Cloud computing is highly being used for several years for various purpose s. From daily tasks, such as reading e-mails, watching videos to the factory automation and device control, it changed where the data is being processed and how it is accessed. However, increasing number of connected devices brings problems, such as low Quality of Service (QoS) due to infras-tructure resources and high latency because of the bandwidth limitations. The current tendency to solve the problems that the Cloud computing has is performing the computations as close as possible to the device. This paradigm is called Edge Computing. There are several proposed architectures for the Edge Computing, but there is no an accepted standard by the community or the industry. Besides, there is not a common agreement on how the Edge Computing architecture physically looks like. In this paper, we describe the Edge Computing, explain how its architecture looks like, its requirements, and enablers. We also define the major features that one Edge Server should support.
Table of Contents
1. INTRODUCTION
2. ARCHITECTURE DESIGN
3. CONCLUSION AND FUTURE WORK
Research Objectives and Topics
The primary objective of this paper is to explore the paradigm of Edge Computing as a solution to the latency and bandwidth limitations inherent in traditional Cloud Computing architectures. The work focuses on defining a modular and extensible Edge Server architecture, detailing its fundamental requirements, and explaining the communication flow between end-devices and the Edge tier.
- Evolution of connected devices and Internet of Things (IoT) growth.
- Limitations of Cloud Computing, specifically latency and Quality of Service (QoS).
- Design of a modular Edge Server architecture.
- Key requirements for Edge Computing including interoperability, scalability, and security.
- Future implementation and simulation of Edge Server components.
Excerpt from the Book
2. ARCHITECTURE DESIGN
Edge Computing adds an additional tier between the Cloud and IoT devices for computing and communication. The data produced by the devices themselves are not directly sent to the Cloud or back-end infrastructure, but initial computing is performed on this tier. Considering the number of connected devices and the data they produced, this tier is used to aggregate, analyse, and process the data before sending it into the upper layer, the infrastructure. Figure 2 depicts the proposed core functionalities for an Edge Server.
The proposed Edge Server architecture is to be designed modular and should provide functionalities for real-time and non-real-time control, as well as real-time communication.
Core node runs on an operating system and tracks resources and makes decisions on where to execute a task. In the proposed architecture, addition of a new hardware or software modules enable new functionalities and improve the usability of the server. For example, in the case that machine learning algorithms are desired to be executed on the server, connecting a dedicated artificial intelligence (AI) module with dedicated Graphics Processing Unit (GPU) should require none to minimal configuration to be active.
Summary of Chapters
1. INTRODUCTION: This chapter introduces the proliferation of connected IoT devices and highlights the resulting performance bottlenecks in Cloud Computing, positioning Edge Computing as the necessary evolutionary paradigm.
2. ARCHITECTURE DESIGN: This chapter details the proposed modular Edge Server architecture, emphasizing the roles of the core node, real-time control, and the functional requirements necessary to manage data offloading efficiently.
3. CONCLUSION AND FUTURE WORK: This chapter summarizes the findings regarding the Edge Computing architecture and outlines the next steps, including software/hardware component selection and simulation-based validation.
Keywords
Edge computing, Extensible Architecture, Cloud computing, Internet of Things, IoT, latency, Quality of Service, QoS, Edge Server, scalability, interoperability, data aggregation, modularity.
Frequently Asked Questions
What is the core focus of this research paper?
The paper focuses on the definition and architectural design of Edge Computing, a paradigm designed to process data closer to end-devices to mitigate the limitations of centralized Cloud Computing.
What are the primary challenges addressed by Edge Computing?
It addresses high latency, bandwidth limitations, and low Quality of Service (QoS) caused by the massive increase in connected IoT devices that rely on centralized Cloud resources.
What is the ultimate goal of the proposed architecture?
The goal is to create a modular, extensible Edge Server architecture that can handle real-time and non-real-time control, as well as data aggregation and analysis, before transmitting data to the Cloud.
Which scientific approach does the author use?
The author uses a descriptive and design-based approach, analyzing current industry trends and system requirements to propose a new, modular framework for Edge Servers.
What content is covered in the main body of the work?
The main body covers the rationale behind moving computing to the "edge," the proposed architectural design including core nodes and gateways, and the essential requirements such as interoperability, security, and abstraction.
Which keywords best describe this work?
Key terms include Edge computing, Extensible Architecture, IoT, latency, QoS, scalability, and Edge Server.
How does the proposed architecture handle AI-related tasks?
The architecture allows for modular expansion; for instance, adding an AI module with a dedicated GPU requires minimal configuration, enabling the server to handle advanced computing tasks efficiently.
Why is the "extensible" aspect of the architecture important?
Extensibility is crucial because computing technology evolves rapidly; the architecture is designed to allow for the easy deployment of new services and hardware components as processing requirements increase over time.
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- Ajit Singh (Autor:in), 2018, Extensible Edge Computing Architecture, München, GRIN Verlag, https://www.grin.com/document/488802
