program

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