Energy-efficient rOUTING technique for Wireless sensor Networks under energy constraints

Elbassiouny, Shady O.; Hassan, Ayman M.

doi:10.1109/iwcmc.2015.7289159

Cited by 2 publications

(4 citation statements)

References 9 publications

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“…The average size of routing table for the uncompressed approach characterized by Equation (15) was measured for randomly generated networks with 100 to 1000 nodes (20 samples for each network size). Figure (13) depicts those results together with the values estimated from Equation (15), (17) and (18). For this set of simulations, T fix = 5 and the value of h obtained by interpolating the experimental results is 0.305.…”

Section: Size Of Packet Header and Routing Tablementioning

confidence: 98%

“…Elbassiouny et al propose an energy efficient routing protocol in [17]. This protocol is based on assigning a path cost to all possible paths from sender to receiver and select the minimum-cost path for message transmission.…”

Section: Related Workmentioning

confidence: 99%

“…All energy-efficient routing protocols discussed in Section 2 [10,[15][16][17][18] are based on minimum cost routing and minimize routing cost for communication Table 8 compares the MCF and SRMCF protocols. In comparison with the other protocols, SRMCF shows good performance in terms of scalability, mobility and robustness.…”

Section: Relative Comparisonmentioning

confidence: 99%

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Analysis and Evaluation of anEnergy-Efficient Routing Protocol for WSNsCombining Source Routing and MinimumCost Forwarding

Miyandoab

Ferreira

Tavares

2019

JMM

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Source routing (SR) minimum cost forwarding (MCF)-SRMCF-is a reactive, energy-efficient routing protocol proposed to improve the existent MCF methods utilized in heterogeneous wireless sensor networks (WSN). This paper presents an analytical analysis with experimental support that demonstrates the effectiveness of the proposed protocol. SRMCF stems from SR concepts and MCF methods exploited in ad hoc WSNs, where all unicast communications (between sensor nodes and the base station, or vice versa) use minimum cost paths. The protocol utilized in the present work was updated and now also handles link and node failures. Theoretical analysis and simulations show that the final protocol exhibits better throughput and energy consumption than MCF. Memory requirements for the routing table in the base station are also analyzed. Experimental results in a real scenario were obtained for implementations of both protocols, MCF and SRMCF, deployed in a small network of TelosB motes. Results show that SRMCF presents a 33% higher throughput and 24% less energy consumption than MCF. Extensive

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Section: Size Of Packet Header and Routing Tablementioning

confidence: 98%

Section: Related Workmentioning

confidence: 99%

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Analysis and Evaluation of anEnergy-Efficient Routing Protocol for WSNsCombining Source Routing and MinimumCost Forwarding

Miyandoab

Ferreira

Tavares

2019

JMM

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“…These networks are usually used to gather information about the natural conditions of the environment where they are placed, such as temperature, humidity, acidity, and others that eventually lead scientists to know the state of that specific region [4]. Another characteristic of this type of network is that due to the lack of energy, not all IoT devices can use high energy consumption protocols for transmitting/receiving data and must rely on low energy consumption protocols such as ZigBee or Bluetooth LE [5].…”

Section: Introductionmentioning

confidence: 99%

A Green Routing Mathematical Model for IoT Networks in Critical Energy Environments

Lozano-Garzón

Montoya

Donoso

2020

INT J COMPUT COMMUN

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In this paper, we propose a multi-objective mathematical optimization model that is the underlying support for the proposal of a new routing algorithm that aims to extend the lifetime in IoT networks for applications in critical energy environment. The network lifetime is evaluated for three approaches: the Hop Count approach, the Energy Consumption approach, and the Multiobjective approach based on Free Space Loss and the battery energy level of the IoT nodes. After this evaluation, we compared the different approaches in terms of how many transmissions were possible to do under a particular approach until none path cannot be found from an origin node to a destination node. Finally, we conclude that the Multi-objective method was the best strategy for extending the network lifetime since building short distance paths and considering battery level of the IoT nodes every time is, in the long run, a better strategy than just building paths considering nodes with a high battery level or building paths minimizing the number of network hops.

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Energy-efficient rOUTING technique for Wireless sensor Networks under energy constraints

Cited by 2 publications

References 9 publications

Analysis and Evaluation of anEnergy-Efficient Routing Protocol for WSNsCombining Source Routing and MinimumCost Forwarding

Analysis and Evaluation of anEnergy-Efficient Routing Protocol for WSNsCombining Source Routing and MinimumCost Forwarding

A Green Routing Mathematical Model for IoT Networks in Critical Energy Environments

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