A Distributed Cloud Architecture Based on General De Bruijn Overlay Network

A Distributed Cloud Architecture Based on General De Bruijn Overlay Network

Osama R. S. Ramadan, Mohamed Yasin I. Afifi, Ahmed Yahya
Copyright: © 2024 |Pages: 19
DOI: 10.4018/IJCAC.339892
Article PDF Download
Open access articles are freely available for download


Distributed cloud systems enable the distribution of computing resources across various geographical locations. While offering benefits like accelerated content delivery, the scalability and coherence maintenance of these systems pose significant challenges. Recent studies reveal shortcomings in existing distributed system schemes to meet modern cloud application demands and maintain coherence among heterogeneous system elements. This paper proposes a service-oriented network architecture for distributed cloud computing networks. Using a De Bruijn network as a software-defined overlay network, the architecture ensures scalability and coherence. Through service-based addressing, requests are issued to designated service address bands, streamlining service discovery. The architecture's evaluation through extensive simulations showcases sustainable scalability and inherent load-balancing properties. The paper concludes with insights into future research directions, emphasizing the extension of the proposed architecture to emerging distributed cloud use cases and decentralized security.
Article Preview

Overlay Networks

An overlay network is a logical network built on top of a physical network that provides an abstract layer with the purpose of overlaying the existing physical network infrastructure. The goal of an overlay network is to allow more flexibility in how data is transmitted and processed, irrespective of the physical network’s technical implementation. It uses the existing infrastructure to connect and allow communication between nodes, while adding an additional layer of abstraction to enable advanced routing and network management algorithms. Creating an overlay on top of an existing physical network enables new mechanisms, protocols, and services to be introduced that can enhance the overall performance and functionality of the system.

Overlay networks are commonly used in a variety of systems and applications, including peer-to-peer (P2P) file-sharing systems, content delivery networks (CDNs), virtual private networks (VPNs), and distributed cloud computing platforms. In each of these applications, the overlay network allows for application-optimized routing and network management algorithms, while abstracting out the details and limitations of the underlying physical network.

Overlay networks represent a crucial building block in the design and implementation of scalable, efficient distributed systems. Their ability to overcome the limitations of the underlying physical infrastructure and provide enhanced functionality makes them a fundamental component in modern networking architectures (Lua et al., 2005).

De Bruijn Graph

A de Bruijn graph, symbolized as G = (V, E), is a form of directed graph commonly used in computer networks and bioinformatics. At its core, this graph provides a structured representation of sequential data, often DNA sequences in genomics or symbol sequences in network routing algorithms.

The set of nodes, denoted by V within a de Bruijn graph, encompasses all possible substrings of a predetermined length, typically referred to as k-mers. K-mers are contiguous sequences of symbols in which the length k determines the size of the substring. For instance, in a networking scenario, a 3-mer (k-mer of length 3) could represent a sequence of three consecutive bytes or characters within a packet payload.

Each node in the de Bruijn graph corresponds to a unique k-mer derived from the original sequence of symbols. The edges, denoted by E, represent transitions between adjacent k-mers. Specifically, an edge (ki, kj) exists if and only if the last k-1 symbols of ki match the first k-1 symbols of kj, indicating a sequential relationship between the two k-mers.

The essence of the de Bruijn graph lies in its ability to compactly capture the sequential relationships between k-mers. This graphical representation simplifies the analysis and manipulation of sequences, facilitating tasks such as genome assembly, sequence alignment, and network routing optimization algorithms.

Complete Article List

Search this Journal:
Volume 14: 1 Issue (2024)
Volume 13: 1 Issue (2023)
Volume 12: 4 Issues (2022): 2 Released, 2 Forthcoming
Volume 11: 4 Issues (2021)
Volume 10: 4 Issues (2020)
Volume 9: 4 Issues (2019)
Volume 8: 4 Issues (2018)
Volume 7: 4 Issues (2017)
Volume 6: 4 Issues (2016)
Volume 5: 4 Issues (2015)
Volume 4: 4 Issues (2014)
Volume 3: 4 Issues (2013)
Volume 2: 4 Issues (2012)
Volume 1: 4 Issues (2011)
View Complete Journal Contents Listing