Performance analysis of Routing Protocol for Low power and Lossy Networks (RPL) in large scale networks

With growing needs to better understand our environments, the Internet-of-Things (IoT) is gaining importance among information and communication technologies. IoT will enable billions of intelligent devices and networks, such as wireless sensor networks (WSNs), to be connected and integrated with computer networks. In order to support large scale networks, IETF has defined the Routing Protocol for Low power and Lossy Networks (RPL) to facilitate the multi-hop connectivity. In this paper, we provide an in-depth review of current research activities. Specifically, the large scale simulation development and performance evaluation under various objective functions and routing metrics are pioneering works in RPL study. The results are expected to serve as a reference for evaluating the effectiveness of routing solutions in large scale IoT use cases

Evaluation of RPL’s Single Metric Objective Functions

In this paper, we evaluate the performance of RPL (IPv6 Routing Protocol for Low Power and Lossy Networks) based on the Objective Function being used to construct the Destination Oriented Directed Acyclic Graph (DODAG). Using the Cooja simulator, we compared Objective Function Zero (OF0) with the Minimum Rank with Hysteresis Objective Function (MRHOF) in terms of average power consumption, packet loss ratio, and average end-to-end latency. Our study shows that RPL performs better in terms of packet loss ratio and average endto-end latency when MRHOF is used as an objective function. However, the average power consumption is noticeably higher compared to OF0

Evolving SDN for Low-Power IoT Networks

Software Defined Networking (SDN) offers a flexible and scalable architecture that abstracts decision making away from individual devices and provides a programmable network platform. However, implementing a centralized SDN architecture within the constraints of a low-power wireless network faces considerable challenges. Not only is controller traffic subject to jitter due to unreliable links and network contention, but the overhead generated by SDN can severely affect the performance of other traffic. This paper addresses the challenge of bringing high-overhead SDN architecture to IEEE 802.15.4 networks. We explore how traditional SDN needs to evolve in order to overcome the constraints of low-power wireless networks, and discuss protocol and architectural optimizations necessary to reduce SDN control overhead - the main barrier to successful implementation. We argue that interoperability with the existing protocol stack is necessary to provide a platform for controller discovery and coexistence with legacy networks. We consequently introduce {\mu}SDN, a lightweight SDN framework for Contiki, with both IPv6 and underlying routing protocol interoperability, as well as optimizing a number of elements within the SDN architecture to reduce control overhead to practical levels. We evaluate {\mu}SDN in terms of latency, energy, and packet delivery. Through this evaluation we show how the cost of SDN control overhead (both bootstrapping and management) can be reduced to a point where comparable performance and scalability is achieved against an IEEE 802.15.4-2012 RPL-based network. Additionally, we demonstrate {\mu}SDN through simulation: providing a use-case where the SDN configurability can be used to provide Quality of Service (QoS) for critical network flows experiencing interference, and we achieve considerable reductions in delay and jitter in comparison to a scenario without SDN

Towards Efficient Load Balancing Strategy for RPL Routing Protocol in IoT Networks

학위논문 (석사)-- 서울대학교 대학원 : 공과대학 컴퓨터공학부, 2018. 8. Chong-Kwon Kim.The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) has been considered as the new standard routing protocol designed to meet the requirements of wide range of Low Power and Lossy Networks (LLNs) applications including industrial and environmental monitoring, smart grid, and wireless sensor networks. However, due to the uneven deployment of sensor nodes in large-scale networks and the heterogeneous traffic patterns, some sensor nodes have much heavier workload than others. The lack of load balancing mechanism results in these sensor nodes quickly exhausting their energy, therefore shorten the network lifetime of battery-powered wireless sensor networks. To overcome this problem, we propose a skewness and load balancing routing protocol based on the RPL protocol, named SB-RPL that exploits various routing metrics including link quality and skewness among subtrees of the network in support topology construction. In this work, we first investigate the load balancing and related issues of RPL both via numerical simulations and via actual large-scale testbed. Performance analysis results show that RPL trees suffer from severe skewness regardless of routing metrics in randomly generated networks. Through extensive computer simulations and actual experiments, we demonstrate that SB-RPL significantly improves end-to-end packet delivery performance and tree balance compared to the standard RPL.Contents ABSTRACT…………………………………………………………..i Contents…………………………………………………………….iii List of Figures...……………………………………………………vi List of Tables…...…………………………………………………vii Glossary…………..…………………………………………………viii Chapter I: Introduction ................................................. 1 1.1. Overview ............................................................... 1 1.2. Motivation ............................................................. 2 1.3. Key Idea ................................................................. 4 1.4. Contribution ........................................................... 4 1.5. Thesis Organization ................................................. 6 Chapter II: Background and Literature Review ................. 7 2.1. RPL Overview .......................................................... 7 2.2. DODAG Construction ............................................... 7 2.3. Trickle Timer .............................................................10 2.4. RPL Operation Modes ...............................................11 2.5. Literature Review ......................................................11 2.5.1. RPL Objective Functions: ........................................11 2.5.2. Balanced Routing protocols ...................................13 Chapter III: System Modeling .......................................... 15 3.1. System Models .........................................................15 3.2. RPL Objective Function: ............................................17 Chapter IV: SB-RPL Design .............................................. 20 4.1. Topology-Aware Node Influence ...............................20 4.2. RPL Control Message DIO extension in support of balancing routing .............................................................20 4.3. SB-RPL Design ...........................................................21 Chapter V: Evaluation ...................................................... 25 5.1. RPL in Contiki OS .......................................................25 5.2. Methodology .............................................................26 5.2.1. Testbed Experiments: ..............................................26 5.3. Compared Objective Functions ...................................28 5.4. Metrics........................................................................29 5.5. Testbed Experiments....................................................30 5.5.1. Impact of α and β: ....................................................30 5.5.2. Objective Function Comparison ...............................36 5.6. Cooja-based Simulations ............................................38 5.6.1. Impact of Network Scales ........................................40 5.6.2. Impact of Network Density ......................................41 Chapter VI: Conclusion ..................................................... 43 Bibliography ..................................................................... 44 요 약.................................................................................. 50 Acknowledgments ............................................................ 52Maste

Topology Construction in RPL Networks over Beacon-Enabled 802.15.4

In this paper, we propose a new scheme that allows coupling beacon-enabled IEEE 802.15.4 with the RPL routing protocol while keeping full compliance with both standards. We provide a means for RPL to pass the routing information to Layer 2 before the 802.15.4 topology is created by encapsulating RPL DIO messages in beacon frames. The scheme takes advantage of 802.15.4 command frames to solicit RPL DIO messages. The effect of the command frames is to reset the Trickle timer that governs sending DIO messages. We provide a detailed analysis of the overhead incurred by the proposed scheme to understand topology construction costs. We have evaluated the scheme using Contiki and the instruction-level Cooja simulator and compared our results against the most common scheme used for dissemination of the upper-layer information in beacon-enabled PANs. The results show energy savings during the topology construction phase and in the steady state

IETF standardization in the field of the Internet of Things (IoT): a survey

Smart embedded objects will become an important part of what is called the Internet of Things. However, the integration of embedded devices into the Internet introduces several challenges, since many of the existing Internet technologies and protocols were not designed for this class of devices. In the past few years, there have been many efforts to enable the extension of Internet technologies to constrained devices. Initially, this resulted in proprietary protocols and architectures. Later, the integration of constrained devices into the Internet was embraced by IETF, moving towards standardized IP-based protocols. In this paper, we will briefly review the history of integrating constrained devices into the Internet, followed by an extensive overview of IETF standardization work in the 6LoWPAN, ROLL and CoRE working groups. This is complemented with a broad overview of related research results that illustrate how this work can be extended or used to tackle other problems and with a discussion on open issues and challenges. As such the aim of this paper is twofold: apart from giving readers solid insights in IETF standardization work on the Internet of Things, it also aims to encourage readers to further explore the world of Internet-connected objects, pointing to future research opportunities

Role Playing Learning for Socially Concomitant Mobile Robot Navigation

In this paper, we present the Role Playing Learning (RPL) scheme for a mobile robot to navigate socially with its human companion in populated environments. Neural networks (NN) are constructed to parameterize a stochastic policy that directly maps sensory data collected by the robot to its velocity outputs, while respecting a set of social norms. An efficient simulative learning environment is built with maps and pedestrians trajectories collected from a number of real-world crowd data sets. In each learning iteration, a robot equipped with the NN policy is created virtually in the learning environment to play itself as a companied pedestrian and navigate towards a goal in a socially concomitant manner. Thus, we call this process Role Playing Learning, which is formulated under a reinforcement learning (RL) framework. The NN policy is optimized end-to-end using Trust Region Policy Optimization (TRPO), with consideration of the imperfectness of robot's sensor measurements. Simulative and experimental results are provided to demonstrate the efficacy and superiority of our method