scholarly journals A Performance Analysis of Point-to-Point Routing along a Directed Acyclic Graph in Low Power and Lossy Networks

2010 ◽  
Author(s):  
W. Xie ◽  
M. Goyal ◽  
H. Hosseini ◽  
J. Martocci ◽  
Y. Bashir ◽  
...  
Keyword(s):  
Performance Analysis ◽  
Low Power ◽  
Directed Acyclic Graph ◽  
Lossy Networks ◽  
Acyclic Graph ◽  
Point To Point ◽  
A Performance

scholarly journals Performance Analysis of Routing Protocol for Low Power and Lossy Networks (RPL) in Large Scale Networks

2017 ◽  
Vol 4 (6) ◽  
pp. 2172-2185 ◽  
Author(s):  
Xiyuan Liu ◽  
Zhengguo Sheng ◽  
Changchuan Yin ◽  
Falah Ali ◽  
Daniel Roggen
Keyword(s):  
Performance Analysis ◽  
Low Power ◽  
Routing Protocol ◽  
Large Scale ◽  
Lossy Networks ◽  
Large Scale Networks

scholarly journals A Review of Intrusion Detection Systems in RPL Routing Protocol Based on Machine Learning for Internet of Things Applications

2021 ◽  
Vol 2021 ◽  
pp. 1-32
Author(s):  
Ali Seyfollahi ◽  
Ali Ghaffari
Keyword(s):  
Machine Learning ◽  
Intrusion Detection ◽  
Low Power ◽  
Routing Protocol ◽  
Directed Acyclic Graph ◽  
Intrusion Detection Systems ◽  
Lossy Networks ◽  
Detection Systems ◽  
Information Object ◽  
Network Router

IPv6 routing protocol for low-power and lossy networks (RPL) has been developed as a routing agent in low-power and lossy networks (LLN), where nodes’ resource constraint nature is challenging. This protocol operates at the network layer and can create routing and optimally distribute routing information between nodes. RPL is a low-power, high-throughput IPv6 routing protocol that uses distance vectors. Each sensor-to-wire network router has a collection of fixed parents and a preferred parent on the path to the Destination-oriented directed acyclic graph (DODAG) graph’s root in steady-state. Each router part of the graph sends DODAG information object (DIO) control messages and specifies its rank within the graph, indicating its position within the network relative to the root. When a node receives a DIO message, it determines its network rank, which must be higher than all its parents’ rank, and then continues sending DIO messages using the trickle timer. As a result, DODAG begins at the root and eventually extends to encompass the whole network. This paper is the first review to study intrusion detection systems in the RPL protocol based on machine learning (ML) techniques to the best of our knowledge. The complexity of the new attack models identified for RPL and the efficiency of ML in intelligent and collaborative threats detection, and the issues of deploying ML in challenging LLN environments underscore the importance of research in this area. The analysis is done using research sources of “Google Scholar,” “Crossref,” “Scopus,” and “Web of Science” resources. The evaluations are assessed for studies from 2016 to 2021. The results are illustrated with tables and figures.

Performance Analysis of the IOTA DAG-Based Distributed Ledger

2021 ◽  
Vol 6 (3) ◽  
pp. 1-20
Author(s):  
Caixiang Fan ◽  
Sara Ghaemi ◽  
Hamzeh Khazaei ◽  
Yuxiang Chen ◽  
Petr Musilek
Keyword(s):  
Performance Analysis ◽  
Internet Of Things ◽  
Directed Acyclic Graph ◽  
Arrival Rate ◽  
Design Parameters ◽  
Optimal Time ◽  
Acyclic Graph ◽  
Layered Model ◽  
Selection Algorithms ◽  
The Impact

Distributed ledgers (DLs) provide many advantages over centralized solutions in Internet of Things projects, including but not limited to improved security, transparency, and fault tolerance. To leverage DLs at scale, their well-known limitation (i.e., performance) should be adequately analyzed and addressed. Directed acyclic graph-based DLs have been proposed to tackle the performance and scalability issues by design. The first among them, IOTA, has shown promising signs in addressing the preceding issues. IOTA is an open source DL designed for the Internet of Things. It uses a directed acyclic graph to store transactions on its ledger, to achieve a potentially higher scalability over blockchain-based DLs. However, due to the uncertainty and centralization of the deployed consensus, the current IOTA implementation exposes some performance issues, making it less performant than the initial design. In this article, we first extend an existing simulator to support realistic IOTA simulations and investigate the impact of different design parameters on IOTA’s performance. Then, we propose a layered model to help the users of IOTA determine the optimal waiting time to resend the previously submitted but not yet confirmed transaction. Our findings reveal the impact of the transaction arrival rate, tip selection algorithms, weighted tip selection algorithm randomness, and network delay on the throughput. Using the proposed layered model, we shed some light on the distribution of the confirmed transactions. The distribution is leveraged to calculate the optimal time for resending an unconfirmed transaction to the DL. The performance analysis results can be used by both system designers and users to support their decision making.

scholarly journals Reactive Discovery of Point-to-Point Routes in Low-Power and Lossy Networks

2013 ◽  
Author(s):  
E. Baccelli ◽  
M. Philipp ◽  
A. Brandt ◽  
J. Martocci
Keyword(s):  
Low Power ◽  
Lossy Networks ◽  
Point To Point

scholarly journals Perbandingan Performa Relational, Document-Oriented dan Graph Database Pada Struktur Data Directed Acyclic Graph

2017 ◽  
Vol 8 (2) ◽  
Author(s):  
Pradana Setialana ◽  
Teguh Bharata Adji ◽  
Igi Ardiyanto
Keyword(s):  
Social Network ◽  
Directed Graph ◽  
Relational Database ◽  
Directed Acyclic Graph ◽  
Performance Test ◽  
Performance Comparison ◽  
Graph Database ◽  
Acyclic Graph ◽  
Database Performance ◽  
A Performance

Abstract. Directed Acyclic Graph (DAG) is a directed graph which is not cyclic and is usually employed in social network and data genealogy. Based on the characteristic of DAG data, a suitable database type should be evaluated and then chosen as a platform. A performance comparison among relational database (PostgreSQL), document-oriented database (MongoDB), and graph database (Neo4j) on a DAG dataset are then conducted to get the appropriate database type. The performance test is done on Node.js running on Windows 10 and uses the dataset that has 3910 nodes in single write synchronous (SWS) and single read (SR). The access performance of PostgreSQL is 0.64ms on SWS and 0.32ms on SR, MongoDB is 0.64ms on SWS and 4.59ms on SR, and Neo4j is 9.92ms on SWS and 8.92ms on SR. Hence, relational database (PostgreSQL) has better performance in the operation of SWS and SR than document-oriented database (MongoDB) and graph database (Neo4j).Keywords: database performance, directed acyclic graph, relational database, document-oriented database, graph database Abstrak. Directed Acyclic Graph (DAG) adalah graf berarah tanpa putaran yang dapat ditemui pada data jejaring sosial dan silsilah keluarga. Setiap jenis database memiliki performa yang berbeda sesuai dengan struktur data yang ditangani. Oleh karena itu perlu diketahui database yang tepat khususnya untuk data DAG. Tujuan penelitian ini adalah membandingkan performa dari relational database (PostgreSQL), document-oriented database (MongoDB) dan graph database (Neo4j) pada data DAG. Metode yang dilakukan adalah mengimplentasi dataset yang memiliki 3910 node dalam operasi single write synchronous (SWS) dan single read (SR) pada setiap database menggunakan Node.js dalam Windows 10. Hasil pengujian performa PostgreSQL dalam operasi SWS sebesar 0.64ms dan SR sebesar 0.32ms, performa MongoDB pada SWS sebesar 0.64ms dan SR sebesar 4.59ms sedangkan performa Neo4j pada operasi SWS sebesar 9.92ms dan SR sebesar 8.92ms. Hasil penelitian menunjukan bahwa relational database (PostgreSQL) memiliki performa terbaik dalam operasi SWS dan SR dibandingkan document-oriented database (MongoDB) dan graph database (Neo4j).Kata Kunci: performa database, directed acyclic graph, relational database, document-oriented database, graph database

Sign in / Sign up

Export Citation Format

Share Document