Real-time and energy aware opportunistic mobile crowdsensing framework based on people’s connectivity habits

Bradai, Salma; Khemakhem, Sofien; Jmaïel, Mohamed

doi:10.1016/j.comnet.2018.06.013

Cited by 4 publications

(1 citation statement)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, several kinds of crowdsensing tasks like audio, visual, or audio-visual transmission which generates large-scale sensed data may bring high network traffic costs to participants using a 3G, 4G and 5G networks thus affecting their satisfaction. With the increased number of smartphone uptake which stands at over 4.5 billion gadgets, human mobility patterns and daily actions have increased tremendously with a possibility of many participants taking part in MCS data collection in a passive or opportunistic manner [16]. The advantages and disadvantages of MCS are summarized in Table 1.…”

Section: Introductionmentioning

confidence: 99%

Simulation of Trust-Based Mechanism for Enhancing User Confidence in Mobile Crowdsensing Systems

et al. 2020

View full text Add to dashboard Cite

With the rapid development of mobile technology and subsequent mass adoption of mobile devices, mobile crowdsensing (MCS) has gained a lot of research attention. In MCS systems, trust is a key focus in the overall improvement in the participant uptake of the sensing tasks. The trust-based scheme of MCS is studied to predict the damage level, the scores of quality-of-service (QoS), and the levels of qualityof-data (QoD) of MCS systems. Users can participate in MCS sensing based on trustworthy indicators that are related to user experience and system reputation, as well as the knowledge obtained about the MCS systems. This paper illustrates the establishment of user confidence during recruitment in MCS as it is very critical for the success of MCS systems and proposes a simulation trust-based mechanism (SiTBaM) approach. The level of MCS security is enhanced to protect the privacy of participants, so that participants can be assured that the MCS system they are working with during sensing moment is trustworthy. The application of SiTBaM in MCS is verified to yield better results as the simulations show that it offers higher QoS levels, QoD scores, as well as low damage levels in the presence of any task or many malicious users. These results were validated through comparisons with other schemes. INDEX TERMS Mobile crowdsensing, quality-of-data, quality-of-service, security, trust-based scheme.

show abstract

Section: Introductionmentioning

confidence: 99%