The potential impact of IoT has advanced from a dream, to a marketing cliché, to a reality with fierce industrial (and academic) contention. Despite earlier efforts to introduce IoT as a platform for connecting billions of devices, the realizations today (over dozens of companies) are far from interoperable. A truly scalable IoT has to meet four conditions that are thus far unachievable under proprietary IoT solutions: 1) It has to tap into the significant resources of billions of networked devices that are readily available, dispersed, operational but mostly untapped. 2) It has to expand in scalable operation through uniform policy management that enforces synergetic operation between IoT entities and encourages cooperation, 3) It must maintain a clear decoupling between data providers and their identities to encourage users to provide data with realizable incentive schemes, and 4) resources pooled from heterogeneous devices should be uniformly evaluated for Quality and Value to yield a clearly calibrated spectrum of services which are based on resources and their profiles, rather than producers and their own proprietaries. These directions will transcend elastic definitions of connectivity, to a convergent paradigm that encourages all connected devices to turn into pro-active prosumers in a new economy of interaction and possibilities.
In its 3rd iteration, this workshop will build on its success to address challenges in realizing a scalable and inherently heterogeneous IoT, and solicit novel solutions to functional elasticity and spatial scalability. Today, most industrial contenders (IBM, CISCO, Jasper, HP, Google, EVRYTHNG, etc.) are advocating for their versions of IoT (e.g., Smarter Planet, IoEverything, Brillo, etc.), while mainstream research efforts address singular views of scalable sensing, massive RFID-based identification, and other topological remedies to handle the ensuing Big Data communication and sense-making processes.
Specific Topics
Topics of interest to the Convergent IoT (C-IoT) workshop include but are not limited to:
- Data and organization Interoperability challenges for IoT systems
- Quality of Information pruning for crowd-solicited data in heterogeneous IoT
- Resource identification, discovery, and profiling in heterogeneous IoT
- IoT Interoperability issues
- Resource sharing and actuation conflicts resolution
- Crowd-solicited IoT proliferation
- IoT systems collaboration and cooperation mechanisms
- Innovative IoT incentive schemes
- Convergent paradigms in the Internet of Things
- Non-proprietary standardization frameworks for a heterogeneous IoT
- Convergent services on malleable IoT infrastructures (i.e. based on Information/data planes)
- IoT edge analytics
- IoT service orchestration and scheduling
- Industrial Internet – Value creation and challenges
