Enabling heterogeneous self-organizing machine-to-machine networks

机器对机器（M2M）通信为创建分布式应用程序创造了一种新的范例，这些应用程序连接了以前从未见过的智能设备。据估计，M2M系统的全球收入估计每年增长38%，到2020年将达到数千亿美元。M2M应用必须满足对低成本、可扩展性和低开销的需求，并且必须能够在不同通信系统的混合上操作。 因此，M2M应用可以极大地受益于网络的自组织方法，因为它们能够适应网络拓扑、业务混合和服务需求的变化。然而，异构M2M系统的自组织设计原理的使用在很大程度上仍然是未开发的。该研究项目的目标是挖掘M2M通信自组织网络的潜力。拥有可以即时和低成本部署的大规模网络的能力为更简单和更具资源和成本效益的联网创造了机会，并可能为具有重大商业价值的创新技术奠定基础。 该项目将使用新的理论和实践方法来解决战略领域的问题，以实现自组织M2M通信。该项目将产生新的技术和方法，用于（1）有线和无线网络集合上的可扩展路由和名称解析;（2）网络优化的实时性能监控;以及（3）M2M网络的动态可扩展和灵活的流量控制算法。拟议的项目将把拟议的解决方案从理论到现实生活中的实施，从而提供适合商业化工作的概念验证原型。

Machine-to-machine (M2M) communications has created a new paradigm for creating distributed applications that connect previously unseen numbers of intelligent devices. By some estimates, the worldwide revenues from M2M systems are estimated to grow by 38% annually, and reach several hundred billion dollars by 2020. M2M applications must satisfy demands for low cost, scalability, and low overhead, and must be able to operate over a mix of different communication systems. Thus, M2M applications can greatly benefit from self-organizing approaches to networking, because of their ability to adapt to changes of network topology, traffic mix, and service requirements. However, the use of self-organizing design principles for heterogeneous M2M systems remains largely unexplored. The goal of this research project is to harvest the potential of self-organizing networks for M2M communications. The ability to have large-scale networks that can be deployed instantaneously and inexpensively creates opportunities for simpler and more resource- and cost-efficient networking, and may lay the foundation for innovative technologies with significant commercial value. This project will use new theoretical and practical approaches to address strategic areas problems to enable self-organizing M2M communications. The project will result in novel techniques and methodologies for (1) Scalable routing and name resolution over collections of wired and wireless networks; (2) Real-time performance monitoring for network optimization; and (3) Dynamically loadable and flexible traffic control algorithms for M2M networks. The proposed project will carry the proposed solutions from theory to a real-life implementation, and thus provide proof-of-concept prototypes suitable for commercialization efforts.