Eryk Schiller

Network Store: Exploring Slicing in Future 5G Networks

In this paper, we provide a revolutionary vision of 5G networks, in which SDN technologies are used for the programmability of the wireless network, and where a NFV-ready network store is provided to Mobile Network Operators (MNO), Enterprises, and Over-The-Top (OTT) third parties. The proposed network serves as a digital distribution platform of programmable Virtualized Network Functions (VNFs) that enables 5G application use-cases. Currently existing application stores, such as Apples App Store for iOS applications, Googles Play Store for Android, or Ubuntus Software Center, deliver applications to user specific software platforms. Our vision is to provide a digital marketplace, gathering 5G enabling Network Applications and Network Functions, written to run on top of commodity cloud infrastructures, connected to remote radio heads (RRH). The 5G Network Store will be the same to the network provider as the application store is currently to a software platform.

Critical issues of centralized and cloudified LTE-FDD Radio Access Networks

Cloudification of the Centralized-Radio Access Network (C-RAN) in which signal processing runs on general purpose processors inside virtual machines has lately received significant attention. Due to short deadlines in the LTE frequency division duplex access method, processing time fluctuations introduced by the virtualization process have a deep impact on C-RAN performance. This paper evaluates bottlenecks of the OpenAirInterface (OAI is an open-source software-based implementation of LTE) cloud performance, provides feasibility studies on C-RAN execution, and introduces recommendations for cloud architecture that significantly reduces the encountered execution problems. In typical cloud environments, the OAI processing time deadlines cannot be guaranteed. Our proposed cloud architecture shows good characteristics for OAI cloud execution. As an example, in our setup more than 99.5% processed LTE subframes reach reasonable processing deadlines close to performance of a dedicated machine of a single core CPU.

Integrating hydrological modelling, data assimilation and cloud computing for real-time management of water resources

Online data acquisition, data assimilation and integrated hydrological modelling have become more and more important in hydrological science. In this study, we explore cloud computing for integrating field data acquisition and stochastic, physically-based hydrological modelling in a data assimilation and optimisation framework as a service to water resources management. For this purpose, we developed an ensemble Kalman filter-based data assimilation system for the fully-coupled, physically-based hydrological model HydroGeoSphere, which is able to run in a cloud computing environment. A synthetic data assimilation experiment based on the widely used tilted V-catchment problem showed that the computational overhead for the application of the data assimilation platform in a cloud computing environment is minimal, which makes it well-suited for practical water management problems. Advantages of the cloud-based implementation comprise the independence from computational infrastructure and the straightforward integration of cloud-based observation databases with the modelling and data assimilation platform. A cloud-based real-time modelling and data assimilation framework is established.Can be connected to a cloud-based data acquisition and monitoring module.HydroGeoSphere is used as the hydrological forward model.The tiltedV-catchment problem is used as a benchmark for the system.

5G Architectural Design Patterns

In this work, we present novel Architectural Design Patterns towards open, cloud-based 5G communications. We provide a brief classification of technologies that cannot be ignored in the design process of 5G systems and illustrate how a new technological added value can be created, when current methodologies, design paradigms, as well as design patterns and their extensions are properly exploited in efficient Radio Access Network (RAN) architectures. We believe that in many cases, the required technology is already there; nevertheless the correct approach has to be worked out and placed within an appropriate context, especially in the case of the integration of complex RAN systems. The enhancements in RF optimization, the progress in cloud computing, Software Defined Networks (SDN) and Network Function Virtualization (NFV), new design concepts such as Network Slicing have to become part of the RAN design methodology. Diverse architectural concepts should break existing stereotypes to pave the way towards the true 5G system integration.

Binary waypoint geographical routing in wireless mesh networks

We propose Binary Waypoint Routing, a novel geographical routing protocol for wireless mesh networks. Its idea is to learn and maintain source routes to a small number of nodes called binary waypoints that are placed in subspaces constructed as a result of binary space partitioning. A source node sends a packet to a waypoint for a given destination and intermediate nodes try to adapt the packet route by aiming at waypoints that are closer to the destination. Our simulation results show that the proposed scheme achieves high packet delivery rate with a traffic pattern similar to the Optimal Shortest Path Routing.

Demo: Closer to Cloud-RAN: RAN as a Service

Commoditization and virtualization of wireless networks are changing the economics of mobile networks to help network providers (e.g., MNO, MVNO) move from proprietary and bespoke hardware and software platforms toward an open, cost-effective, and flexible cellular ecosystem. In addition, rich and innovative local services can be efficiently created through cloudification by leveraging the existing infrastructure. In this work, we present RANaaS, which is a cloudified radio access network delivered as a service. RANaaS provides the service life-cycle of an on-demand, elastic, and pay as you go 3GPP RAN instantiated on top of the cloud infrastructure. We demonstrate an example of real-time cloudified LTE network deployment using the OpenAirInterface LTE implementation and OpenStack running on commodity hardware as well as the flexibility and performance of the platform developed.

Properties of Greedy Geographical Routing in Spontaneous Wireless Mesh Networks

We analyze greedy geographical routing in spontaneous wireless mesh networks to show several interesting properties. First, we can approximate the dependence of packet loss probability on the mean node rank with a Fermi-Dirac function. When the mesh network grows, it becomes opaque to packets regardless of the average node rank. We also show that packet loss probability in mesh networks with greedy geographical routing does not exhibit the behavior of percolating systems. Finally, we propose an analytical model of greedy geographical routing and use it to derive packet loss probability.

An architecture for seamless mobility in spontaneous wireless mesh networks

In this paper, we consider spontaneous wireless mesh networks that can provide wide coverage connectivity to mobile nodes. Our mobility scheme builds upon separation between a persistent node identifier and its current address. When joining the mesh, a mobile node associates with a mesh router that updates a location service managed in the mesh as a distributed hash table. Mobility implies changing addresses while a node moves in the mesh. To keep the rate of location updates and correspondent node notifications low, the address of the new mesh router with which the mobile node is associated needs to be topologically close to the previous one. Thus, such a mobility scheme requires an addressing space with specific properties. We achieve this by defining an algorithm for constructing a pseudo-geographical addressing space: a few nodes know their exact locations and others estimate their relative positions to form a topologically consistent addressing space. Such an addressing space also enables scalable and low overhead routing in the wireless mesh---we propose a trajectory based long distance ballistic geographical routing.

Toward a Fully Cloudified Mobile Network Infrastructure

Cloud computing enables the on-demand delivery of resources for a multitude of services and gives the opportunity for small agile companies to compete with large industries. In the telco world, cloud computing is currently mostly used by mobile network operators (MNO) for hosting non-critical support services and selling cloud services such as applications and data storage. MNOs are investigating the use of cloud computing to deliver key telecommunication services in the access and core networks. Without this, MNOs lose the opportunities of both combining this with over-the-top (OTT) and value-added services to their fundamental service offerings and leveraging cost-effective commodity hardware. Being able to leverage cloud computing technology effectively for the telco world is the focus of mobile cloud networking (MCN). This paper presents the key results of MCN integrated project that includes its architecture advancements, prototype implementation, and evaluation. Results show the efficiency and the simplicity that a MNO can deploy and manage the complete service lifecycle of fully cloudified, composed services that combine OTT/IT- and mobile-network-based services running on commodity hardware. The extensive performance evaluation of MCN using two key proof-of-concept scenarios that compose together many services to deliver novel converged elastic, on-demand mobile-based but innovative OTT services proves the feasibility of such fully virtualized deployments. Results show that it is beneficial to extend cloud computing to telco usage and run fully cloudified mobile-network-based systems with clear advantages and new service opportunities for MNOs and end-users.

Real-Time Environmental Monitoring for Cloud-Based Hydrogeological Modeling with HydroGeoSphere

This paper describes an architecture for real-time environmental modeling. It consists of a wireless mesh network equipped with sensors and a cloud-based infrastructure to perform real-time environmental simulations using a physics-based model combined with an Ensemble Kalman Filter. The purpose of the system is to optimize groundwater abstraction close to a river. These initial studies demonstrate that the cloud infrastructure can simultaneously compute a large number of simulations, thus allowing for the implementation of Ensemble Kalman Filters in real-time.