A Novel Approach for RPL Assessment Based on the Objective Function and Trickle Optimizations

Lamaazi, Hanane; Benamar, Nabil

doi:10.1155/2019/4605095

Cited by 32 publications

(19 citation statements)

References 20 publications

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“…The control overhead can be reduced further in such existing works by adjusting the RPL parameters. The RPL based on a flexible trickle algorithm in [18] considers fuzzy logic and provides a set of variables as input to enforce even energy dissipation without affecting the routing performance. However, there is a possibility for enhancing routing performance, using several networks and RPL parameters.…”

Section: Related Workmentioning

confidence: 99%

Load Balancing in RPL to Avoid Hotspot Problem for Improving Data Aggregation in IoT

Arunachalam¹,

Nallamothu²

2021

IJIES

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Data aggregation plays a vital role in the Internet of Things (IoT), and it aggregates the collected sensor data from devices to suppress redundant data transmissions. Many-to-one traffic pattern in the IoT induces hotspot problem and inefficient data aggregation. The Routing protocol for low-power and lossy networks (RPL) in the network layer impacts the hotspot problem due to the frequent usage of forwarding nodes and load imbalance. The processes of network layer protocol, such as trickle algorithm and Objective Functions (OF) for Destination Oriented Directed Acyclic Graph (DODAG) construction, need more attention to avoid hotspot for efficient data aggregation. This work proposes a Load Balanced RPL (LoB-RPL) protocol to avoid hotspot creation using a composite metric based parent selection, DODAG construction, and local topology adaptive decision on trickle parameters. The LoBRPL improves the Minimum Hop with Hysteresis Objective Function(MRHOF) using the composite metric based parent selection and tunes the parameters of the Trickle algorithm. It ensures efficient maintenance of DODAG structure, hotspot avoidance, and unnecessary DIO transmissions. Beyond the advantages of composite metric based parent selection, consideration of dynamic parameters may induce frequent parent switching in RPL. To avoid frequent changes in the DODAG structure, the LoB-RPL optimally decides the parent switching threshold. Thus, the proposed work ensures a load-balanced and an energy-efficient RPL routing as well as data aggregation in the IoT environment. The LoB-RPL delivers outperforming results compared to the base RPL under various inter-packet interval time over 50 node topologies.

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Section: Related Workmentioning

confidence: 99%

Load Balancing in RPL to Avoid Hotspot Problem for Improving Data Aggregation in IoT

Arunachalam¹,

Nallamothu²

2021

IJIES

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“…Further, Sharkawy et al (2014) utilized node capabilities, resources and locations as the metrics for rank selection; moreover, Nurmio, Nigussie, and Poellabauer (2015) carried out a ranking estimation based on ETX and the remaining energy of the sensor node. A recent work on a fuzzy-based RPL routing scheme combined metrics, such as the battery level, crowdedness and distance to compute the rank (Agarkhed, 2017), whereas Lamaazi, Benamar, and Jara (2019) proposed an adaptive fuzzy-based new objective function that combined ETX and energy consumption metrics to perform the ranking.…”

Section: Related Workmentioning

confidence: 99%

An expert system for low‐power and lossy indoor sensor networks

et al. 2020

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We have developed an expert system comprising a self-aware framework for resource-efficient and accurate data transmission within a low-power lossy sensor network (LLN) deployed for indoor monitoring. We derived both individual and group awareness, which could ensure the awareness of each sensor regarding its resources, neighbours and network environment. The proposed expert system facilitates decision-making under dynamic environmental conditions and employs a multicriteria decision-making (MCDM) model to determine the selection of the best path towards the sink node with awareness of the existing network environment. The proposed system is validated by constructing a 6LoWPAN network in the Contiki Cooja simulator. MCDM is applied to generate an adaptive objective function for the IPv6 routing protocol for the LLN (RPL) and to aid in ranking the nodes to select the best available neighbouring node, while the data accuracy is ensured by the cluster head through data correlation among its associated members. The network performance is assessed by analyzing the packet delivery rate, throughput and energy consumption against varying sensors and by comparing our proposed MCDM-RPL with a standard RPL and a fuzzy-based RPL, where the results show that our framework is found to be better with gains of 13, 25 and 13%, respectively.

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“…DODAG Advertisement Object packets (DAO) are used to collect information about the topology. DAO-ACK is sent by a DAO recipient in response to a DAO message [12] [13].…”

Section: Rpl Overviewmentioning

confidence: 99%

OF-ECF: A New Optimization of the Objective Function for Parent Selection in RPL

Lamaazi

Ahmadi

Benamar

et al. 2019

2019 International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

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The RPL routing protocol is designed to respond to the requirements of a large range of Low-power and Lossy Networks (LLNs). RPL uses an objective function (OF) to build the route toward a destination based on routing metrics. Considering only a single metric, some network performances can be improved while others may be degraded. In this paper, we present a flexible Objective Function based on Expected Transmission Count (ETX), Consumed Energy and Forwarding Delay (OF-ECF) built on a combination of metrics using an additive method. The main goal of this proposed solution is to balance energy consumption and minimize the average delay. To improve the reliability of the network, a flexible routing scheme that provides the diversity of paths and a higher availability is presented. Simulations results show that the new objective function OF-ECF outperforms the OF-FUZZY, and the standards OF0 and MRHOF. In terms of network lifetime and reliability.

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A Novel Approach for RPL Assessment Based on the Objective Function and Trickle Optimizations

Cited by 32 publications

References 20 publications

Load Balancing in RPL to Avoid Hotspot Problem for Improving Data Aggregation in IoT

Load Balancing in RPL to Avoid Hotspot Problem for Improving Data Aggregation in IoT

An expert system for low‐power and lossy indoor sensor networks

OF-ECF: A New Optimization of the Objective Function for Parent Selection in RPL

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