A Test Bed for Evaluating the Performance of IoT Networks

The use of smaller, personal IoT networks has increased over the past several years. These devices demand a lot of resources but only have limited access. To establish and sustain a flexible network connection, 6LoWPAN with RPL protocol is commonly used. While RPL provides a low-cost solution for connection, it lacks load balancing mechanisms. Improvements in OF load balancing can be implemented to strengthen network stability. This paper proposes a test bed configuration to show the toll of frequent parent switching on 6LoWPAN. Contiki’s RPL 6LoWPAN software runs on STM32 Nucleo microcontrollers with expansion boards for this test bed. The configuration tests frequency of parent changes and packet loss to demonstrate network instability of different RPL OFs. Tests on MRHOF for RPL were executed to confirm the working configuration. Results, with troubleshooting and improvements, show a working bed. The laid-out configuration provides a means for testing network stability in IoT networks

A New Load-Balancing Aware Objective Function for RPL’s IoT Networks

The IPv6 Routing Protocol for Low-power and Lossy Networks (RPL) has been recently standardized as the de facto solution for routing in the context of the emerging Internet of Things (IoT) paradigm. RPL, along with other standards, has provided a baseline framework for IoT that has helped advance communications in the world of embedded resource-constrained networks. However, RPL still suffers from issues that may limit its efficiency such as the absence of an efficient load-balancing primitive. In this study, we show how RPL suffers from a load-balancing problem that may harm both the reliability of the protocol and its network lifetime. To address this problem, a novel load-balancing scheme is introduced that significantly enhances the reliability of RPL and fosters the protocol’s efficiency in terms of power consumption

A burst and congestion-aware routing metric for RPL protocol in IoT network

The packet loss and power consumption are the main issues considered once congestion occurs in any network, such as the Internet of Things (IoT) with a huge number of sensors and applications. Since IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) is not initially designed for high stream traffic load, this restricts the application domain of RPL in several IoT scenarios such as burst traffic scenarios. The performance of RPL suffers in a network with burst traffic load, which leads to reducing the lifetime of the network and causing traffic congestion among the neighbour nodes. Therefore, to address this issue, we proposed a Burst and Congestion-Aware Metric for RPL called BCA-RPL, which calculates the rank, considering the number of packets. Also, the proposed mechanism includes congestion avoiding and load balancing techniques by switching the best parent selection to avoid the congested area. Our scheme is built and compared to the original RPL routing protocol for low power and lossy network with OF0 (OF0-RPL). Simulation results based on Cooja simulator shows BCA-RPL performs better than the original RPL-OF0 routing protocol in terms of packet loss, power consumption and packet delivery ratio (PDR) under burst traffic load. The BCA-RPL significantly improves the network where it decreases the packet loss around 50% and power consumption to an acceptable level with an improvement on the PDR of the IoT network

TFUZZY-OF: a new method for routing protocol for low-power and lossy networks load balancing using multi-criteria decision-making

The internet of things (IoT) based on a network layer perspective includes low-power and lossy networks (LLN) that are limited in terms of power consumption, memory, and energy usage. The routing protocol used in these networks is called routing over low-power and lossy networks (RPL). Therefore, the IoT networks include smart objects that need multiple routing for their interconnections which makes traffic load balancing techniques indispensable to RPL routing protocol. In this paper, we propose a method based on fuzzy logic and the technique for the order of prioritization by similarity to the ideal solution (TOPSIS) as a well-known multi-criteria decision-making method to solve the load balancing problem by routing metrics composition. For this purpose, a combination of both link and node routing metrics namely hop count, expected transmission count, and received signal strength indicator is used. The results of simulations show that this method can increase the quality of services in terms of packet delivery ratio and average end-to-end delay

The RPL load balancing in IoT network with burst traffic scenarios

In Low Power and Lossy Networks (LLNs) sensor nodes are deployed in various traffic load conditions such as, regular and heavy traffic load. The adoption of Internet-of-Things enabled devices in the form of wearables and ubiquitous sensors and actuators has demanded LLNs to handle burst traffic load, which is an event required by myriad IoT devices in a shared LLN. In the large events, burst traffic load requires a new radical approach of load balancing, this scenario causes congestion increases and packet drops relatively when frequent traffic burst load rises in comparison with regular and heavy loads. In this paper, we introduced a new efficient load balance mechanism for traffic congestion in IPv6 Routing Protocol for Low Power and Lossy Network (RPL). To measure the communication quality and optimize the lifetime of the network, we have chosen packet delivery ratio (PDR) and power consumption (PC) as our metrics. We proposed a traffic-aware metric that utilizes ETX and parent count metrics (ETXPC), where communication quality for LLNs with RPL routing protocol are playing an important role in traffic engineering. In addition, we provided analytical results to quantify the impact of Minimum Rank with Hysteresis Objective on Function (MRHOF) and Objective Function zero (OF0) to the packet delivery, reliability and power consumption in LLNs. The simulation results pragmatically show that the proposed load balancing approach has increased packet delivery ratio with less power consumption

저전력 손실 네트워크에서 대규모 응용분야를 위한 전송전력 제어기법

학위논문 (석사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2015. 8. 박세웅.Transmission power is an important factor which impacts on routing topology in low power and lossy networks (LLNs). LLNs have been designed for low rate traffic where use of maximum transmission power is the best choice for performance maximization since it results in reduced hop distance and transmission overhead. However, large scale applications also require LLNs to deliver very high rate traffic. In such large scale applications, the nodes which are near the root node will incur heavy traffic even though each node generates low rate traffic. As a result, it will cause severe link congestion. In this paper, we first investigate the effect of transmission power control on the performance of the routing protocol for LLNs (RPL) at heavy traffic load through testbed experiments. Our experiments show that, unlike LLNs in low rate applications, packet delivery performance at heavy load first increases and then decreases with transmission power. And we further investigate the reasons of what makes packet loss rate have a convex curve according to transmission power by per node analysis. We classify packet losses into link loss and queue loss. From the experiment results, we observe that link and queue losses are significantly unbalanced among nodes, which causes the load balancing problem of RPL. Furthermore, queue losses occur at the nodes which experience severe link loss. To solve this problem, we propose a simple power control mechanism, which allows each node to adaptively control its transmission power according to its own link and queue losses. Our proposal significantly improves the packet delivery performance by balancing the traffic load within a routing tree. We show performance improvement through experimental measurements on a real mutihop LLN testbed running RPL over IEEE 802.15.4.Contents Abstract i Contents iii List of Figures iii List of Tables v Chap 1 Introduction 1 Chap 2 Experimental Environments 4 2.1. IPv6 routing protocol for low power and lossy networks (RPL) 4 2.2. Experimental environments 5 Chap 3 Load Balancing Problem of RPL 7 3.1. Packet loss rate 7 3.2. Queue loss and link loss 8 3.3. Topology analysis 11 3.4. Per node analysis 12 Chap 4 Transmission Power Control Mechanism 15 4.1. Effect of proposed power control on load balancing 15 4.2. Power control mechanism 17 Chap 5 Experimental Results 20 5.1. Packet loss rate 20 5.2. Queue loss and link loss 22 5.3. Packet loss rate 23 Chap 6 Conclusions 25 References 26 초 록 30 감사의 글 32Maste

A Novel Technique to Parameterize Congestion Control in 6TiSCH IIoT Networks

The Industrial Internet of Things (IIoT) refers to the use of interconnected smart devices, sensors, and other technologies to create a network of intelligent systems that can monitor and manage industrial processes. 6TiSCH (IPv6 over the Time Slotted Channel Hopping mode of IEEE 802.15.4e) as an enabling technology facilitates low-power and low-latency communication between IoT devices in industrial environments. The Routing Protocol for Low power and lossy networks (RPL), which is used as the de-facto routing protocol for 6TiSCH networks is observed to suffer from several limitations, especially during congestion in the network. Therefore, there is an immediate need for some modifications to the RPL to deal with this problem. Under traffic load which keeps on changing continuously at different instants of time, the proposed mechanism aims at finding the appropriate parent for a node that can forward the packet to the destination through the least congested path with minimal packet loss. This facilitates congestion management under dynamic traffic loads. For this, a new metric for routing using the concept of exponential weighting has been proposed, which takes the number of packets present in the queue of the node into account when choosing the parent at a particular instance of time. Additionally, the paper proposes a parent selection and swapping mechanism for congested networks. Performance evaluations are carried out in order to validate the proposed work. The results show an improvement in the performance of RPL under heavy and dynamic traffic loads.Comment: The paper has been submitted, accepted, and presented at the 2023 IEEE Global Communications Conference: Next-Generation Networking and Internet, with plans for publication. It was delivered during the IEEE Global Communications Conference held on December 6th, 2023, in Kuala Lumpur, Malaysi

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

Optimization Based Hybrid Congestion Alleviation for 6LoWPAN Networks

The IPv6 over Low-Power Wireless Personal Area Network (6LoWPAN) protocol stack is a key part of the Internet of Things (IoT) where the 6LoWPAN motes will account for the majority of the IoT ‘things’. In 6LoWPAN networks, heavy network traffic causes congestion which significantly effects the network performance and the quality of service (QoS) metrics. Generally, two main strategies are used to control and alleviate congestion in 6LoWPAN networks: resource control and traffic control. All the existing work of congestion control in 6LoWPAN networks use one of these. In this paper, we propose a novel congestion control algorithm called optimization based hybrid congestion alleviation (OHCA) which combines both strategies into a hybrid solution. OHCA utilizes the positive aspects of each strategy and efficiently uses the network resources. The proposed algorithm uses a multi-attribute optimization methodology called grey relational analysis for resource control by combining three routing metrics (buffer occupancy, expected transmission count and queuing delay) and forwarding packets through non-congested parents. Also, OHCA uses optimization theory and Network Utility Maximization (NUM) framework to achieve traffic control when the non-congested parent is not available where the optimal nodes’ sending rate are computed by using Lagrange multipliers and KKT conditions. The proposed algorithm is aware of node priorities and application priorities to support the IoT application requirements where the applications’ sending rate allocation is modelled as a constrained optimization problem. OHCA has been tested and evaluated through simulation by using Contiki OS and compared with comparative algorithms. Simulation results show that OHCA improves performance in the presence of congestion by an overall average of 28.36%, 28.02%, 48.07%, 31.97% and 90.35% in terms of throughput, weighted fairness index, end-to-end delay, energy consumption and buffer dropped packets as compared to DCCC6 and QU-RPL