Challenges Associated With Resources For Big Data And Cloud-Based Applications In Smart Cities

Introduction to the problem and domain

Since few years the concept and application smart city is grabbing the attention of the consumers. Though, this application is costly and advanced as well but still certain challenges are associated to it that are to be eliminated soon for the successful implementation of the smart city. In most of the cases the combination between the automation, architecture, infrastructure and environment are not properly formed as a result the entire process become costlier and time consuming at the same time. From technical and privacy point of perspectives certain issues and challenges are always identified related to smart city application. Resource management has been identified as the main issue of cloud technology application in smart city. As cloud allows huge storage thus data management always come up as a major challenge.

Introduction: This section of the paper demonstrates the details of the topic to provide idea to the readers about the application of IoT and the resource wastage in cloud domain and big data challenges. Moreover, the readers will be able to understand the aim and objectives regarding the problems and its relevant solution. 

Literature review: In this section the concept of resource wastage in cloud domain and big data challenges are evaluated through choosing 10 relevant peered review journal papers (secondary data).

Revised problem statement: Depending on the literature the list of requirements for the project are demonstrated in this section. 

Methodology: In order to collect information in context with the topic proper research methodology is needed to be selected 

Proposed solution: Depending on the identified problems a solution has been proposed for the resource management system using IoT in this section.    

This report demonstrates the resource wastage in cloud domain and big data application. Within the urban agendas the concept of smart city is continuously incorporating which is improving the technical atmosphere of the urban areas all over. The new concept of smart city is being currently found in Asia, America and Europe as well. In order to design such smart cities this is mandatory to utilize the advanced development strategies accordingly.

From the promising perspectives of smart city it can be said that, smart application of Internet of things delivers quality life to those people who are associated to such ambiance. The aims, objectives and the problem statement associated to the project are elaborated in this paper. However, in order to conduct the topic this is mandatory to follow accurate research methodology by the researchers in terms of research philosophy, approaches, and research method. Secondary research method is applied for collecting information throughout. 

The aim of the report is to demonstrate the resource wastage in cloud domain and big data applications in the smart city. The challenges and issues of the smart city application are defined and identified in this paper. This is very much important to mitigate the issues and challenges of resource wastage in cloud domain and big data application specifically in the field of smart city design and development.

Smart Cities: Definitions, Dimensions, Performance, and Initiatives

Structure of the report

Albino, V., Berardi, U., & Dangelico, R. M. (2015). Smart cities: Definitions, dimensions, performance, and initiatives. Journal of Urban Technology, 22(1), 3-21.

In this new of technology it is determined that for designing and developing new smart city both the concept of big data analytics and cloud computing are widely used. According to (), crucial measurements of data are required to keep the security and value of smart city. The hidden possibilities as well as competitive advantages of data are aiming to be unlocked by the enterprise owners nowadays. According to the Hadoop market and digital market analysis report it is identified that the revenue structure may reach a rate of $99 Billion (approximately) by 2022 which is currently around $12.90 Billion (approximately) (Lee& Lee, 2015). On the other hand the global business market of big data market can obtain $46.34 Billion by the end of 2018.

Zanella, A., Bui, N., Castellani, A., Vangelista, L., & Zorzi, M. (2014). Internet of things for smart cities. IEEE Internet of Things journal, 1(1), 22-32.

The essence of this article is focused on using the concept of IOT application in the smart cities for managing resources. The resources are all well managed with the help of the OOT application. The dramatic growth is the major challenge in big data application which is another fault in resource management (Zanella et al., 2015). Introduction of new process and storing capacity can eliminate the issues of the big data challenge.

Mohanty, S. P., Choppali, U., & Kougianos, E. (2016). Everything you wanted to know about smart cities: The internet of things is the backbone. IEEE Consumer Electronics Magazine, 5(3), 60-70.

According to the granters the data are predicted to grow by 800% in the upcoming next 5 years. Improper resource management has been identified as a major challenge in the application of big data in cloud computing for effective decision making (Botta et al., 2016). Based on the data those are collected in a large amount must be managed well to improve the opportunities. For any application and technology resources can be discriminated in various segments such as human resources, material resources etc. Proper management of these resources is very much crucial from operational and functional perspectives.

Ejaz, W., Naeem, M., Shahid, A., Anpalagan, A., & Jo, M. (2017). Efficient energy management for the internet of things in smart cities. IEEE Communications Magazine, 55(1), 84-91.

The ideas of Internet of Things (IoT) specifically in smart cities are extremely energy efficient. This journal depicts the energy management for IOT in the smart cities (Ejaz et al., 2017). The concern is compared considering some big data initiatives and big data applications details in the field of public, private as well as other third sectors. Armstrong and Taylor (2014), stated that, in order to design a smart city the concept if internet of things should have to be considered and applied accurately. IOT has the ability to design sustainable structure for the consumers. Most of the renewable resources such as solar energy, wave energy, and thermal power are used for designing the smart city.

Background

If traditional archetype design concept is used for developing a smart city different challenges nay occur. The roles of big data initiatives should be properly analyzed so that the issues of resource wastage can be mitigated accordingly (Fang et al., 2014) .

Bifulco, F., Tregua, M., Amitrano, C. C., & D’Auria, A. (2016). ICT and sustainability in smart cities management. International Journal of Public Sector Management, 29(2), 132-147.

In order to manage a smart city successfully the application of internet communication technology is very much crucial which is demonstrated in this journal (Bifulco et al., 2016). The aim of IOT is to make the application of IOT more impressive and effective at the same time. The way of communication data access and security will become stronger with the application of the IOT for developing smart city.

The sensor technology will become stronger with the installation of surveillance cameras, monitoring instances as well as smart home appliances. The development of the smart city will be foster with the installation of actuators, display, vehicles etc (Kerzner & Kerzner, 2017). Not only this but also, many different domains like home automation, industrial automation, application based healthcare industry, traffic management are the other application of IOT those are necessary for the successful design of the smart city (Arasu et al., 2016). In this journal qualitative research methodology is applied.

Tachizawa, E. M., Alvarez-Gil, M. J., & Montes-Sancho, M. J. (2015). How “smart cities” will change supply chain management. Supply Chain Management: An International Journal, 20(3), 237-248.

The process of supply chain management will be changed if the smart cities are successfully designed and implemented considering all the innovation factors (Tachizawa et al., 2015). The ways through which the smart city can change the supply change management approach are elaborated in this journal. However the paradigm of the smart city is not applicable in the urban or rural locations. For managing the public traffics the so called application the government is also pushing most of the industries to adopt the ICT based solutions.

A smart city is capable of delivering structural health, waste management, reduced traffic congestion, energy consumptions, smart car parking system, automation on the public buildings etc (Tao et al., 2014). Apart from this some other solutions offered by the smart city include noise monitoring to reduce noise pollution, air quality management etc.

Djahel, S., Doolan, R., Muntean, G. M., & Murphy, J. (2015). A communications-oriented perspective on traffic management systems for smart cities: Challenges and innovative approaches. IEEE Communications Surveys & Tutorials, 17.

Communication related to the traffic management process in a smart city is elaborated in this journal. It is comprises of the challenges and approaches of innovation in smart cities. Different challenges are associated to the application of big data in the smart cities. According to Djahel et al., (2015), before entering to any battle generally it is important for the designer and developers to design the concept in such a way so that it can meet all the expected objectives. Big data is defined as a technical tool that is mainly used by the business organizations or making effective decisions. Accurate strategies can structure the technology and develop the solution. The challenges identified for the big data application and cloud computing technology in resource management are as follows:

Aim

Tang, B., Chen, Z., Hefferman, G., Wei, T., He, H., & Yang, Q. (2015, October). A hierarchical distributed fog computing architecture for big data analysis in smart cities. In Proceedings of the ASE BigData & SocialInformatics 2015 (p. 28). ACM.

For successful management of resources in the smart city project the application of fog computing and cloud computing is mandatory. This journal defines the role of distributed fog computing in smart city (Tang et al., 2015). It may happen that the system developer and the analyzer are not having enough knowledge regarding the application of the bid data based solution. Rather it can also be defined as lack of numbers if experts. 

It is found that without proper understanding if big data application is adopted to any project then it will lead to project failure. Lots of time and resources that are assigned for the successful implementation of the project will be a waste if the project designer fails to apply them in the right way (Bi, Da Xu & Wang, 2014).

Gharaibeh, A., Salahuddin, M. A., Hussini, S. J., Khreishah, A., Khalil, I., Guizani, M., & Al-Fuqaha, A. (2017). Smart cities: A survey on data management, security, and enabling technologies. IEEE Communications Surveys & Tutorials, 19(4), 2456-2501.

This articles demonstrates the security issue and data management level issues associated to IOT application in the smart cities (Gharaibeh et al., 2017). Again lots of loss in resources will impact the budget structure of the projects. On job training and development program about the big data application can reduce this specific challenge. The big data solution should have to be monitored and controlled by the top business management authority and the smart city designer.

The big data technology has lots of variety thus, most of the cases the developer become confuse about which one of the tools will be suitable for the specific solution (Yan, Zhang & Vasilakos, 2014). Incorrect selection of the big data tool may lead the project towards business failure. If due to any technical failure any information loss from the server or storage then that cannot be fetched or retrieved easily. In order to resolve this issue backup services should have to be adopted.

Monzon, A. (2015, May). Smart cities concept and challenges: Bases for the assessment of smart city projects. In Smart Cities and Green ICT Systems (SMARTGREENS), 2015 International Conference on (pp. 1-11). IEEE.

The essence of this specific article defines the challenges and concepts related to smart city design based on IOT (Monzon, 2015). Though, big data gives the users a public platform thus, security is referred to as a major components that much be considered by the project designer to avoid further project escalation. If proper security channels and security mechanisms are not adopted then, the confidentiality of the system will be interrupted. In order to resolve this challenge it is mandatory for the project manager to adopt mandatory encryption technology, firewall mechanism etc.

Proper quality management of the information is identified as a major challenge for the big data application. Data integration issues can be resolved by the project leads if the comparison is failed to meet the success criteria and objectives (Shrouf, Ordieres & Miragliotta, 2014). Before using any data that should be compared with rest of the data to make sure that the absolute suitable solution of data has been chosen for designing the final solution

Literature review

Requirements of the project

As per the details in order to design the resource management system using the concept of IOT it is found that all accurate resources are to be identified by the project manager. The concept of IOT involves RFID, near field communication, universal accessibility of mobility and wireless sensor network (Jennings & Stadler, 2015). The information that is stored in the server using cloud technology must have the ability to get retrieved by the users regardless of their location and time as well. The android application users can collect data from the stored server. In case of financial field of application authorized users are only allowed to access data from the server and none of the unwanted users are allowed to retrieve any data without permission. The requirements are again discriminated in two segments such as functional and non functional requirements (Hashem et al., 2015). The details of the requirements are as follows:

• Purpose of the design of the bug data and cloud based resource management system
• Business process
• Security requirements
• Performance
• Data migration
• Data conversion

• Reliability
• Scalability
• Security
• Interoperability

For this project the factor which is chosen is security requirements. In order to maintain the confidentiality of the services and financial details this is mandatory to adopt the mechanism of application firewall and encryption. In this technique a shared key is used by the developers and that must not be shared by any of the external third party. The access for the information are restricted and customized as well. The approach of IOT will be a successful one if all the components are installed accurately for a successful resource management.

Explanation of techniques used in past and present

As the project is based on smart city and the problem identified is about resource wastage in cloud domain as well as big data challenges. The smart city applications are being developed to manage the urban flows in addition to flow for real time purposes. Smartainability approach is used as methodology for estimating with qualitative as well as quantitative information to determine extent the smart cities are sustainable for deployment of smart IoT technologies. Mackey and Gass (2015) stated that there are various tools for analyzing and evaluating performance of smart city to provide with innovative technological solutions. In this particular framework, Smartainability is developed to support the decision makers the benefits of IoT system enables smart services for cities.

This method is used in the article “Smart cities: Definitions, dimensions, performance, and initiatives”. It is used to determine relative importance of indicators as well as sub-indicators. This particular method is dealt with medium sized cities along with perceptions for further development. In order to predict town towards the smart city, various parameters are to be used for the purpose of feasibility of the smart city (Brinkmann, 2014). Fuzzy logic is an efficient way to map input space into the output space. It is easier to understand the basic rules that the rules are to be derived from experts.

 This method is used in the article “Everything You wanted to know about Smart Cities”. The big data is being processed with use of this particular methods as well as tools for retrieving of useful data and information. According to Flick (2015), this method is started with single case and it is included of application of innovative methods for data transformation as well as analysis of unrecognized trends as well as patterns into the data. Linear regression analysis is one of the basic algorithms of the advanced analytics by which people can observe how the input data are related to the output data. It is highlighting the existing literature as well as empirical evidences to redefine existing framework towards the Smart cities.

This method is used in the article “Efficient energy management for the internet of things in smart cities”. Decomposition method is focused on analyzing the components of individuals of time series. This method is used to solve with large scale problems related to big data. In this article, this method is used to handle of big data. As IoT devices into the smart city applications are operated on limited battery, therefore lower power design infrastructure is better for addressing energy management into the IoT based smart cities (Ledford & Gast, 2018). The existing application protocols for the devices are not as per the energy efficiency perspective. Therefore, this method is explored to reduce radio duty cycle of the IoT devices and result to achieve of energy efficiency environment.

 This method is used in the article “How “smart cities” will change supply chain management”. It is used to measure the performance of the city. The big data is being analyzed for the insights which lead to get better decisions as well as strategic movers. The machine learning is considered as field of AI by use of the software applications that can increase accuracy to get expected outcomes.

This method is used in the article “ICT and sustainability in smart cities management”. It is required to perform interviews by use of qualitative before an in-depth interview is gaining an understanding to the answers (Silverman, 2016). The smart city concept is based on developed cities such as Asia, Europe and America. This research is included of respondents from those organizations. The focused is based on Asia, Europe and America countries due to complexity of environment towards development of Smart city. Qualitative research method is based on taking interviews of the managers for various organizations so that the main issues in cloud domain related to resource management are identified  (Ledford & Gast, 2018). It is used for analyzing and evaluating the non-numerical data. It is applied to such study where there is involvement of relationships among the individuals and business environments (Smith, 2015).

Factors	Fuzzy method	Advanced analytics and algorithmic method	Decomposition method	Machine learning	Qualitative methods
Definition	It is used to determine relative importance of indicators as well as sub-indicators	It is included of application of innovative methods for data transformation as well as analysis of unrecognized trends.	Decomposition method is focused on analyzing the components of individuals of time series.	The big data is being analyzed for the insights which lead to get better decisions as well as strategic movers.	It is based on taking interviews of the managers for various organizations so that the main issues in cloud domain related to resource management are identified.
Feature	It is form of valued logic where the truth values of the variables are real number in between 0 and 1.	It is measuring the predictor variables into the business models.	This method is developed to discover aggregate attributes as well as descriptions.	It is measurable to the phenomenons which are observed. It is consisted of effective algorithms into the pattern recognitions.	It is based on understanding the situations and elimination responds to the opportunities towards new paths.

Explanation of technology suits the IoT application

The smart city is described as city which allows real world urban data to collect as well as analyze by use of software or IoT system, server architecture and network infrastructure along with client services. In this study, IoT applications are implemented as proposed solution to the smart city project. It is consisted of solutions with support of instrumentation as well as interconnection of sensors along with mobile devices (Tao et al., 2014). It is included with service production which exploits of accessible information and adopts of information flows among the urban regions. The proposed problem in this paper is about resource wastage in the cloud domain and big data challenges.

The smart city is consisted of optimal utilization of natural resources, safer and better cities by efficient regulation of traffic system in addition to well-organized emergency system(Qu et al., 2016). The smart city concept is included with the application of IoT system that allows cities to better use of urban networking. It supports better economic growth which is resulted into efficient and technological solution to deal with the city challenges. The IoT system is installed near buildings where there is exchange of information with others and sends of information to server through use of wireless communication (Thota et al., 2018). The IoT system processes some of data management activities such as query, storage, and execution of semantics to capture proper meaning of information from the massive data efficiency. There is improvement of resource usage in IoT by use of resource management system where the smart devices are being accessed on single platform and also handle of real time information for the smart devices.

IoT resource management system is given reliable way to remote monitoring as well as controlling of sensor devices with no overridden of resources (Fan et al., 2014). The proposed system enables resources to access and control along with manage the business operations of Smart city project. IoT system serves communities across various domains. Because of huge number of network elements interacted and worked used of IoT based information system, there is required of resource management system to run IoT operations. The resources are managed by implementation of protocols, and processes to enhance reliability into the IoT operations (Bera et al., 2018). There is domain of resource management throughout operations of IoT based on the information systems.

Figure 1: IoT based Resource Management System

(Source: Aazam& Huh, 2015, pp-689)

The main activities of resource management system are resource modelling, discovery, estimation, allocation as well as resource monitoring. Based on the resource wastage issues, the data management activities are involved such as queries which are used to filter data required and data extracted from the query are being stored into the folder and space in IoT devices. It also helps to manage power as well as processing time (Aazam& Huh, 2015). By use of IoT system, sensors as well as IoT devices are not integrated with cloud by enabled to utilize of cloud related services.

Figure 2: The growth revenue of the system

(Source:Zanella et al., 2014, pp-30)

 IoT resources are become a part of the cloud resource pool along with shared of service cloud resources. Therefore, IoT based resource management system is considered as best solution for resources wastage issue and big data challenges (Fan et al., 2014). There are huge amount of data that are generated by the sensor objects of real world into the IoT system. The IoT applications are complex processing which are included of historical data along with time series analysis.

Figure 3: Global growth of smart city application and percentage of revenue till 2018

(Source: Lee & Lee, 2015, pp-436)

Factors of IoT system	Description
Functional requirement	Wireless connections, devices which are ranged with higher performance systems. There is also required of proper security of the system (Thota et al., 2018).
Platform	There is such an IoT platform with protocol support for data integration.
Hardware requirements	Power sources, memory storage, wireless communication, sensors and Smartphone (Aazam& Huh, 2015).

From the above table, it is seen that the proposed IoT system should be helpful to manage with the resource wastage as well as big data issues in Smart city project work.

References

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