FOG COMPUTING PDF
𝗣𝗗𝗙 | Fog Computing extends the Cloud Computing paradigm to the edge of the network, thus enabling a new breed of applications and services. Defining. PDF | In Cloud Computing, all the processing of the data collected by the node is done in the central server. This involves a lot of time as data has to be. Cisco and/or its affiliates. All rights reserved. This document is Cisco Public. Page 1 of 6. White Paper. Fog Computing and the Internet of Things: Extend.
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Keywords: Internet of Things; cloud of things; fog computing; fog as a service; IoT with fog computing; cloud pdf (accessed on 8 April ). cloud computing; cloudlet; edge computing; fluid computing; fog computing; fluid yazik.info taxonomy of Fog computing according to the identified challenges and its this sense, Fog computing better meets the requirements with respect to IoT appli-.
Some studies modify the OpenFlow control message operation to reduce flow setup latency and boost network throughput [ 24 ] or utilize hardware, such as a multi-core architecture [ 49 ] or a GPU [ 22 ]. However, those studies did not resolve the performance bottleneck in Linux, which limits the baseline of performance improvement. Our optimization techniques improve the performance baseline even better by optimizing the network stack in Linux, and so, other techniques for SDN controllers can benefit from our techniques.
Previous studies developed techniques to overcome the limitations of existing SDN controllers in terms of isolation and performance. However, they focused on enhancing the internal architecture of SDN controllers or introducing additional components, which still limits the degree of isolation and performance.
In terms of isolation, existing techniques are still implemented as user-level processes. As SDN controllers running on the same physical server share the same OS such as Linux, a misbehaving controller can affect others quite easily.
With regard to performance, because major performance bottlenecks in the network stack of the OS were not resolved in the previous work, their improvement is limited by complex network processing of the existing OS.
We aim to overcome the limitations of control planes running as user-level processes by developing two optimization techniques for Linux: SE2 and SP2.
SE2 provides stronger isolation between control planes using virtual machine abstraction, which offers an independent Linux environment to each control plane in order to prevent a controller from affecting other control planes.
Furthermore, SP2 revises the existing network stack of Linux and offers faster packet processing for control planes. Design This paper presents two optimization techniques for Linux specifically to enhance the isolation and performance of control planes in SDN.
In this section, we describe the design goals of our approaches and explain the details of the proposed techniques.
Enhancing the Isolation and Performance of Control Planes for Fog Computing
Design Goals In developing optimization techniques, we focus on three principal goals as follows. Running existing SDN controllers and control applications without modification: Most of the SDN controllers and control applications are based primarily on Linux.
Providing isolated execution environments while removing dependency on specific hardware: To be used in an existing SDN deployment, we provide a general execution environment architecture, which is not dependent on specific hardware. In addition, the control plane in the execution environment does not affect other control planes, when multiple control planes are co-located in the same physical server.
Guaranteeing high control plane performance compared to existing Linux: Even though several studies improved the control plane performance, they focused on optimizing the control plane itself, leaving room for further improvement: the Linux kernel. We aim to achieve high performance of control planes during packet processing by optimizing the network stack of Linux.
By satisfying three design goals, SE2 and SP2 can improve the deployment and the network performance of fog computing. First, SE2 allows different types of networks in the fog such as 3G, LTE and WiFi to be managed simultaneously in an independent manner by running multiple controllers in each isolated environment. In addition, when virtual networks interconnect geographically-dispersed fog clouds, SE2 can offer different execution environments to the control plane of each virtual network.
This enables the tenants of different virtual networks in the fog to control their own virtual network independently of other virtual networks. For example, when a smart grid management application and a smart lighting application construct their own virtual networks individually, SE2 allows the two virtual networks to be managed independently by employing their different control planes in each isolated environment.
Cloud computing makes computing that makes computing resources available over the resources such as hardware, application Internet on a utility costing basis.
Cloud computing development platform and computer offers many advantages to users in terms of reduced applications available as services over the cost, elimination of system administrative functions, Internet. The services made available this increased flexibility, better reliability and location manner are commonly known as Infrastructure independence.
Though these are definite advantages, cloud computing also suffers from as a Service IaaS , Platform as a Service certain limitations. Hosting of cloud data centres in the Internet layers as how they are stacked on each other. Also location layer provide the required platform along the independence of processing in cloud computing with necessary security and isolation for may also not desirable for certain types of networks multiple systems to run simultaneously.
Fog Computing in the Internet of Things
These services are known as location aware services and require location dependent fast processing. In order to overcome these limitations, researchers have proposed a new cloud computing model called fog computing where the cloud system is located either at the edge of the private network or very close to it. In this paper, the authors take an in depth look at both these technologies to investigate fog Figure 1 Layers of Cloud Computing computing can reliably overcome the limitations of cloud computing and effectively replace it and Cloud computing provides many advantages to become the de facto cloud computing model of the users compared to traditional download, own future.
Users can access the cloud Cloud computing has gained the attention of services and pay for only the services accessed both users and service providers as the most on a utility costing basis .
Section 3 introduces Fog Similar to this, cloud computing services are Computing the emerging cloud computing also priced on a per unit time basis irrespective model along with its features, advantages and of how much of resources were used.
As all the disadvantages. Sections 4 presents an in-depth computing hardware and software is hosted in a analysis and cloud computing and fog remote data centre owned and operated by a computing based with respect to their service provider, the clients can only capabilities. Finally Section 5 concludes by concentrated on their core business functions.
Prior to the arrival of cloud computing, computing resources including Though cloud computing has so many hardware and software were downloadd outright advantages, it also suffers from certain and installed in house at a data centre shortcomings too. These shortcomings include maintained by the organization or hardware was the requirement of high capacity bandwidth leased from a public data centre on a fixed client access link, high latency and security charges .
The hardware resources leased ,,.
These limitations have heavy from data centres were of fixed capacity similar impacts on certain kinds of computing needs to the hardware installed in house irrespective such as sensor networks and especially the of the usage. The downside of this kind of emerging Internet of Things paradigm that arrangement is, most of the time hardware thus envisages to have every device on the Internet downloadd or leased idle due to under loading .
In order to overcome the limitations of wasting precious financial capital that could be cloud computing to meet the demands of invested on some other resource or the core emerging computing models and paradigms, business operations .
If the hardware was new kind of cloud computing model has been undersized, the performance would suffer proposed by researchers. Hence network or very close to it rather than far away both over capacity as well under capacity in an unknown location in the middle of the affects the profitability of business operations. Internet cloud. This kind of cloud computing On the other hand hardware leased from a cloud model has been given the name "Fog service provider does not require any upfront Computing".
In this paper, we embark on a investment and the charges are based on usage. As there limitations of the current cloud computing is no initial investment on computing resources model and respond to the changing demand of and only usage charges need to be paid, cloud the users and emerging computing paradigms.
In addition to releasing the additional benefit of widespread collaboration capital, cloud computing also protects the users between users across large geographical area from resource starvation as the cloud based irrespective of where they are physically resources are elastic that can respond to the residing or working from.
This feature is very demands dynamically . The dynamic handy for application developers as it is resource provisioning property of cloud possible to have a multinational workforce computing allows the resource provisioning to working on a single project without leaving follow the demand pattern dynamically even their place of origin.
Cloud systems can also be considered to be more reliable than in-house maintained systems The other advantage of cloud computing is its as the backup and disaster management layered architecture that allows customers to facilities are generally a part of the service download services at different levels of provider's offerings .
The availability and abstractions commonly known as IaaS, PaaS operation of backup and disaster management and SaaS . Like in traditional leasing of systems are transparent to the ultimate users. Customers can download infrastructure can be spread across a large computing resources at hardware level, customer base. downloading resources at 2. PaaS provides it has certain limitations as well . The the application developers a ready-made prominent limitations of cloud computing platform comprising operating system, include requirement of high speed reliable development and testing tools, project Internet connectivity and sometimes multi- management applications and deployment tools homing to avoid link outages, high latency, that can be customized to suit their undefined security etc ,,.
The requirements. Hence, the applications emerging trends in networking such as large developers can get on with their jobs with distributed Internet connected sensor networks, minimal delay as all the required tools are Internet of Things IoT , mobile data networks readily available. On the other hand SaaS and also real time streaming applications have provides the customers ready-made web based characteristics that cannot be satisfied by cloud applications that can be personalized and used computing .
PaaS and SaaS also relive the customers from the hassle of downloading Since cloud computing is basically Internet and managing software licenses .
If the link outage occurs independence as a user can access the system or due to any reason the total system would be application from anywhere with an Internet unreachable making a total blackout. Multi- connection and a standard web browser . Similarly the availability of the very expensive and technically more involved cloud systems can also be attacked using in setting up multi-homing computer networks various methods . Thus it can be seen that . Because of the non-homogeneous The term "Fog Computing" was introduced by and loosely controlled nature of the Internet, the Cisco Systems as new model to ease there are many issues especially quality of wireless data transfer to distributed devices in service related ones remain unresolved.
One the Internet of Things IoT network paradigm such issue that affects the quality of service ,. According to Bonomi et al. Real time rationale for coining this term to identify this applications with which users directly interact model is that fog is nothing but cloud that is with are badly affected by delay and delay jitter closer to the ground.
Hence cloud computing caused by latency in networks .
It is very carried out closer to the end users' networks is difficult to control the delay and delay jitter thus identified as fog computing. Fog arising from latency in a network of Internet computing is a virtualized platform that is scale. Most importantly, the Internet typically located between end user devices and architecture has been originally designed to be the cloud data centres hosted within the Internet a quality of service and security agnostic one as . Thus fog computing can provide better ensuring availability was of paramount quality of service in terms of delay, power importance those days .
Still major portion consumption, reduced data traffic over the of the original design principles of the Internet Internet etc . The main feature of fog stays intact and not going to change in the computing is its ability to support applications future unless there is a wholesale change with a that require low latency, location awareness and design and implementation of a new Internet. This ability is made possible by the Hence it is safe to say that latency and the fact that the fog computing systems are issues caused by latency are not going to be deployed very close to the end users in a widely resolved in the near future.
Fog computing nodes thus hosted must possess sufficient computing The other major issue confronted with cloud power and storage capacity to handle the computing is security and privacy . Since the resource intensive user requests. Other similar cloud systems have been located with the concepts where the computing resources have Internet, user requests, data transmission and been proposed to be located closer to the users system responses need to traverse a large to overcome the limitations of cloud computing number of intermediate networks depending on include cloudlets and edge computing ,.
Seminar Report.pdf - SEMINAR REPORT ON FOG COMPUTING
When customer data is out there in a public Cloudlets are resource rich computer or a cloud, there is a risk of them being cluster of them with the virtualization capability compromised of their integrity and and located closer to mobile users, so that they confidentiality . Deeper the data inside the can respond to their requests fast while Internet, higher the risk as the data has to travel maintaining a strong Internet connectivity .
Satyanarayanan et al. But on the contrary, the users in order to meet the requirements of emerging applications and paradigms such as emerging computing and networking scenarios, interactive media, augmented reality, natural they all in fact have the same or very similar language processing, speech recognition etc.
PaaS vs. Connecting your company to the cloud, you get access to the above-mentioned services from any location and via different devices.
Hence, availability is the greatest advantage. Moreover, there is no need to maintain local servers and worry about downtimes — the vendor supports everything for you, saving you money. The integration of the Internet of Things with the cloud is a cost-effective way to do business. Off-premise services provide the necessary scalability and flexibility to manage and analyze data gathered by connected devices, while specialized platforms e.
Pros of Cloud for IoT Since connected devices have limited storage capacity and processing power, the integration with cloud computing comes to assistance: Improved performance the communication between IoT sensors and data processing systems is faster Storage capacities highly scalable and unlimited storage space are able to integrate, aggregate and share the enormous amount of data Processing capabilities remote data centers provide unlimited virtual processing capabilities on-demand Reduced costs license fees are lower than the cost of the on-premise equipment and its continuous maintenance Cons of Cloud for IoT Unfortunately, there is nothing immaculate, and cloud technology has some downsides, especially for the Internet of Things services.
Public Cloud Computing Fog Computing The term fog computing or fogging was coined by Cisco in , so it is new for the general public. Fog and cloud computing are interconnected. In nature, fog is closer to the earth than clouds; in the technological world, it is just the same, fog is closer to end-users, bringing cloud capabilities down to the ground.
The definition may sound like this: fog is the extension of cloud computing that consists of multiple edge nodes directly connected to physical devices.
Such nodes are physically much closer to devices if compared to centralized data centers, which is why they are able to provide instant connections. The considerable processing power of edge nodes allows them to perform the computation of a great amount of data on their own, without sending it to distant servers. Fog can also include cloudlets — small-scale and rather powerful data centers located at the edge of the network.
Their purpose is to support resource-intensive IoT apps that require low latency. The main difference between fog computing and cloud computing is that cloud is a centralized system, while the fog is a distributed decentralized infrastructure.Secure vicinity location has turned out to be a standout amongst the most important viewpoints in our everyday daily schedule. As there limitations of the current cloud computing is no initial investment on computing resources model and respond to the changing demand of and only usage charges need to be paid, cloud the users and emerging computing paradigms.
Let us suppose that two tenants A and B have their own virtual networks [ 51 ] and run their control planes in different execution environments provided by SE2. This document also contains the difference between the fog computing and cloud computing.
Services are hosted at the network edge or even end devices such as set-top-boxes or access points. In spite of the attractive solutions found in fog computing, it also inherited some security problems from the cloud.
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