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The challenge of exchanging and processing of big data over MobileCrowdsensing (MCS) networks calls for the new design of responsive and seamlessservice provisioning as well as proper incentive mechanisms. Althoughconventional onsite spot trading of resources based on real-time networkconditions and decisions can facilitate the data sharing over MCS networks, itoften suffers from prohibitively long service provisioning delays andunavoidable trading failures due to its reliance on timely analysis of complexand dynamic MCS environments. These limitations motivate us to investigate anintegrated forward and spot trading mechanism (iFAST), which entails a newhybrid service trading protocol over the MCS network architecture. In iFAST,the sellers (i.e., mobile users with sensing resources) can provide long-termor temporary sensing services to the buyers (i.e., sensing task owners). iFastenables signing long-term contracts in advance of future transactions through aforward trading mode, via analyzing historical statistics of the market, forwhich the notion of overbooking is introduced and promoted. iFAST furtherenables the buyers with unsatisfying service quality to recruit temporarysellers through a spot trading mode, upon considering the currentmarket/network conditions. We analyze the fundamental blocks of iFAST, andprovide a case study to demonstrate its superior performance as compared toexisting methods. Finally, future research directions on reliable serviceprovisioning for next-generation MCS networks are summarized.

Accelerating the Delivery of Data Services over Uncertain Mobile Crowdsensing Ecosystems