Queuing Algorithm for Effective Target Coverage in Mobile Crowd Sensing

Obinikpo, Alex Adim; Zhang, Yuwei; Song, Houbing; Luan, Tom H.; Kantarcih, Burak

doi:10.1109/jiot.2017.2688366

Cited by 20 publications

(5 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The effective target coverage measures the capability to provide sensing coverage with a certain quality to monitor a set of targets in an area [199]. The problem is tackled with queuing model-based algorithm where the sensors arrive and leave the coverage region following a birth process and death process.…”

Section: Theoretical Work Operational Research and Optimizationmentioning

confidence: 99%

A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities

Capponi

Fiandrino

Kantarcı

et al. 2019

IEEE Commun. Surv. Tutorials

Self Cite

427

176

View full text Add to dashboard Cite

Mobile crowdsensing (MCS) has gained significant attention in recent years and has become an appealing paradigm for urban sensing. For data collection, MCS systems rely on contribution from mobile devices of a large number of participants or a crowd. Smartphones, tablets, and wearable devices are deployed widely and already equipped with a rich set of sensors, making them an excellent source of information. Mobility and intelligence of humans guarantee higher coverage and better context awareness if compared to traditional sensor networks. At the same time, individuals may be reluctant to share data for privacy concerns. For this reason, MCS frameworks are specifically designed to include incentive mechanisms and address privacy concerns. Despite the growing interest in the research community, MCS solutions need a deeper investigation and categorization on many aspects that span from sensing and communication to system management and data storage. In this paper, we take the research on MCS a step further by presenting a survey on existing works in the domain and propose a detailed taxonomy to shed light on the current landscape and classify applications, methodologies and architectures. Our objective is not only to analyze and consolidate past research but also to outline potential future research directions and synergies with other research areas.

show abstract

Section: Theoretical Work Operational Research and Optimizationmentioning

confidence: 99%

A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities

Capponi

Fiandrino

Kantarcı

et al. 2019

IEEE Commun. Surv. Tutorials

Self Cite

427

176

View full text Add to dashboard Cite

show abstract

“…On the other hand, Obinikpo et al [27] proposed queue theory to model target coverage in MCS. The model is based on birth-and-death mechanism which represents the arrival and exit of sensors in an MCS environment.…”

Section: Literature Reviewmentioning

confidence: 99%

Security analysis of mobile crowd sensing applications

Owoh

Singh

2020

ACI

View full text Add to dashboard Cite

The proliferation of mobile phones with integrated sensors makes large scale sensing possible at low cost. During mobile sensing, data mostly contain sensitive information of users such as their real-time location. When such information are not effectively secured, users’ privacy can be violated due to eavesdropping and information disclosure. In this paper, we demonstrated the possibility of unauthorized access to location information of a user during sensing due to the ineffective security mechanisms in most sensing applications. We analyzed 40 apps downloaded from Google Play Store and results showed a 100% success rate in traffic interception and disclosure of sensitive information of users. As a countermeasure, a security scheme which ensures encryption and authentication of sensed data using Advanced Encryption Standard 256-Galois Counter Mode was proposed. End-to-end security of location and motion data from smartphone sensors are ensured using the proposed security scheme. Security analysis of the proposed scheme showed it to be effective in protecting Android based sensor data against eavesdropping, information disclosure and data modification.

show abstract

“…In a related research work, Howard et al in [26] presented a greedy method of sensor deployment in a maximum coverage region, but the drawbacks still remain their use of GPS network, while the target or interest points was inconclusive and remained undefined. A queuing algorithm based on birthand-death models for effective target coverage proposed by Obinikpo et al in [27] was introduced for mobile crowd sensing in order to determine the waiting time of target, the mean busy period and idle period of the deployed sensors. While an NP-hard problem was evidently resolved in [28], in other to guarantee a defined lifetime for the sensor nodes for unspecified networks.…”

Section: Preliminaries and Related Workmentioning

confidence: 99%

Novel MA-VFBC Based Deployment of Obstacle-Avoiding Scattered Sensors for Region-of-Interest Incidence Monitoring

2020

View full text Add to dashboard Cite

The deployment of mobile and adaptive virtual force barrier coverage (MA-VFBC) classification scheme using a mobile emergency response and command interface (MERCI) platform that is functionally implemented to track and report incidences and consequent collateral damages to infrastructures within a region of interest (ROI) is proposed. Considering the enormous use of the global positioning system (GPS) devices for location data-gathering and processing, and its inherent limitations, the proposed GUIbased MA-VFBC platform is implemented using self-deploying and obstacle-avoiding scattered mobile sensor nodes. The GPS service is kept as alternatives, since only initial coordinates from where the deployed sensor starts to move and the maximum boundary location of the target location is considered. The practical experimentation work appraises the use and feel of the (MERCI) platform when integrated with the proposed novel MA-VFBC path-tracking classification schemes, while the simulation work investigates evident real-time system reliability issues as direction of node deployment with path distances, system computation time and system overheads in the presence of dissimilar multiple obstacles. INDEX TERMS Emergency response, mobile and adaptive virtual force barrier coverage (MA-VFBC), MERCI, obstacle-avoiding sensor nodes, ROI incidence assessment.

show abstract

Queuing Algorithm for Effective Target Coverage in Mobile Crowd Sensing

Cited by 20 publications

References 26 publications

A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities

A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities

Security analysis of mobile crowd sensing applications

Novel MA-VFBC Based Deployment of Obstacle-Avoiding Scattered Sensors for Region-of-Interest Incidence Monitoring

Contact Info

Product

Resources

About