REERS: Reliable and energy‐efficient route selection algorithm for heterogeneous Internet of things applications

Nayagi, D. Salangai; Sivasankari, G G; Ravi, Vinayakumar; Venugopal, K. R.; Sankar, S.

doi:10.1002/dac.4900

Cited by 16 publications

(12 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An overall PDR ratio for ETALGOR is improved by 10.58% over LOADng. A PDR ratio improvement of 12.86% is attained by the Reliable and Energy Efficient Route Selection algorithm (REERS) (7) . Thus, 10.2% better PDR ratio performance is accomplished by ETALGOR over REERS.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…ETALGOR accomplishes an improvement of 7.69% better lifetime over Energy Efficient Routing based on Reinforcement Learning (EER-RL) (6) . Network lifetime improvement of 71.64% is attained by REERS (7) . Thus, 5.80% better lifetime is accomplished using ETALGOR over REERS.…”

Section: Fig 8 Pdr Ratio Of Etalgormentioning

confidence: 98%

“…Also, existing route selection approaches route real-time and non-real-time packets utilizing the same path, thus reducing the system performance. Also, this method lacks low operational cost, security, reliability, and efficient energy management (7) .…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

ETX-Aware Energy-Efficient Algorithm to Reduce Packet Retransmissions in the Internet of Things

Newton¹,

Felix²

2022

IJST

View full text Add to dashboard Cite

Objectives: An energy-efficient optimum path selection to reduce the number of packet retransmissions in a path is proposed in this paper using a new metric New-Expected Transmission Count (N-ETX), Residual Energy (RE), and Path Objective Function (POF). Methods: Energy efficiency, packet retransmission, and RE is considered while making the best choice of the optimum path. The refined N-ETX metric is employed to measure the Packet Delivery Ratio (PDR) of a node. If the PDR ratio is higher, this node is included in the optimum path set. The proposed algorithm avoids the inclusion of critical nodes such as dead nodes if the RE of the nodes is lower than the predefined Energy Threshold (E T HR ). The Unicast message reply to strategy significantly decreases the quantity of control message overhead. The T-test's Degree of Variance and Degree of Independence is used to discover the energy-efficient optimum path. It is demonstrated through performance outcomes that the obtained Quality of Service (QoS) parameters for the proposed algorithm stands superior to the state-of-art protocols. Findings: An algorithm established on N-ETX and RE metrics is proposed, and the discussions have shown that this approach is energy efficient. This metric decreases the quantity of packet retransmission effectively for a path. As an outcome, the sensor's higher energy consumption is reduced. The proposed algorithm outperforms the current algorithm by decreasing energy consumption, reducing the quantity of packet retransmission, improving the PDR ratio, and enhancing the network life expectancy. The simulation outcome established that energy consumed is decreased by 19.07%, RE of the nodes is increased by 10.51%, PDR ratio is increased to 98%, and network lifespan is increased by 30.54%. Novelty: Internet of Things (IoT) gadgets are bound by hardware limits regarding computation, memory, and energy proficiency. To effectively transmit data packets, every IoT device must have a routing communications protocol that is easy to create. IoT devices necessitate the demand for self-adaptive routing algorithms. During network operation, packet energy dissipation during the broadcast and reception process is significantly higher when assessed to other https://www.indjst.org/ energy-consuming processes like sensing, data processing, etc.

show abstract

Section: Simulation Resultsmentioning

confidence: 99%

Section: Fig 8 Pdr Ratio Of Etalgormentioning

confidence: 98%

See 1 more Smart Citation

ETX-Aware Energy-Efficient Algorithm to Reduce Packet Retransmissions in the Internet of Things

Newton¹,

Felix²

2022

IJST

View full text Add to dashboard Cite

show abstract

“…the parameter 𝑦 𝑗 in (10) can be replaced with lower limits 𝑦 𝑗 𝑚𝑖𝑛 for upper limiting the anticipated lifetime improvement as given in (11);…”

Section: Adaptive Load Optimization Of Different Clustermentioning

confidence: 99%

Adaptive traffic aware clustering and routing model for wireless sensor networks

Veeregowdanadoddi Chandraiah,

Ramalingappa

2023

IJEECS

View full text Add to dashboard Cite

<span>Designing effective clustering algorithms plays a very important role in improving network lifetime target coverage (NLTC) in heterogeneous wireless sensor networks (HWSNs). However, the current clustering mechanism failed to address hotspot problem resulting in poor coverage and network lifetime performance. Recently, unequal clustering has been used for addressing hotspot problem in HWSNs. However, when performing inter-cluster routing, load balancing is not efficient and the energy degradation is high, which affects the overall network performance. This work introduces an effective model namely adaptive traffic aware clustering and routing (ATACR) model to address hotspot and load balancing issues. The ATACR introduces a novel unequal clustering and ideal distribution of load in different cluster levels. The ATACR model improves network lifetime, reduces control channel overhead, and attains better throughput in comparison with existing routing models.</span>

show abstract

“…Nevertheless, due to unequal clustering environments, relatively little effort has been made to tackle route optimization with QoS constraints. In addition, induced load-balancing difficulties that impact overall QoS are becoming a problem when it comes to the deployment of contemporary workflow applications [19]. The work has the objective of developing the energy aware reliable routing (EARR) architecture for IoT-WSNs because of the limitations and demands of modern IoT workflows in terms of QoS.…”

Section: Introductionmentioning

confidence: 99%

Energy aware reliable routing model for sensor network enabled internet of things environment

Mysuru Srikantha,

Kuzhalvaimozhi,

Mallikarjun Silli

et al. 2023

IJEECS

View full text Add to dashboard Cite

Wireless sensor networks (WSNs), which are facilitated by the internet of things (IoTs), can be difficult to improve the lifespan of the network target area. Although the hotspot issue (i.e., the cluster head closest to the base station fails quickly) is mitigated by the clustered-based routing technique, it still has an important effect on the network's lifespan and target area. However, improper distribution of load between cluster heads has been shown to negatively impact network lifespan efficiency, so even though unequal clusters have been utilized successfully to tackle the hotspot issue, further work is needed. This study provides an energy-aware reliable routing (EARR) model for resolving the hotspot as well as load balancing issues simultaneously. To extend the lifespan of the network, the EARR model effectively minimizes energy consumption by the cluster heads using enhanced multi-objective optimization parameters. Further, EARR provides improved routing optimization metrics to improve data delivery with energy efficiency, less delay, and packet loss. The results of the experiments demonstrate that the EARR model provides excellent throughput and lifespan efficiency with low delay and communication overhead.

show abstract

REERS: Reliable and energy‐efficient route selection algorithm for heterogeneous Internet of things applications

Cited by 16 publications

References 42 publications

ETX-Aware Energy-Efficient Algorithm to Reduce Packet Retransmissions in the Internet of Things

ETX-Aware Energy-Efficient Algorithm to Reduce Packet Retransmissions in the Internet of Things

Adaptive traffic aware clustering and routing model for wireless sensor networks

Energy aware reliable routing model for sensor network enabled internet of things environment

Contact Info

Product

Resources

About