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

A generalized resource allocation framework in support of multi-layer virtual network embedding based on SDN

Network Virtualization (NV) allows multiple heterogeneous architectures to simultaneously coexist in a shared infrastructure. Embedding multiple virtual networks (VNs) in a shared substrate deals with efficient mapping of virtual resources in the physical infrastructure and is referred to as the Virtual Network Embedding problem (VNE-problem). Although there is recently a number of research work in the area of network virtualization based on the Software-Defined Networking (SDN) technology, virtual network embedding in SDN remains challenging from both theoretical and practical points of view.This article focuses on virtual network embedding strategies and related issues for Infrastructure-as-a-Service (IaaS) paradigms under the constraint of fixed virtual node locations. Special considerations are given to the problems related to resource allocation and link sharing of multi-layer virtual networks on top of the physical substrate. Firstly, a heuristic virtual network embedding algorithm is proposed that can improve the mapping acceptance ratio and resource efficiency in the IaaS context. Secondly, REsource reSERvation in generalized Virtual NETworks (ReServNet), a Software-Defined Networking platform designed for embedding multi-level virtual networks in physical infrastructures is developed. By defining new softwarized logical functions, ReServNet allows network administrators to create and manage multiple virtual networks on top of the physical network and allocate bandwidth resources to them accordingly. Moreover, the ReServNet framework allows for designing, prototyping, benchmarking and evaluating the performance of different network embedding algorithms easily in real SDN virtualization environments. Different issues related to virtual network embedding on SDN-based physical substrate are also analyzed and discussed in detail

A generalized resource allocation framework in support of multi-layer virtual network embedding based on SDN

Network Virtualization (NV) allows multiple heterogeneous architectures to simultaneously coexist in a shared infrastructure. Embedding multiple virtual networks (VNs) in a shared substrate deals with efficient mapping of virtual resources in the physical infrastructure and is referred to as the Virtual Network Embedding problem (VNE-problem). Although there is recently a number of research work in the area of network virtualization based on the Software-Defined Networking (SDN) technology, virtual network embedding in SDN remains challenging from both theoretical and practical points of view. This article focuses on virtual network embedding strategies and related issues for Infrastructure-as-a-Service (IaaS) paradigms under the constraint of fixed virtual node locations. Special considerations are given to the problems related to resource allocation and link sharing of multi-layer virtual networks on top of the physical substrate. Firstly, a heuristic virtual network embedding algorithm is proposed that can improve the mapping acceptance ratio and resource efficiency in the IaaS context. Secondly, REsource reSERvation in generalized Virtual NETworks (ReServNet), a Software-Defined Networking platform designed for embedding multi-level virtual networks in physical infrastructures is developed. By defining new softwarized logical functions, ReServNet allows network administrators to create and manage multiple virtual networks on top of the physical network and allocate bandwidth resources to them accordingly. Moreover, the ReServNet framework allows for designing, prototyping, benchmarking and evaluating the performance of different network embedding algorithms easily in real SDN virtualization environments. Different issues related to virtual network embedding on SDN-based physical substrate are also analyzed and discussed in detail