Energy efficient selective hop selection optimization to maximize lifetime of wireless sensor network

Kakhandki, Arun L.; Hublikar, Shivaraj; Priyatamkumar,

doi:10.1016/j.aej.2017.01.041

Cited by 23 publications

(6 citation statements)

References 24 publications

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“…Several works [39][40] addressed energy efficiency in wireless sensor networks in a similar way as we do in the current contribution. In addition, [41] proposes a solution to place edge servers in order to support both energy efficiency and diminishment of the access latency.…”

Section: Mmentioning

confidence: 94%

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Energy-aware and adaptive fog storage mechanism with data replication ruled by spatio-temporal content popularity

Vales

Moura

Marinheiro

2019

Journal of Network and Computer Applications

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Section: Mmentioning

confidence: 94%

“…Table 2 compares our proposal with previous work, highlighting the novel aspects integrated by our research. [39] No No Yes No [40] No No Yes No [25] No No No Yes [41] Yes No Yes No Our current proposal Yes Yes Yes Yes…”

Section: Accepted Manuscriptmentioning

confidence: 95%

Energy-aware and adaptive fog storage mechanism with data replication ruled by spatio-temporal content popularity

Vales

Moura

Marinheiro

2019

Journal of Network and Computer Applications

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“…According to [7], an efficient distributed MAC optimization strategy can cut energy consumption by 88%, node latency by 84%, and connectivity overhead by 80%. In addition, the method is associated with those already in use.…”

Section: Related Workmentioning

confidence: 99%

Modern Energy Optimization Approach for Efficient Data Communication in IoT-Based Wireless Sensor Networks

Kumar

Ahmad

Routray

et al. 2022

Wireless Communications and Mobile Computing

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Many researchers are drawn to mobile wireless sensor networks (WSN) and the Internet of Things (IoT) because of the significant challenges of power consumption and network connectivity. A technique that takes into consideration the characteristics such as network probability, the identified region of individual nodes, and the radius of the whole identified region is presented in this article. Free-space propagation is carried out in the region of interest. This approach assures network connection, long-term communication sustainability, and maximum energy efficiency. It was discovered that a mathematical network model can be built using the probability theory. It has been possible to examine and evaluate the changes in sensor nodes as a function of distance from the detection region using this approach. As a result, a correlation has been established between a network’s communication radius and the identified region. Additionally, a novel method has been developed to reduce energy consumption and sustain connectivity through boosting the connectivity feature. Notably, IoT-based WSN architectures require more energy optimization than any other network, because they have resource-limited nodes. Also, a simulation plot of the proposed approach’s mathematical network scheme is shown to show if it works. The proposed method consumes much less energy averagely 40% compared to the existing methods, which are LEACH, ZTR, and DSR when the radius is 100.

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“…However, cluster‐based cooperative communication concentrates for minimizing energy but lifetime not increased. Hence, a distributed MAC 27 uses transceiver optimization and selects next hop node; thereby, both lifetime and energy are improved. WSN virtualization using 802.15.4 MAC faces resource management problem.…”

Section: Related Workmentioning

confidence: 99%

FRAME routing with game theory optimization for wireless networks

Radha

Bala

Nagabushanam

2019

Int J Communication

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Summary Wireless ad hoc networks have a wide variety of applications in the present world. Creating routes between the nodes and with low energy consumption is a major challenge in wireless ad hoc networks. In this paper, we have proposed FRAME routing for ad hoc networks, which consider the entire network based on hierarchal Bayesian model. It works on game theory–based Chow‐Liu algorithm for establishing routes from source to destination considering the best neighbors in the path. FRAME routing is further analyzed with SMAC and conventional MAC in various scenarios. They are also compared with conventional MAC in AODV routing in terms of energy consumption, delay, throughput, PDR, and goodput. The entire simulations are carried out using NS2 and SMAC in FRAME routing that give better performance compared with conventional MAC in FRAME, AODV routing.

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Energy efficient selective hop selection optimization to maximize lifetime of wireless sensor network

Cited by 23 publications

References 24 publications

Energy-aware and adaptive fog storage mechanism with data replication ruled by spatio-temporal content popularity

Energy-aware and adaptive fog storage mechanism with data replication ruled by spatio-temporal content popularity

Modern Energy Optimization Approach for Efficient Data Communication in IoT-Based Wireless Sensor Networks

FRAME routing with game theory optimization for wireless networks

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