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RFC 6550: On Minimizing the Control Plane Traffic of RPL-based Industrial Networks
... IP-connected IoT systems utilize 6LowPAN to integrate with the traditional Internet [3]. The Routing Over Low Power and Lossy Networks (ROLL) [4] group of the IETF standardized the RPL to address LLN routing needs, RPL operates at the network layer, enabling efficient route formation and dissemination [5]. However, RPL is vulnerable to various attacks. ...
... RPL, a lightweight routing protocol based on IPv6, is designed explicitly for 6LoWPAN [5]. RPL efficiently connects resource-constrained IoT nodes, adapting to diverse network setups to maintain quality of service (QoS) [7]. Figure 1 illustrates an overview of an RPL network, in which RPL defines a Destination-Oriented Directed Acyclic Graph (DODAG) utilizing an objective function (OF), a collection of metrics, and constraints [5]. ...
... RPL, a lightweight routing protocol based on IPv6, is designed explicitly for 6LoWPAN [5]. RPL efficiently connects resource-constrained IoT nodes, adapting to diverse network setups to maintain quality of service (QoS) [7]. Figure 1 illustrates an overview of an RPL network, in which RPL defines a Destination-Oriented Directed Acyclic Graph (DODAG) utilizing an objective function (OF), a collection of metrics, and constraints [5]. ...
The Routing Protocol for Low-Power and Lossy Networks (RPL) is an open standard routing protocol defined by the Internet Engineering Task Force (IETF) to address the constraints of IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN). RPL is susceptible to various attacks, including isolation attacks, in which a node or a set of RPL nodes can be isolated from the rest of the network. Three significant isolation attacks are the black hole attack (BHA), selective forwarding attack (SFA), and destination advertisement object (DAO) inconsistency attack (DAO-IA). In a BHA, a malicious node drops all packets intended for transmission silently. In an SFA, a malicious node forwards only selected packets and drops the other received packets. In a DAO-IA, a malicious node drops the received data packet and replies with a forwarding error packet, causing the parent node to discard valid downward routes from the routing table. We review the literature on proposed mechanisms, propose a taxonomy, and analyze the features, limitations, and performance metrics of existing mechanisms. Researchers primarily focus on power consumption as the key performance metric when mitigating BHA (47%), SFA (51%), and DAO-IA (100%), with downward latency being the least addressed metric for BHA (4%) and SFA (3%), and control packet overhead being the least addressed for DAO-IA (37%). Finally, we discuss the unresolved issues and research challenges in mitigating RPL isolation attacks.
... The work by Kwon et al. [10] analysed the End-to-End delay and cited the impact of long slotframe on the network formation. In addition, Sourailidis et al. [11] note that the network stability relies on the interval of the DODAG Information Object (DIO) messages, as unstable networks have more additional DIO messages. ...
... In addition, the impact over high depth mesh networks may affect the RPL Objective Function metrics and change the trickle timer forcing RPL message overhead, e.g. rising the amount of DIO and DODAG Information Solicitation (DIS) messages has been discussed by Sourailidis et al. [11]. In addition, the lack of DAO-ACK messages causes the nodes to generate new Destination Advertisement Object (DAO) messages. ...
Composed of constrained devices, Low-Power and Lossy Networks (LLNs) have been applied for numerous Internet of Things (IoT) applications. In addition, the Time-Slotted Channel Hopping (TSCH) media access control has been specified by IEEE aiming at Industrial IoT (IIoT). TSCH brings in the deterministic factor over wireless communication; it balances energy, bandwidth and latency, offering reliable communication. This paper conducted an experiment to reach the Contiki-NG’s TSCH Minimal Schedule breaking point. We analysed network factors to identify evidence that may lead to performance degradation. The located evidence might be employed by edge resilient counter-measures systems developers, vertical integration researchers or scheduling function designers to improve systems and increase the IIoT reliability.
... We also need sophisticated power-saving techniques to make this Internet of Things technology more adaptable. Because these IoT devices' memory and power resources are constrained, transmitting data to the IoT hub requires more power-efficient routing algorithms [7]. One of the IoT networks enabled by WSN is "Low-power and Lossy Networks" (LLN). ...
A revolutionary idea that has gained significance in technology for Internet of Things (IoT) networks backed by WSNs is the " Energy-Efficient Cluster-Based Routing Protocol with a Secure Intrusion Detection" (EECRPSID). A WSN-powered IoT infrastructure's hardware foundation is hardware with autonomous sensing capabilities. The significant features of the proposed technology are intelligent environment sensing, independent data collection, and information transfer to connected devices. However, hardware flaws and issues with energy consumption may be to blame for device failures in WSNassisted IoT networks. This can potentially obstruct the transfer of data. A reliable route significantly reduces data retransmissions, which reduces traffic and conserves energy. The sensor hardware is often widely dispersed by IoT networks that enable WSNs. Data duplication could occur if numerous sensor devices are used to monitor a location. Finding a solution to this issue by using clustering. Clustering lessens network traffic while retaining path dependability compared to the multipath technique. To relieve duplicate data in EECRPSID, we applied the clustering technique. The multipath strategy might make the provided protocol more dependable. Using the EECRPSID algorithm, will reduce the overall energy consumption, minimize the End-to-end delay to 0.14s, achieve a 99.8% Packet Delivery Ratio, and the network's lifespan will be increased. The NS2 simulator is used to run the whole set of simulations. The EECRPSID method has been implemented in NS2, and simulated results indicate that comparing the other three technologies improves the performance measures.
... In addition, the impact over high-depth mesh networks may affect the RPL OF metrics and change the trickle timer forcing RPL message overhead, e.g. rising the amount of DIO and DODAG Information Solicitation (DIS) as has been discussed by Sourailidis et al. [17]. ...
Low-power and Lossy Networks (LLN) are utilised for numerous Internet of Things (IoT) applications. IEEE has specified the Time-slotted Channel Hopping (TSCH) Media Access Control (MAC) to target the needs of Industrial IoT. TSCH supports deterministic communications over unreliable wireless environments and balances energy, bandwidth and latency. Furthermore, the Minimal 6TiSCH configuration defined Routing Protocol for Low power and Lossy networks (RPL) with the Objective Function 0 (OF0). Inherent factors from RPL operation, such as joining procedure, parent switching, and trickle timer fluctuations, may introduce overhead and overload the network with control messages. The application and RPL control data may lead to an unpredicted networking bottleneck, potentially causing network instability. Hence, a stable RPL operation contributes to a healthy TSCH operation. In this paper, we explore TSCH MAC and RPL metrics to identify factors that lead to performance degradation and specify indicators to anticipate network disorders towards increasing Industrial IoT reliability. A TSCH Schedule Function might employ the identified aspects to foresee disturbances, proactively allocate the proper amount of cells, and avoid networking congestion.
... The RPL nodes use the trickle timer to send DODAG Information Object (DIO) messages to disseminate information over the formed topology. As cited by [36], RPL nodes use the trickle timer for sending DIO messages, and the higher the trickle timer, the more stable the network. In addition, the work notes that the network stability relies on the interval between DIO messages, as unstable networks require the transmission of more supplementary DIO messages. ...
The support of critical industrial applications using constrained sensing devices will require deterministic communication technologies, which has motivated the design of TSCH media access control mechanisms. TSCH carefully manages the necessary energy to support deterministic communications while trying to cope with the bandwidth and latency required for the application. Nevertheless, using TSCH to support Industrial critical applications is still challenging since scheduling strategies lack the elasticity to cope with dynamic and error-prone communication environments. Also, scheduling adaptation strategies may be designed to benefit from the information in other layers. We propose a distributed TSCH scheduling based on analysing network behaviour, particularly employing the RPL Trickle algorithm to support dynamic and network-aware scheduling. The proposed strategy contributes to anticipating disturbances and the network’s overall stability. The proposal was evaluated for its performance at the application and MAC layers, and we may observe that it contributes to increasing network efficiency.
... The performance metric of RPL can be studied in many ways like End-to-End (E2E) delay, energy efficiency, length of the path, network convergence time and Packet Delivery Ratio (PDR), stability of DODAG and Trickle timer configurations [14]. As far as number of hops rank in RPL denotes the distance of router from the DODAG root. ...
The sensor enabled applications coupled with Internet are currently increasing among everyone. Low power and lossy network (LLN) equipment have diminished memory, energy, and refining resources. In LNN power conservancy and network lifetime improvement are foremost challenges. The high energy depletion, packet loss ratio and increased traffic are due to ineffective route selection. In Internet of Things (IoT) LLN system, the routing protocol should improvise the network lifetime by enhancing proactive routing method for each node to keep up a functioning way to the sink hub. The synchronization between sinks makes it to know about the network state of nearby sink nodes and uses the occasional course support messages provided by RPL to deal network status with its neighboring sinks. The sinks can formulate a decision to improve overall performance with increased network lifetime. To appraise the performance of projected work regarding network lifetime and packet delivery ratio (PDR) over traffic load and routing metric, Contiki COOJA simulator is used.
In WSN assisted IoT networks, the devices have to search the path up to the IoT hub for data transmission. Although the device’s hardware capabilities are increasing day by day, the device’s battery capacity is not increasing at the same rate. IoT devices have limited-power batteries that are not rechargeable. It is also challenging to replace their battery while the devices are in use. Moreover, we need advanced power-saving schemes to make these IoT technologies more adaptable. Due to the energy constraints and limited memory capacity of these IoT devices, we require more energy-efficient routing protocols to route data to the IoT hub. This paper has surveyed the most recent state-of-the-art routing protocol and highlighted their limits and path for future research.
The Internet of Things (IoT) is an evolving concept that has achieved prominence in the modern era. An autonomous sensor-equipped device is the major component of WSN-assisted IoT infrastructure. These devices intelligently sense the environment, automatically collect the data, and deliver the information to paired devices. However, in WSN-assisted IoT networks, energy depletion and hardware faults might result in device failures. Additionally, this might affect data transmission. A reliable route significantly reduces data retransmissions, which can help in congestion reduction and energy conservation. Generally, the sensor devices are typically deployed densely throughout the WSN-assisted IoT networks. A high number of sensor devices covering a monitoring area might result in duplicate data. The clustering method can be used to overcome this problem. The clustering technique reduces network traffic, whereas the multipath technique ensures path reliability. In CRPSH, we used the clustering technique to reduce the duplicate data. Moreover, the multipath approach can increase the reliability of the proposed protocol. CRPSH is intended to minimize the overhead associated with control packets and extend the network’s lifetime. The complete set of simulations is carried out using the Castalia simulator. The proposed protocol is found to reduce energy consumption and increase the lifetime of IoT infrastructure networks.
Important changes in electricity consumption model require a communication network within the electrical grid, which is called the Advanced Metering Infrastructure (AMI) that can handle the increase of multiple and fluctuating production sites. Recently, we witness the convergence of this communication network and the electricity network into what is now called Smart Grid. This communication network will serve the purpose of automatic meter reading, but new usages and services could be developed on top of this network. The massive integration of renewable energy sources will shift the production level close to the consumption sites. Therefore, new communication models are required to control the energy consumption depending on the production capabilities. In this Chapter, we explain why a two‐way communication network is necessary for future Smart Grid. Furthermore, we present the required network characteristics, and we particularly describe what are the current protocols selected to achieve these goals.
Traffic-aware Objective Function
- R Koutsiamanis
- G Z Papadopoulos
- E I Sanchez
- C Ji
- D Dujovne
- N Montavont
Use cases for DIS Modifications
- G Z Papadopoulos
RPL: IPv6 Routing Protocol for Low-Power and Lossy Networks