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Atitallah, N.; Cheikhrouhou, O.; Mershad, K.; Koubaa, A.; Hajjej, F. Routing Protocol for Wireless Sensor Networks. Encyclopedia. Available online: https://encyclopedia.pub/entry/52664 (accessed on 03 July 2024).
Atitallah N, Cheikhrouhou O, Mershad K, Koubaa A, Hajjej F. Routing Protocol for Wireless Sensor Networks. Encyclopedia. Available at: https://encyclopedia.pub/entry/52664. Accessed July 03, 2024.
Atitallah, Nesrine, Omar Cheikhrouhou, Khaleel Mershad, Anis Koubaa, Fahima Hajjej. "Routing Protocol for Wireless Sensor Networks" Encyclopedia, https://encyclopedia.pub/entry/52664 (accessed July 03, 2024).
Atitallah, N., Cheikhrouhou, O., Mershad, K., Koubaa, A., & Hajjej, F. (2023, December 13). Routing Protocol for Wireless Sensor Networks. In Encyclopedia. https://encyclopedia.pub/entry/52664
Atitallah, Nesrine, et al. "Routing Protocol for Wireless Sensor Networks." Encyclopedia. Web. 13 December, 2023.
Routing Protocol for Wireless Sensor Networks
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This entry is adapted from the peer-reviewed paper 10.3390/s23218834

Wireless sensor networks (WSNs), constrained by limited resources, demand routing strategies that prioritize energy efficiency. The tactic of cooperative routing, which leverages the broadcast nature of wireless channels, has garnered attention for its capability to amplify routing efficacy.

RPL Arduino-based sensor nodes Wireless sensor networks (WSNs)

1. Introduction

Wireless sensor networks (WSNs) are an important part of the infrastructure that supports the Internet of Things (IoTs) [1][2]. Due to the advancement of the underlying technology, WSNs have found widespread use in a variety of contexts [3]. As a result, they are extensively used in many different disciplines to conduct research, monitor the environment, monitor industry and even collect intelligence for defense and national security purposes [4][5]. The primary responsibilities of sensor nodes are detecting and communicating data correctly to the cluster head (CH). The latter is concerned with gathering data from nodes in the cluster and transmitting these to the hub [6]. But, the routing process is the one that uses the most power [7]. Therefore, it is crucial to make routing as efficient as possible to save energy and extend the lifetime of sensors. To address the requirements of WSNs, the Internet Engineering Task Force (IETF) has proposed the Routing Protocol for Low-Power and Lossy Networks (RPL) [8], which operates over IPv6 [9]. It is a powerful routing system that can be readily tweaked to suit the user’s needs by adjusting the weights of various objectives. While this is happening, RPL nodes may become unreliable as they choose routes that are less efficient than others [8]. Promoting RPL reliability by the selection of more stable and higher-quality routes remains an unresolved research challenge in RPL design. Several research efforts focus on improving the RPL protocol so that it can satisfy the stringent needs of WSNs in terms of energy savings, reliability, lifetime, latency, etc.
RPL reliability can be improved by leveraging the wireless medium’s broadcast capabilities to establish effective communication among its components. More precisely, channels from the source to the relay nodes, which have received a copy of the data packet, are utilized in every transmission strategy between any source–destination pair. This serves to instigate spatial diversity at the destination [10].
The recipient combines multiple signal duplicates, making use of the channel statistics established between itself and the different transmitters. In case of a transmission failure, a chosen relay is utilized to transmit the same data, providing a more energy-efficient alternative compared to a direct transmission from the source to the destination. Relay techniques become especially relevant when there is a significant distance, an extensive mid-range, or less-than-ideal channel conditions between the source and the destination.

2. RPL Routing Mechanism Overview

Numerous embedded devices with constrained power, memory, and computing capabilities are joined through various connections, such as IEEE 802.15.4, to form WSNs [1]. The IETF ROLL working group created an IPv6 RPL to help with battery life. It may be utilized in data-collecting networks while using very little power. Table 1 summarizes the abbreviations used.
Table 1. Abbreviations.
Abbreviation Full Form
BEP Bit error probability
CH Cluster head
DAO Destination advertisement object
DIO Destination information object
DIS DODAG information solicitation
DODAG Destination-oriented directed acyclic Graphs
IETF Internet Engineering Task Force
OF Objective function
RPL Routing Protocol for Low Power and Lossy Networks
RSSI Received signal strength indication
SDR Selective digital relaying
SNR Relaying (SDR)
WSNs Wireless sensor networks
Routing in RPL is performed using the destination-oriented directed acyclic graphs (DODAGs) idea, making it a distance vector routing protocol [11]. This is accomplished by constructing and updating a decentralized data structure whilst the WSN is in operation. The RPL method constructs this kind of distributed routing table to direct data packets throughout the network [12]. A root node is one that has no child nodes or outbound connections. The low power and lossy network is connected to the Internet and other external networks through “roots”. Using three predetermined messages, the root node chooses the optimal way based on predefined parameters (such as hop count, energy cost, dependability, latency, etc.) as shown in Figure 1:
Sensors 23 08834 g001
Figure 1. RPL DODAG building process.
  • Destination information object (DIO): sent from the DODAG’s root to its child nodes in order to perform certain operations.
  • Destination advertisement object (DAO): broadcasts information about a destination node up the distributed outage distribution graph (DODAG) to update the routing tables of parent nodes.
  • DODAG information solicitation (DIS): in the case of grounding and floating DODAGs, it can help locate them. It is the DIO’s job to respond to a DIS transmission.
Depending on the specific use case, scholars categorize RPL functionality into one of three distinct modes [13] as follows:
1.
Collect protocol: Data from all the other nodes are gathered via the collect protocol and then sent to the root node. As for the route, all one have to do is follow the DODAG.
2.
Distribute protocol: With the help of the distribute protocol, information may be sent from the hub to individual nodes. The path is determined by using the name and origin place provided in the DAO message.
3.
Peer-to-peer protocol: Data may be sent from one node to another via the P2P protocol, with the most often used route being through the parents or the root node.
Yet research shows that the packet loss ratio for multi-hop lines may approach 20 percent or more as the number of hops grows [8]. Thus, selecting more stable and high-quality routes is a viable method to improve RPL’s reliability. This is achieved by taking into account more efficient link quality [9].

2. Routing Protocol for Wireless Sensor Networks

Much work has gone into creating new energy-efficient routing protocols and improving existing ones. In the realm of WSNs, RPL is a well-known example of an energy-efficient protocol. In addition, the Internet Engineering Task Force (IETF) has adopted it as the default standard routing protocol [14]. However, RPL nodes may be unreliable since inferior pathways are used. This is a topic for further study in RPL architecture since it might be used to improve the service’s dependability by allowing for the selection of more robust and high-quality routes [8]. In contrast, cooperative routing algorithms account for the potential for physical-layer cooperative transmission. In [15], the partner node’s relay selection for cooperative routing depends on criteria such as residual energy and SNR of the source–partner connection. The authors demonstrate that using SNR-based criteria yields superior outcomes regarding stability period, decreased latency, and packet loss. Optimal relay selection protocols that save energy and work together are presented for underwater WSNs. This uses the position and depth of the sensor nodes together to make its selections. In [16], the authors show that data packets are less vulnerable to variations in channel quality. They proposed CoopRPL, an implementation of RPL that incorporates a cooperative communication technique, to improve the dependability of advanced metering infrastructure (AMI) networks [17]. The authors in [18] addressed energy efficiency and demonstrated that cooperative methods may achieve better results than non-cooperative ones. In reality, if the energy is most effectively distributed between the source and the relay, the system performance of cooperative systems may be further enhanced. Many academics are interested in how cooperative diversity might be used to reduce power consumption in WSNs [18][19]. As cooperative transmission has become popular, it is considered in the routing mechanism, and there has been much effort put into developing and assessing cooperative routing protocols [20]. In [21], Matlab simulations are used to test and evaluate a suggested routing method that cooperatively considers energy route and channel awareness. Using the CoEPACA protocol, a higher degree of dependability may be attained with much less power. In [22], To ensure that IoT devices use as little energy as possible, a new routing measure, SPR, was created, and a more nuanced cross-layer goal function for RPL was suggested. Aslani et al. [17] demonstrated that, compared to RPL and opportunistic RPL, their suggested protocol improves the packet delivery ratio (PDR) by up to 20% and 10%, respectively, under best-effort conditions. They also demonstrated a 15% reduction in end-to-end latency compared to the RPL protocol.
In [23], the authors present the cooperation-aided routing protocol for lossy networks, which is the result of incorporating cooperative communication into the RPL protocol. Each node may send data to its desired parent through a relay node, which improves the dependability and decreases the energy usage at each hop in the network. The simulation findings show that their solutions may significantly reduce the energy use.
Similarly, in [24], considering the quality of the interlinks, the authors suggest a hybrid energy-efficient cluster-parent-based RPL routing protocol (HECRPL) to improve both efficiency and dependability. In terms of extending the network lifespan and delivering more consistent data transmission, they show via simulation results that their proposed protocol exceeds the benchmark RPL.
Energy efficiency has been investigated [25] from many directions, with some focusing on fostering cooperation between the nodes performing different sensing functions and others on creating numerous versions of the system. This resulted in the authors demonstrating a rise in node energy usage, complexity, and expense compared to RPL.
The authors in [26] assessed RPL’s performance across three parameters, namely network density, throughput, and sink localization. More precisely, three essential metrics are considered: Expected transmission count (ETX), hop count (HC), and energy. The evaluation results demonstrate that the parameters are influenced by the number of nodes in all scenarios. Notably, the ETX metric consistently exhibits a strong performance in terms of packet delivery ratio (PDR), while the energy metric consistently records the highest energy consumption among all the tested scenarios.
To address the challenge of reliability in RPL, the authors in [27] proposed RAARPL: reliability-aware adaptive RPL routing protocol. RAARPL enhances the RPL reliability by selecting parents based on multiple reliability-related criteria and considering path conditions during the decision-making process. This ensures network stability by controlling the parent selection and children assignment to minimize errors. Simulation results, compared to CLRPL and RPL protocols in various scenarios using Cooja, demonstrate the significant efficiency of RAARPL in improving data exchange reliability, successful delivery ratios, reducing topology instability, and enhancing network throughput.
Furthermore, some work addressed the security aspect of the RPL protocol [28][29][30][31]. In [32], the authors focused on the detection and mitigation of rank attacks within RPL. They proposed a rank attacks detection algorithm that minimizes the control packet overhead by appending extra fields in DAO and DIO messages and introduces a local alarm mechanism for energy conservation in cases of minor attack impact, alongside employing random sampling for efficient internal attacker identification. The authors in [33] introduced a novel RPL attack named dropped destination advertisement object (DDAO). The DDAO attack disrupts network connectivity by preventing the formation of downward routes, affecting a significant portion of the network. To counter this threat, the paper proposes an efficient, lightweight intrusion detection system that efficiently detects DDAO attacks through distributed monitoring of parent node behavior with respect to forwarded destination advertisement object (DAO) messages.
In summary, much effort must be put into studying, evaluating, and improving the RPL mechanism’s performances to increase its dependability and efficiency.

References

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Subjects: Computer Science, Cybernetics
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Nesrine Atitallah
,
Omar Cheikhrouhou
,
Khaleel Mershad
,
Anis Koubaa
,
Fahima Hajjej
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Revisions: 2 times (View History)
Update Date: 18 Dec 2023
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