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.

翻译：移动群智感知（MCS）网络中大数据交换与处理的挑战，要求设计响应迅速且无缝的服务供给机制以及合理的激励策略。尽管基于实时网络条件与决策的传统现场现货资源交易可促进MCS网络中的数据共享，但由于其依赖对复杂动态MCS环境的及时分析，常导致服务供给延迟过长及不可避免的交易失败。这些局限性促使我们研究一种集成式远期与现货交易机制（iFAST），该机制提出了一种基于MCS网络架构的新型混合服务交易协议。在iFAST中，卖家（即拥有感知资源的移动用户）可为买家（即感知任务所有者）提供长期或临时传感服务。iFAST通过分析市场历史统计数据，在远期交易模式下提前签署长期合约（为此引入并推广了超量预订概念），从而为未来交易提供保障。进一步地，iFAST允许服务质量不达标的买家在考虑当前市场/网络条件的情况下，通过现货交易模式招募临时卖家。本文分析了iFAST的核心模块，并通过案例研究验证其相较于现有方法的优越性能。最后，总结了面向下一代MCS网络可靠服务供给的未来研究方向。