A keyword-based ICN-IoT platform

Information-Centric Networking (ICN) has been proposed as a promising solution for the Internet of Things (IoT), due to its focus on naming data, rather than endpoints, which can greatly simplify applications. The hierarchical naming of the Named-Data Networking (NDN) architecture can be used to name groups of data values, for example, all temperature sensors in a building. However, the use of a single naming hierarchy for all kinds of different applications is inflexible. Moreover, IoT data are typically retrieved from multiple sources at the same time, allowing applications to aggregate similar information items, something not natively supported by NDN. To this end, in this paper we propose (a) locating IoT data using (unordered) keywords combined with NDN names and (b) processing multiple such items at the edge of the network with arbitrary functions. We describe and evaluate three different strategies for retrieving data and placing the calculations in the edge IoT network, thus combining connectivity, storage and computing

A network-aware framework for energy-efficient data acquisition in wireless sensor networks

Wireless sensor networks enable users to monitor the physical world at an extremely high fidelity. In order to collect the data generated by these tiny-scale devices, the data management community has proposed the utilization of declarative data-acquisition frameworks. While these frameworks have facilitated the energy-efficient retrieval of data from the physical environment, they were agnostic of the underlying network topology and also did not support advanced query processing semantics. In this paper we present KSpot+, a distributed network-aware framework that optimizes network efficiency by combining three components: (i) the tree balancing module, which balances the workload of each sensor node by constructing efficient network topologies; (ii) the workload balancing module, which minimizes data reception inefficiencies by synchronizing the sensor network activity intervals; and (iii) the query processing module, which supports advanced query processing semantics. In order to validate the efficiency of our approach, we have developed a prototype implementation of KSpot+ in nesC and JAVA. In our experimental evaluation, we thoroughly assess the performance of KSpot+ using real datasets and show that KSpot+ provides significant energy reductions under a variety of conditions, thus significantly prolonging the longevity of a WSN

A Taxonomy of Information-Centric Networking Architectures based on Data Routing and Name Resolution Approaches

This study presents a vast coverage of current Information-Centric Network (ICN) submission by evaluating eight distinct and popular routing and name resolution approaches. Internet build-up and initial deposition were based on a host-driven approach. With the increasing demands for mediadriven data flooding the cost of the Internet, a new semantic and paradigm shift was envisioned known as ICN. InformationCentrism is an approach that partly dissociates the host dependencies by referring to contents by unique identifiers called name. However, to benefit from the content network, forwarding, naming and routing, among other issues are still in its developmental stages. The taxonomy serves as a basis for research directions, challenges, implementation and future studies for standardizing the ICN routing and naming. Routing and Name Resolution were themed in categories of strategies, contributions, issues and drawbacks. The major findings of this paper are providing a classification and review of the data routing and name resolutions approaches that are proposed on eight ICN architectures; presenting drawback areas in the selected architectures; and finally highlighting some challenges of ICN routing for the ICN research community vending