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Abstract-Large-scale information dissemination in multicast communications has been increasingly attracting attention, be it through uptake in new services or through recent research efforts. In these, the core issues are supporting increased forwarding speed, avoiding state in the forwarding elements, and scaling in terms of the multicast tree size. This paper addresses all these challenges-which are crucial for any scalable multicast scheme to be successful-by revisiting the idea of in-packet Bloom filters and source routing. As opposed to the traditional in-packet Bloom filter concept, we build our Bloom filter by enclosing limited information about the structure of the tree. Analytical investigation is conducted and approximation formulas are provided for optimal-length Bloom filters, in which we got rid of typical Bloom filter illnesses such as false-positive forwarding. These filters can be used in several multicast implementations, which are demonstrated through a prototype. Thorough simulations are conducted to demonstrate the scalability of the proposed Bloom filters compared to its counterparts.

Abstract-Failure dependent protection (FDP) is known to achieve optimal capacity efficiency among all types of protection, at the expense of longest recovery time and more complicated signaling overhead. This particularly hinders the usage of FDP in an all-optical mesh networks. As a remedy, the paper investigates a new restoration framework that enables all-optical fault management and device configuration via state-of-the-art failure localization techniques, such that the FDP restoration process can be implemented without relying on any control plane signaling. With the proposed restoration framework, a novel spare capacity allocation problem is defined, and is further analyzed on circulant topologies for any single link failure, aiming to to gain a solid understanding of the problem. By allowing reuse of monitoring resources for restoration capacity, we are particularly interested in the monitoring resource hidden property where less or even no monitoring resources are consumed as more working traffic is in place. To deal with general topologies, we introduce a novel heuristic approach to the proposed spare capacity allocation problem, which is comprises a generic FDP survivable routing scheme followed by a novel monitoring resource allocation method. Extensive simulation is conducted to examine the proposed scheme and verify the proposed restoration framework.

As emerging network technologies and softwareization render networks more flexible, the question arises of how to exploit these flexibilities for optimization. Given the complexity of the involved network protocols and the context in which networks are operating, such optimizations are increasingly difficult to perform. An interesting vision in this regard are "self-driving" networks: networks which measure, analyze and control themselves in an automated manner, reacting to changes in the environment (e.g., demand), while exploiting existing flexibilities to optimize themselves. A fundamental challenge faced by any (self-)optimizing network concerns the limited knowledge about future changes in the demand and environment in which the network is operating. Indeed, given that reconfigurations entail resource costs and may take time, an "optimal" network configuration for the current demand and environment may not necessarily be optimal also in the near future. Thus, it is desirable that (self-)optimizations also prepare the network for possibly unexpected events. This paper makes the case for empowering self-driving networks: empowerment is an information-centric measure which accounts for how "prepared" a network is and how much flexibility is preserved over time. While empowerment has been successfully employed in other domains such as robotics, we are not aware of any applications in networking. As a case study for the use of empowerment in networks, we consider self-driving networks offering topological flexibilities, i.e., reconfigurable edges.

The emerging trend to softwarize networks based on concepts such as Network Virtualization, Software Defined Networking and Network Functions Virtualization promises to increase flexibility in networking. So far, flexibility is used rather as a qualitative argument for a network design choice. Furthermore, the meaning of flexibility behind such qualitative arguments is highly varying in the state of the art as a common understanding of flexibility is missing. In this paper, we present an approach towards evaluating network flexibility through a definition of a flexibility measure, which provides a quantitative analysis and a comparison of different network designs. For us, network flexibility refers to the ability to support new requests that can be, for example, changes in the requirements or new traffic distributions. We show with two case studies how an application of such measure could lead to a better understanding of different network designs with respect to flexibility. We also illustrate the trade-off between flexibility and cost needed to provide flexibility. With our proposed flexibility measure, we would like to stimulate the discussion towards a more quantitative analysis of softwarized networks and beyond. I. INTRODUCTIONIn recent years, network operation has become more software-oriented. Concepts such as Network Virtualization (NV), Software Defined Networking (SDN), and Network Functions Virtualization (NFV) provide a new level of indirection and new interfaces for setting up (virtual) networks and (virtual) network functions on demand. These concepts support the adaptation of networks to changes that arise from user demands as well as from traffic fluctuations. When designing networks for adaptation to changes, flexibility is claimed to be the competitive advantage of new network designs.Although researchers claim flexibility, a common comparison of flexibility is not performed due to a missing consensus of how flexibility can be quantified. Thus the available qualitative arguments vary a lot in literature, since the use of flexibility as a measure is not well understood or has not been deeply investigated. A missing definition leaves readers to draw conclusions on their own.We would like to close this gap by proposing an initial definition of a flexibility measure and show its practical application with two case studies.Such flexibility measure enables a quantitative analysis and comparison of different network design choices. Thus, it supports decision making for designs considering softwarization concepts where flexibility is an important design goal due to the increase of design choices in addition to performance metrics, e.g., high throughput or low latency. Today, the rather qualitative statements on flexibility can not fully support decision makers in particular from the industry. For research and development, a flexibility definition fosters the understanding of which technical concepts lead to more flexibility in network design. In this way, design guidelines for flexibility can...