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RPL routing protocol over IoT: A comprehensive survey, recent advances, insights, bibliometric analysis, recommendations, and future directions
Abstract
In the course of time, the Internet of Things (IoT) has attracted significant research interest. However, IoT devices have limited resources available in terms of battery power, processing capacity, memory, bandwidth, etc. In an attempt to provide connectivity and Internet Protocol version 6 (IPv6) support to IoT devices, the IPv6 routing protocol for Low-Power and Lossy Networks (RPL) was officially launched as the standard routing protocol for IoT in 2012. Despite being reputed and used in diverse applications, several recent studies have revealed RPL's drawbacks and limitations. The main objective of this work is to help the IoT research community understand all aspects of RPL. The paper also provides a detailed description of the operation of the RPL protocol. What is more, this work includes novel and thorough examples, thereby gaining practical knowledge of the pros and cons of this protocol. In addition, this paper reviews and summarizes relevant RPL-based protocols and conducts comprehensive comparisons among them from the perspectives of reliability, robustness, energy efficiency, and flexibility. Technically speaking, after studying and reviewing the majority of the proposed RPL solutions, we are ultimately capable, in this work, of highlighting all the challenges faced by IoT researchers while enhancing RPL and providing what is expected to be dealt with professionally. The present work also gives more details about RPL simulation platforms and RPL applications. Not only to this extent, but rather the historical bibliometric analysis of RPL, which shows the trends in the area of research to be focused on, has been professionally analyzed based on RPL challenges over the years 2010 and 2021. To this end, the conclusions and recommendations of this study are presented along with the effective directions for future RPL, and their applicability. As a result, the authors believe that this work will be a valuable reference for all RPL researchers and designers.
Internet of Things (IoT) studies to facilitate human life are increasing day by day. There are more than 100.0000 academic studies related to the IoT in the Web of Science (WoS) database. Therefore, it would be useful to examine the bibliometric performance, conceptual structure and thematic development of IoT. This paper conducts a bibliometric performance analysis using VosViewer and a conceptual structure analysis using SciMat from 2013 to 2022 for IoT. In this context, bibliometric data of 9679 articles were downloaded from the WoS. Bibliometric performance analyses such as changes in the number of publications, and determination of prominent authors and journals were carried out. Finally, scientific mapping analysis was performed using the SciMat. In this way, themes related to the IoT were revealed and a wide-ranging description of the IoT was made. In addition, the relations between the themes and the evolution of these relations were also revealed.
The Internet of Things (IoT) provides a common platform to connect the heterogeneous devices over the internet. Hence, the number of devices connected via the internet and consequently congestion is exponentially increased. Congestion reduces the network performance and negatively affects QoS. RPL (routing protocol for low-power and lossy networks) significantly has responded to IoT routing needs, but controlling congestion and QoS needs have been failed to be considered. Therefore, this paper improved the RPL protocol based on the congestion control and QoS requirements and proposed a protocol called Congestion and QoS-Aware RPL for IoT applications (CQARPL). This protocol selects parents based on multi-metric evaluation, considering the conditions of routes to the root. In addition, it somehow controls the parent selection and the children's acceptance that a balanced DODAG graph is formed. Furthermore, it provides the ability to predict congestion and prevents it from occurring as much as possible. The proposed protocol is implemented by the Cooja simulator and evaluated with different scenarios compared to CLRPL and RPL. The simulation results showed that CQARPL maintains the quality of transmissions and controls congestion in IoT.
RPL (IPv6 Routing Protocol for Low power and Lossy Networks) is the pseudo-standard routing protocol for Internet of Things. RPL employs a customizable objective function to optimize the routing. The default objective functions used in RPL are i) OF0 (Objective Function Zero) and ii) MRHOF (Minimum Rank with Hysteresis Objective Function). The OF0 is based on the routing metric hop count, whereas the MRHOF uses the ETX metric. They both do not measure the actual link quality. The link quality is directly related to the reliability of the network. The quality of the link can be estimated through methods that are both hardware and software based. The software-based methods are easy to implement and to ensure the reliability of the network. There are different software-based link quality estimation methods; the prominent methods among them are ETX and Link Quality Level (LQL). The ETX is a method of approximation of the transmitted packets. It uses probe packets to predict the expected transmission count, and it may not accurately reflect the link quality. The proposed Link Quality-Based Objective Function (LQBOF) makes use of the LQL metric which provides better link estimation values than the ETX method. The proposed method intends to provide a more reliable routing based on the link quality. The LQL is estimated through a metric called Packet Reception Rate (PRR). The LQL is calculated and ranked as values from 1 to 7, reflecting the best and worst link quality, respectively. The estimated LQL value is linked with the default ETX in computing the best path. This method intends to increase the reliability of the network. The reliability of the objective function is evaluated with the performance metrics packet delivery ratio, power consumption, throughput, convergence time, control traffic overhead and hop count.
IPv6 routing protocol for low-power and lossy networks (RPL) has been developed as a routing agent in low-power and lossy networks (LLN), where nodes’ resource constraint nature is challenging. This protocol operates at the network layer and can create routing and optimally distribute routing information between nodes. RPL is a low-power, high-throughput IPv6 routing protocol that uses distance vectors. Each sensor-to-wire network router has a collection of fixed parents and a preferred parent on the path to the Destination-oriented directed acyclic graph (DODAG) graph’s root in steady-state. Each router part of the graph sends DODAG information object (DIO) control messages and specifies its rank within the graph, indicating its position within the network relative to the root. When a node receives a DIO message, it determines its network rank, which must be higher than all its parents’ rank, and then continues sending DIO messages using the trickle timer. As a result, DODAG begins at the root and eventually extends to encompass the whole network. This paper is the first review to study intrusion detection systems in the RPL protocol based on machine learning (ML) techniques to the best of our knowledge. The complexity of the new attack models identified for RPL and the efficiency of ML in intelligent and collaborative threats detection, and the issues of deploying ML in challenging LLN environments underscore the importance of research in this area. The analysis is done using research sources of “Google Scholar,” “Crossref,” “Scopus,” and “Web of Science” resources. The evaluations are assessed for studies from 2016 to 2021. The results are illustrated with tables and figures.
The Internet of Things (IoT) aims to transform everyday physical objects into an interconnected ecosystem with digital data accessible anywhere and anytime. "Things" in IoT are embedded with sensing, processing and actuating capabilities and cooperate in providing smart and innovative services autonomously. The rapid spread of IoT services arises different security vulnerabilities that need to be carefully addressed. Several emerging and promising technologies and techniques are introduced to improve the security of IoT. This paper aims to provide an up-to-date vision of the current research topics related to IoT security. Initially, we introduce common elements and protocols of IoT to demystify the origins of threats in IoT. Then, we propose a taxonomy of IoT attacks and analyze the security vulnerabilities of IoT at different layers. Subsequently, we povide a comparison of recent security schemes based on emerging solutions including fog computing, edge computing, software defined networking (SDN), blockchain, lightweight cryptography, homomorphic and searchable encryption, and machine learning. Finally, security challenges are discussed and future directions are highlighted for future interested researchers.
The rapid growth in the Internet of Things (IoTs)
has change our life to be more intelligent and smart,
the development in the Wireless Sensors Networks
(WSNs), besides the wide use of the embedded devices
in different area like industry, home automation,
transport, agriculture and health care, which was led
the Routing Over Low-power and Lossy-network
(ROLL) working group to introduce the IPv6 Routing
Protocol for Low-Power and Lossy Networks (RPL),
therein the RPL nodes have organized topology as a
Directed Acyclic Graph (DAG) and terminated at one
root to form the Destination Oriented DAGs
(DODAGs). In this paper by using InstantContiki3.0
and CoojaGUI we analyze the DODAG formations,
the RPL control messages that are send downward
and upward routes to construct and maintain
DODAG and the Rank computation by Objective
Function (OF) for inconsistency and loop detection,
also we evaluate the performance of the RPL based
on the Expected Transmission Count (ETX) OF that
enable RPL to select and optimize routes within RPL
instance, as well as we evaluate the following metrics:
The ETX Reliability Object (ETX), Radio Duty Cycle
(RDC), energy consumption, the received packets by
the motes and neighbor count. The simulation results
show that the RPL control messages flow in consistent
manner, the DODAG root able to connect to all of the
neighbor motes, also Rank illustration shows no loops
and DODAG topology consistent, as well as the ETX
can essentially take control over DODAG formations
and it has an effects in the RDC ratio, furthermore
most of the motes show reasonable low power
consumption, also the motes show acceptable number
of the received packets.
Energy conservation is a significant task in the Internet of Things (IoT) because IoT involves highly resource-constrained devices. Clustering is an effective technique for saving energy by reducing duplicate data. In a clustering protocol, the selection of a cluster head (CH) plays a key role in prolonging the lifetime of a network. However, most cluster-based protocols, including routing protocols for low-power and lossy networks (RPLs), have used fuzzy logic and probabilistic approaches to select the CH node. Consequently, early battery depletion is produced near the sink. To overcome this issue, a lion optimization algorithm (LOA) for selecting CH in RPL is proposed in this study. LOA-RPL comprises three processes: cluster formation, CH selection, and route establishment. A cluster is formed using the Euclidean distance. CH selection is performed using LOA. Route establishment is implemented using residual energy information. An extensive simulation is conducted in the network simulator ns-3 on various parameters, such as network lifetime, power consumption, packet delivery ratio (PDR), and throughput. The performance of LOA-RPL is also compared with those of RPL, fuzzy rule-based energy-efficient clustering and immune-inspired routing (FEEC-IIR), and the routing scheme for IoT that uses shuffled frog-leaping optimization algorithm (RISA-RPL). The performance evaluation metrics used in this study are network lifetime, power consumption, PDR, and throughput. The proposed LOA-RPL increases network lifetime by 20% and PDR by 5%-10% compared with RPL, FEEC-IIR, and RISA-RPL. LOA-RPL is also highly energy-efficient compared with other similar routing protocols.
IoT supports a spectrum of applications, each of which has certain specific requirements. For instance, mission critical applications cannot tolerate delay in data transmission however simple monitoring applications are delay tolerant. The lifetime and performance of IoT sensor networks depend on the metric/constraint (ETX, Energy etc.) selected for routing path, data size and quality of service required. The selection of metric /constraint dependent Objective function (OF) in RPL provides a range of solutions for IoT applications. However, state-of-art solutions mainly focus on single metric/constraint resulting in poor performance of protocol. To understand the protocol behavior for different metrics (single and combined) a complete evaluation of RPL over important performance parameters is needed. Researchers have proposed several routing algorithms which are application specific and do not define a generic parent selection process. We require a structured algorithm for Minimum Rank Hysteresis Objective Function (MRHOF) applicable to majority of IoT applications. In this paper we have proposed a generalized algorithm for MRHOF along with routing path cost evaluation which defines the complete parent selection process. Further, comparative analysis of different RPL OFs has been done to identify suitable OF for enhanced RPL performance. Performance evaluation parameters have been extended to PDR, power consumption, hop count, average ETX, Rt metric and inter packet time, for different network size and link quality. Results are obtained using Cooja simulator of Contiki. RPL with combined metric provide 24% higher PDR, 28% lower power consumption and 39% lower inter-packet time as compared to RPL with single metric.
Low-Power and Lossy networks are an integral part of the IoT ecosystem. These networks are defined by their shared features such as having limited resources and high occurrence of packet loss. A routing protocol for such networks called Routing Protocol for Low-Power and Lossy Networks (RPL) was proposed in 2012. Even though RPL is now standardized and well-accepted by the community, it still has areas to be improved such as load balancing, stability, and support for mobility. This study focuses particularly on approaches proposed for the load balancing problem in RPL. In the literature, many researchers aimed to tackle this problem by creating different routing metrics that handle different objectives. This review makes a thorough assessment of these works, their strengths and shortcomings, and provides future directions on the issue.
The Internet of Things (IoT) is the network of physical objects or things embedded with electronics, software, sensors, and network connectivity, which enables these objects to collect and exchange data. The Internet of Things allows objects to be sensed and controlled remotely across existing network infrastructure. The IoT is enabled by the latest developments in RFID, smart sensors, communication technologies, and Internet protocols. Cooja Simulator is a network simulator specifically designed for Wireless Sensor Networks. A simulated Contiki Mote in COOJA [1] is an actual compiled and executing Contiki system. The system is controlled and analyzed by COOJA. This is performed by compiling Contiki for the native platform as a shared library, and loading the library into Java using Java Native Interfaces (JNI). Several different Contiki libraries can be compiled and loaded in the same COOJA simulation, representing different kinds of sensor nodes (heterogeneous networks). COOJA controls and analyzes a Contiki system via a few functions. For instance, the simulator informs the Contiki system to handle an event, or fetches the entire Contiki system memory for analysis. This approach gives the simulator full control of simulated systems. Unfortunately, using JNI also has some annoying side-effects. The most significant is the dependency on external tools such as compilers and linkers and their run-time arguments. COOJA was originally developed for Cygwin/Windows and Linux platform, but has later been ported to MacOS. Java version 1.6 or later is required to run COOJA. We recommend using the latest version from Sun. In addition, the build tool ant is also required for building COOJA [12]. Contiki is an open source operating system for the Internet of Things. Contiki connects tiny low-cost, low-power microcontrollers to the Internet. Contiki is a powerful toolbox for building complex wireless systems.
The advent of various wireless technologies has paved the way for the realization of new infrastructures and applications for smart cities. Wireless Sensor Networks (WSNs) are one of the most important among these technologies. WSNs are widely used in various applications in our daily lives. Due to their cost effectiveness and rapid deployment, WSNs can be used for securing smart cities by providing remote monitoring and sensing for many critical scenarios including hostile environments, battlefields, or areas subject to natural disasters such as earthquakes, volcano eruptions, and floods or to large-scale accidents such as nuclear plants explosions or chemical plumes. The purpose of this paper is to propose a new framework where WSNs are adopted for remote sensing and monitoring in smart city applications. We propose using Unmanned Aerial Vehicles to act as a data mule to offload the sensor nodes and transfer the monitoring data securely to the remote control center for further analysis and decision making. Furthermore, the paper provides insight about implementation challenges in the realization of the proposed framework. In addition, the paper provides an experimental evaluation of the proposed design in outdoor environments, in the presence of different types of obstacles, common to typical outdoor fields. The experimental evaluation revealed several inconsistencies between the performance metrics advertised in the hardware-specific data-sheets. In particular, we found mismatches between the advertised coverage distance and signal strength with our experimental measurements. Therefore, it is crucial that network designers and developers conduct field tests and device performance assessment before designing and implementing the WSN for application in a real field setting.
RPL, the standard IPv6 routing protocol for low-power and lossy networks in the emerging Internet of things (IoT), is designed mainly for efficient many-to-one data collection scenarios where the majority of the traffic flows from embedded devices to a gateway. Although RPL does support root-to-node downwards routing and peer-to-peer (P2P) communication, its P2P performance is inefficient and unsatisfactory due to excessively high churn and bottlenecks in the P2P path. However, P2P routing is important for machine-to-machine communication where nodes in IoT applications communicate with one another and control devices beyond simply collecting data. In this work, we propose a neighbor-graph-based RPL (NG-RPL) that significantly improves P2P routing performance. By including additional routing information when a packet passes through the root node for the first time in a P2P communication, NG-RPL finds efficient P2P routes opportunistically, when available, without significant overhead. We implement NG-RPL in Contiki-NG and evaluate its performance through extensive Cooja simulations. Results show that NG-RPL reduces routing churn, which improves packet reception ratio, round-trip time, and energy usage of P2P communication compared to standard RPL.
In this paper, we consider non-time slotted
cognitive radio ad-hoc networks in order to propose a routing
protocol without a common control channel, thereby adhering
to practicality. This is performed using multicast and unicast
transmission of the control packets. The performance of this
protocol is studied and compared with a quite relevant and
recent protocol, called Probabilistic and Deterministic Path
Selection (PDPS), using a special simulator, which is built in
Java language and developed upon PDPS’s simulator. The
PDPS protocol creates two paths between the source and
destination while using all the channels in the network.
Interestingly, their results are promising in terms of
throughput. On the other hand, our protocol builds as many
paths as possible between the source and destination. Besides, in
our protocol, we use all the channels in the network. The
performance metric considered is the throughput whereas our
results are even better than those of PDPS protocol.
The Internet of things (IoT) is a concept that has gained traction over the last decade. IoT networks have evolved around the wireless sensor network (WSN), and the following research looks at relevant IoT concepts and the different security issues that occur specifically at the network layer. This analysis is performed using a structured literature review (SLR). This form of bibliographic review has been a trend in recent years. Its strength is the performance of a bibliometric analysis that allows studying both trends in the line of research that you want to address and the relevant authors. This SLR reviews 53 proposals between 2011 and 2020, whose contribution is to mitigate attacks in the RPL (Routing Protocol for Low-Power and Lossy Networks) protocol. The revised proposals emerged after selecting keywords and databases in which to apply the search. Initially, approximately 380 research works appeared, for which it was necessary to continue using filters to refine the proposals to be included. After reading titles and abstracts, 53 papers were finally selected. In addition to analyzing the attacks mitigated in the RPL protocol, it is intended to identify the trend by which these attacks are reduced, as a result of the review, nine attacks have been found: rank, blackhole, selective forwarding, wormhole, DODAG (Destination-Oriented Directed Acyclic Graph) version number, DAO (Destination Advertisement Object) inconsistency, DIO (DODAG Information Object) suppression, Sybil, and sinkhole. Each of the 53 proposals analyzed in this review has an associated mitigation strategy, these strategies have been categorized into four groups, based on authentication or cryptography, based on network monitoring, based on secure parent node selection and other. According to the results, the authors’ primary mitigation strategy is based on network monitoring, with 30%. This review also identifies the principal authors and countries that need the development of this line of research.
For the sake of fulfilling the ever-increasing demands on the Internet of Things (IoT) applications, researchers are implementing Cognitive Radio (CR) technology in Ad-Hoc Networks (AHNs). Moreover, In-Band Full-Duplex (IBFD) technology in CRAHNs is gaining scholars' interests recently. Hence, we are considering non-time-slotted IBFD-CRAHNs to clear up the reactivation failure and frequent hand-off problems confronting Primary Users (PUs) and Secondary Users (SUs), respectively, in Half-Duplex (HD) CRAHNs. We propose two HD-CRAHN routing protocols without a common control channel intended for practicality. This is accomplished by adopting multi-and unicast transmissions in the Route Request Packets (RRQPs) delivery. The first protocol is tested with data transmission in HD mode. However, the second routing protocol adopts a channel assignment technique proposed in the literature for FD communications; thus, we apply FD data transmission on it. Additionally, this paper offers an IBFD-based CRAHN routing protocol that broadcasts the RRQP over the channels that have SUs sensing them or even transmitting over them. This is possible because of two patents that allow wireless nodes to receive (transmit) in a sweeping manner while transmitting to (receiving from) another node. The three protocols' performance is studied and compared with the most pertinent and recent protocol named Probabilistic and Deterministic Path Selection (PDPS) using an exclusive simulator, built-in Java language, over the simulator used in PDPS experiments. As far as the throughput performance metric is concerned, our simulation results show noticeable and undeniable improvements over the PDPS protocol.
Multi-channel non-time-slotted cognitive radio ad hoc networks are attractive to researchers nowadays; because they utilize the spectrum efficiently and represent a useful network design for Internet of Things (IoT) applications. From this point, a simulator that mimics these networks is developed using Java language. Further, researchers have proven that many problems facing these networks can be solved by using Full Duplex (FD) nodes. Thus, the proposed simulator is extended to support FD cognitive radio nodes. Each one of these nodes is allowed to receive in a sweeping pattern from various nodes, while transmitting to another node. In an alternative scenario, the node can transmit in a sweeping pattern to various nodes while receiving from one node in a specific direction. Both scenarios are adopted in the route request packet broadcasting phase. However, in the route reply packet delivery, the nodes are allowed to operate in FD transmit and sense or in FD transmit and receive modes. Interestingly, the simulator is tested using FD protocol, also introduced in this paper, that can be useful for IoT applications. Besides the proposed protocol is compared with very recent and close related routing protocol called Probabilistic and Deterministic Path Selection (PDPS). The results are logical; as they are compatible with the theoretical expectations, and the FD protocol surpassed PDPS by almost doubling the throughput.
RPL (IPv6 routing protocol for low power and lossy networks) proposed by the IETF (Internet Engineering Task Force) ROLL (routing over low-power and lossy networks) working group is a de facto standard routing protocol for IoT environments. Since the standardization was proposed, RPL has been extensively improved for diverse application scenarios and environments. Congestion control is one of the most important reasons why RPL has been improved. In an LLN (low power and lossy network), congestion may even lead to network lifetime reduction. In resource-constrained networks where end-to-end congestion control is not feasible, RPL should play a more crucial role in congestion control. In this survey, we review the RPL schemes proposed for congestion control and load-balancing and discuss future research directions.
With the widespread use of IoT applications and the increasing trend in the number of connected smart devices, the concept of routing has become very challenging. In this regard, the IPv6 Routing Protocol for Low-power and Lossy Networks (PRL) was standardized to be adopted in IoT networks. Nevertheless, while mobile IoT domains have gained significant popularity in recent years, since RPL was fundamentally designed for stationary IoT applications, it could not well adjust with the dynamic fluctuations in mobile applications. While there have been a number of studies on tuning RPL for mobile IoT applications, but still there is a high demand for more efforts to reach a standard version of this protocol for such applications. Accordingly, in this survey, we try to conduct a precise and comprehensive experimental study on the impact of various mobility models on the performance of a mobility-aware RPL to help this process. In this regard, a complete and scrutinized survey of the mobility models has been presented to be able to fairly justify and compare the outcome results. A significant set of evaluations has been conducted via precise IoT simulation tools to monitor and compare the performance of the network and its IoT devices in mobile RPL-based IoT applications under the presence of different mobility models from different perspectives including power consumption, reliability, latency, and control packet overhead. This will pave the way for researchers in both academia and industry to be able to compare the impact of various mobility models on the functionality of RPL, and consequently to design and implement application-specific and even a standard version of this protocol, which is capable of being employed in mobile IoT applications.
Energy consumption is a major challenge in IoT devices, which was aimed to be improved by employing energy-efficient Objective Functions (OF) in the structure of RPL routing protocol. Meanwhile, the majority of the existing OFs mainly perform the parent selection based on the gathered information from the routing layer. Nevertheless, based on our investigations, there exists a series of transmission operations in the MAC layer, which significantly affects the energy consumption in IoT devices. Therefore, in this paper we propose ELITE, an energy-efficient cross-layer OF, which introduces a novel routing metric, called Strobe per Packet Ratio (SPR). SPR indicates the number of transmitted strobes per packet due to Radio Duty Cycling (RDC) policies in the MAC layer. This newly defined metric, which has been designed to be coupled with asynchronous MAC protocols, could be differentiated node by node and based on the existing relative phase shift between the communicating nodes. In this regard, ELITE tries to select a path, which imposes less number of strobe transmissions to its nodes. According to the evaluation results, while ELITE could reduce the average amount of required strobes per packet by up to 25%, it can significantly improve the average amount of consumed energy in an IoT node by up to 39% compared to its counterpart OFs.
The main objective of Internet of Things (IoT) is to connect almost all the devices anywhere and everywhere in the world. IoT network is heterogeneous in nature, hence routing the data packets in this network is a big challenge. Routing Protocol for Low Power Lossy Network (RPL), has been designed by Internet Engineering Task Force (IETF) for such type of network. The existing design of RPL Objective Function (OF) is insufficient to cover all the issues of IoT applications. In this paper, the proposed OFs designs using various routing metrics are used to enhance the performance of the IoT applications. The analysis for various scenarios for these designs shows that only traditional hop and Expected Transmission Count (ETX) routing parameters will not fit for the smart applications need. The routing metric selection according to the application requirement is the principal idea of the proposed design. Three metrics ETX, Content and Energy, single and combination with each other are used to enhance the design of objective function of RPL for IoT applications. The enhanced triggering technique is added in these designs for the improvement of RPL. This technique will eliminate the cumulative effect of the short-listen problem of default trickle timer. The result analysis done using Cooja simulator along with Contiki Operating System (OS) states that, all the designs are performing well in one or other manner than the traditional OF. Energy combined with Content (EC) and aggregation with Enhanced timer (EC_En_Timer) design gives better result for Packet Delivery Ratio (PDR) and Latency Delay (LD) as compared to default OF design. Residual Energy (RE) combined with ETX (EE) and conjunction with Enhanced timer (EE_En_Timer) design works well for energy consumption. Overhead is very less in RE and ETX design. Conversion time is reduced by almost 50% in an En_Timer design. Higher PDR and low delay values of EC and EC_En_Timer design encourages its use in health monitoring application where reliability is essential. Low energy consumption results of RE, EE and EE_En_Timer designs are comfortable for forest monitoring application, as energy is a crucial aspect. This comparative result outcome will help to fulfill the IoT application requirements.
Sustainable cities are widely adopting the standards of the Internet of Things (IoT) in almost every domain e.g. Smart Grids (SG) to provide services to a sustainable community. It enables two-way communication to manage the energy resources, where routing protocol has a significant role in communication. The diversification of IoT networks arises many challenges for the Routing Protocol for Low Power and Lossy Networks (RPL). The dynamic and lossy environment is one of the key challenges in various IoT networks, specifically SG. RPL does not able to adjust its link metric efficiently against the dynamic and lossy environment, which have a great impact on the performance metrics. To address this issue, we have introduced cognition in RPL by integrating learning automata with the Objective Function (LA-OF). Learning Automata (LA) is applied to Expected Transmission Count (ETX) to tune it according to the environment. LA learns through interacting with the environment and yields the best ETX values, afterwards the environment is monitored to trace down the instability in the environment. The proposed LA-OF is compared with standardized techniques MRHOF and OF0. The simulation results show a significant improvement with overall 7.04% in PRR, 17.52% in energy consumption, and 18.72% in overhead.
Routing Protocol for Low power lossy network (RPL) is emerged to evade the energy issues in the Internet of Things (IoT) network. Although, RPL noticeably satisfies the requirement of the IoT network, still there exist certain open issues to resolve. This paper addresses the problem of routing overhead, packet losses and load imbalance in RPL based IoT network. These downsides are solved using the proposed Dual Context‐based Routing and Load Balancing in RPL based Network (DCRL‐RPL). Primarily, we implement the grid construction where the network area is split into a different level of the unequal grid. The ranking based Grid Selection process is executed to select the optimal grid head node in each grid. The grid head node in the network schedules its member node using the Reputation based Scheduling method. The elected grid head classifies the data received from its member using Adam Deep Neural Network (ADNN) to provide better routing performance. Here, the sensitive and non‐sensitive data are considered as context for objective function selection. At last, the efficacy of the DCRL‐RPL is analyzed using the Network Simulator 3.26 (NS3) tool. From comprehensive validation results, we show that DCRL‐RPL acquires better results.
Internet of things (IoT) proposes the use of devices with low energy capacity, processing, and memory power for a range of applications such as environmental monitoring and smart health. Such devices usually have sensing and wireless communication capabilities. Low power and lossy networks on mobile devices are a common type of wireless network in IoT applications. This article proposes the mobility aware RPL (MARPL), which is an extension of the IPv6 routing protocol for low‐power and lossy network (RPL) in order to enhance its performance in networks with mobile nodes. The mobility of nodes increases packet loss in the canonical RPL protocol. The MARPL mobility mechanism adopts a crosslayer approach. The network layer uses signal strength measurements from the media access layer to calculate a node's variability neighborhood. Performance evaluation results obtained by the Cooja simulator confirm the effectiveness of MARPL regarding link disconnection prevention, packet delivery rate, low overhead, and energy consumption when compared with other protocols. The Internet of things (IoT) is a concept that aims to include wireless connectivity on everyday devices in order to enable many forms of smart applications.
Recently, IoT has been massively applied in different areas of human life. Meanwhile, in many of the IoT applications, e.g., the remote patient health-care monitoring systems, the reliability of communications, and the consumed energy in IoT devices, which are mostly battery-operated, are very challenging. Since IoT devices are typically operated in lossy environments, providing a reliable transmission for the packets imposes a noticeable amount of energy consumption. In addition, the run-time movement of the IoT devices in mobile networks further intensifies these issues. Therefore, the applied policies in the IPv6 RPL as the standard routing mechanism in IoT networks, play an important role in providing a reliable and energy-efficient packet delivery. Nevertheless, RPL is significantly suffering from low reliability in mobile applications due to the existence of outdated parents in the limited neighbor table of the moving objects. Hence, in this study, we propose REFER; a mobility-aware version of RPL, which provides reliable and energy-efficient communication between IoT devices with utilizing a new neighbor placement policy based on a leasing time of the parents along with considering various node/link metrics for its path selections in mobile situations. Based on our evaluations, which have been conducted in different network configurations and under different mobility models, while REFER has enhanced the amount of energy consumption in the nodes, it is able to improve the reliability of the communications by at least 2.2x compared with its counterpart.
Routing Protocol for Low-Power and Lossy Networks (RPL) is a standard routing protocol for the Low Power and Lossy Networks (LLNs). It is a part of the IPv6 over Low-Power Wireless Personal Area Network (6LoWPAN) protocol stack. Features such as energy-efficient mechanisms and availability of the secure modes of operations make RPL suitable for the constrained Internet of Things (IoT) devices. Hence, the majority of IoT applications rely on RPL for data communication. However, routing security in RPL-based IoT networks is a significant concern, motivating us to study and analyze routing attacks and suggested countermeasures against them. To this end, we provide a comprehensive survey on the state-of-the-art security threats and their corresponding countermeasures in RPL-based IoT networks. Based on our study, we propose a novel classification scheme that uses a mapping between RPL attacks and their countermeasure techniques to the RPL control messages used to develop these techniques. Furthermore, we provide an in-depth statistical analysis that includes analysis of routing attacks through the RPL control messages, distribution of various mitigation techniques as per the method used, RPL control messages involved in the mitigation techniques, and details of the tools used by multiple researchers. In the end, we highlight some open challenges and future research opportunities on this topic. We believe that this survey will be beneficial to researchers and practitioners working in the area of RPL security.
RPL (Routing Protocol for Low-Power and Lossy Networks) is a crucial and widely accepted routing protocol of the Internet of Things (IoT). RPL constructs similar to a tree structure for the data routing. For efficient routing, RPL offers a different mode of operations for effectively satisfying the different applications. We are considering several approaches and parameters, including other factors in this paper that contribute to designing the hybrid mode of operations. This paper provides a comprehensive and systematic survey of various hybrid modes of operations for RPL. We outline the challenges, methodologies in the pseudocode format, taxonomy and subsequently analyze all the possible format properties with different network conditions.
The indispensable part of IoT is the Low-power and Lossy Network (LLN), which is required to connect plenty of resource-constrained (e.g., power and memory) wireless devices. Interestingly, the IPv6 Routing Protocol for LLNs (i.e., RPL), which is the standard routing protocol for IoT, relies primarily on constructing a destination-oriented directed acyclic graph governed by a variety of routing metrics that help in choosing the Objective Function (OF), which is liable for selecting the best preferred parent of each node which in turn gets involved in the route establishment towards the destination. In fact, establishing an OF based on a single metric, as the majority of research considers, has flaws or drawbacks, as it only benefits a few IoT applications. To put it another way, the network lifetime is improved for a few IoT apps but degraded for the majority. In this article, we address not only the limitation of using a single metric, but also the limitations of those works employed a composite metric by putting forward a cross-layer design and accordingly developing a fuzzy logic system that brings together four input metrics, namely, hop count, energy consumption, latency, and received signal strength indicator as a new OF, abbreviated as FL-HELR-OF. The simulation findings, acquired by the Cooja simulator, prove the effectiveness of our new OF, which particularly outperforms other existing studies concerning the packet delivery ratio, control message overhead, latency, energy consumption, and average hop count.
The intricate features and autonomous configuration of Routing Protocol for Low-power and Lossy Networks (RPL) make it challenging to provide a key management solution and deploy it on constrained resources sensing systems. So far, various types of attacks, such as rank attacks, have been identified on this protocol, so it is necessary to take appropriate countermeasures to mitigate and isolate their effects. This paper proposes the Moth-Flame Optimization-based secure scheme for RPL (MFO-RPL) to optimize the routing process and rank attack detection in RPL. MFO-RPL uses the petal algorithm to select the next-hop nodes and form the optimal path between the source and root in the graph. Then, rank attacks in RPL are detected using the Moth-Flame algorithm to prevent malicious nodes from being selected as the preferred parent. Simulation findings under different scenarios revealed that MFO-RPL has fewer lost packets, rank switching, convergence time, and attacks than comparative schemes.
Internet of Things (IoT) includes numerous sensing nodes that constitute a large scale-free network. Optimizing the network topology to increase resistance against malicious attacks is a complex problem, especially on 3-dimension (3D) topological deployment. Heuristic algorithms, particularly genetic algorithms, can effectively cope with such problems. However, conventional genetic algorithms are prone to falling into premature convergence owing to the lack of global search ability caused by the loss of population diversity during evolution. Although this can be alleviated by increasing population size, the additional computational overhead will be incurred. Moreover, after crossover and mutation operations, individual changes in the population are mixed, and loss of optimal individuals may occur, which will slow down the population's evolution. Therefore, we combine the population state with the evolutionary process and propose an Adaptive Robustness Evolution Algorithm (AREA) with self-competition for scale-free IoT topologies. In AREA, the crossover and mutation operations are dynamically adjusted according to population diversity to ensure global search ability. A self-competitive mechanism is used to ensure convergence. We construct a 3D IoT topology that is optimized by AREA. The simulation results demonstrate that AREA is more effective in improving the robustness of scale-free IoT networks than several existing methods.
Internet of Things technology has given rise to Smart Cities, Smart Health, Smart Transport Logistics, Smart Production and Supply chain management, Smart Home and the list is long. Smart city deployments are gaining momentum around the world. Security and Reliability of IoT infrastructure in smart cities remain important challenges. In this regard, ROLL-WG has standardised RPL for urban environment (RFC 5548). RPL is designed to address the needs of constrained IoT environment. RPL uses Objective Functions (ETX & Hop Count) to optimise parent selection as well as route selection. Newer Objective Functions for IoT applications are suggested by researchers to manage network and security. In this paper, we propose Multi DODAG’s in RPL for improved performance and reliable smart city applications.We have tested the proposed model in Contiki OS with Cooja simulator. Proposed model provides improved efficiency in convergence time, Packet Delivery Ratio, Control Traffic Overhead, Power consumption. For reliability, node participation is evaluated. Hence, Multi DODAG’s in RPLcan better optimize constrained resources and provide reliability to the network.
The possibility of Internet of Things (IoT) is that a large number of live items (e.g., apparatuses) in the network are available, detected, and interconnected. In any case, the performance of IoT networks may be limited due to several impairments, most importantly, the energy-constrained IoT nodes. In fact, this limitation opens the door to many researchers where using network clustering has proven to be efficient energy saving mechanism. To the best of our knowledge, there are no prior research, in the field of multi-hop clustered IoT networks, which addressed the energy-constrained IoT nodes problem along with the delay in receiving data messages from devices, located far away from the remote users (or control center), in timely basis. Practically, it is significantly challenging to contemplate and clarify this issue. Consequently, in this paper, we make major amendments on the prior work, Improved Energy and Distance Based CH Selection with Balanced Objective Function (IEDB-CHS-BOF), and particularly propose a multi-hop routing (MR) protocol in which the IoT network is divided into a number of virtual sections with lengths held below the cross-over communication distance, thereby ensuring minimal energy depletion. Over those virtual sections, efficient forwarder and cluster head selection algorithms are further proposed. Interestingly, we propose a novel delay-, power-, and interference-aware time slot allocation model in which Time Division Multiple Access (TDMA) and Direct Sequence Spread Spectrum (DSSS) MAC protocols are operated. Furthermore, it is a good representation of the above-mentioned proposals. As a result, our protocols are referred to as MR-IEDB-CHS-TDMA and MR-IEDB-CHS-DSSS, respectively. To this end, numerous simulations have been conducted for evaluating the performance of the proposed protocols in the perspective of IoT network lifetime. In addition, sufficient comparisons have been conducted with the existing state-of-the-art protocols. In overall, the MR-IEDB-CHS-TDMA protocol keeps the IoT network functioning the longest.
The Internet of Things (IoT) has been extensively deployed in smart cities. However, with the expanding scale of networking, the failure of some nodes in the network severely affects the communication capacity of IoT applications. Therefore, researchers pay attention to improving communication capacity caused by network failures for applications that require high quality of services (QoS). Furthermore, the robustness of network topology is an important metric to measure the network communication capacity and the ability to resist the cyber-attacks induced by some failed nodes. While some algorithms have been proposed to enhance the robustness of IoT topologies, they are characterized by large computation overhead, and lacking a lightweight topology optimization model. To address this problem, we first propose a novel robustness optimization using evolution learning (ROEL) with a neural network. ROEL dynamically optimizes the IoT topology and intelligently prospects the robust degree in the process of evolutionary optimization. The experimental results demonstrate that ROEL can represent the evolutionary process of IoT topologies, and the prediction accuracy of network robustness is satisfactory with a small error ratio. Our algorithm has a better tolerance capacity in terms of resistance to random attacks and malicious attacks compared with other algorithms.
For Internet of Things (IoT), unmanned aerial vehicles (UAVs) can be deployed at a large scale to collect and control a wide range of terminals. To enable such applications, a routing protocol is required to balance the energy load as much as possible while ensuring communication quality, as well as support emergency communications between UAVs. To this end, this article proposes an energy efficient routing protocol based on RPL for UAVs in IoT applications. This novel protocol supports two transmission modes, one is a large-scale information aggregation network, and the other is urgent point-to-point communication between UAVs. These two modes jointly organize the data transmission between nodes to meet the demand of UAV applications in IoT. As an important feature of UAV networks, a metric for energy load balance is proposed in the protocol to optimize the network performances. Simulation results show that the proposed protocol has better performance than the existing routing protocols in IoT applications.
The routing protocol RPL for low power and lossy networks (LLNs) suffers from reduced reliability, increase in control overhead, longer latency and higher energy utilization on experiencing high node density, link or node failures in the network. This paper aims to elaborately study the behaviour of RPL’s expected transmissions count (ETX) based path selection for lengthier routes and the impact of node density and link or node failures on them. Our study finds that the path selection along long routes suffers due to the lack of decisive information on the neighbourhood links. As an alternate, a laplacian energy based path selection is proposed to enrich RPL by bringing in additional neighbourhood connection information into the path selection process to provide stable paths. Laplacian energy drop, a two-walk neighbourhood connectivity measure that is incorporated in L-RPL helps a node to pick the most resilient path. By simulation and testbed experiment results, it is shown that the proposed L-RPL improves path selection and reduces control overhead (29.05% and 39.68% reduction in (Destination Advertisement Object) control data when 9% of nodes fail and during normal conditions respectively), latency and also improves energy utilization.
Nowadays, the Internet of Things (IoT) research domain attracts the researchers, due to its extensive collection of applications and ease in deploying in several domains of real life, particularly for environments that are considered critical such as E-health, smart homes, and smart cities. Things in smart cities are intractable via the Internet. These things are naturally deployed in a distributed environment wirelessly. They become vulnerable to the diverse security attacks that can adversely influence their proper functionalities at any time. The stated problem severity even becomes higher when they are deployed in smart cities. In addition, it is very likely to compromise data while transferring from one source to another until reaching the destination during data routing. Existing Routing Protocols for Low Power and Lossy Networks (RPL) are considered lightweight and secure routing protocols for IoT devices, which offer a slight safeguard against innumerable forms of RPL routing attacks. Based on the nature of the IoT network, being resource constraints, the conventional routing techniques do not suit them at all. The IoT routing security is therefore, a challenging task. This review aims to elaborate on the current research literature, opportunities and research gaps of secure RPL routing protocols. Where mainly considering the Rank and Version number attacks types for IoT applications. Further, the review extravagant the need for a new secure RPL protocol to address the security issues of IoT applications for smart cities particularly based on available literature.