Routing Protocol For Low-Power Research Articles

Trust-aware and cooperative routing protocol for IoT security

The resource-constrained nature of IoT objects makes the Routing Protocol for Low-power and Lossy Networks (RPL) vulnerable to several attacks. Although RPL specification provides encryption protection to control messages, RPL is still vulnerable to internal attackers and selfish behaviours. To address the lack of robust security mechanisms in RPL, we design a new Metric-based RPL Trustworthiness Scheme (MRTS) that introduces trust evaluation for secure routing topology construction. Extensive simulations show that MRTS is efficient in terms of packet delivery ratio, energy consumption, nodes’ rank changes, and throughput. In addition, a mathematical modelling analysis shows that MRTS meets the requirements of consistency, optimality, and loop-freeness and that the proposed trust-based routing metric has the isotonicity and monotonicity properties required for a routing protocol. By using game theory concepts, we formally describe MRTS as a strategy for the iterated Prisoner’s Dilemma and demonstrate its cooperation enforcement characteristic. Both mathematical analysis and evolutionary simulation results show clearly that MRTS, as a strategy, is an efficient approach in promoting the stability and the evolution of the Internet of Things network.

Multiple intrusion detection in RPL based networks

<span lang="EN-US">Routing Protocol for Low Power and Lossy Networks based networks consists of large number of tiny sensor nodes with limited resources. These nodes are directly connected to the Internet through the border router. Hence these nodes are susceptible to different types of attacks. The possible attacks are rank attack, selective forwarding, worm hole and Denial of service attack. These attacks can be effectively identified by intrusion detection system model. The paper focuses on identification of multiple intrusions by considering the network size as 10, 40 and 100 nodes and adding 10%, 20% and 30% of malicious nodes to the considered network. Experiments are simulated using Cooja simulator on Contiki operating system. Behavior of the network is observed based on the percentage of inconsistency achieved, energy consumption, accuracy and false positive rate. Experimental results show that multiple intrusions can be detected effectively by machine learning techniques.</span>

Control Messages Overhead Impact on Destination Oriented Directed Acyclic Graph—A Wireless Sensor Networks Objective Functions Performance Comparison

Routing Protocol for Low-power and Lossy Network (RPL) with IPv6 support is the de facto standard for routing over Low-power and Lossy Network (LLN) called Wireless Sensor Networks (WSN). Objective Functions namely Minimum Rank with Hysteresis Objective Function (MRHOF) and Objective Function Zero (OF0) together with the Internet Control Messaging Protocol (ICMP) control messages, propel RPL to constructs routing paths called Destination Oriented Directed Acyclic Graph (DODAG), for packet routing within the sensor network. To the best knowledge of the authors, no detailed investigation has been carried out to unravel the dynamics of how these control messages impact on the network with respect to DODAG formation right before convergence is attained, particularly from the perspective of MRHOF and OF0. In this paper, the authors investigated the various types of control messages (DODAG Information Solicitation, DODAG Information Object and Destination Advertisement Object) used to setup the DODAG. RPL Simulations was carried out on one 100 nodes, starting with 10 nodes and incremented by 10 until the 100th node. Each simulation was repeated five times with a confidence level of 95%, which statistically signifies a reliable and acceptable confidence interval, for a duration of thirty minutes. Results obtained showed that the DIS–OF0 generated the least packets with 125 packets, followed by DAO–MRHOF with 1357 packets and the most generated; DIO–MRHOF with 1536 packets. Subsequently, MRHOF had higher Convergence Time of 130.67 seconds as to 87.93 seconds for OF0. This information is valuable for both the academia and industry.

Routing protocol for Low-Power and Lossy Networks for heterogeneous traffic network

In a real network deployment, the diverse sensor applications generate a heterogeneous traffic pattern which may include basic sensing measurements such as temperature readings or high-volume multimedia traffic. In a heterogeneous traffic network, the two standardized objective functions (OFs), i.e., objective function zero (OF0) and the Minimum Rank with Hysteresis Objective Function (MRHOF) for routing protocol for Low-Power and Lossy Networks (RPL) perform poor routing decisions by selecting an already congested parent node and cause more re-transmissions across the network. Therefore, careful consideration is required in designing a new OF for heterogeneous traffic scenarios. In this study, we examine the RPL protocol under a heterogeneous traffic pattern and proposed a new protocol based on queue and workload-based condition (QWL-RPL). The aim of the proposed protocol is to achieve a reliable path with better overall performance. The proposed OF model considers the link workload in addition to mapping the congestion status of the node using the packet queue. We implement the proposed routing model in the Contiki operating system (OS) Cooja environment to compare with the existing technique. The simulation results show that QWL-RPL can improve the performance of a heterogeneous traffic network as compared with both OF0 and MRHOF, specifically in terms of the amount of overhead, packets reception ratio (PRR), average delay, and jitter. Final results indicate that on average, there is a 5%–30% improvement in PRR, 25%–45% reduction in overheads, 12%–30% reduction in average delay, and 20%–40% reduction in jitter.

A Cloud Based Disaster Management System

The combination of wireless sensor networks (WSNs) and 3D virtual environments opens a new paradigm for their use in natural disaster management applications. It is important to have a realistic virtual environment based on datasets received from WSNs to prepare a backup rescue scenario with an acceptable response time. This paper describes a complete cloud-based system that collects data from wireless sensor nodes deployed in real environments and then builds a 3D environment in near real-time to reflect the incident detected by sensors (fire, gas leaking, etc.). The system’s purpose is to be used as a training environment for a rescue team to develop various rescue plans before they are applied in real emergency situations. The proposed cloud architecture combines 3D data streaming and sensor data collection to build an efficient network infrastructure that meets the strict network latency requirements for 3D mobile disaster applications. As compared to other existing systems, the proposed system is truly complete. First, it collects data from sensor nodes and then transfers it using an enhanced Routing Protocol for Low-Power and Lossy Networks (RLP). A 3D modular visualizer with a dynamic game engine was also developed in the cloud for near-real time 3D rendering. This is an advantage for highly-complex rendering algorithms and less powerful devices. An Extensible Markup Language (XML) atomic action concept was used to inject 3D scene modifications into the game engine without stopping or restarting the engine. Finally, a multi-objective multiple traveling salesman problem (AHP-MTSP) algorithm is proposed to generate an efficient rescue plan by assigning robots and multiple unmanned aerial vehicles to disaster target locations, while minimizing a set of predefined objectives that depend on the situation. The results demonstrate that immediate feedback obtained from the reconstructed 3D environment can help to investigate what–if scenarios, allowing for the preparation of effective rescue plans with an appropriate management effort.

Evaluating and improving the scalability of RPL security in the Internet of Things

Wireless Sensor and Actuator Networks (WSANs) will represent a key building block for the future Internet of Things, as a cheap and easily-deployable technology to connect smart devices on a large scale. In WSAN the Routing Protocol for Low-Power and Lossy Networks (RPL) has a crucial role as the standard IPv6-based routing protocol. RPL specifications define a basic set of security features, without which it would be open to disruptive routing attacks. However, the impact of these features on the WSAN performance has not been thoroughly investigated yet. The contribution of this paper is two-fold. First, we extensively evaluate the impact of security mechanisms on the scalability of WSANs by means of both simulations and real experiments. We show that the protection against eavesdropping and forgery has a modest impact on the performance, whereas the protection against replay has a more considerable impact, especially on the network formation time which increases noticeably. Despite this, we show that protecting against replay reduces the number of control messages exchanged and improves routes optimality. For these reasons, we recommend to always use the security mechanisms. Finally, we propose a standard-compliant optimization for defending against replay that reduces the impact on the overall performance.

Service-aware objective function with QoS for RPL routing

The routing protocol for low power and lossy network (RPL), constructed according to the objective function (OF), is the standard for routing selection in low power and lossy networks (LLNs). Most schemes utilise the expected transmission count (ETX) as the routing metric for the next hop. Designing effective and efficient routing protocols in LLNs require the mechanism to meet the criteria of different applications or services. In this paper, we propose a service-aware OF with quality of service (SOF-QoS) mechanism which integrates received signal strength indicator (RSSI), energy consumption, and hop count metrics into RPL OF for path selection according to different services, such as normal data, video packets and emergency messages transmission in LLNs. The proposed SOF-QoS mechanism defines various weights with fuzzy logic for the next routing selection in response to each service. We conduct the simulation under different network topologies with static and mobile scenarios to analyse the performance of the proposed SOF-QoS mechanism and compare them with the traditional RPL schemes. The simulation result shows that our proposed SOF-QoS mechanism provides relatively better or superior performance with reliability than traditional ones for different services.

Downward traffic retransmission mechanism for improving reliability in RPL environment supporting mobility

With the diversification of industrial Internet of Things applications, there is a growing demand for mobility support in industrial wireless networking environments. However, the routing protocol for low-power and lossy networks is designed based on a static environment and is vulnerable in a mobility environment. Routing protocol for low-power and lossy networks is an Internet engineering task force standard in the low-power and lossy network environments used mainly in industrial environments. In addition, although routing protocol for low-power and lossy networks is based on collection tree protocol and is suitable for data collection and upward traffic transmission, it struggles with downward traffic transmission in terms of control, actuation, and end-to-end transmission. In this article, the problems caused by mobile nodes in routing protocol for low-power and lossy networks are discussed, and a retransmission scheme named IM-RPL is proposed. This retransmission scheme can improve the performance of downward traffic for the mobile nodes by retransmitting the packets to the neighbor nodes, the mobile node’s new parent sets, and relaying them to the mobile node. Its performance is evaluated through an experiment. The results demonstrate that using OpenMote in OpenWSN’s time slotted channel hopping induces a packet reception ratio improvement and a lower transmission delay as compared to standard routing protocol for low power and lossy.

Service-aware objective function with QoS for RPL routing

The routing protocol for low power and lossy network (RPL), constructed according to the objective function (OF), is the standard for routing selection in low power and lossy networks (LLNs). Most schemes utilise the expected transmission count (ETX) as the routing metric for the next hop. Designing effective and efficient routing protocols in LLNs require the mechanism to meet the criteria of different applications or services. In this paper, we propose a service-aware OF with quality of service (SOF-QoS) mechanism which integrates received signal strength indicator (RSSI), energy consumption, and hop count metrics into RPL OF for path selection according to different services, such as normal data, video packets and emergency messages transmission in LLNs. The proposed SOF-QoS mechanism defines various weights with fuzzy logic for the next routing selection in response to each service. We conduct the simulation under different network topologies with static and mobile scenarios to analyse the performance of the proposed SOF-QoS mechanism and compare them with the traditional RPL schemes. The simulation result shows that our proposed SOF-QoS mechanism provides relatively better or superior performance with reliability than traditional ones for different services.

Multi-Topology Based QoS-Differentiation in RPL for Internet of Things Applications

The rapid development of the Internet of Things (IoT) concept has promoted the presence of routing protocol for low power and lossy network (RPL). Unlike traditional applications, many applications envisioned for IoT networks may have different and sometimes conflicting requirements. In this context, the underlying routing protocol requires to provide quality of service (QoS) for multipurpose IoT and is inevitable. However, the routing approach in RPL is not efficient because default objective functions (OFs) rely on a single metric, which can result in a tradeoff in routing performance, particularly for multipurpose IoT that enchant different QoS requirements in the same network. Although RPL specification allows the use of multiple metrics for parent selection, however, no specific guideline is defined for metric combinations. Besides, many studies have revealed that RPL encounters severe problems in large scale networks as it was mainly designed for low data traffic network. To address these problems, in this paper, we primarily focus on QoS differentiation by exploiting the multi-topology routing feature of the RPL standard. For this, we propose different OFs, which ensures the QoS differentiation at the network level by splitting the physical network virtually into multiple RPL Instances. Each Instance can incorporate different traffic by associating with differing OFs, and routed it through the corresponding virtual network topology. We also present a new parent selection framework based on a multi-attribute decision-making approach that addresses the single routing metric problem in RPL. The extensive simulation results verify that our multi-topology routing approach can support the QoS provisioning and is suitable for large scale networks as compared with standard RPL.

Mitigation Mechanisms Against the DAO Attack on the Routing Protocol for Low Power and Lossy Networks (RPL)

Destination Advertisement Objects (DAOs) are sent upward by RPL nodes toward the DODAG root, to build the downward routing paths carrying traffic from the root to its associated nodes. This routing mechanism can be exploited by a malicious node periodically transmitting a large volume of DAO messages towards its parent, which in turn will forward such messages to its own parent and so on, until they arrive at the Direction-Oriented Directed Acyclic Graph (DODAG) root. This ultimately results in a negative effect on network performance in terms of energy consumption, latency and reliability. The first objective of this paper is to evaluate the effect of such a DAO attack in the context of an RPL IoT network. In particular, identifying the particular performance metrics and network resources affected most greatly. The second objective is the proposal of mitigating security mechanisms in relation to DAO attacks and to evaluate their effectiveness. The simulation results have shown how the attack can damage the network performance by significantly increasing the DAO overhead and power consumption. It also demonstrated that the DAO attack affect the reliability of the downward traffic under specific conditions. The proposed mechanisms showed a good capacity in restoring the optimal performance of the network by up to 205%, 181%, 87% and 6%, in terms of overhead, latency, power consumption and packet delivery ratio respectively.

RPL Attack Detection and Prevention in the Internet of Things Networks Using a GRU Based Deep Learning

Cyberattacks targeting Internet of Things (IoT), have increased significantly, over the past decade, with the spread of internet-connected smart devices and applications. Routing Protocol for Low-Power and Lossy Network (RPL) enables messages to be routed between nodes for the Wireless Sensor Network in the network layer. RPL protocol, which is sensitive and difficult to protect, is exposed to various attacks. These attacks negatively affect data transmission and cause great destruction to the topology by consuming the resources. Hello Flooding (HF) attacks against RPL cause consumption of constrained resources (memory, processing and energy) in nodes. Therefore, in this study, a Gated Recurrent Unit network model based deep learning has been proposed to predict and prevent HF attacks on RPL protocol in IoT networks. The proposed model has been compared with Support Vector Machine and Logistic Regression methods, and different power states and total energy consumptions of the nodes have been taken into consideration and experimented with. The results confirm the promised and expected performance from the model in terms of source efficiency and IoT security. In addition, attack detection has been carried out with a much lower error rate than literature studies for HF attacks from RPL flood attacks.

Increased Network Lifetime and Load Balancing Based on Network Interface Average Power Metric for RPL

The technological paradigm of the Internet of Things has attracted the attention of the market, industry, and scientific community. The possibility of integrating wireless sensor network (WSN) devices to the Internet has prompted the Internet Engineering Task Force (IETF) to specify new standards and protocols, such as the Routing Protocol for Low-Power and Lossy Networks (RPL), designed to find stable routing paths via links that have considerable losses. Among the routing metrics, the expected transmission count (ETX) is notable because its implementation in RPL helps choosing reliable paths. However, the rapid exhaustion of battery energy at bottleneck nodes remains a problem. In this context, this study introduces the network interface average power metric (NIAP), a new metric based on the estimated average power consumption of the network interface, which contributes not only to the choice of reliable paths but also to load balancing and lifetime increasing of a wireless sensor network. The results of several experiments conducted in a simulated environment demonstrate that NIAP is a promising alternative to ETX due to its simple implementation without modifications of the RPL standard.

Impacts of Mobility Models on RPL-Based Mobile IoT Infrastructures: An Evaluative Comparison and Survey

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.

A Versatile Out-of-Band Software-Defined Networking Solution for the Internet of Things

The Internet of Things (IoT) is gradually incorporating multiple environmental, people, or industrial monitoring deployments with diverse communication and application requirements. The main routing protocols used in the IoT, such as the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL), are focusing on the many-to-one communication of resource-constraint devices over wireless multi-hop topologies, i.e., due to their legacy of the Wireless Sensor Networks (WSN). The Software-Defined Networking (SDN) paradigm appeared as a promising approach to implement alternative routing control strategies, enriching the set of IoT applications that can be delivered, by enabling global protocol strategies and programmability of the network environment. However, SDN can be associated with significant network control overhead. In this paper, we propose VERO-SDN, an open-source SDN solution for the IoT, bringing the following novelties in contrast to the related works: (i) programmable routing control with reduced control overhead through inherent protocol support of a long-range control channel; and (ii) a modular SDN controller and an OpenFlow-like protocol improving the quality of communication in a wide range of IoT scenarios through supporting two alternative topology discovery and two flow establishment mechanisms. We carried out simulations with various topologies, network sizes and high-volume transmissions with alternative communication patterns. Our results verified the robust performance and reduced control overhead of VERO-SDN for alternative IoT deployments, e.g., achieved up to 47% reduction in network's overall end-to-end delay time compared to RPL and a packet delivery ratio of over 99.5%.

IETF 6TiSCH: A Tutorial

The IETF IPv6 over the TSCH mode of IEEE802.15.4e (6TiSCH) working group has standardized a set of protocols to enable low power industrial-grade IPv6 networks. 6TiSCH proposes a protocol stack rooted in the Time Slotted Channel Hopping (TSCH) mode of the IEEE802.15.4-2015 standard, supports multi-hop topologies with the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) routing protocol, and is IPv6-ready through 6LoWPAN. 6TiSCH has defined the missing control plane protocols to match link-layer resources to the routing topology and application communication needs. 6TiSCH has also defined a secure light-weight join processes combining link-layer security features (through Counter with CBC-MAC (CCM*)) with a secure joining procedure using the Constrained Application Protocol (CoAP). This tutorial provides a comprehensive overview of the 6TiSCH architecture and protocol suite, including the 6TiSCH Operation Sublayer (6top), the 6top Protocol (6P), and how it uses 6LoWPAN, IP-in-IP encapsulation, and RPL. This document is meant to be used both as a primer, and as a reference. It is tailored to the advanced researcher and engineer implementing and building upon IETF 6TiSCH specifications.

Routing Protocol for Low-Power and Lossy Network Performance Comparison for Objective Functions

Routing Protocol for Low-Power and Lossy Network Performance Comparison for Objective Functions

Design and develop Quality of Service Framework using Fog Computing for Smart City Applications

In today's world, Internet of Things (IoT) is has become the most promising and life-changing technology. In the past few years, IoT has become most productive in the area of healthcare, to improve the quality of care to the patients. This paper aims to reduce the delay, energy consumption of cloud data-centers and minimized the power consumption IoT devices using fog devices. To solve the problem mentioned above, we proposed the Quality of Service framework using fog computing for smart city applications named FATEH, a three-tier architecture for IoT-based application. Various quality of services parameters are optimized as For minimizing the power consumption of IoT devices, the Routing Protocol for Low power and Lossy network (RPL). The other QoS parameter is computing the performance of the proposed framework which has been evaluated through the iFogsim toolkit and the Cooja simulator. Results show the efficient reduction in the delay as well as energy consumption in the proposed scenario and provide better QoS framework

Energy and Delay Aware Data Aggregation in Routing Protocol for Internet of Things.

Energy conservation is one of the most critical problems in Internet of Things (IoT). It can be achieved in several ways, one of which is to select the optimal route for data transfer. IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) is a standardized routing protocol for IoT. The RPL changes its path frequently while transmitting the data from source to the destination, due to high data traffic in dense networks. Hence, it creates data traffic across the nodes in the networks. To solve this issue, we propose Energy and Delay Aware Data aggregation in Routing Protocol (EDADA-RPL) for IoT. It has two processes, namely parent selection and data aggregation. The process of parent selection uses routing metric residual energy (RER) to choose the best possible parent for data transmission. The data aggregation process uses the compressed sensing (CS) theory in the parent node to combine data packets from the child nodes. Finally, the aggregated data transmits from a downward parent to the sink. The sink node collects all the aggregated data and it performs the reconstruction operation to get the original data of the participant node. The simulation is carried out using the Contiki COOJA simulator. EDADA-RPL’s performance is compared to RPL and LA-RPL. The EDADA-RPL offers good performance in terms of network lifetime, delay, and packet delivery ratio.

Attestation-enabled secure and scalable routing protocol for IoT networks

Cybercrime in the past decade has experienced an all-time high due to the inclusion of so-called smart devices in our daily lives. These tiny devices with brittle security features are often dubbed as the Internet of Things (IoT). Their inclusion is not only limited to our daily lives but also in different fields, for example, healthcare, smart-industries, aviation, and smart-cities. Although IoT devices make our lives easy and perform our jobs in a smart way, but their fragile security mechanisms pose a severe challenge regarding safety and privacy of its users. Attacks like Stuxnet, and Mirai-botnet are the key examples of the damages that can be caused by maliciously controlling these devices. One effective tool to identify a malicious entity at a network device is to perform Remote Attestation (RA). However, performing RA over a large, heterogeneous IoT network is difficult tasks due to resource constrain nature of these networks. To this end, we propose a novel scheme called SARP, which is an attestation-assisted secure and scalable routing protocol for IoT networks. SARP performs attestation in large scale IoT networks by using Routing Protocol for Low Power and Lossy Networks (RPL) framework and exploiting the inbuilt features of RPL. In particular, SARP uses attestation technique that not only secures the network from internal attacks, but it also provides security to RPL’s data communication process, which helps to improve the overall network performance. Moreover, SARP supports network mobility, device heterogeneity, and network scalability, while it does not sacrifice the key requirements of IoT networks such as low energy and memory consumption, and low network overhead. The simulation results obtained in different IoT scenarios in presence of various types of attacks show the effectiveness of SARP, concerning energy consumption, packet delivery ratio, network overhead, data integrity, and communication security.