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Performance evaluation of RPL on a mobile scenario with different ContikiMAC radio duty cycles
... This process repeats for every child node until the root node is reached. Meanwhile, any node upon not receiving DIO message, within a specified time interval, sends DIS messages to the neighbor nodes for seeking DIO message to join the DODAG [25]. ...
... The Objective function starts playing its role when a node receives more than one DIO message from nearby preferred parents. The objective function is defined as a criterion for the route selection [25]. The computation of rank and the selection of parents are also governed by the objective function. ...
... The OF along with a set of metrics are used for the selection of DODAG, computing the ranks of the nodes, listing the preferred parents and selection of routes based on the metrics [23]. In RPL routing protocol, every child has to choose a preferred parent among the neighboring nodes towards the root node, depending upon the information available in objective function [25]. ...
The Internet of Things (IoT) is an extensive network between people-people, people-things and things-things. With the overgrown opportunities, then it also comes with a lot of challenges proportional to the number of connected things to the network. The IPv6 allows us to connect a huge number of things. For resource-constrained IoT devices, the routing issues are very thought-provoking and for this purpose an IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is proposed. There are multi-HOP paths connecting nodes to the root node. Destination Oriented Directed Acyclic Graph (DODAG) is created taking into account different parameters such as link costs, nodes attribute and objective functions. RPL is flexible and it can be tuned as per application demands, therefore, the network can be optimized by using different objective functions. This paper presents a novel energy efficient analysis of RPL by performing a set of simulations in COOJA simulator. The performance evaluation of RPL is compared by introducing different Objective functions (OF) with multiple metrics for the network.
... This process repeats for every child node until the root node is reached. Meanwhile, any node upon not receiving DIO message, within a specified time interval, sends DIS messages to the neighbor nodes for seeking DIO message to join the DODAG [25]. ...
... The Objective function starts playing its role when a node receives more than one DIO message from nearby preferred parents. The objective function is defined as a criterion for the route selection [25]. The computation of rank and the selection of parents are also governed by the objective function. ...
... The OF along with a set of metrics are used for the selection of DODAG, computing the ranks of the nodes, listing the preferred parents and selection of routes based on the metrics [23]. In RPL routing protocol, every child has to choose a preferred parent among the neighboring nodes towards the root node, depending upon the information available in objective function [25]. ...
The Internet of Things (IoT) is an extensive
network between people-people, people-things and things-things.
With the overgrown opportunities, then it also comes with a lot of
challenges proportional to the number of connected things to the
network. The IPv6 allows us to connect a huge number of things.
For resource-constrained IoT devices, the routing issues are very
thought-provoking and for this purpose an IPv6 Routing
Protocol for Low-Power and Lossy Networks (RPL) is proposed.
There are multi-HOP paths connecting nodes to the root node.
Destination Oriented Directed Acyclic Graph (DODAG) is
created taking into account different parameters such as link
costs, nodes attribute and objective functions. RPL is flexible
and it can be tuned as per application demands, therefore, the
network can be optimized by using different objective functions.
This paper presents a novel energy efficient analysis of RPL by
performing a set of simulations in COOJA simulator. The
performance evaluation of RPL is compared by introducing
different
... The simulation in the paper was carried out with the Contiki Operating System (OS) [25], Contiki OS is the stateof-the-art Linux-based operating system for IEEE 802.15.4 wireless network devices. It can be used for both simulation and real-life implementation for WSN. ...
The IEEE 802.15.4 standard regulates the operations of low-rate wireless personal area network devices that forms the building block for the Internet of Things (IoT) and the modern-day smart world. Defined in 2003, by the IEEE 802.15 working group, it focuses on the Physical and Data Link Layers; which is further sub-layered into the Medium Access Control (MAC) and Logical Link Control (LLC) sub-layers. Of all things in the IEEE 802.15.4 domain, power is the most paramount as IEEE 802.15.4 devices are power constrained due to their small form factor and independent power nature, hence it become imperative to effectively manage the scarce power in other to prolong the operational lifetime of the Wireless Sensor Network (WSN). While managing the power of IEEE 802.15.4 devices, a poorly designed MAC protocols may lead to early power drainage and hence shortened operational lifetime. In this paper, four MAC implementations have been analysed and compare with respect to power efficiency; the ContikiMAC, CXMAC, XMAC and NullMAC. With 95% statistical confidence level, results show that ContikiMAC is the most power efficient MAC, which consumes the least of all three power-consuming operations, Low Power Mode (LPM) or sleep mode - 0.154 milliwatts, Listen - 0.4 milliwatts and Transmit - 0.36 milliwatts. Other forms of MAC exceed one milliwatts for all forms of power consuming operations. Detailed analysis on the subject matter is presented in this paper.
(PDF) Performance Evaluation for ContikiMAC, XMAC, CXMAC and NullMAC Protocols for Energy Efficient Wireless Sensor Networks. Available from: https://www.researchgate.net/publication/338938779_Performance_Evaluation_for_ContikiMAC_XMAC_CXMAC_and_NullMAC_Protocols_for_Energy_Efficient_Wireless_Sensor_Networks [accessed Feb 14 2020].
... Já no trabalho apresentado em [18], o RPLé avaliado em cenários móveis híbridos, ou seja, na presença de nós fixos e nós móveis. Em [19]é analisado como o ciclo de trabalho dos nós influencia no desempenho do RPL em cenários fixos e móveis. ...
This work is a minicourse on the RPL routing protocol for the Internet of Things (IoT), standardized by the IETF for low power and lossy networks. It aims to show the main characteristics of the protocol, as well as to raise the problems and proposals of solutions for mobility and information security related to routing for IoT. With the expectation of an increase in the applications in this new scenario, we present new research issues. We show practical examples of simulations in the Contiki operating system, which can serve as a tutorial for those interested in using the system.
The development of IP-based Internet of Things (IoT) networks would facilitate more effective end-to-end IP network architectures, but it remains a challenge. Network routing needs to be effectively addressed in the IoT environments of scarce computational and energy resources. Accordingly, the Internet Engineering Task Force (IETF) has specified the IPv6 Routing Protocol for Low Power and Lossy Network (RPL) to provide a bespoke IPv6-based routing framework for IoT networks. However, RPL comes with no Quality of Service (QoS) support which is an essential requirement for many IoT applications. The network research community has introduced a number of research proposals enhancing RPL with different QoS solutions. This paper presents a review of these proposed solutions and aims to establish a firm understanding of recent QoS developments for RPL and possible areas for future IoT routing research. The focus is on comprehending the protocol and networking properties that can affect QoS performance in RPL networks. Consideration is also given to different objective functions developed for addressing varying QoS aspects such as throughput, delay, and packet loss. RPL is also extended in a number of QoS solutions following different approaches at the MAC, network, and application layers. However, there is still a need for further developments to address effective QoS support, particularly for dynamic RPL networks. © 2022, Institute of Computing Technology, Chinese Academy of Sciences.
In low-power Internet of Things (IoT) devices, designed for harsh environments, radio duty cycle (RDC) at the MAC layer provides energy efficiency to achieve network longevity. RDC can be either static or dynamic. In a static RDC (SRDC) mechanism, all nodes possess the same but fixed RDC value. In a dynamic RDC (DRDC) mechanism, nodes possess different RDC values due to indigenous conditions, for example, traffic load and battery status. To synchronize, IoT nodes use a phase-lock mechanism, where the sender estimates the wake-up time of the receiver in order to awake with it. Phase lock works well in SRDC because all nodes have the same RDC value, but it is affected in the DRDC mechanism because a sender does not know the wake-up time of the receiver that has changed the RDC value. This creates a problem. Although ContikiMAC is the most wide SRDC mechanism, it does not perform well in DRDC environments. State-of-the-art DRDC mechanisms, which predominantly work based on the RDC mechanism of ContikiMAC, do not share their RDC with neighbors and, therefore, work poorly in dynamic environments. This article proposes a novel adaptive dynamic RDC (AD-RDC) mechanism based on the extended phase lock, where nodes dynamically adjust their RDC based on traffic load and residual energy and share it with neighbors to remain synchronized. Simulations, performed in the Cooja emulator, reveal that the proposed AD-RDC has improved the packet delivery ratio, network lifetime, end-to-end delay, and broadcast reachability in DRDC environments.
Mobility is the most issues for the majority of protocols including the RPL (IPv6 Routing Protocol for Low Power and Lossy Networks). RPL a routing protocol standardized by IETF is usually used in Internet of Things Technology. It is proposed to support communications in Low power and Lossy Networks (LLNs). However, mobility limits the use of RPL protocol in realistic study. In this paper we have classify the mobility models in two entities in order to evaluate the performances of RPL in each entity separately. So we have defines two different scenarios. We first, evaluate characteristics of RPL with a group mobility models which contain Reference Point Mobility Model (RPGM) and Nomadic Mobility Model (Nomadic) Mobility Models. Then we give another evaluation of features of RPL with the Entity mobility models which contain Random Walk Mobility Model (RWK), Random Waypoint Mobility Models (RWP) and self-similar least action walk (SLAW) Mobility models. In this study, we use Contiki OS and Cooja software for all simulations. The results show that the type of mobility models has a direct influence on the protocol performances. In addition, increasing of number of nodes causes an increasing of all parameters, especially in delivered and received data. Furthermore, the group mobility models give better metrics than entity mobility models in terms of lost packets, Packet Delivery Ratio (PDR) and Throughput. Also, in each type of mobility models each model provides better metrics than others. RPG offers best number of lost packets and PDR than Nomadic model and lowest in terms of Throughput while SLAW models gives the best value in all metrics than RWK and RWP. Our simulation shows clearly that lost packets, PDR and Throughput are directly related to the type of mobility models.
Mobility support for wireless sensor networks has always been a challenging research topic. This paper addresses the issue of mobility support in the Routing Protocol for Low power and lossy networks (RPL), the recently adopted IETF routing protocol standard for low power wireless sensor networks. RPL was originally designed for static networks, with no support for mobility. In this work, we address this gap and propose Co-RPL as an extension to RPL based on the Corona mechanism to support mobility. To demonstrate the effectiveness of Co-RPL, we conducted an extensive simulation study using the Contiki/Cooja simulator and compared the performance against standard RPL. We study the impact of node speed, packet transmission rate and number of Directed Acyclic Graphs (DAG) roots on network performance. The simulation results show that Co-RPL decreases packet loss ratio by 45%, average energy consumption by 50% and end-to-end delay by 2.5 seconds, in comparison with the standard RPL.
In this paper, we investigate the problem of supporting mobility over RPL (IPv6 Routing Protocol for Low power and Lossy Networks) when applied to route traffic in Wireless Sensor Networks (WSNs). RPL is a routing protocol adapted for information routing with low power, low storage and processing sensor devices, in static topologies commonly found in WSNs, but which is not directly designed for mobile scenarios. Specifically, RPL actively decreases control traffic, at the price of lower reactivity to topology changes. In this paper, we propose to introduce some new mechanisms to the native RPL that reconcile decrease in control traffic and reactivity. They are based on an identification of mobile nodes, and furthermore they enhance RPL behavior in case of node mobility. Our approach will be, henceforth, called ME-RPL (Mobility Enhanced RPL).
This paper focuses on routing for vehicles getting
access to infrastructure either directly or via multiple hops
through other vehicles. We study routing protocol for low-power and lossy networks (RPL), a tree-based routing protocol
designed for sensor networks. Many design elements from RPL
are transferable to the vehicular environment. We provide a
simulation performance study of RPL and RPL tuning in
VANETs. More specifically, we seek to study the impact of RPL's
various parameters and external factors (e.g., various timers and
speeds) on its performance and obtain insights on RPL tuning
for its use in VANETs. We then fine tune RPL and obtain
performance gain over existing RPL.
This paper focuses on the routing protocol for driving safety that vehicle collects state message from roadside sensors in VANET-WSN. Routing Protocol for Low Power and Lossy Networks (RPL), a tree-based routing protocol, adapts naturally to our routing requirement. But RPL is designed for static wireless sensor network, so we need to modify RPL to fit in with high dynamic topology of VANET-WSN. For the first time, we utilize Geographical Information (GI) as the metric for RPL (GI-RPL), which lets RPL in a timely fashion. We also propose some strategies for tuning RPL in VANET-WSN. To demonstrate the performance of GI-RPL, we set up a simulation by using Cooja and compare with another modified RPL. The result of simulation shows that GI-RPL has high Package Delivery Ratio (PDR), reasonable overhead and low delay.
To guarantee that a Wireless Sensor Network succeeds in delivering its expected QoS, it is essential to understand and optimize cross-layer interactions. This paper presents a study on the interactions between the RPL routing protocol and Radio Duty Cycling (RDC) protocols. This study constitutes a fi�rst step towards a full understanding of their impact on the QoS of the network. By means of simulation and real world measurements, diff�erences in the performance of RPL with diff�erent RDC protocols were observed and explained, and several properties of the RDC protocols impairing the performance of RPL were discovered.
Energy-efficient operation is one of the prominent challenges for successful deployment of Wireless Sensor Networks (WSN's) along with maintaining certain quality of service (QoS) requirements. In this paper, we tackle the energy-efficient operation of WSN nodes implementation based on the Contiki real-time operating system (RTOS). We review the effect of applying spatial configuration for the radio duty-cycle (RDC) frequencies of WSN nodes running ContikiMAC. We propose an approach for enhancing the ContikiMAC duty cycling protocol, using adaptive radio duty cycling. Such approach would enhance multiple performance metrics of WSN's such as lifetime and sensory packets delivery ratio. Our proposal is based on two temporal duty cycles update mechanisms namely: a distributed mechanism in which a WSN sink node collects network-wide statistics and broadcasts a threshold value to sensory nodes for duty cycles adjustment, and an autonomous mechanism in which each node individually updates its duty-cycle based on local measured statistics. Such proposed framework should help achieving optimal balance between network lifetime and QoS requirements. Our simulation results for Contiki-AMAC show significant gains in network lifetime while maintaining network sensory packets delivery ratio at the same level, compared to static schemes of ContikiMAC.
Recently, mobile devices have been introduced in various wireless sensor network (WSN) applications in order to solve complex tasks or to increase the data collection efficiency. However, the current generation of low-power WSN protocols is mainly designed to support data collection and address application-specific challenges without any particular considerations for mobility. In this paper, we introduce MoMoRo, a mobility support layer that can be easily applied to existing data collection protocols, thereby enabling mobility support in the network. MoMoRo robustly collects neighborhood information and uses a fuzzy estimator to make link quality estimations. This fuzzy estimator continuously reconfigures its thresholds for determining the fuzzy sets, allowing MoMoRo to easily adapt to changing channel environments. Furthermore, MoMoRo includes an active destination search scheme that allows disconnected mobile nodes with sparse traffic to quickly reconnect if there are packets in the network destined to this mobile node. We evaluate MoMoRo both indoor and outdoor and show that a continuously moving device in a MoMoRo-enabled RPL (i.e., IPv6 Routing Protocol for Low-Power and Lossy Networks) network can achieve a high packet reception ratio of up to 96% and stay connected in areas where RPL alone cannot and with less than half the packet overhead needed by the well-known Ad hoc On-Demand Distance Vector routing protocol.
Low-power wireless devices must keep their radio transceivers off as much as possible to reach a low power consumption, but must wake up often enough to be able to receive communication from their neighbors. This report describes the ContikiMAC radio duty cycling mechanism, the default radio duty cycling mechanism in Contiki 2.5, which uses a power efficient wake-up mechanism with a set of timing constraints to allow device to keep their transceivers off. With ContikiMAC, nodes can participate in network communication yet keep their radios turned off for roughly 99% of the time. This report describes the ContikiMAC mechanism, measures the energy consump-tion of individual ContikiMAC operations, and evaluates the efficiency of the fast sleep and phase-lock optimiza-tions.
RFC 6206 - The Trickle Algorithm
- P Levis
- T Clausen
- J Hui
- O Gnawali
- J Ko