Increased Network Lifetime and Load Balancing Based on Network Interface Average Power Metric for RPL

Pereira, Hermano; Moritz, Guilherme Luiz; Souza, Richard Demo; Munaretto, Anelise; Fonseca, Mauro

doi:10.1109/access.2020.2979834

Cited by 25 publications

(15 citation statements)

References 19 publications

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“…When calculating the expected transmission count (ETX), the update metric timer algorithm determines the routing metric, which is crucial because it allows Routing Protocol for Low‐Power and Lossy Networks (RPL) to select a reliable path 6 …”

Section: Literature Surveymentioning

confidence: 99%

Design of efficient location‐based multipath self‐adaptive balancer router using particle swarm optimization in wireless sensor network

Sakthivel¹,

Manikandan²,

Vivekanandhan³

2022

Int J Communication

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Summary The power sensor terminals control in wireless sensor network (WSN) communicate within a small number of its radio range. As a branch operating based on the cluster routing protocol, it has proven to be effective in network topology management, energy reduction, and path connection link quality of the path. Location‐based clusters are categorized into member nodes and group/cluster heads (CHs). The CH election process increases the overhead of the network. The processing and energy limitations of the nodes are considered for the CH election process. The allocation of system resources is the major issue in the area of networks. In this work, the proposed multipath self‐adaptive balancer routing‐based particle swarm optimization (MLBAR‐PSO) achieves load balancing by means of the link quality of the route and the calculated average latency and reliability of the path. In this way, different trust values are set in each category. The forwarding node value is the value of each node based on the weight value, which is calculated based on the energy ratio of the node and the distance between the hiding node and the target node. Particle swarm optimization (PSO) selects the head cluster from a specific location within the cluster to enable other nodes to interact with the CH without spending energy. Also, the algorithm is used to find the optimal path for the base station and significantly increases the energy to reduce the distance and delay over the lifetime of the network.

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Section: Literature Surveymentioning

confidence: 99%

Design of efficient location‐based multipath self‐adaptive balancer router using particle swarm optimization in wireless sensor network

Sakthivel¹,

Manikandan²,

Vivekanandhan³

2022

Int J Communication

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“…The results were obtained by Cooja network simulation in terms of energy consumption, delay, and transmission rate. Pereira et al [15] proposed a new routing metric for the RPL. This metric gives not only provides a reliable path selection like ETX on the network, but also important results such as load balancing and lifetime increasing on the network.…”

Section: Related Workmentioning

confidence: 99%

Experimental Analysis of Energy Efficient and QoS Aware Objective Functions for RPL Algorithm in IoT Networks

Arat

Demirci

2021

Sakarya University Journal of Computer and Information Sciences

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The Internet of Things (IoT) refers to smart devices with limited resources that connect to the Internet and transmit data. Routing is an important process in this structure, which can be described as the general frame of wireless sensor networks (WSNs). The Routing Protocol for Low-Power and Lossy Networks (RPL) is recommended by the Internet Engineering Task Force (IETF) to provide communication in resource-constrained networks and is designed for routing in IoT. Basically, it is the Internet Protocol Version 6 (IPv6) protocol developed based on the energy consumed by devices. The algorithm has an important place in the performance of the IoT network. In this paper, the performance of the RPL under different objective functions (OFs) is examined. OFs are symbolized and defined by detailed equations. This study provides an experimental analysis of the RPL algorithm. An overview of the RPL algorithm is also included. Finally, the RPL algorithm is simulated by a custom simulator which is performing on the application layer, created using the Python programming language. The algorithm's behaviour in terms of different OFs such as throughput maximization, energy efficiency maximization and energy consumption minimization was observed and the results were evaluated under different parameters such as packet size, number of nodes and different signal-to-noise ratio (SNR) values. Our experimental results may be useful for both researchers and practitioners working in related fields.

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“…Kechiche [38] proposed Reliable and Delay Aware RPL (RDARPL) protocol which uses a combination of average delay of the complete path, ETX and hop count to select PP. The authors in their study [39] have introduced a new metric called network interface average power metric (NIAP) which indicates the average power consumption of network interface. NIAP metric identifies the reliable path and provides load balancing among nodes which claims to work faster and efficiently than ETX metric.…”

Section: Related Workmentioning

confidence: 99%

MEQA-RPL: A Mobility Energy and Queue Aware Routing Protocol for Mobile Nodes in Internet of Things

Cyriac

Durai

2021

Preprint

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Increase in mobile nodes has brought new challenges to IoT’s routing protocol-RPL. Mobile nodes (MN) bring new possibilities as well as challenges to the network. MN creates frequent route disruption, energy loss and increases end-to-end delay in the network. This could be solved by improving RPL to react faster to route failures through route prediction, while keeping energy expenditure for this process in reasonable limits. In this context a new Mobility Energy and Queue Aware-RPL (MEQA-RPL) is proposed that have the capability to sense route failure and to identify proactively the next possible route before the current route fails. While identifying the next route, MEQA-RPL employs constraint check on energy and queue availability to guarantee QoS for MN and better lifetime for the network. When compared to RPL with mobility support our model reduce average signaling cost by 31%, handover delay by 32% and improve packet delivery ratio by 17%. We run simulations with multiple mobile nodes which have also shown promising results on aforementioned parameters.

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Increased Network Lifetime and Load Balancing Based on Network Interface Average Power Metric for RPL

Cited by 25 publications

References 19 publications

Design of efficient location‐based multipath self‐adaptive balancer router using particle swarm optimization in wireless sensor network

Design of efficient location‐based multipath self‐adaptive balancer router using particle swarm optimization in wireless sensor network

Experimental Analysis of Energy Efficient and QoS Aware Objective Functions for RPL Algorithm in IoT Networks

MEQA-RPL: A Mobility Energy and Queue Aware Routing Protocol for Mobile Nodes in Internet of Things

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