Accelerating the Delivery of Data Services over Uncertain Mobile Crowdsensing Networks
arxiv(2022)
摘要
The challenge of exchanging and processing of big data over mobile
crowdsensing (MCS) networks calls for designing seamless data service
provisioning mechanisms to enable utilization of resources of mobile
devices/users for crowdsensing tasks. Although conventional onsite spot trading
of resources based on real-time network conditions can facilitate data sharing,
it often suffers from prohibitively long service provisioning delays and
unavoidable trading failures due to requiring timely analysis of dynamic
network environment. These limitations motivate us to investigate an integrated
forward and spot trading mechanism (iFAST), which entails a novel hybrid data
trading protocol with time efficiency, over uncertain MCS ecosystems. In iFAST,
the sellers (i.e., mobile devices who can contribute data) can provide
long-term or temporary sensing services to the buyers (i.e., sensing tasks).
Specifically, it enables signing long-term contracts in advance of future
transactions through a forward trading mode, via analyzing historical
statistics of the network/market, for which the notion of overbooking is
introduced and promoted. iFAST further encourages the buyers with unsatisfying
service quality to recruit temporary sellers through a spot trading mode,
considering the current network/market conditions. We analyze the fundamental
blocks of iFAST and provide a case study to demonstrate its performance.
Inspirations for future research directions of next-generation sensing and
communication are summarized.
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