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, [email protected]
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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