Simranbir Singh's Fog and Edge Computing Project Analysis

This project delves into the realm of fog and edge computing, recognizing its significance as a cornerstone of the Internet of Things (IoT). The study investigates the computational characteristics and feasibility of applications within challenging scenarios, aiming to create a functional hybrid platform for IoT by integrating fog/edge technology with cloud computing. The project explores the advantages and disadvantages of fog and edge computing, detailing their applications in various fields. The study focuses on minimizing cloud dependency and global internet traffic. The project outlines the methodology, research design, and expected outcomes, including reducing network traffic and creating a hybrid architecture to minimize cloud resource access by offering computation and storage capability in edge devices. The project also includes a schedule for the study, outlining the tasks, subtasks, and time allocated for each phase. The project incorporates literature review, methodology, and design to establish a comprehensive understanding of fog and edge computing within the context of IoT.

FOG AND EDGE
COMPUTING PROJECT
Simranbir Singh
Simr0008

Abstract
 Fog and edge becomes pillar of internet of things. It offers several
emerging things of infrastructure that exploits unlimited resource.
 The study will demonstrate the computing characteristics as well as
evaluating the feasibility of the applications in difficult scenario.
 In addition, the current paper has purposes to create a functional hybrid
platform for IoT through implementing a combination of fog/edge
technology with the combination of cloud technology.

Introduction
 With rapid growth of technology, internet becomes a major part of
human life. Present life requires edge internet for the purpose of
increasing production in several fields like operation as well as control
engineering.
 The innovation of Internet of things (IoT) has a great influence on human
life [3]. Hence, it becomes important to develop a empirical study that
has potential for enriching the lifestyle as well as productivity as utilizing
the process that can be monitored and deployment phase.
 Hence, through an amalgamation of IoT, cloud as well as fog computing
can be incorporated through a higher level of automation resulting more
productivity and creativity.

Background of the study
 Cisco has made a remarkable change in fog technology through
developing the platform and made the application available for fog
computing.
 IOX and Linux enable the resource capability of sharing the developed
devices in the environment. The cloudlet solution produces the generic
edge devices related to the virtual platform deployed through
Openstack+.
 It remains important categorizing the concept to multiple scenarios that
are potential so that anyone can be able to evaluate technical feasibility
as well as projects a design in term of architecture, which can be
effectively be deployed in the IoT associated process.

Significance and purpose of the
study
 The significance of the research is enhancing the livelihood of the
human society. The concept of edge and fog computing remains a
significant part as it makes easier and enhance the living standards by
enhancing production in several fields.
 On the other hand, trying to fulfill the demands, the dependency of the
Cloud can be minimized.
 The purpose of the study is carrying out an investigation regarding the
concept of edge and fog technology that influences livelihood of human
societal live standards.

Aim, objectives and research
questions
 The aim of the study is minimizing the cost of IOT based applications through minimizing
cloud dependency. In addition, minimizing the global internet traffic.
 The objectives of the study are:
 To identify the type of resource needs for the applications based on IOT
 To find out the strength and weakness of cloud based Internet of things that are existing
 The research questions are:
 What is the computational model that is used in the cloud sim?
 What is the connection between internet and cloud computing?
 What are cloud system and its importance?
 What is edge technology and it importance to the current technology?
 What is fog computing?

Literature review
Overview
 Internet of Things: It is a collaboration of several technologies such as
embedded system, wireless sensor network as well as real time
processing system.
 Cloud system: It is considered as a virtualized technology that
provides ability of seamless configuration of the resource.
 Edge technology: it is considered as one of the significant elements of
modern IoT platform. It assists in storing data and improve the
capability to the specific parameters of IoT applications.
 [5]
 Fog computing: Fog computing is a miniature version of cloud
technology.

Overview of the concept
 IoT usually refers to a comprehensive environment that connects a
multitude distinctive physical objects and things like appliance as well
as facilities, for example logistics and manufacturing and agriculture
field applications.
 Fog and Edge computing assists in advancing the cloud-centred Internet
of Things (CIoT) by extending cloud computing model as well as edge
networks of the IoT that engages the participation of the network
intermediate nodes.

Fog and Edge Computing
 Fog and edge computing refers to the ability of getting closer process
data in order to minimize the cost of latency as well as improve the user
experience for the customers.
 The major difference between Fog computing and Edge computing is the
fact that Fog computing pushes the intelligence of data validation into a
local network.
 However, edge computing propels same data validation as well as
intelligence processing onto edge devices like switches and routers.

Applications of Fog and Edge computing
 Fog and edge computing provide elements like in the case of cloud in
IoT through fulfilling several vacancies within cloud and other things for
working towards providing applications in several fields.
 Security: FEC has the ability to ensure safe as well as trustworthy
transactions through providing extra security.
 Cognition: Fog and edge computing assists the client in taking
autonomous decisions related to the process of implementing storage,
computing as well as control functions.
 Agility: FEC also improves the speed of implementing large scope IoT
system.

Role of FEC in storage
 The mechanism of storage of fog and edge computing is associated with
the storing of data.
 It is considered as temporary as well as catching at the nodes of fog and
edge computing.
 Fog and edge computing work in enhancing efficiency as well as
performance of the content information or the content that is to be
delivered.

How does FEC help in
acceleration?
 Fog and edge computing help in providing facilities with networking as
well as the concept of ‘programmable’. The nodes can provide support
and acceleration in the aspects such as networking acceleration and
computing acceleration.
 It assists in the mechanism of network acceleration that is based on
virtualization technology. It can enable the nodes of fog and edge
computing for operating the routing tables parallel as well as realize the
software defined network.

Advantages of Edge and Fog computing
 Use of Fog and edge computing also reduces the local bandwidth costs
by reducing the total bandwidth needed.
 Fog and edge computing is considered is referred as the response of the
procedure through end device. It underpins the internet of things. The
devices produce a continuous data stream and it has to be validated
properly.

Disadvantages of Edge and Fog computing
 Edge and fog computing develops the entire network as well as the
system complicated and increase the time taken for root analysis.
 Edge and fog computing develops the network as well as the system
complicated that increases the time taken for making root analysis.
 The increase of fog and edge computing processing capabilities are
generally moved to the process of decentralized location.

The theory supporting the study
 Design science research methodology will be selected.
 The aim of the methodology is supplying vital information that can
assist the design researchers learning, evaluating and performing vital
aspects of the design science research.

Selection of methodology
 The design Science methodology was opted because it is the best
method that remains used in the collection of the data in the practical
discipline like this.
 The aim of creating new and effective outcome in the empirical study. It
is selected in the design approach in the research strategy. It is
considered as design science.

Proposed methodology
 Identify problem and motivate
 Problem identification can be done by analysing different case studies.
 Different sections and types of problems can be understood by examining
Current as well as an envisioned company versions of bearers and Subject
Matter expertise across businesses.
 A single model of business can be treated as a unit component for analysis.
 Define Objectives Of a Solution [4]
 The method of reviewing the literature body is followed.
 There are three relevant outcomes identified as follows
 1. The natural world of electronic techs,
 2. Model development of specific Business,
 3. Model requirements at the initial stage from last phase are established as
well as extended by theory

Research Design
 Modified IoT platform design
 Generic API design
 Proof of Concept designing
 Analysis of performance

Limitations of the study
 The outcomes of the specific prototype includes a high range of
distinctiveness in the design as well as deployment during comparing
with the real-world product. It will be developed as well as deployed
after the stage of implementation.
 The context where simulation is achieved that is included in the same
terms with the real world context.
 The research is based on the theories that are well-developed.. There is
a scope of inappropriate comprehension of the theories.

Expected Outcome
 1. The sole expectation of this project is to reduce network traffic
by placing a fog node in the overloaded fog nodes.
 2. Secondly, it is the creation of a hybrid architecture that needs to
minimizes the cloud resource access by offering computation as well as
storage capability in edge devices
 3. A common Application program interface needed through which
any type of IoT based applications that utilize the proposed platform in
the application domain.

Schedule of the study
Task: Design of modified IoT platform
Sub Task Time Allocated Start date Finish date
Envisioning 10 hours 2018/10/8 2018/10/8
Preparing 5 hours 2018/10/8 2018/10/8
Prototyping 10hours 2018/10/8 2018/10/8
Architecting 12hours 2018/10/11 2018/10/11
Implementing 8 hours 2018/10/11 2018/10/11
Task: Design of generic API
Sub Task Time Allocated
Design and prototype API 8 hours 2018/10/12 2018/10/12
Building the API 18 hours 2018/10/12 2018/10/12
Publishing the API 08 hours 2018/10/14 2018/10/14
Securing the API from threats 12 hours 2018/10/15 2018/10/17
Proof of Concept designing
Sub Task Time Allocated
Mapping points to the solutions 10 hours 2018/10/18 2018/10/18
Getting the feedback 10 hours 2018/10/18 2018/10/18
Applying the redesign steps 08 hours 2018/10/19 2018/10/20
Performance Analysis
Sub Task Time Allocated
Check for performance by testing 16 hours 2018/10/22 2018/10/22
Review program design and function configuration 16 hours 2018/10/22 2018/10/23

References
1. Polianytsia A., O. Starkovaand K. Herasymenko (2016), "Survey of hardware IoT platforms," 2016
Third International Scientific-Practical Conference Problems of Infocommunications Science and
Technology (PIC S&T), Kharkiv, 2016, pp. 152-153.
2. Grønbæk I (2018), "Architecture for the Internet of Things (IoT): API and Interconnect," 2008 Second
International Conference on Sensor Technologies and Applications (sensorcomm 2008), Cap Esterel,
2008, pp. 802-807.
3. Amazon Web Services. "What is Cloud Computing?". 2013-03-19. Retrieved 2013-03-20.
4. Kuhnen, Eric (2008). "Jumping to SaaS? Take Agile Software Development Along with You". DevX.
QuinStreet. Retrieved
5. H. Xu and B. Li, "Dynamic Cloud Pricing for Revenue Maximization," in IEEE Transactions on Cloud
Computing, vol.1, no.2, pp.158-171, July-December2013.
doi: 10.1109/TCC.2013.15
6. Garcia Lopez, Pedro; Montresor, Alberto; Epema, Dick; Datta, Anwitaman; Higashino, Teruo;
Iamnitchi, Adriana; Barcellos, Marinho; Felber, Pascal; Riviere, Etienne (2015-09-30). "Edge-centric
Computing: Vision and Challenges". ACM SIGCOMM Computer Communication Review. 45 (5): 37–42.
doi:10.1145/2831347.2831354. ISSN 0146-4833.