Collaborative Research: CISE-MSI: RCBP-RF: CNS: Truthful and Optimal Data Preservation in Base Station-less Sensor Networks: An Integrated Game Theory and Network Flow Approach

该奖项的全部或部分资金来自《2021年美国救援计划法案》(公法117-2)。该项目的目标是为新兴的无基站传感器网络创建一个真实和最佳的资源分配框架。由于这种网络部署在没有数据收集基站(例如水下探测)的具有挑战性的环境中，最重要的任务是在获得上传机会之前在网络中保存大量生成的数据。然而，在分布式环境和不同的控制下，具有有限资源(即能量、功率和存储空间)的传感器节点可能会为了节省自己的资源和最大化自己的利益而表现出自私行为。以节点为中心的自私性和以数据为中心的数据保存之间的紧张关系带来了新的挑战，需要综合研究博弈论(战略交互科学)和网络流(研究如何高效和有效地移动网络对象)。本项目部署了以下研究推力。首先，从纳什均衡、无政府状态代价、稳定代价和Shapley方案四个方面分析了自私数据保存问题。其次，运用机制设计的方法，找出现有方法的局限性，提出新的激励机制。第三，设计了一套新的数据保存和数据聚合游戏，以纳入特定于网络的功能，如数据值和数据空间相关性。所有的研究都将博弈论和网络流技术相互交织在一起，以实现真实的、最优的数据保存。最后，设计的技术将通过模拟、现有的网络流量和博弈论软件以及CloudBank进行评估。通过保存物理世界的大量数据，否则无法访问，无基站传感器网络提供了科学前沿的全面视角，包括科学探索、灾害预警和气候变化，从而造福社会。该项目由加州州立大学长滩经济系和加州州立大学多明格斯·希尔斯计算机科学系合作完成。这种跨机构和跨学科的合作为学生提供了综合的研究和教育体验。教育的目标不仅是招收几个最好的学生并与他们合作，而且要在这两所学校激励和教育尽可能多的代表不足的学生。计划的活动包括学生校园参观和海报展览，校园内合作，会议演示和参与，课程更新和开发，以及与两所学校现有的少数群体服务计划相结合。该项目的详细信息可在https://web.csulb.edu/~ychen7/bsn_gametheory/.上找到该网站将随着研究的进展定期更新，并将保持五到十年的公众查看。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).The goal of the project is to create a truthful and optimal resource allocation framework for emerging base station-less sensor networks. As such networks are deployed in challenging environments without data-collecting base station (e.g., underwater exploration), the paramount task is to preserve large amounts of generated data inside the networks before uploading opportunities become available. In a distributed setting and under different control, however, the sensor nodes with limited resources (i.e., energy power and storage spaces) could behave selfishly in order to save their own resources and maximize their own benefits. The tension between node-centric selfishness and data-centric data preservation gives rise to new challenge that calls for integrated study of game theory (the science of strategic interaction), and network flows (that studies how to move network objects efficiently and effectively). This project deploys following research thrusts. First, selfish data preservation is analyzed in terms of Nash equilibrium, price of anarchy, price of stability, and Shapley scheme. Second, mechanism design approach is used to identify the limitations of existing methodology and propose new incentive mechanisms. Third, a suite of new data preservation and data aggregation games are designed to incorporate network-specific features such as data values and data spatial correlations. All the research thrusts intertwine game-theoretic and network flow technique to achieve the truthful and optimal data preservation. Finally, the designed techniques will be evaluated by simulations, existing network flow and game theory software, as well as CloudBank.By preserving large amounts of data of the physical world otherwise inaccessible, base station-less sensor networks provide a comprehensive view of scientific frontiers including scientific exploration, disaster warning and climate change, thus benefiting the society. This project is collaborated between California State University Long Beach Economics Department and California State University Dominguez Hills Computer Science Department. This cross-institutional and interdisciplinary collaboration provides an integrative research and education experience for students. The educational goal is not just recruiting and working with a few best students but inspiring and educating as many underrepresented students as possible at both institutions. Planned activities include student campus visit and poster exhibition, intra-campus collaboration, conference presentation and participation, curriculum update and development, and integrating with existing minority-serving programs at both institutions.Details of the project can be found at https://web.csulb.edu/~ychen7/bsn_gametheory/. This website will be updated regularly as the research progresses and will be maintained for public view for five to ten years.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.