Query-response geocast for vehicular crowd sensing

Timpner, Julian; Wolf, Lars

doi:10.1016/j.adhoc.2015.06.003

Cited by 7 publications

(5 citation statements)

References 27 publications

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“…Hichem Sedjelmaci [7] et al, designed and implements an intrusion detection method to prevent dangerous attacks in the network. Sofiane Zemouri [14] et al, proposed distributed dissemination protocol "Road-casting protocol" for safety message in urban areas to cooperatively forward the data.K.Karuppasamy [9] et al, analyzed the various routing algorithms in a mobile network environment. But, the traditional routing protocol supported in mobile wireless networks does not suit for communication.…”

Section: Related Workmentioning

confidence: 99%

Comfort and Danger Zone Boundary Prediction for Flying Car Safe Overtaking in Highways

Srithar¹,

Saravanakumar²

2020

IJRTE

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Nowadays the road transportation system is enlarged much due to the population and fast-moving world. Due to human fault, vehicle accidents are quite unavoidable. The primary cause for accidents is the desecration of traffic rules such as over speed, unplanned overtake, etc. To increase the safety of vehicle rider the autonomous cars are coming into the picture. The autonomous vehicles can decide on their own for safe self-driving. But, the autonomous vehicles are still on the bench because lots of realistic considerations and predictions are needed to make the system more intelligence. The vehicular adhoc network acts an important role in autonomous vehicle building by considering various facts. The motive of the research is to give assistance message to the drivers for safe overtaking. In the literature, safety assistance is provided through the Road Side Control Units (RSCU). But the construction cost and maintenance for the RSCU is too high. Our methodology will give a sustainable solution for safety assistance when the vehicle tries to overtake. The proposed methodology uses Cooperative Overtaking Sight Assistance (COSA) which predicts the comfort zone and danger zone boundaries for safe overtaking. The methodology greatly reduces infrastructure dependency. The experimental evaluations are carried out in SUMO and NS2.

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Section: Related Workmentioning

confidence: 99%

Comfort and Danger Zone Boundary Prediction for Flying Car Safe Overtaking in Highways

Srithar¹,

Saravanakumar²

2020

IJRTE

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“…The geocasting-based approaches [ 47 , 48 , 49 , 85 ] provide capability of sending a query to nodes within a range of location in a distributed architecture. These approaches do not have concrete clusters thus are more flexible for mobile nodes, and are often used in Vehicular Networks [ 47 , 48 ]. However, the reliability of the query is hard to be guaranteed as available services cannot be known through geocasting techniques only.…”

Section: Classification Viewpoint—basic Principlesmentioning

confidence: 99%

“…However, the reliability of the query is hard to be guaranteed as available services cannot be known through geocasting techniques only. In addition, query response may need extra techniques to send messages to the query sender, especially mobile ones [ 47 , 48 ].…”

Section: Classification Viewpoint—basic Principlesmentioning

confidence: 99%

Search Techniques for the Web of Things: A Taxonomy and Survey

Zhou

Wang

et al. 2016

Sensors

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The Web of Things aims to make physical world objects and their data accessible through standard Web technologies to enable intelligent applications and sophisticated data analytics. Due to the amount and heterogeneity of the data, it is challenging to perform data analysis directly; especially when the data is captured from a large number of distributed sources. However, the size and scope of the data can be reduced and narrowed down with search techniques, so that only the most relevant and useful data items are selected according to the application requirements. Search is fundamental to the Web of Things while challenging by nature in this context, e.g., mobility of the objects, opportunistic presence and sensing, continuous data streams with changing spatial and temporal properties, efficient indexing for historical and real time data. The research community has developed numerous techniques and methods to tackle these problems as reported by a large body of literature in the last few years. A comprehensive investigation of the current and past studies is necessary to gain a clear view of the research landscape and to identify promising future directions. This survey reviews the state-of-the-art search methods for the Web of Things, which are classified according to three different viewpoints: basic principles, data/knowledge representation, and contents being searched. Experiences and lessons learned from the existing work and some EU research projects related to Web of Things are discussed, and an outlook to the future research is presented.

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“…The service consumer, mobile users, local servers, and centralized servers are the key factors of mobile crowdsourcing. 5 In Social Media, the research community provides a new user profile and an advertisement. When a user sees or clicks on an advertisement, they are directed to crowdsourcing sites.…”

mentioning

confidence: 99%

“…Several researchers 1,2,[4][5][6][7][8][9][11][12]10,[13][14][15][16][17] considered either cost or latency as the objective function 9,[13][14][15][16][17][18][19] and did not consider the privacy concerns. In recent years, optimization algorithms has been acheived better performance in engineering applications.…”

mentioning

confidence: 99%

An efficient privacy‐preserving model based on OMFTSA for query optimization in crowdsourcing

Renukadevi¹,

Anita

Geetha³

2021

Concurrency and Computation

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Crowdsourcing is now one of the most important and transformative paradigms, with great success in a variety of application tasks. Crowdsourcing obtains knowledge and information to solve cognitive or intelligence-intensive tasks from an evolving group of participants via the Internet. Unfortunately, providing a hard privacy guarantee and query optimization is incompatible when a higher task acceptance rate needs to be accomplished and this case is common in most existing crowdsourcing solutions. The state of art systems suffered from different complexities such as lack of crowdsourcing optimization techniques, increased cost, latency, security, and scalability issues. In this paper, we have proposed a crowdsourcing model to optimize the cost and latency, issues that occur while query optimization using the Moth Flame and Tunicate Swarm Algorithm (MF-TSA). The TSA algorithm is added to the MF algorithm to enhance its exploitation capability and yield fast convergence. The data privacy concerns of the worker and the requestor are addressed using homomorphic encryption that simultaneously enhances the efficiency of the crowdsourcing framework. The main aim of this work is to optimize the cost and latency for query plan selection along with security. Initially, the homomorphic encryption model is used to encrypt the data. In query design, two kinds of crowd-controlled administrators, that is, Crowd Powered Selection (CSelect) and Crowd Powered Join (CJoin) are connected for assessing query. The proposed framework utilizes MF-TSA to optimize the selection and join queries with low cost and latency. Finally, the experimental results demonstrate better query optimization performance than other existing algorithms such as sequential, parallel, andcrowdsourcing, moth flame-based tunicate swarm algorithm, query, select and join queries INTRODUCTIONRecently, large-scale user representations of extensive collaboration have been made available through the Internet via various types of technologies and mechanisms. The collection of text documents and data source connections is an important part of the World Wide Web (WWW). The emerging crowdsourcing platform has been authorized to collect and distribute human computing for a wide range of tasks. 1 To generate an accurate and efficient solution, crowdsourcing targets a massive audience. The consensus is shared between the crowdsourcing system and implementations, such as employees who participate and delegate tasks that differ. When it comes to tasks such as answering questions, some workers are smarter and faster than others. 2,3

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Query-response geocast for vehicular crowd sensing

Cited by 7 publications

References 27 publications

Comfort and Danger Zone Boundary Prediction for Flying Car Safe Overtaking in Highways

Comfort and Danger Zone Boundary Prediction for Flying Car Safe Overtaking in Highways

Search Techniques for the Web of Things: A Taxonomy and Survey

An efficient privacy‐preserving model based on OMFTSA for query optimization in crowdsourcing

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