Accelerating the Delivery of Data Services over Uncertain Mobile Crowdsensing Ecosystems

The challenge of exchanging and processing of big data over Mobile Crowdsensing (MCS) networks calls for the new design of responsive and seamless service provisioning as well as proper incentive mechanisms. Although conventional onsite spot trading of resources based on real-time network conditions and decisions can facilitate the data sharing over MCS networks, it often suffers from prohibitively long service provisioning delays and unavoidable trading failures due to its reliance on timely analysis of complex and dynamic MCS environments. These limitations motivate us to investigate an integrated forward and spot trading mechanism (iFAST), which entails a new hybrid service trading protocol over the MCS network architecture. In iFAST, the sellers (i.e., mobile users with sensing resources) can provide long-term or temporary sensing services to the buyers (i.e., sensing task owners). iFast enables signing long-term contracts in advance of future transactions through a forward trading mode, via analyzing historical statistics of the market, for which the notion of overbooking is introduced and promoted. iFAST further enables the buyers with unsatisfying service quality to recruit temporary sellers through a spot trading mode, upon considering the current market/network conditions. We analyze the fundamental blocks of iFAST, and provide a case study to demonstrate its superior performance as compared to existing methods. Finally, future research directions on reliable service provisioning for next-generation MCS networks are summarized.