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The standardized IPv6 Routing Protocol for Low-power and Lossy Networks (RPL) has enabled efficient communications between thousands of smart devices, sensors, and actuators in a bi-directional, and end-to-end manner, allowing the connection of resource constraint devices in multi-hop IoT infras-tructures. RPL is designed to cope with the major cha...
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... it has been illustrated in Fig. 1, the structure of CBR-RPL includes four types of nodes with different responsibilities: 1) Sink: The root of the DODAG, 2) Simple Node (S): A small-sized buffer node, which its parent is not the sink, 3) Simple Cluster Head (sCH): A small-sized buffer node, whose parent is the sink, and 4) Cluster Head (CH): A large-sized buffer node. ...
Context 2
... it has been illustrated in Fig. 1, the structure of CBR-RPL includes four types of nodes with different responsibilities: 1) Sink: The root of the DODAG, 2) Simple Node (S): A small-sized buffer node, which its parent is not the sink, 3) Simple Cluster Head (sCH): A small-sized buffer node, whose parent is the sink, and 4) Cluster Head (CH): A large-sized buffer node. ...
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... However, no new method/OF was proposed. Similarly, the paper [24] introduced the concept of organising nodes into clusters and then routing those packets using the proposed OF. Although their results had shown an improvement in PDR values, the experiment was only constrained to static nodes. ...
... Interestingly, it is worth noting that studies from [19][20][21][22][23][24][25][26][27][28][29][30][31][32][33]51] had thrived for static nodes in RPL, whereas studies from [34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50] had labored for mobile nodes in RPL but IoT networks. It tends to be gathered that a proactive exploration is needed in the field of RPL considering mobility. ...
The Routing Protocol for Low power and Lossy networks (RPL) utilises the Objective Function (OF) to form a Destination Oriented Directed Acyclic Graph (DODAG) to reach the destination by selecting the best path. Many works in literature have explored this domain concerning the Internet of Things (IoT) applications. Although, the application of RPL protocol from IoT to the Internet of Vehicles (IoV) in the smart city still presents a big test. Since this gap has not been much traversed, it motivated us to present our findings on this research gap. This paper has realised the transition of RPL protocol from IoT to IoV for the first time. The network performance has been analysed using RPL in a static and mobile environment based on three configurations: Quality of Service (QoS) parameters, network scalability and mobility models. Also, a comprehensive analysis of the RPL performance in both environments has been bestowed in our paper. Finally, we have summarised our inputs and stated potential future directions for researchers. The experiments have been performed using Contiki OS/Cooja Simulator, BonnMotion tool and Wireshark. Simulation results have shown that Self-similar Least Action Walk (SLAW) has outperformed Random Way-Point (RWP) and Nomadic mobility model. High value of Packet Delivery Ratio (PDR) is achieved in mobile/dynamic environment than static. These findings can be directly applied to IoV and IoT applications using RPL protocol like Traffic Monitoring System (TMS), smart corridors, Electronic Toll Collection (ETC), etc. in smart city. Moreover, this article will help the researchers in gaining a better insight of RPL protocol in static and mobile environments for future works.
... Traditional wireless sensor network routing protocol design is to avoid network congestion and link bottleneck, and to ensure network connectivity and reliable data transmission as the main goal [8][9][10][11]. On the one hand, in the process of implementing the routing algorithm, the Identification (ID) number of the sensor node on the network layer is used to define the network location to distinguish different sensor nodes to achieve data exchange and reliable data transmission or on the other hand, we can also use IPv6 or SDNs without obtaining node ID information. Since this paper mainly studies data transmission and multi-hop routing, this paper mainly adopts the first method to complete data transmission and routing [12][13][14]. ...
With the help of fog computing theory, this paper proposes Cluster Routing Optimized Algorithm of Nonlinear Event Migration Strategy, CR-NEMS. First, the fog node is used for high computing power and control ability to match and schedule sensor nodes to make them evenly distributed to achieve the purpose of network energy balance. Secondly, the intelligent algorithm is adopted to optimize the data transmission link to reduce network delays and improve transmission efficiency. Thirdly, the routing optimization is achieved through the iterative change and update strategy of controllable parameters to improve the global traversal capability of the entire network. Finally, the simulation experiment shows that the algorithm is compatible with other algorithms under the conditions of data transmission in the entire network. Compared with the network delay, network energy and network lifetime, the proposed strategy reduces by 23.49%, 13.22% and 12.17% respectively. It verifies that the algorithm in this paper effectively balances the network energy while solving the routing optimization problem and resource allocation problem in the target area.
... This paper discusses the CBR-RPL technique, which uses a unique drop-aware Objective Function (OF) to arrange nodes into route data. The newly defined OF takes into account both queue occupancy and node transceiver drop rates [24]. The Energy Hole problem, which is common in WSN, drastically affects the lifetime of any established network. ...
The goal of today’s technological era is to make every item smart. Internet of Things (IoT) is a model shift that gives a whole new dimension to the common items and things. Wireless sensor networks, particularly Low-Power and Lossy Networks (LLNs), are essential components of IoT that has a significant influence on daily living. Routing Protocol for Low Power and Lossy Networks (RPL) has become the standard protocol for IoT and LLNs. It is not only used widely but also researched by various groups of people. The extensive use of RPL and its customization has led to demanding research and improvements. There are certain issues in the current RPL mechanism, such as an energy hole, which is a huge issue in the context of IoT. By the initiation of Grid formation across the sensor nodes, which can simplify the cluster formation, the Cluster Head (CH) selection is accomplished using fish swarm optimization (FSO). The performance of the Graph-Grid-based Convolution clustered neural network with fish swarm optimization (GG-Conv_Clus-FSO) in energy optimization of the network is compared with existing state-of-the-art protocols, and GG-Conv_Clus-FSO outperforms the existing approaches, whereby the packet delivery ratio (PDR) is enhanced by 95.14%.
... In many implementations of the RPL, these tables are merged into a single data structure known as the neighbor table [12]. Due to the resource-constrained nature of IoT platforms, the existing memory size does not suffice for storing the routing information for all of the neighbors, and the neighbor table size in IoT nodes is typically limited [19]. This issue could be very challenging in dense and mobile networks, where there are plenty of neighbors in the transmission range of the nodes. ...
Mobile portable embedded devices are becoming an integral part of our daily activities in the vision of Internet of Things. Nevertheless, due to lack of mobility support in the IPv6 Routing Protocol for Low-power and lossy networks (RPL), which is standardized for multi-hop IoT infrastructures, providing reliable communications in terms of Packet Delivery Ratio (PDR) in mobile IoT applications has become significantly challenging. While several studies tried to enhance the adaptability of RPL to network dynamics, their utilized routing metrics have prevented them from establishing long-lasting reliable paths. Furthermore, the stochastic parent replacement policy in the standard version of RPL has intensified this challenge. Aside from this, due to the existing trade-off between reliability and power-efficiency, most of the existing approaches have only concentrated on one of these concerns without paying attention to the other one. To address these issues, this paper introduces ARMOR, a routing mechanism built upon RPL, which employs a novel mobility-aware routing metric, i.e. Time-to-Reside (TTR), and a corresponding parent replacement policy. According to the motion characteristics of the mobile objects, TTR provides an estimation of how long the nodes will be in the transmission range of each other. This enables ARMOR to select nodes, which provide longer connection period and consequently higher reliability. In comparison with the state-of-the-art, while keeping the power consumption constant, ARMOR significantly improves the amount of PDR in the network by up to 2.5x, while it enhances the reliability against the original version of this protocol by up to 4.2x.
