在不确定的移动群智感知网络上加速数据服务交付
Accelerating the Delivery of Data Services over Uncertain Mobile Crowdsensing Networks
AI总结：
针对不确定MCS网络中现货交易延迟高、易失败的问题，提出融合远期合同与现货补充的iFAST混合数据交易机制，以加速数据服务交付。
摘要：
在移动群智感知（MCS）网络上交换和处理大数据所面临的挑战，要求设计无缝的数据服务供给机制，以便利用移动设备/用户的资源完成群智感知任务。尽管传统上基于实时网络状况进行资源的现场现货交易能够促进数据共享，但由于需要及时分析动态网络环境，它往往会遭遇高得令人难以承受的服务供给延迟以及不可避免的交易失败。这些局限促使我们研究一种在不确定MCS生态系统中的远期与现货一体化交易机制（iFAST），该机制包含一种具有时间效率的新型混合数据交易协议。在iFAST中，卖方（即能够贡献数据的移动设备）可以向买方（即感知任务）提供长期或临时感知服务。具体而言，该机制通过分析网络/市场的历史统计数据，以远期交易模式在未来交易之前预先签订长期合同，并为此引入和推广了超售概念。iFAST还结合当前网络/市场状况，鼓励服务质量不令人满意的买方通过现货交易模式招募临时卖方。我们分析了iFAST的基本组成模块，并提供案例研究以展示其性能。文中还总结了对下一代感知与通信未来研究方向的启发。
英文摘要：
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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