Fog Computing ( Foggy Cloud)

Presented by:Nazia AlamIffat Anjum

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Fog Computing: Principles,

Architectures, and

Applications

Internet of Things, Chapter 04

Amir Vahid Dastjerdi, Rajkumar Buyya; Morgan Kaufmann 2016

Fog Computing: Helping the Internet of Things Realize Its Potential

Amir Vahid Dastjerdi and Rajkumar Buyya, University of Melbourne; Computer, IEEE, vol. 49, Aug. 2016

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IntroductionIoT environments consist of loosely connected devices that are

connected through heterogeneous networks.

In general, the purpose of building such environmentsis collecting and processing data from IoT devices to mine and

detect patterns, or

perform predictive analysis or optimization and

finally make smarter decision in a timely manner.3

IntroductionThe Internet of Everything (IoE) solutions gradually bring every object

online.

Data is collected and aggregated from IoT devices and sent to the centralized cloud to storage and processing.

But processing data in centralized cloud does not scale to requirements of such environment, where data flows can reach even up to 25000 tuple per second.

There are applications such as health monitoring and emergency response that require low latency

delay caused by transferring data to the cloud and then back to the application can seriously impact the performance.

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IntroductionHere comes the need of alternative paradigm that

capable of bringing the computation to more computationally capable devices

geographically closer to the sensors than to the clouds and that have connectivity to the Internet.

Such devices, which are in the edge of the network and therefore referred to as edge devices,

can build local views of data flows

can aggregate data to be sent to the cloud for further off-line analysis.

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Introduction to Fog ComputingFog computing is a plagiarism,

where cloud computing is extended to the edge of the network to decrease the latency and network congestion.

which manages a highly distributed and possibly virtualized environment that provides compute, storage and network services between end-devices and cloud data centers.

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Introduction to Fog ComputingFog computing essentially involves components of an application

running both in the cloud as well as in edge devices between sensors and the cloud i.e. in smart gateways, routers or dedicated fog devices.

Fog computing is a distributed paradigm that provides cloud-like services to the network edge.

It leverages cloud and edge resources along with its own infrastructure

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Distributed data processing in a fog-computing environment8

Why Fog Computing?Reduction of network traffic

Suitable for IoT tasks and queries

Low latency requirement

Scalability

Raw data management

Monitoring

Resource Provisioning9

Architecture of Fog Computing

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Fog-computing ComponentsFog systems generally use the sense-process- actuate and stream-

processing programming models.

Sensors stream data to IoT networks, applications running on fog devices subscribe to and process the information, and the obtained insights are translated into actions sent to actuators.

Fog systems dynamically discover and use APIs to build complex functionalities.

Components at the resource-management layer use information from the resource monitoring service to track the state of available cloud, fog, and network resources and identify the best candidates to process incoming tasks. 11

Range of applications benefitting from Fog Computing

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Fog Computing ApplicationsHealthcare and activity tracking

Smart utility services

Augmented reality, cognitive systems, and gaming

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Fog Computing ChallengesRealizing fog computing’s full potential presents several challenges

Balancing load distribution between edge and cloud resources,

API and service management and sharing, and

SDN communications.

There are some others like

Enabling real-time analytics

Programming models and architectures

Security, reliability, and fault tolerance

Power consumption

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Foggy clouds and cloudy fogs: a real need for coordinated

management of fog-to-cloud (F2C) computing systems

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Xavi Masip-Bruin, Eva Marín-Tordera, Ghazal TashakorUniversitat Politècnica de CatalunyaCRAAX-UPC, Spain

Admela JukanTechnische Universität BraunschweigGermany

Guang-Jie RenIBM, Almaden Research Center, USAgren@us.ibm.com

IEEE Wireless Communications Magazine

December 2015

IntroductionThe most recent developments in the information and communications technologies area have started to make a profound impact,

through massive connectivity of humans and computers,

massive increase of edge devices carried by humans (i.e. smart phones)

These two major commodities,

have facilitated the true “anywhere, anyhow, anytime” users’ connectivity,

have enabled the data collection, the deployment of new value-added services.

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IntroductionAlthough cloud computing an indispensable communication and computing paradigm for all users and Internet applications, a couple of major limitations remain unsolved in regard to edge-devices.

First, the larger the distance between the cloud and the edge device,

lower the performance,

efficiency of resource usage,

security/reliability guarantees.

Second, cloud computing and storage service notoriously cannot provide guarantees to low latency applications. 17

Introduction to Fog ComputingFog computing is a concept where edge devices and user clients have the capability to compute, store and exchange data among each other and with the cloud

In fog computing, data to be processed is usually close to the user,

It will facilitate the deployment of new services that cloud computing cannot provide particularly those with real time guarantee

A classical example of a fog computing service: emergency medicine service

real-time low-latency constraints associated with implantable medical devices,

emergency car communications, or

mobile access to patient health records.

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Introduction to Fog ComputingFog computing can incorporate the user’s mobility as an inherent feature:

For example,

vehicular fog-clouds can be built by grouping cars located in a parking lot,

roadside clouds can be built by putting together buildings, traffic lights, etc.

Even humans can “group” by creating neighborhoods clouds, ad-hoc communities,

customized dynamic clouds that can be set, released and offered on-demand19

Fog Computing ChallengesFog computing alone is not solution to all difficulties, a few issues needed to be resolved:

Volatility due to intermittent presence

Security and reliability

Business model

Reliability

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Fog-to-Cloud Computing SystemThe author's addresses the need of a joint framework that,

Capable of managing the emerging Fog-to-Cloud (F2C) computing and network architecture

User’s edge devices and IoT devices will continue to leverage the capacities provided by cloud, and gradually include functions innate to fog computing

This joint process will be available to collect, exchange and analyze data.

These services will be provided at either cloud or fog premises, or both, and that according to the required services needs and demands. 21

The Fog-to-Cloud (F2C) ArchitectureF2C is a novel hierarchical architecture consisting of a layered

management structure

It is a dynamic hierarchy, where services can dynamically use and choose

a specific cloud offer (i.e., a specific layer in hierarchy) and

the suitable cloud or fog resources for the service execution (inside each layer).

Provides features for real-time application support, low latency, load reduction and energy efficiency

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Cloud evolution towards fog-to-cloud computing

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The Fog-to-Cloud (F2C): coordinated managementFor the whole ecosystem of Fog-to-Cloud computing to work in a dynamic, collaborative and coordinated way, there are a number of challanges:

Cloud/fogs identificationAn existing cloud capacity must be identified before being used.

Semantic adaptationPerformance and expected capacities are far different depending on the cloud/fog

characteristics.

Coordinated layer orchestrationOverall orchestration is required to generate an individual workflow of actions for each

Service and coordinate the interactions among the different layers involved in the execution of the service.

Cloud resources discovery and allocationA management entity must be responsible for discovering the set of available (visible)

fogs and then choosing those that can best meet the service’s requirements

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The Fog-to-Cloud (F2C): coordinated managementChallenges:

Services execution schedulingService scheduling is required to decide how a service’s individual functions are split

into the different fog layers, and how each layer processes the services

Seamless-transparent managementThe overall performance observed by the client (i.e., the service) must be completely

transparent to the real resources utilized to deploy the service.

QoS guaranteesstrategies to achieve QoS (or near QoS) must be set to guarantee quality including

resource availability, minimization of service response time and improvement of reliability

Security/data privacySecurity and privacy are well-known and currently unsolved challenges in the cloud

arena, and remain as such also in F2C.

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F2C Performance Analysis

Medical emergency scenario for F2C performance evaluation 26

THANK YOU

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