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JournalISSN: 2454-132X

International Journal of Advance Research, Ideas and Innovations in Technology 

IJARIT Research Foundation
About: International Journal of Advance Research, Ideas and Innovations in Technology is an academic journal. The journal publishes majorly in the area(s): Cloud computing & Population. It has an ISSN identifier of 2454-132X. Over the lifetime, 3149 publications have been published receiving 3431 citations.

Papers published on a yearly basis

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Journal Article
TL;DR: Mobile cloud computing maps cloud computing ideas and overcomes obstacles that deal with performance such as battery life, CPU, storage, bandwidth, environment that means heterogeneity, scalability, availability and security discussed in mobile computing.
Abstract: Mobile devices such as smart phones and tablets have become an essential part of our lives, because of their powerful capabilities Along with the explosive growth of the mobile applications and up-raising cloud computing concept, mobile cloud computing appears to be a new potential technology for mobile services Mobile cloud computing maps cloud computing ideas and overcomes obstacles that deal with performance such as battery life, CPU, storage, bandwidth, environment that means heterogeneity, scalability, availability and security discussed in mobile computing To solve these problems by accessing cloud computing platforms To access these platforms is not always guaranteed to be available and is too expensive to access themTo overcome this issue by creating a virtual cloud computing platform using mobile phones

99 citations

Journal Article
TL;DR: A framework which will have fundamental sensor like IR sensor to identify the measure of junk canister filled and discharge flag to the line following bot to gather the effectively isolated fluid and strong waste to make the encompassing a cleaner put.
Abstract: Squander administration is turning into a hotly debated issue in strategy urban communities. Municipal governments, which are to a great extent in charge of building and keeping up squander transfer systems, are quick to discover methods for limiting the cost of discarding waste and the sheer measure of waste society produces. Sadly, market and corporatist methodologies don't think about waste administration, rather leaving waste administration to nearby experts, and without government compulsion will as a rule not worry about condition benevolent item configuration, squander minimization or the reuse, re-assembling or reusing of the item toward the finish of its life cycle. We propose a framework which will have fundamental sensor like IR sensor to identify the measure of junk canister filled and discharge flag to the line following bot to gather the effectively isolated fluid and strong waste. The isolated waste will be simpler to dispose. Standard gathering of waste will make the encompassing a cleaner put.

88 citations

Journal Article
TL;DR: This paper takes care of this open issue with a novel plan in view of strategies including polynomial-based validation labels and homomorphic straight authenticators and beats existing POR and PDP plans while giving the extra usefulness of deduplication.
Abstract: Information uprightness and capacity effectiveness are two essential necessities for distributed storage. Verification of Retrievability (POR) and Confirmation of Information Ownership (PDP) strategies guarantee information respectability for distributed storage. Evidence of Proprietorship (POW) enhances stockpiling proficiency by safely evacuating superfluously copied the information on the capacity server. Be that as it may, an insignificant blend of the two systems, with a specific end goal to accomplish both information trustworthiness and capacity proficiency, brings about non-minor duplication of metadata (i.e., validation labels), which repudiates the destinations of POW. Late endeavors to this issue present huge computational and correspondence costs and have likewise been demonstrated not secure. It requires another answer for bolster effective and secure information trustworthiness inspecting with capacity deduplication for distributed storage. In this paper, we take care of this open issue with a novel plan in view of strategies including polynomial-based validation labels and homomorphic straight authenticators. Our plan permits deduplication of both documents and their relating confirmation labels. Information respectability examining and capacity deduplication are accomplished all the while. Our proposed plan is likewise portrayed by consistent ongoing correspondence and computational cost on the client side. Open inspecting and group reviewing are both upheld. Henceforth, our proposed conspire beats existing POR and PDP plans while giving the extra usefulness of deduplication. We demonstrate the security of our proposed conspire in light of the Computational Diffie-Hellman issue, the Static Diffie-Hellman issue, and the t-Solid Diffie-Hellman issue. Numerical investigation and trial come about on Amazon AWS demonstrate that our plan is proficient and versatile.

72 citations

Journal Article
TL;DR: An Internet of Things (IoT) approach enabled by Fuzzy Inference System (FIS) to intelligently and efficiently predict the coronavirus is implemented, which smartly monitors and predicts either human is the victim of Coronavirus or not.
Abstract: Almost 3,000 cases of respiratory disease due to a new coronavirus from Wuhan, China were registered between 1 December 2019 and 26 January 2020. The diagnosis of coronavirus in a human being on a wide scale was so hectic. This proposed research implements an Internet of Things (IoT) approach enabled by Fuzzy Inference System (FIS) to intelligently and efficiently predict the coronavirus known as ' IoT enabled Smart Monitoring of Coronavirus empowered with Fuzzy Inference System (IoTSMCFIS) ' which smartly monitors and predicts either human is the victim of Coronavirus or not. For simulations, the IoTSMCFIS proposed system uses MATLAB 2019a and the proposed system indicates promising results regarding the simulations.

65 citations

Journal Article
TL;DR: This project proposes the first computational mechanism to resolve conflicts for multi-party privacy management in Social Media that is able to adapt to different situations by modeling the concessions that users make to reach a solution to the conflicts.
Abstract: Information shared through Social Media may affect more than one user’s privacy e.g., Information that depicts different users, comments that mention different users, events in which different users are invited, etc. Many types of privacy management support in present mainstream Social Media foundation makes users unable to appropriately control the sender and receiver. Computational mechanisms that are able to merge the privacy preferences of different users into a single policy for an item can help solve this problem. Merging different user’s personal preferences is difficult hence conflicts occur in privacy preferences, so methods to resolve conflicts are needed. Moreover, these techniques need to consider how users’ would actually reach an engagement about a solution to the conflict in order to propose solutions that can be acceptable by all of the users affected by the information to be shared. present approaches are either too demanding or only consider fixed ways of aggregating privacy preferences. Here, we introduce the basic computational procedure to overcome problems in Social Media that is able to adapt to different situations by modeling the concessions that users make to reach answers to the conflicts. The present results of a user study in which our introduced mechanism outperformed other present approaches in terms of how many times each approach matched users’ action. Computational mechanisms that are able to merge the privacy preferences of multiple users into a single policy for an item can help solve this problem. However, merging multiple users’ privacy preferences is not an easy task, because privacy preferences may conflict, so methods to resolve conflicts are needed. Moreover, these methods need to consider how users’ would actually reach an agreement about a solution to the conflict in order to propose solutions that can be acceptable by all of the users affected by the item to be shared. Current approaches are either too demanding or only consider fixed ways of aggregating privacy preferences. In this project, we propose the first computational mechanism to resolve conflicts for multi-party privacy management in Social Media that is able to adapt to different situations by modeling the concessions that users make to reach a solution to the conflicts. We also present results of a user study in which our proposed mechanism outperformed other existing approaches in terms of how many times each approach matched users’ behavior.

57 citations

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Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
202142
2020399
2019625
20181,022
2017831
2016204