Axel Küpper

Towards a federated cloud ecosystem: enabling managed cloud service consumption

While cloud computing has seen widespread usage, there exist domains where the diminishing of management capabilities associated with cloud computing prevent adoption. One such domain is the health sector, which is the focus of the TRESOR project. Enabling cloud computing usage under strict compliance constraints such as enterprise policies and legal regulations is the goal of TRESOR. The main approach consists of a distributed cloud proxy, acting as a trusted mediator between cloud consumers and service providers. In this paper we analyze issues which arise within the TRESOR context and show how an architecture for a proposed ecosystem bypasses these issues. The practicability of our solution is shown by a proof of concept proxy implementation. As all components of the architecture will be part of our proposed cloud ecosystem, we provide a holistic and generic proposal to regain management capabilities in cloud computing.

Estimating locations and coverage areas of mobile network cells based on crowdsourced data

Mobile network operators usually keep the data about their mobile network topology very secret. However, having this data, many sophisticated and innovative applications could be realized. Todays smartphones provide the means to measure cell data with which the mobile network topology of different operators can be approximately derived by applying various position estimation algorithms. These approaches deliver different results in terms of distance to the real positions of base stations and positions calculated by Google. In this paper, we analyze and evaluate state-of-the-art approaches for estimating base station positions out of crowdsourced data and integrate the most suitable methode(s) into the OpenMobileNetwork, which is an open-source initiative for publishing mobile network data using the semantic principles of Linked Data. The results show that the grid-based approach provides the best estimates for base station positions when compared with their real locations.

Deriving a Distributed Cloud Proxy Architecture for Managed Cloud Service Consumption

Businesses adopting Cloud Computing often have to comply with strict constraints, such as enterprise policies and legal regulations. From these compliance issues arise the need to enable managed cloud service consumption as a prerequisite for adoption. As we have shown before, the proposed TRusted Ecosystem for Standardized and Open cloud-based Resources (TRESOR) cloud ecosystem can achieve management of cloud service consumption [1]. In this paper we motivate and derive the architecture of the distributed TRESOR cloud proxy from technical, business and legal requirements within the context of the TRESOR project. We apply a derivation method where we evaluate the impact of each incremental architecture decision separately. This process enables researchers with supplementary requirements to adapt the intermediate derivations within other contexts in flexible ways.

Turning the OpenMobileNetwork into a live crowdsourcing platform for semantic context-aware services

The OpenMobileNetwork is a semantic model for mobile network topologies created by following the principles of Linked Data. By correlating data in the Linking Open Data Cloud with the OpenMobileNetwork, innovative Semantic Context-aware Services (CAS) can be realized that are not solely driven by classic context data (e.g., geographic location), but also include further information from the semantics of the context in use. So far, this open-source initiative provided rather static network topology data triplified from open-source cell databases, such as OpenCellID or OpenBMap. Integrating dynamic and live network context data (e.g., current traffic and number of users in a mobile network cell) by exploiting crowdsourcing methods will further improve the Semantic CAS experience since the historic and live state of a mobile network cell is a valuable data source to be taken into consideration when providing personalized services. The challenge in realizing such a crowdsourcing approach lies in motivating a significant number of users to contribute with their data. For this purpose, we have turned the OpenMobileNetwork from a static dataset into a Live Crowdsourcing Platform for Semantic CAS including a semantic cellular database based on extended network context ontologies, two smartphone clients, and a Measurement Framework for gamifying the crowdsourcing process of collecting network measurements. The measurement statistics highlight the effectiveness of this approach.

OpenMobileNetwork: extending the web of data by a dataset for mobile networks and devices

The number of datasets in the Linking Open Data Cloud increases rapidly and has reached a total of 295 by September 2011. Various content domains are covered by those datasets, such as Media, Government or Geographic Data, all directly linked to each other building a huge graph of interlinked structured data. However, data describing the mobile network topology including its components and (dynamic) properties (e.g., traffic or number of users in a radio cell) are not semantically available yet in the LOD Cloud. Therefore, we propose the OpenMobileNetwork -- a dataset for mobile networks and devices, which is semantically modeled using the Linked Data principles. It provides structured RDF data describing mobile networks, their topology and components (e.g., base stations, mobile devices or WiFi access points). Utilizing this dataset in combination with interlinked information that is present in the LOD Cloud, various applications can be realized that depend on mobile network and positioning data, such as Semantic Location-based Services. In this paper, however, we focus on the realization of a Power Management in Mobile Networks.

OpenMobileNetwork: A Platform for Providing Estimated Semantic Network Topology Data

Mobile network operators maintain data about their mobile network topology, which is mainly used for network provisioning and planning purposes restricting its full business potential. Utilizing this data in combination with the extensive pool of semantically modeled data in the Linking Open Data Cloud, innovative applications can be realized that would establish network operators as service providers and enablers in the highly competitive services market. In this article, the authors introduce the OpenMobileNetwork available at http://www.openmobilenetwork.org/ as an open solution for providing approximated network topology data based on the principles of Linked Data along with a business concept for network operators to exploit their valuable asset. Since the quality of the estimated network topology is crucial when providing services on top of it, the authors further analyze and evaluate state-of-the-art approaches for estimating base station positions out of crowdsourced data and discuss the results in comparison to real base station locations.

Cloud Service Matchmaking Using Constraint Programming

Service requesters with limited technical knowledge should be able to compare services based on their quality of service (QoS) requirements in cloud service marketplaces. Existing service matching approaches focus on QoS requirements as discrete numeric values and intervals. The analysis of existing research on non-functional properties reveals two improvement opportunities: list-typed QoS properties as well as explicit handling of preferences for lower or higher property values. We develop a concept and constraint models for a service matcher which contributes to existing approaches by addressing these issues using constraint solvers. The prototype uses an API at the standardisation stage and discovers implementation challenges. This paper concludes that constraint solvers provide a valuable tool to solve the service matching problem with soft constraints and are capable of covering all QoS property types in our analysis. Our approach is to be further investigated in the application context of cloud federations.

TRESOR – Towards the Realization of a Trusted Cloud Ecosystem

The TRESOR (Trusted Ecosystem for Standardized and Open cloud-based Resources http://www.cloud-tresor.de/) project enables cloud computing solutions for the German health sector. This sector deals with sensitive medical information and is in general not suitable for current cloud-based solutions, which are lacking appropriate privacy and security features. The project evaluates and proposes new architectural components to address these shortcomings. These will be combined into a secure and trustworthy ecosystem that will enable the health industry and other sectors to take advantage of cloud computing. The architecture consists of components, such as a marketplace, a broker, a proxy and a PaaS-platform. TRESOR addresses privacy and data protection issues and aims at providing a standardized solution with reduced lock-in effects that can also be used in other domains. In this paper the specific tasks and the architecture of these components are presented, important challenges of the TRESOR project are highlighted and preliminary results, such as a secure transfer protocol, and policy integration are shown.

A Domain Specific Language and a Pertinent Business Vocabulary for Cloud Service Selection

As more cloud computing offerings become available globally, cloud consumers’ efforts of gathering relevant information to support their service selection are raised considerably. On the one hand, high-volume marketplaces, such as Salesforce AppExchange, feature nonformalized offering descriptions. This abstinence of a service formalization impedes cloud consumers’ capabilities to both rapidly assess the fulfillment of their selection criteria and to compare different services uniformly. On the other hand, contemporary research on formalized service marketplaces faces significant challenges in its practical application, especially its ease of use and pertinence. In this article we present a novel textual domain specific language for describing services, a pertinent business vocabulary of selection criteria, and a brokering component. These artifacts raise cloud consumers’ capabilities while being practically applicable, pertinent to businesses, and easy to use.

Exploiting Location Semantics for Realizing Cross-Referencing Proactive Location-Based Services

Location-based Services (LBS) are one of the longest-standing value-added services in the mobile communications industry. The location of a user is the fundamental factor shaping such services and is usually computed solely in terms of the physical location relying on Reverse Geocoding APIs. It does not take into consideration the semantics of the location, but rather only the geographic spatial information, which significantly restricts the intelligibility of the provided LBS. In order to overcome the aforementioned limitations, we have introduced a Semantic Positioning Platform in a previous work being capable of providing semantically enriched self-referencing LBS. In this paper, we extend the platform by enabling cross-referencing proactive LBS (i.e., third-party tracking) based on semantically modeled user-specific location profiles (e.g., school or office) in combination with social relations among users. Furthermore, the independent platforms delivering the Semantic Positioning functionality (i.e., the Positioning Enabler and the Open Mobile Network) have been integrated into the Context Data Cloud, which is a context management ecosystem for delivering semantically enriched context-aware services. In addition, the Context Data Cloud for Android application including a Friend Tracker function has been implemented as a proof of concept. The evaluation in terms of battery consumption and positioning accuracy highlights the added value of our approach.