A Novel Approach for Real-Time Data Management in Wireless Sensor Networks

Sarkar, Joy Lal; Panigrahi, Chhabi Rani; Pati, Bibudhendu; Das, Himansu

doi:10.1007/978-81-322-2529-4_62

Cited by 20 publications

(5 citation statements)

References 9 publications

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“…The proposed technique was built upon for processing the real-time data. Sarkar et al [22], proposed a novel approach for handling real-time database management in WSNs with the help of assembly line scheduling algorithm. The work of each sensor node is fixed which is based on the predefined deadline and from each sensor node finally the data come across to the sink nodes.…”

Section: And Wsns Applications For Information Management and Communi...mentioning

confidence: 99%

“…For example WSNs are used to monitor the climatic conditions of temperature, rain, etc. [22][23][24][25][26][27][28][29][30][31][32][33]. Sensors also find a variety of usages in military and industrial applications, and are typically micro devices which can be embedded at various places and not detectable with a common eye.…”

Section: Introductionmentioning

confidence: 99%

“…However, a particular mobile device is at the centre which initiates the computation and various other mobile devices are well connected in a network to perform the execution of a task that is logically split amongst them. In case the computation task is very huge and cannot be taken care by a network of SMD's, then the offloading approach is followed, wherein the task is executed completely in the cloud and only the final results are sent back to the mobile device for the user [21]. WSNs are very important in today's world as they are used widely to monitor various parameters in the environment and based on these observation values corrective action can be taken for the betterment of the society.…”

Section: Introductionmentioning

confidence: 99%

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Mobile Cloud Computing and Wireless Sensor Networks: A review, integration architecture, and future directions

et al. 2021

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In today's fast advancing world, sensors are used in various applications to provide complete data about different objects present around us. The sensor data when integrated with Mobile Cloud Computing (MCC) is used for further computation to provide useful results advanced warning, forecasting, planning, and plethora of other applications in this uncertain world. Few works have been proposed where sensor nodes are integrated with Wireless Sensor Networks (WSNs) which give a new direction in modern research for developing new technologies which help the users for fast access of sensory data over mobile devices. Herein, a systematic literature review of both MCC and WSNs are conducted and subsequently assimilated them via an architecture which is efficient and achievable within short time-span for a variety of applications. The MCC applications are reviewed from two main perspectives that are energy and information management. The communication aspect in MCC and WSNs has been discussed and the need for integration between the two has been justified in this work. The work done on mobility management in MCC and WSNs is reviewed. Also, the challenges in MCC-WSNs integration along with the comprehensive analysis and findings of the review are identified. Finally, the conclusion and specific future direction of research in this area are provided. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: And Wsns Applications For Information Management and Communi...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mobile Cloud Computing and Wireless Sensor Networks: A review, integration architecture, and future directions

et al. 2021

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“…On the other side, the latter category stores data into both, a central database, and the sensors themselves (local databases), enabling clients to query both. Each approach exhibits advantages and disadvantages, and different management systems have been proposed to optimize their performance [34,35]. The decision-making processes for an autonomous vehicle can further be enhanced with the integration of historical data (e.g., maps of intersections and traffic rules), an approach that is very common in the self-driving car industry [36,37].…”

Section: Autonomous Vehicles For Mining Applicationsmentioning

confidence: 99%

Data Management System for a Semiautonomous Shuttle Car for Underground Room and Pillar Coal Mines

et al. 2021

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In recent years, autonomous solutions in the multidisciplinary field of mining engineering have been an extremely popular applied research topic. This is a result of the increasing demands of society on mineral resources along with the accelerating exploitation of the currently economically viable resources, which lead the mining sector to turn to deeper, more-difficult-to-mine orebodies. An appropriate data management system comprises a crucial aspect of the designing and the engineering of a system that involves autonomous or semiautonomous vehicles. The vast volume of data collected from onboard sensors, as well as from a potential IoT network dispersed around a smart mine, necessitates the development of a reliable data management strategy. Ideally, this strategy will allow for fast and asynchronous access to the data for real-time processing and decision-making purposes as well as for visualization through a corresponding human–machine interface. The proposed system has been developed for autonomous navigation of a coalmine shuttle car and has been implemented on a 1/6th scale shuttle car in a mock mine. It comprises three separate nodes, namely, a data collection node, a data management node, and a data processing and visualization node. This approach was dictated by the large amount of collected data and the need to ensure uninterrupted and fast data management and flow. The implementation of an SQL database server allows for asynchronous, real-time, and reliable data management, including data storage and retrieval. On the other hand, this approach introduces latencies between the data management node and the other two nodes. In general, these latencies include sensor latencies, network latencies, and processing latencies. However, the data processing and visualization module is able to retrieve and process the latest data and make a decision about the next optimal movement of the shuttle car prototype in less than 900 ms. This allows the prototype to navigate efficiently around the pillars without interruptions.

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“…Yu and Li 13 analyze the time cost that complete the aggregation in SA, and the algorithm shows that the time required is not lager than T ( 15 R ( G , s ) + Δ − 3 ) time units, where T is the constant time units in every WP and R ( G , s ) is the transmission range of node s in the network graph G . In Sarkar et al, 14 ARS (Action and Relay Station) line scheduling algorithm is proposed to manage data by cluster nodes collecting the data from different neighbor nodes and then transmit the aggregated data to the sink node. The disadvantages of this scheme are suit for low-consuming nodes only and conflict may be occurred during the transmission.…”

Section: Related Workmentioning

confidence: 99%

A Distributed Collision-Free Data Aggregation Scheme for wireless sensor network

Qin

Zhou

et al. 2018

International Journal of Distributed Sensor Networks

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Due to the advantages of large-scale, data-centric and wide application, wireless sensor networks have been widely used in nowadays society. From the physical layer to the application layer, the multiply increasing information makes the data aggregation technology particularly important for wireless sensor network. Data aggregation technology can extract useful information from the network and reduce the network load, but will increase the network delay. The nonexchangeable feature of the battery of sensor nodes makes the researches on the battery power saving and lifetime extension be carried out extensively. Aiming at the delay problem caused by sleeping mechanism used for energy saving, a Distributed Collision-Free Data Aggregation Scheme is proposed in this article to make the network aggregate data without conflicts during the working states periodically changing so as to save the limited energy and reduce the network delay at the same time. Simulation results verify the better aggregating performance of Distributed Collision-Free Data Aggregation Scheme than other traditional data aggregation mechanisms.

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A Novel Approach for Real-Time Data Management in Wireless Sensor Networks

Cited by 20 publications

References 9 publications

Mobile Cloud Computing and Wireless Sensor Networks: A review, integration architecture, and future directions

Mobile Cloud Computing and Wireless Sensor Networks: A review, integration architecture, and future directions

Data Management System for a Semiautonomous Shuttle Car for Underground Room and Pillar Coal Mines

A Distributed Collision-Free Data Aggregation Scheme for wireless sensor network

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