Enabling heterogeneous self-organizing machine-to-machine networks

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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.