A Multipath Routing for Payment Channel Networks for Internet of Things Microtransactions

Bi, Hongliang; Chen, Yanjiao; Zhu, Xiaotian; Liu, Jinhui

doi:10.1109/jiot.2022.3167098

Cited by 11 publications

(5 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The penultimate phase in the optimization procedure is low speed, which happens when the predator's actions are faster than the prey's. As a result, it is said as the phase of exploitation, and it is represented by Equation (19).…”

Section: • Step 4: Location Searching Of Bcomentioning

confidence: 99%

“…Stop the procedure after getting the better answer, or continue Equations ( 15)-( 19) till the requirements are fulfilled. Equations ( 16)- (19) offer the ideal travel path with least amount of delay. The hyb-MP-BCOA approach gives an optimum route path that iteratively repeat Step 3 till halting criteria t ¼ t þ 1 met.…”

Section: • Step 7: Terminationmentioning

confidence: 99%

“…Several routing algorithms were suggested previously in IoT. [18][19][20] The existing protocol increases the energy consumption by averting redundancy in data, so, effectively lessening bandwidth and memory, and does not provide an optimal path. However, due to the lack of efficient balance of load techniques for routing methods such as Destination-Sequenced Distance Vector Routing (DSDV) and Ad Hoc On-Demand Distance Vector Routing (AODV), a few nodes turn overloaded when others become underloaded and unable to use the resources.…”

Section: Introductionmentioning

confidence: 99%

“…The main objective of multipath routing is to provide available paths to create the communication among the nodes concurrently. Several routing algorithms were suggested previously in IoT 18–20 . The existing protocol increases the energy consumption by averting redundancy in data, so, effectively lessening bandwidth and memory, and does not provide an optimal path.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Hybrid Marine Predators and Border Collie Optimization algorithm for multipath routing in IoT

Kumar

2023

Int J Communication

View full text Add to dashboard Cite

SummaryInternet of Things (IoT) is a network of smart things that connects people and objects for gathering and exchanging information by means of embedded sensor. IoT‐based wireless sensor network (WSN) nodes are monitored as a resource parameter at the variety of methods, including resource calculation, energy resource, and storage resource, with multipath routing protocols necessary to enable extended network lifespan and achieve high energy utilization. The existing routing protocols did not provide optimal path from the multipath route. Hence, in this manuscript, a Hybrid Marine Predators and Border Collie Optimization algorithm is proposed for multipath routing in IoTs. The main aim of this endeavor is to “increase network lifetime.” IoT is simulated initially and multipath routing initiates in internet of things network. Multipath routing is achieved by proposed Hyb‐MP‐BCOA; this is the combination of Hybrid Marine Predators Algorithm and Border Collie Optimization algorithm. The proposed Hyb‐MP‐BCOA algorithm chooses the optimum path from the multiple path obtainable for routing, depending upon fitness parameter, like context awareness, network lifetime, residual energy, trust, and delay. Based on the fitness parameter, the optimal path is selected by using Hyb‐MP‐BCOA algorithm. Finally, the proposed Hyb‐MP‐BCOA‐MR‐IoT model is applied in MATLAB, and efficacy of proposed technique is estimated by using various performance metrics, like drop, normalized network energy, lifetime of network, delay, throughput, energy consumed, packet delivery ratio, and number of sensor nodes versus aggregation level. The proposed method attains lower delay of 14.285%, 50%, 53.846%, and 57.142%, lower packet drop of 14.285%, 50%, 53.846%, and 57.142%, lower energy consumption compared with existing methods such as multiobjective sun flower optimization with gray wolf optimizer (GWO) for multipath routing in IoT (SFO‐GWO‐MR‐IoT), multiobjective Whale Lion Fireworks optimization algorithm and fitness function for multipath routing in IoT (WLFA‐MR‐IoT), multipath routing in IoT using shuffled frog leaping algorithm (SFLA‐MR‐IoT), and multipath routing in IoT using hybrid Whale Optimization Algorithm‐Moth Flame Optimization (MFO)(hyb‐WOA‐MFO‐MR‐IoT). Finally, the safe communication is attained in the IoT network.

show abstract

Section: • Step 4: Location Searching Of Bcomentioning

confidence: 99%

Section: • Step 7: Terminationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Hybrid Marine Predators and Border Collie Optimization algorithm for multipath routing in IoT

Kumar

2023

Int J Communication

View full text Add to dashboard Cite

show abstract

“…Due to the high level of environmental unpredictability, these methods guarantee that sensor networks operate well and that the sensor nodes within them retain their functioning. The Vehicular Ad-Hoc Reliable Routing (VARR) [31,32,33,34] is a dynamic optimization method that should be taken into account for WMSNs. This is due to the fact that in a highly dynamic environment where variables like wireless channel conditions, traffic, and energy restrictions are always changing, effective decision-making is crucial.…”

Section: Introductionmentioning

confidence: 99%

QIBMRMN: Design of a Q-Learning based Iterative sleep-scheduling & hybrid Bioinspired Multipath Routing model for Multimedia Networks

Doorwar,

Malathi

2023

International Journal of Electronics and Telecommunications

View full text Add to dashboard Cite

Enhancement of IOTA implementation in IoT: Comparison and analysis

Vyas,

Raiyani

2023

AIP Conference Proceedings

View full text Add to dashboard Cite

A Multipath Routing for Payment Channel Networks for Internet of Things Microtransactions

Cited by 11 publications

References 24 publications

Hybrid Marine Predators and Border Collie Optimization algorithm for multipath routing in IoT

Hybrid Marine Predators and Border Collie Optimization algorithm for multipath routing in IoT

QIBMRMN: Design of a Q-Learning based Iterative sleep-scheduling & hybrid Bioinspired Multipath Routing model for Multimedia Networks

Enhancement of IOTA implementation in IoT: Comparison and analysis

Contact Info

Product

Resources

About