Fog Computing：边缘计算的革新与IoT中的关键角色

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Fog Computing是一种新兴的计算模型，它将云计算的概念延伸到了网络边缘，旨在提供低延迟、地理位置感知以及高度可扩展的服务。这一创新主要源于对物联网(IoT)环境中特定需求的响应，这些需求包括但不限于： 1. 低延迟和位置感知：与云端处理相比，Fog Computing能够减少数据传输至中心服务器的时间，通过在接近设备或用户的地方进行计算，显著降低了响应时间，特别适用于实时应用如自动驾驶、远程医疗等。 2. 广泛的地理分布：由于Fog节点分散在各种地理位置，无论是工业设施、公共空间还是个人设备，都能形成一个分布式计算网络，增强了服务的可达性和可靠性。 3. 移动性支持：Fog适应于移动设备和物联网设备的流动性，可以在设备移动时提供持续的服务，比如智能家居或无人机的控制。 4. 大量节点：由于Fog由无数小型、嵌入式设备组成，如传感器、路由器等，这种庞大的节点数量使得大规模数据处理和分析成为可能。 5. 无线接入为主：无线通信技术在Fog中扮演核心角色，确保了节点之间的无缝连接，无需依赖复杂的有线基础设施。 6. 流媒体和实时应用：Fog为实时视频流、直播、游戏等对延迟敏感的应用提供了理想的环境，因为数据处理和分析可以快速响应变化。 7. 异构性：由于Fog涉及多种硬件平台和软件环境，它必须具备良好的兼容性和自适应性，以支持多样化的设备和服务。论文作者Vinod Pande等人认为，正是这些特性使得Fog Computing成为物联网时代中许多关键应用的理想平台。它不仅提升了用户体验，还为工业自动化、智慧城市等领域带来了新的机遇和挑战。随着技术的发展，Fog Computing将持续优化资源分配，提高效率，推动未来智能世界的构建。

Vinod Pande et al. Int. Journal of Engineering Research and Application www.ijera.com

ISSN : 2248-9622, Vol. 6, Issue 10, ( Part -4) October 2016, pp.7-11

www.ijera.com 7 | P a g e

A Review- Fog Computing and Its Role in the Internet of Things

Vinod Pande*, Chetan Marlecha**, Sangramsing Kayte ***

*(Department of Computer Science & IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad,

India)

**(Department of Computer Science & IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad,

India)

***(Department of Computer Science & IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad,

India)

ABSTRACT

Fog computing extends the Cloud Computing paradigm to the edge of the network, thus enabling a new breed of

applications and services. Dening characteristics of the Fog are: a) Low latency and location awareness; b)

Wide-spread geographical distribution; c) Mobility; d) Very large number of nodes, e) Predominant role of

wireless access, f) Strong presence of streaming and real time applications, g) Het-erogeneity. In this paper we

argue that the above characteristics make the Fog the appropriate platform for a number of critical Internet of

Things (IoT) services and applications, namely, Connected Vehicle, Smart Grid , Smart Cities, and, in general,

Wireless Sensors and Actuators Net-works (WSANs).

Keywords: Fog Computing, Cloud Computing, IoT, WSAN, Software Dened Networks, Real Time Systems,

Analytics.

I. INTRODUCTION

The pay-as-you-go Cloud Computing

model is an ecient alternative to owning and

managing private data centers (DCs) for customers

facing Web applications and batch processing.

Several factors contribute to the economy of scale of

mega DCs: higher predictability of massive aggre-

gation, which allows higher utilization without

degrading performance; convenient location that

takes advantage of inexpensive power; and lower

OPEX achieved through the deployment of

homogeneous compute, storage, and networking

components.

Cloud computing frees the enterprise and

the end user from the speciation of many details.

This bliss becomes a problem for latency-sensitive

applications, which require nodes in the vicinity to

meet their delay requirements. An emerging wave of

Internet deployments, most notably the Internet of

Things (IoTs), requires mobility support and geo-

distribution in addition to location awareness and

low latency. We argue that a new platform is needed

to meet these requirements; a platform we call Fog

Computing [1], or, briey, Fog, simply because the

fog is a cloud close to the ground. We also claim that

rather than cannibalizing Cloud Computing, Fog

Computing enables a new breed of applications and

services, and that there is a fruitful inter-play

between the Cloud and the Fog, particularly when it

comes to data management and analytics.

This paper is organized as follows. In the

second section we introduce the Fog Computing

paradigm, delineate its characteristics, and those of

the platform that supports Fog services. The

following section takes a close look at a few key

applications and services of interest that substantiate

our argument in favor of the Fog as the natural

component of the platform required for the support

for the Internet of Things. In the fourth section we

examine analytics and big data in the context of

applications of interest. The recognition that some of

these applications demand real-time analytics as well

as long-term global data mining illustrates the

interplay and complementary roles of Fog and

Cloud. We conclude with comments about the state

of the Fog Computing and discussion of future work.

II. THE FOG COMPUTING

PLATFORM

Fog computing, also known as fogging, is a

model in which data, processing and applications are

concentrated in devices at the network edge rather

than existing almost entirely in the cloud. That

concentration means that data can be processed

locally in smart devices rather than being sent to the

cloud for processing. Fog computing is one approach

to dealing with the demands of the ever-increasing

number of Internet-connected devices sometimes

referred to as the Internet of Things (IoT).

In the IoT scenario, a thing is any natural or

man-made object that can be assigned an IP address

and provided with the ability to transfer data over a

network. Some such things can create a lot of data.

Cisco provides the example of a jet engine, which

they say can create 10 terabytes (TB) of data about

its performance and condition in a half-hour.

RESEARCH ARTICLE OPEN ACCESS

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