Automated Pattern-Based Service Deployment in Programmable Networks

This paper presents a flexible service deployment architecture for the automated, on-demand deployment of distributed services in programmable networks. The novelty of our approach is (a) the customization of the deployment protocol by utilizing modular building blocks, namely navigation patterns, aggregation patterns, and capability functions, and (b) the definition of a corresponding service descriptor. A customizable deployment protocol has several important advantages: It supports a multitude of services, and it allows for an ad hoc optimization of the protocol according to the specific needs of a service and the current network conditions. Moreover, our architecture provides an environment for studying new patterns which aim at reducing deployment latency and bandwidth for certain services. We demonstrate how the developed architecture can be used to setup a virtual private network, and we present measurements conducted with our prototype in the PlanetLab test network. Furthermore, a comparison of a distributed pattern with a centralized pattern illustrates the performance trade-off for different deployment strategie

Why (and How) Networks Should Run Themselves

The proliferation of networked devices, systems, and applications that we depend on every day makes managing networks more important than ever. The increasing security, availability, and performance demands of these applications suggest that these increasingly difficult network management problems be solved in real time, across a complex web of interacting protocols and systems. Alas, just as the importance of network management has increased, the network has grown so complex that it is seemingly unmanageable. In this new era, network management requires a fundamentally new approach. Instead of optimizations based on closed-form analysis of individual protocols, network operators need data-driven, machine-learning-based models of end-to-end and application performance based on high-level policy goals and a holistic view of the underlying components. Instead of anomaly detection algorithms that operate on offline analysis of network traces, operators need classification and detection algorithms that can make real-time, closed-loop decisions. Networks should learn to drive themselves. This paper explores this concept, discussing how we might attain this ambitious goal by more closely coupling measurement with real-time control and by relying on learning for inference and prediction about a networked application or system, as opposed to closed-form analysis of individual protocols

Towards a Security, Privacy, Dependability, Interoperability Framework for the Internet of Things

A popular application of ambient intelligence systems constitutes of assisting living services on smart buildings. As intelligence is imported in embedded equipment, the system becomes able to provide smart services (e.g. control lights, airconditioning, provide energy management services etc.). IoT is the main enabler of such environments. However, the interconnection of these cyber-physical systems and the processing of personal data raise serious security and privacy issues. In this paper we present a framework that can guarantee Security, Privacy, Dependability and Interoperability (SPDI) in IoT. Taking advantage of the underlying IoT deployment, the proposed framework not only implements the requested smart functionality but also provide modelling and administration that can guarantee those SPDI properties. Moreover, we provide an application example of the framework in a smart building scenario

Building Programmable Wireless Networks: An Architectural Survey

In recent times, there have been a lot of efforts for improving the ossified Internet architecture in a bid to sustain unstinted growth and innovation. A major reason for the perceived architectural ossification is the lack of ability to program the network as a system. This situation has resulted partly from historical decisions in the original Internet design which emphasized decentralized network operations through co-located data and control planes on each network device. The situation for wireless networks is no different resulting in a lot of complexity and a plethora of largely incompatible wireless technologies. The emergence of "programmable wireless networks", that allow greater flexibility, ease of management and configurability, is a step in the right direction to overcome the aforementioned shortcomings of the wireless networks. In this paper, we provide a broad overview of the architectures proposed in literature for building programmable wireless networks focusing primarily on three popular techniques, i.e., software defined networks, cognitive radio networks, and virtualized networks. This survey is a self-contained tutorial on these techniques and its applications. We also discuss the opportunities and challenges in building next-generation programmable wireless networks and identify open research issues and future research directions.Comment: 19 page