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The term Internet of Things is often used to talk about the trend of embedding microprocessors in everyday devices and connecting them to the Internet. The Internet of Things poses challenging communication requirements since the participating devices are heterogeneous, resource-constrained and operate in an ever changing environment. To cope with those requirements, academic research projects have proposed novel network architectures, such as the Dynamic Protocol Stack (DPS) architecture. In this paper, we use smart camera networks as an example of the Internet of Things and evaluate the DPS architecture in this scenario. Our smart camera nodes are implemented as an FPGA-based system-on-chip architecture that uses the DPS architecture for the network communication. We evaluate our smart camera nodes in two case studies. In the first case study, we demonstrate that our proposed smart camera network can track a single object over the field of view of several camera nodes. In the second case study, we show that an adaptive hardware/software mapping of the network functionality can save about 22% of the FPGA resources as compared to a static mapping. The hardware/software mapping can be adapted at a processing delay of a single video frame.

Modern compute systems continue to evolve towards increasingly complex, heterogeneous and distributed architectures. At the same time, functionality and performance are no longer the only aspects when developing applications for such systems, and additional concerns such as flexibility, power efficiency, resource usage, reliability and cost are becoming increasingly important. This does not only raise the question of how to efficiently develop applications for such systems, but also how to cope with dynamic changes in the application behaviour or the system environment. The EPiCS Project aims to address these aspects through exploring self-awareness and self-expression. Self-awareness allows systems and applications to gather and maintain information about their current state and environment, and reason about their behaviour. Self-expression enables systems to adapt their behaviour autonomously to changing conditions. Innovations in EPiCS are based on systematic integration of research in concepts and foundations, customisable hardware/software platforms and operating systems, and self-aware networking and middleware infrastructure. The developed technologies are validated in three application domains: computational finance, distributed smart cameras and interactive mobile media systems.

Network programming is widely understood as programming strictly defined socket interfaces. Only some frameworks have made a step towards real network programming by decomposing networking functionality into small modullar blocks that can be assembled in a ?exible manner. In this paper, we tackle the challenge of accommodating 3 partially con?icting objectives: (i) high ?exibility for network programmers, (ii) re-configuration of the network stack at runtime, and (iii) high packet forwarding rates. First experiences with a prototype implementation in Linux suggest little performance overhead compared to the standard Linux protocol stack.

Future network architectures aim at solving the shortcomings of the traditional, static Internet architecture. In order to provide optimal service they have to adapt their functionality to different networking situations. This can be achieved by dividing the networking functionality into modular blocks and combining them as required at runtime. While the feasibility and flexibility of novel network architectures have been successfully demonstrated on software-based prototypes, they are often unable to provide sufficient performance due to the lack of hardware acceleration. We present a networking node architecture for future Internet applications that provides a reconfigurable hardware/software platform in which the modules of the node's network stack can be flexibly distributed at runtime across hardware and software. By utilizing novel reconfiguration-aware communication mechanisms for functional blocks both within and across the hardware and software domains, our flexible node architecture enables dedicated hardware acceleration for adaptive networking.