Sensor Cloud: A Cloud of Virtual Sensors

Madria, Sanjay; Kumar, Vimal; Dalvi, Rashmi

doi:10.1109/ms.2013.141

Cited by 172 publications

(107 citation statements)

References 6 publications

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“…Combining sensors allows the sensing data from several heterogeneous sensors to be aggregated to provide applications with indirect measurements of abstract conditions that cannot be directly measured by physical sensors. The virtualization of entire sensor networks has been proposed under multiple alternative names, including virtual sensor networks [40], [38] and sensor cloud [41]. Independently of virtualization research, the grouping of sensor nodes has also been previously studied in the context of WSN routing and is referred to as clustering [42], [12], [43].…”

Section: Redundancy Reduction In Wsnsmentioning

confidence: 99%

Redundancy Reduction in Wireless Sensor Networks via Centrality Metrics

Mocanu

Vega

Liotta

2015

2015 IEEE International Conference on Data Mining Workshop (ICDMW)

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Abstract-The advances in wireless communications, together with the need of sensing and controlling various nature or human made systems in a large number of points (e.g. smart traffic control, environmental monitoring), lead to the emergence of Wireless Sensor Networks (WSN) as a powerful tool to fulfill the above requirements. Due to the large amount of wireless devices needed and cost constraints, such networks are usually made by low-cost devices with limited energy and computational capabilities, these further on being subject to easy communication or hardware fails. At the same time, the deployment of such devices in harsh environments (e.g. in the ocean) may lead to uncontrollable redundant topologies which have to be often refined during the exploitation phase of these networks in an automated manner. In the scope of these arguments, in this paper, we take advantage of the latest theoretical advances in complex networks and we propose an automated solution to refine the topology of WSNs by using centrality metrics to detect the redundant nodes and links in a network, and further on to shut down them safely. Our solution may work in both ways, centralized or decentralized, by choosing a centralized or a decentralized centrality metric, this choice being driven by the application goal. The experiments performed on a wide variety of network topologies with different sizes (e.g. number of nodes and links), using different centrality metrics, validate our approach and recommend it as a solution for the automatic control of WSNs topologies during the exploitation phase of such networks to optimize, for instance, their life time.

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Section: Redundancy Reduction In Wsnsmentioning

confidence: 99%

Redundancy Reduction in Wireless Sensor Networks via Centrality Metrics

Mocanu

Vega

Liotta

2015

2015 IEEE International Conference on Data Mining Workshop (ICDMW)

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“…The described system consists of sensors which acquire their primary data from cameras and Light Detection and Recognition (LIDAR) instruments. In [21] a sensor cloud based on WSN (Wireless Sensor Networks) is proposed which virtualizes the wireless sensors and provides sensing as a service to users.…”

Section: A Cloud Of Sensor With Reactive Sensor Middlewarementioning

confidence: 99%

A Quality Attributes Approach to Defining Reactive Systems Solution Applied to Cloud of Sensors

Skowronski¹,

Werewka

2015

Annals of Computer Science and Information Systems

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Abstract-Reactive systems have been investigated and used for a long time. Due to new methods and new technology development, the reactive systems needs their redefinition. These systems are currently an interesting topic for IT (Information Technology) solution providers. In this paper the authors try to define a new view of the architecture of reactive systems, because reactive systems are evolving and there is no clear definition of them. The starting point of the investigation was the reactive manifesto which defines reactive systems by four main features (quality attributes): responsiveness, resilience, elasticity and message driven interoperability. The mentioned quality attributes are the basis for developing a system solution. For each of the quality attributes, a set of tactics are proposed to maintain attribute required behavior. The suitability of the proposed tactics was investigated for Reactive Sensor Middleware which is part of a CoS (Cloud of Sensors) in the PaaS (Platform as a Service) layer. A cloud of sensors for pollution monitoring in urban areas was used as an example. Verification of the tactics has confirmed that some of the proposed tactics are suitable for the selected CoS subsystem.

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“…Cloud computing can enhance the processing and storage capabilities of wireless sensor networks (WSNs) and improve the performance of WSNs in terms of energy consumption, analytics, computation power, computing latency, and quality of service (QoS). Therefore, merging WSNs and cloud computing is a trend that is expected to result in a computing paradigm called sensor cloud [3]. Sensor cloud enables users to gather, access, process, visualize, analyze, and store large amounts of sensor data easily by using cloud resources.…”

Section: Introductionmentioning

confidence: 99%

Data Collection in Smart Communities Using Sensor Cloud: Recent Advances, Taxonomy, and Future Research Directions

et al. 2018

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The remarkable miniaturization of sensors has led to the production of massive amounts of data in smart communities. These data cannot be efficiently collected and processed in WSNs due to the weak communication capability of these networks. This drawback can be compensated for by amalgamating WSNs and cloud computing to obtain sensor clouds. In this article, we investigate, highlight, and report recent premier advances in sensor clouds with respect to data collection. We categorize and classify the literature by devising a taxonomy based on important parameters, such as objectives, applications, communication technology, collection types, discovery, data types, and classification. Moreover, a few prominent use cases are presented to highlight the role of sensor clouds in providing high computation capabilities. Furthermore, several open research challenges and issues, such as big data issues, deployment issues, data security, data aggregation, dissemination of control message, and on time delivery are discussed. Future research directions are also provided.

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Sensor Cloud: A Cloud of Virtual Sensors

Cited by 172 publications

References 6 publications

Redundancy Reduction in Wireless Sensor Networks via Centrality Metrics

Redundancy Reduction in Wireless Sensor Networks via Centrality Metrics

A Quality Attributes Approach to Defining Reactive Systems Solution Applied to Cloud of Sensors

Data Collection in Smart Communities Using Sensor Cloud: Recent Advances, Taxonomy, and Future Research Directions

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