shilpa chaudhari - Academia.edu (original) (raw)

Papers by shilpa chaudhari

Lot of efforts and struggle has been done by the storage administrators to handle the spiraling d... more Lot of efforts and struggle has been done by the storage administrators to handle the spiraling data like images, audios and videos. Among different data present, images are the stringent data which has to be taken care regarding storage. Most of cloud storage servers demand high cost for storage and also burden backup efficiency. Cloud storage being cost effective have more chance of storing the duplicate images. Instead of finding ways to store multiple copies of data, removal of duplicate data can be achieved by using a technology called data deduplication. Data Deduplication is one of the most popular emerging methods which ensure the storage efficiency by removing the redundant data and storing the unique data only. On the other hand, while storing the valuable image into the centralized server it is necessary to authorize the data being uploaded. This authorization of uploaded data can be accomplished by decentralized system called Blockchain, using which one can authorize the data uploaded and claim for the ownership of the data, thus providing the copyrights of the user. Here in this paper, data deduplication is integrated with Blockchain and implemented which makes the image storage efficient, effective and more secured.

International Journal of Networking and Virtual Organisations, 2021

Wireless sensor networks (WSNs) usually consist of tiny sensor nodes to sense the environmental d... more Wireless sensor networks (WSNs) usually consist of tiny sensor nodes to sense the environmental data that are transferred to the sink node via route discovered using unicast/multipath routing protocol. The multipath routing protocols improve load balancing and quality of service in addition to the reliable transfer of sensed data to the sink simultaneously by reducing delay and congestion. This survey gives a brief introduction about the existing multipath routing protocols in the literature and its classifications into four categories as follows. 1) Distributed meta-heuristic-based route discovery uses intelligent algorithms for path discovery; 2) local-heuristic knowledge-based route discovery uses node level statistics to discover the route; 3) route discovery specific to multimedia applications; 4) route discovery for secure transmission of data. A comparison between these protocols in terms of various routing parameters for path discovery, traffic distribution, and path maintenance is described for each class of multipath routing protocols.

2023 4th International Conference for Emerging Technology (INCET)

International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI) 2018, 2018

Everybody wants the prefabricated construction, just-in-time delivery, the speed, the reduced cos... more Everybody wants the prefabricated construction, just-in-time delivery, the speed, the reduced cost, the quality and the worker safety but nobody wants the hassles, the spread sheets, the phone calls, the paper notes and the miscommunications. ManufactOn construction supply chain solution has given the benefits of prefabrication and material delivery without the hassles. It is the cloud and mobile solution that helps to manage the entire prefabrication and material delivery process, everything from prefab planning to design and manufacturing to shipping in a single view of construction supply chain. Even through ManufactOn application contains different stages and functionalities from the prefab production till delivery of the items to the construction site, it lacks dashboard and shipping inventory functions, which is addressed in this paper. Dashboard functionality statistically analyzes the construction process related data for improving the flexibility in the ManufactOn software from user point of view whereas shipping inventory manages and access the items from the various locations that they are available at. Updating of the ManufactOn software with this functionality gives more weigh and responsibility to the software, even from the user point of view updating and high level development of application will be more users friendly.

2017 International Conference On Smart Technologies For Smart Nation (SmartTechCon), 2017

Quantity of heat produced during the complete burning of a unit mass of coal is indicated as High... more Quantity of heat produced during the complete burning of a unit mass of coal is indicated as Higher Heating Value (HHV). Accurate measurement of HHV of coal within the specific time is an important step in mine processing and power plant operations for the optimized operation, emission control and economic operation of the coal fired power plant. HHV is computed using the coal properties which are obtained through the proximate analysis or ultimate analysis. The proximate analysis yields moisture, ash, volatile matter and fixed carbon whereas the ultimate analysis yields carbon, hydrogen, nitrogen, oxygen and Sulphur as coal properties. Existing techniques of HHV determination are either linear or non-linear. As the relationship between the HHV and Coal properties are non-linear in nature, Neural Network (NN) and Wavelet model are suitable for HHV determination. Compare to NN, wavelet model estimates more accurate results but does not support real-time and recursive characteristics seen in NN. Hybrid model of wavelet and NN called as Wavelet Neural Network (WNN) has good prediction capability in non-linear environment. Hence, the prediction capability of WNN with respect to HHV estimation is analyzed in this paper by comparing the Mean Square Error of WNN and NN. The obtained result from our developed WNN and NN model for HHV estimation shows that WNN is better than NN.

2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS), 2019

Wireless Sensor Networks (WSN) is been a huge evolution (growth) in the current years. The growth... more Wireless Sensor Networks (WSN) is been a huge evolution (growth) in the current years. The growth is particularly because of the availability or requirement of small size sensors, which senses the environment with the help of tiny size sensor nodes and which is used in the communication of sensed data. WSNs are usually contains huge number of huge sink nodes and a sensor nodes. The multipath routing technique is the important task in the WSN for reliable transfer of data simultaneously by reducing delay and congestion. The multipath routing protocols improves Quality of service (QoS) and load balancing in addition to the reliable communication in the network. This survey gives a brief introduction about the multipath routing and the classifications of the various geographic multipath routing protocols based on the routing information (data) update mechanism using local or global heuristics knowledge. A comparison between these protocols in terms of various routing parameters for path maintenance, path discovery, traffic distribution is described for each class of geographic multipath routing protocols.

2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT), 2018

Thermal power plant consumes large amount of coal to generate heat and electricity. Scarcity of c... more Thermal power plant consumes large amount of coal to generate heat and electricity. Scarcity of coal targets energy saving and emission reduction. Optimal usage of coal in boiler of thermal plant can be achieved through accurate values of boiler operation parameters. Power plant operator faces the challenge of examining the data and evaluates these values for optimal performance of the plant operation. Usage of theory of thermodynamics in complex, uncertain, non-stable, inertial, time-delaying, and nonlinear of combustion process is difficult. Hence, many researchers proposed expert systems (called as combustion model of the boiler) to monitor and control the run-time efficiency and heat rate of the boiler and to suggest appropriate actions for the operation. Recent, expert system used to model the thermal efficiency of the pulverized coal furnace are mainly based on intelligent control approaches. In this paper, we categorize all up-to-date and published works based on current intelligent control approaches for prediction of boiler efficiency into three groups’ rule-based expert systems, soft-computing techniques and hybrid system. Their findings and important contributions are highlighted.

2021 Asian Conference on Innovation in Technology (ASIANCON), 2021

Studies show that the total digital resource has already exceeded the global storage capacity due... more Studies show that the total digital resource has already exceeded the global storage capacity due to the information explosion due to the speed of the development of digital data. It has become crucial to store this data securely and effectively. The deduplication concept helps to identify redundant data which can be removed leaving only one copy. To handle this deduplication authentically, we propose a three-phase coarse-to-fine model to identify duplicate images in a faster and efficient way for cloud image data storage. The phases are Global features based, Local features based, and Merkle hash tree-based image deduplication. It is observed that the proposed model is fast and efficient.

International Journal of Communication Networks and Distributed Systems, 2018

QoS outing in multimedia applications over MANET is affected by limited resources, shared channel... more QoS outing in multimedia applications over MANET is affected by limited resources, shared channel, unpredictable mobility, improper load balancing, and variation in signal strength. Existing works on MANET QoS routing focuses on only one of the factor such as bandwidth, mobility or energy neglecting dependent behaviour. In this paper, resource prediction-based routing is proposed wherein intelligent agents identify routes for communication with adequate future availability of buffer-space, energy and bandwidth resources considering mobile nodes. It has four steps of execution: resource prediction, resource prediction factor computation, route establishment, and route maintenance. Resources are predicted to compute resource prediction factors for reliable route establishment and route maintenance against link and node failure. Simulation results show an improvement in terms of packet delivery ratio, packet delivery latency, memory overhead and energy consumption.

Journal of Network and Computer Applications, 2016

Mobile Ad hoc NETwork (MANET) characteristics such as limited resources, shared channel, unpredic... more Mobile Ad hoc NETwork (MANET) characteristics such as limited resources, shared channel, unpredictable mobility, improper load balancing, and variation in signal strength affect the routing of real-time multimedia data that requires Quality of Service (QoS) provisioning. Accurate prediction of the resource availability assists efficient resource allocation before the routing of such data. Most of the published work on resource prediction in MANET focuses on either bandwidth or energy without considering mobility effects. Adoption of intelligent software agent such as Cognitive Agent (CA) for the accurate resource prediction has a significant potential to solve the challenges of resource prediction in MANET. The intelligence provided in CA is similar to the logical thinking like a human for decision-making. The predominant CA architecture is the Belief-Desire-Intention (BDI) model, which performs the various tasks on behalf of the human user as an assistant.In this paper, we propose a CA-based Resource Prediction mechanism considering Mobility (CA-RPM) that predicts the resources using agents through the resource prediction agency consisting of one static agent, one cognitive agent and two mobile agents. Agents predict the traffic, mobility, buffer space, energy, and bandwidth effectively that is necessary for efficient resource allocation to support real-time and multimedia communications. The mobile agents collect and distribute network traffic statistics over MANET whereas a static agent collects the local statistics. CA creates static/mobile agent during the process of resource prediction. Initially, the designed time-series Wavelet Neural Networks (WNNs) predict traffic and mobility. Buffer space, energy, and bandwidth prediction use the predicted mobility and traffic. Simulation results show that the predicted resources closely match with the real values at the cost of little overheads due to the usage of agents. Simulation analysis of predicted traffic and mobility also shows the improvement compared to recurrent WNN in terms of mean square error, covariance, memory overhead, agent overhead and computation overhead. We plan to use these predicted resources for its efficient utilization in QoS routing is our future work.

Computers & Electrical Engineering, 2016

Identification of Coffee White Stem Borer (CWSB) pest in the Arabica coffee plantation is a huge ... more Identification of Coffee White Stem Borer (CWSB) pest in the Arabica coffee plantation is a huge menace.Cluster-Based Data Aggregation (CBDA) is proposed with the use of Ultrasonic Active Sensors (UAS) for identifying CWSB pests.Clustering scheme is designed using solid-disc clustering for selection of Cluster-Head (CH).Data aggregation with redundancy elimination using Kolmogorov's zero-one law is carried at the CH.The aggregated data are delivered to the BS by establishing the route through the standard AODV protocol for further processing. Display Omitted This paper proposes a Cluster-Based Data Aggregation (CBDA) method for identifying pests in Arabica Coffee plantation using Wireless Sensor Networks (WSNs). Acoustic signals that are generated with biting sound by the pests inside stem are captured by WSN. Information regarding existence of pests is aggregated at Cluster-Head (CH) and is conveyed to base station. CH is selected using five states of each node: i-band, o-band, cluster-head request, idle and cluster-head. CH performs data aggregation with residual energy, time stamp using Kolmogorov's zero-one law to eliminate redundancy. Simulation analysis of CBDA is compared with fast local clustering, energy-efficient reliable data aggregation technique and energy-efficient data aggregation transfer in terms of aggregation ratio, message overhead, control overhead, packet delivery ratio, algorithmic complexity, delay, energy consumption, time-out period and clustering time. The CBDA simulation results outperform compared to the corresponding techniques.

Optical Character Recognition (OCR) technology offers a complete alphanumeric recognition of prin... more Optical Character Recognition (OCR) technology offers a complete alphanumeric recognition of printed or handwritten characters from pictures such as scanned bills and invoices. Intelligent extraction and storage of text in structured document serves document analytics. The current research attempts to find a methodology through which any information from the printed invoice can be extricated. The intermediate image is passed over using an OCR engine for further processing. Segmentation extracts written text in various fonts and languages. Image classification helps in making a decision based on the classification results. This paper surveys these techniques and compares them in terms of metrics, algorithm and results.

Journal of King Saud University - Computer and Information Sciences, May 1, 2022

This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Journal of information and communication convergence engineering, Jun 30, 2023

High-utility itemset mining (HIUM) has emerged as a key data-mining paradigm for object-of-intere... more High-utility itemset mining (HIUM) has emerged as a key data-mining paradigm for object-of-interest identification and recommendation systems that serve as frequent itemset identification tools, product or service recommendation systems, etc. Recently, it has gained widespread attention owing to its increasing role in business intelligence, top-N recommendation, and other enterprise solutions. Despite the increasing significance and the inability to provide swift and more accurate predictions, most at-hand solutions, including frequent itemset mining, HUIM, and high average-and fast high-utility itemset mining, are limited to coping with real-time enterprise demands. Moreover, complex computations and high memory exhaustion limit their scalability as enterprise solutions. To address these limitations, this study proposes a model to extract high-utility frequent closed itemsets based on an improved cumulative summary list structure (CSLFC-HUIM) to reduce an optimal set of candidate items in the search space. Moreover, it employs the lift score as the minimum threshold, called the cumulative utility threshold, to prune the search space optimal set of itemsets in a nested-list structure that improves computational time, costs, and memory exhaustion. Simulations over different datasets revealed that the proposed CSLFC-HUIM model outperforms other existing methods, such as closed-and frequent closed-HUIM variants, in terms of execution time and memory consumption, making it suitable for different mined items and allied intelligence of business goals.

Ad Hoc Sens. Wirel. Networks, 2021

International Journal of Computers and Applications, May 21, 2019

Nowadays, Internet of Things (IoT) is turning into an attractive framework to drive a substantive... more Nowadays, Internet of Things (IoT) is turning into an attractive framework to drive a substantive jump on merchandise and enterprises through physical, digital, and social spaces. This paper enhances IoT security authentication by utilizing cryptographic-based methodologies. In this study, we secure IoT sensitive data with the help of Optimal Homomorphic Encryption (OHE) with high dependability. Sensitive data from IoT dataset are classified based on Deep Learning Neural Network structure (DNN). After classification, OHE performs sensitive data in the process of encryption and decryption. During encryption, the key is authenticated and the optimal key is selected by using Step size Fire Fly (SFF) optimization algorithm. This strategy can build up the encrypted key and attains the most prominent privacy-preserving data in IoT. The outcome shows that the performance of the proposed IoT security model achieves maximum key breaking time and less computational time with high security.

Cloud computing allows users to store and process their data in third party data centers. There i... more Cloud computing allows users to store and process their data in third party data centers. There is a need for secure and reliable measures to be taken to prevent loss of data, authentication problems and other security issues. This paper discusses steps followed to set up a private cloud using an open source software platform, OpenStack. Setting up the private cloud not only ensures the privacy as it eliminates the involvement of a third party cloud service provider but also provides us with a cheaper alternative. A Denial of Service (DoS) attack is a type of security attack where in the main aim is to overload the machine making it inaccessible to legitimate users. To assess DoS attack, we develop a web application running on one of the instances of our cloud. We analyze the DoS attack on this application using a DoS algorithm running on one of the instances in cloud. The performance of the cloud under the attack and without the attack is analyzed and conclusions about the risks involved are drawn. By assessing these risks, the performance degradation of the cloud is visualized using Wireshark and SlowHTTPTest tools.