A new framework to integrate wireless sensor networks with cloud computing

Shah, Sajjad Hussain; Khan, Fazle Kabeer; Ali, Wajid; Khan, Jamshed

doi:10.1109/aero.2013.6497359

Cited by 26 publications

(11 citation statements)

References 9 publications

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“…Because each application manages both of physical sensors and sensor data, users, having no specialty physical sensors, cannot use the specialty monitoring system directly. The objective of an integration framework between cloud computing and WSNs is to facilitate the shift of sensor data from WSNs to the cloud computing environment so that the scientifically and economically valuable data may be fully utilized [5][6][7][8].…”

Section: Related Workmentioning

confidence: 99%

An Integrated Framework for Analysis and Mining of the Massive Sensor Data Using Feature Preserving Strategy on Cloud Computing

Song

Wang

Gao

2014

2014 Seventh International Symposium on Computational Intelligence and Design

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Cloud computing can provide a powerful, scalable storage and the massive data processing infrastructure to perform both online and offline analysis and mining of the heterogeneous sensor data streams. In contrast to traditional data objects, the sensor data objects from the Internet of Thing (IoT) monitoring application have continuously changing, high-dimensional, spatiotemporal relation and heterogeneous attributes. Therefore, the analysis and mining problem of the massive sensor data objects can be more complicated. The paper formally presents an integrated framework for analysis problem of the massive sensor data with insights into the high-dimensional problem using the feature preserving on cloud computing. The proposed framework realized the cloud resources independent dynamic allocation and scheduling for the massive sensor data mining using kernel methods for reducing the computation of spatial data retrieval. As the experiment results shown, the strategy can preserve important spatial feature information and provide effective preprocessing analysis results.

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Section: Related Workmentioning

confidence: 99%

An Integrated Framework for Analysis and Mining of the Massive Sensor Data Using Feature Preserving Strategy on Cloud Computing

Song

Wang

Gao

2014

2014 Seventh International Symposium on Computational Intelligence and Design

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“…According to Cisco 1 , the sensor market is going to be a $19 trillion market within the coming years, including a projected $2.9 trillion market for manufacturing. In 2013, International Data Corporation (IDC) 3 , the global IoT market stood at around $1.9 trillion, and around 90 percent of all IoT devices being installed in the world's developed regions. Based on IDC's predication, the global IoT market is expected to grow by more than $5 trillion over the next six years, will research to $7.1 trillion by 2020.…”

Section: Introductionmentioning

confidence: 99%

“…As the advance of the Internet of Things (IoT), more machine-to-machine sensors and devices are connected to the Internet [1][2][3]. These sensors and devices generate sensor-based big data and bring new business opportunities and demands for creating and developing sensor-oriented big data infrastructures, platforms and analytics service applications.…”

Section: Introductionmentioning

confidence: 99%

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Big Data Sensing and Service: A Tutorial

Gao

Lei

2015

2015 IEEE First International Conference on Big Data Computing Service and Applications

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As the advance of the Internet of Things (IoT), more M2M sensors and devices are connected to the Internet. These sensors and devices generate sensor-based big data and bring new business opportunities and demands for creating and developing sensor-oriented big data infrastructures, platforms and analytics service applications. Big data sensing is becoming a new concept and next technology trend based on a connected sensor world because of IoT. It brings a strong impact on many sensor-oriented applications, including smart city, disaster control and monitor, healthcare services, and environment protection and climate change study. This paper is written as a tutorial paper by providing the informative concepts and taxonomy on big data sensing and services. The paper not only discusses the motivation, research scope, and features of big data sensing and services, but also exams the required services in big data sensing based on the state-of-the-art research work. Moreover, the paper discusses big data sensing challenges, issues, and needs.

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“…In a WSN, the major issue with the deployment of sensors is the data storage, because sensors have temporary memory to store data and then send it to an end destination that can be a data repository [36]. The combination of a WSN with a cloud facilitates the network to store data on the cloud [37].After an in-depth study of the literature, the authors of References [1,8,38] integrated a wireless sensor network with a cloud network. Their proposed framework has been updated, and the authors of this present article proposed their own WSN-cloud framework which is presented in Figure 1.An in-depth analysis was performed for fuzzy evaluations to explain the synthetic priority weights for each criterion.…”

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confidence: 99%

Prioritization of Information Security Controls through Fuzzy AHP for Cloud Computing Networks and Wireless Sensor Networks

Tariq

Ahmed

Memon

et al. 2020

Sensors

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With the advent of cloud computing and wireless sensor networks, the number of cyberattacks has rapidly increased. Therefore, the proportionate security of networks has become a challenge for organizations. Information security advisors of organizations face difficult and complex decisions in the evaluation and selection of information security controls that permit the defense of their resources and assets. Information security controls must be selected based on an appropriate level of security. However, their selection needs intensive investigation regarding vulnerabilities, risks, and threats prevailing in the organization as well as consideration of the implementation, mitigation, and budgetary constraints of the organization. The goal of this paper was to improve the information security control analysis method by proposing a formalized approach, i.e., fuzzy Analytical Hierarchy Process (AHP). This approach was used to prioritize and select the most relevant set of information security controls to satisfy the information security requirements of an organization. We argue that the prioritization of the information security controls using fuzzy AHP leads to an efficient and cost-effective assessment and evaluation of information security controls for an organization in order to select the most appropriate ones. The proposed formalized approach and prioritization processes are based on International Organization for Standardization and the International Electrotechnical Commission (ISO/IEC) 27001:2013. But in practice, organizations may apply this approach to any information security baseline manual. Under many contradictory obstacles, the decisions made by humans are not reliable, because the human brain is only capable of evaluating and acting on a limited amount of information at any given moment [17]. To help decision makers solve actual problems for organizations, Thomas Sati (1980) [23] introduced the Analytical Hierarchy Process (AHP). This approach is based on the comparison of pairs between an alternative and a best possible alternative. The strength of the AHP lies in its neutral and logical classification and its flexibility to integrate various functions such as the deployment of quality functions, linear programming, and fuzzy. The benefit of the AHP methodology in conjunction with fuzzy logic is called fuzzy AHP which is the most important method of the multi-criteria decision-making methodology for various types of applications [24]. The fuzzy AHP approach helps to make decisions with various inclinations, fuzziness, and vulnerability. Research has shown the fuzzy AHP philosophy and furthered the supreme utilization of it [25]. It is practical for dealing with uncertainty, complexity, and decision making for complex issues of a controversial nature [26].The structure of the article is as follows: Section 2 is related to the integration of wireless sensor networks with cloud computing. Section 3 reviews previous approaches for the selection of ISCs in organizations. Section 4 presents the AHP, and...

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A new framework to integrate wireless sensor networks with cloud computing

Cited by 26 publications

References 9 publications

An Integrated Framework for Analysis and Mining of the Massive Sensor Data Using Feature Preserving Strategy on Cloud Computing

An Integrated Framework for Analysis and Mining of the Massive Sensor Data Using Feature Preserving Strategy on Cloud Computing

Big Data Sensing and Service: A Tutorial

Prioritization of Information Security Controls through Fuzzy AHP for Cloud Computing Networks and Wireless Sensor Networks

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