An Adaptive Energy Saving Scheme of DTN based on Geographic Grid for Human Living Areas

Fu, Tingwei; Zhan, Wen; Liu, Jianwei; Zhang, Zheng; Li, Wenzao

doi:10.1109/itoec.2018.8740575

Cited by 2 publications

(3 citation statements)

References 9 publications

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“…Recent studies have incorporated geographic information into energy-efficient routing strategies, as demonstrated by the works of [28,29], which utilize GPS technology to acquire precise geographical location data for each node. The GEER algorithm, proposed by [28], dynamically determines the optimal number of nodes for data transfer based on geographic area and degree centrality.…”

Section: Related Workmentioning

confidence: 99%

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Dynamic Co-Operative Energy-Efficient Routing Algorithm Based on Geographic Information Perception in Opportunistic Mobile Networks

Wang,

Cui,

Chang

et al. 2024

Electronics

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Opportunistic mobile networks, as an important supplement to the traditional communication methods in unique environments, are composed of mobile communication devices. It is a network form that realizes message transmission by using the opportune encounter of these mobile communication devices. Consequently, mobile communication devices necessitate periodic contact detection in order to identify potential communication opportunities, thereby leading to a substantial reduction in the already limited battery life of such devices. Previous studies on opportunistic networks have often utilized geographic information in routing design to enhance message delivery rate. However, the significance of geographic information in energy conservation has been overlooked. Furthermore, previous research on energy-efficient routing has lacked diversification in terms of the methods employed. Therefore, this paper proposes a dynamic co-operative energy-efficient routing algorithm based on geographic information perception (DCEE-GIP) to leverage geographic information to facilitate dynamic co-operation among nodes and optimize node sleep time through probabilistic analysis. The DCEE-GIP routing and other existing algorithms were simulated using opportunistic network environment (ONE) simulation. The results demonstrate that DCEE-GIP effectively extends network service time and successfully delivers the most messages. The service time of DCEE-GIP increased by 8.05∼31.11%, and more messages were delivered by 14.82∼115.9%.

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Section: Related Workmentioning

confidence: 99%

“…For future smart cities, Ref. [29] specifically proposes an energy protection mechanism based on human encounter characteristics, which can be applied to various existing OMN routing protocols. In accordance with city scenario rules, nodes can sleep dynamically to save energy.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Co-Operative Energy-Efficient Routing Algorithm Based on Geographic Information Perception in Opportunistic Mobile Networks

Wang,

Cui,

Chang

et al. 2024

Electronics

View full text Add to dashboard Cite

show abstract

“…A number of geographic metrics have been studied [8]. For instance, LIPS is a geographic scheme where the complication caused by the multiturning point structure can be overcame by the virtual plane mirror algorithm [9]. To handle asymmetric links, FQ-AGO [10] utilizes a fuzzy logic approach and employs the Q-learning algorithm to select the most stable link.…”

Section: Related Workmentioning

confidence: 99%

MR-Pareto: A Multiattribute Opportunistic Routing Method Based on Pareto Optimal Solution for Mobile Crowdsensing

Han

Wang

Tan

et al. 2022

Wireless Communications and Mobile Computing

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Mobile crowdsensing (MCS) is a new perception mode for solving large-scale mobile sensing tasks. Traditional data transmission methods are inapplicable, as the MCS is affected by coverage, user preference, and network access cost. Opportunistic network data transmission schemes in MCS have recently witnessed a surge of research efforts due to their ability of high delivery and low consumption. However, existing works only focus on the impact of the geographical location of nodes on user needs or the interaction between social information and data, which do not take into account the temporal and spatial characteristics of nodes. To address these issues, this paper proposes a multiattribute routing method based on Pareto optimal (MR-Pareto) solution to construct a balance between the energy consumption and resource constraints of nodes in transmission protocols. First, the attribute relationship between nodes is analyzed, which was aimed at selecting the nodes within a contact time threshold. Then, based on a nondominated sorting approach, we achieve a Pareto optimal set of candidate nodes. Finally, the relay nodes for forwarding messages are determined by comparing the cache size and the remaining energy. The experimental results demonstrate that our proposed method has low network overhead, low packet loss, and high message delivery rate, compared to epidemic and prophet routing strategies.

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An Adaptive Energy Saving Scheme of DTN based on Geographic Grid for Human Living Areas

Cited by 2 publications

References 9 publications

Dynamic Co-Operative Energy-Efficient Routing Algorithm Based on Geographic Information Perception in Opportunistic Mobile Networks

Dynamic Co-Operative Energy-Efficient Routing Algorithm Based on Geographic Information Perception in Opportunistic Mobile Networks

MR-Pareto: A Multiattribute Opportunistic Routing Method Based on Pareto Optimal Solution for Mobile Crowdsensing

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