Ubiquitous sensing environments such as sensor networks collect large amounts of data. This data volume is destined to grow even further with the vision of the Internet of Things. Cloud computing promises to elastically store and process such sensor data. As an additional benefit, storage and processing in the Cloud enables the efficient aggregation and analysis of information from different data sources. However, sensor data often contains privacy-relevant or otherwise sensitive information. For current Cloud platforms, the data owner looses control over her data once it enters the Cloud. This imposes adoption barriers due to legal or privacy concerns. Hence, a Cloud design is required that the data owner can trust to handle her sensitive data securely. In this paper, we analyze and define properties that a trusted Cloud design has to fulfill. Based on this analysis, we present the security architecture of SensorCloud. Our proposed security architecture enforces end-to-end data access control by the data owner reaching from the sensor network to the Cloud storage and processing subsystems as well as strict isolation up to the service-level. We evaluate the validity and feasibility of our Cloud design with an analysis of our early prototype. Our results show that our proposed security architecture is a promising extension of today's Cloud offers.

Dynamic adaptive HTTP streaming (DASH) is a new concept for video streaming using consecutive downloads of short video segments. 3GPP has developed the basic DASH standard which is further extended by the Open IPTV Forum (OIPF) and MPEG. In all versions available to date, only very simple content protection use cases are enabled. Extensions are needed to enable important advanced use cases like pay-per-view and license change in an ongoing video channel.

This paper deals with the intertwined problems of feasibility, power allocation and call admission control on the basis of the signal-to-interference-ratio in multi-cell CDMA networks. Positively homogeneous in-cell interference functions are introduced. Under this general concept optimum power allocations are determined by first solving in-cell interference problems with fixed background noise, and subsequently a small system of linear coupling equations. This approach simultaneously clarifies the existence of some power allocation such that minimum SIR requirements are fulfilled. The decomposition is also utilized for designing a decentralized admission control algorithm. Finally, guidelines are given on how required parameters may be estimated in existing network structures.

Today mobile TV services in cellular spectrum are delivered over unicast radio bearers as offered by 3G technologies like WCDMA and HSDPA. Since unicast transmission does not scale very well if mobile TV becomes a true mass service, 3GPP has defined a broadcast extension for UMTS, called multimedia broadcast multicast service (MBMS). MBMS introduces radio broadcast bearers serving all users in common, thus providing true broadcast capabilities. A not so well known feature of MBMS is its support for hybrid broadcast-unicast transmission. In this mode the more popular channels are broadcasted over point- to-multipoint radio bearers while the less popular channels are delivered over point-to-point bearers only on request. In this paper we will present a theoretical framework which allows an analytic evaluation of the capacity limits when delivering mobile TV services over hybrid broadcast-unicast transmission schemes provided by MBMS.

This paper is concerned with linear multiuser receivers for code division multiple access (CDMA). Mainly three are of practical relevance: the matched filter (MF), the successive interference cancellation (SIC) and the minimum mean squared error (MMSE) receiver. For the first time, an explicit representation of the signal-to-interference-plus-noise (SINR) ratio for the linear SIC receiver under general random spreading is given. For the MMSE receiver the SINR is obtained by using the asymptotic large system regime as an accurate approximation. Once the SINR for each receiver type is known, the question arises what quality-of-service (QoS) requirements can be supported by an adequate power assignment. A vector of QoS requirements (gammai) is called feasible, if there exists some power assignment such that the SINR of each user i does not fall short of threshold gammai. It is shown that for each receiver type there exists a componentwise minimal power assignment such that the SINR of each user equals this threshold. This minimal vector may be determined for the MF and SIC receiver by solving a system of linear equations with coefficients explicitly known. For the MMSE receiver in the large system regime an iterative algorithm is derived, which converges to the optimum power allocation.

Fast radio wave propagation predictions are of tremendous interest, e.g., for planning and optimization of cellular radio networks. We propose the use of ordinary graphics cards and specialized algorithms to achieve extremely fast predictions. Our implementation of the empirical COST-Walfisch-Ikegami model allows the computation of several hundred predictions in one second in a 7 km urban area. Further, we present a ray-optical approach exploiting the programming model of graphics cards. This algorithm combines fast computation times with high accuracy.

We consider a stable CDMA cellular network of N users with given quality-of-transmission requirements, and ask the question if an additional user can be admitted to the network without violating any of the active quality-of-service thresholds. An important point is that, although the inclusion of a new user impinges on the power adjustment of all mobiles in the network, this decision is made on the basis of information locally collected at the base stations only. We achieve this goal by an appropriate agglomeration of outer- and inner-cell interference, and an according dimensionality reduction scheme. The corresponding admission control algorithm applies an interference prediction phase prior to making a decision about accepting further customers to the wireless network. Capacity is exploited in that users are admitted whenever there is room to. Individual power constraints are included in our system model, which makes the resulting admission control algorithm widely applicable for practical purposes.

Accurate power control is an essential requirement in the design of cellular code-division multiple-access (CDMA) systems. In this paper, we contribute three main themes to the power control problem. First, we derive an efficient algorithm for computing minimal power levels for large-scale networks within seconds. Nice and intuitive conditions for the existence of feasible power solutions follow from this approach. Second, we define the capacity region of a network by the set of effective spreading gains, or data rates, respectively, which can be supplied by the network. This is achieved by bounding the spectral radius of a certain matrix containing system parameters and mutual transmission gain information. It is shown that the capacity region is a convex set. Finally, we reveal an interesting duality between the uplink and downlink capacity region. In a clear-cut analytical way, it substantiates the fact that the uplink is the more restricting factor in cellular radio networks. The same methods carry over to certain models of soft handover. In the case that the channel gains are subject to log-normal shadowing, we introduce the concept of level-/spl alpha/ capacity regions. Despite the complicated structure, it can still be shown that this set is sandwiched by two convex sets coming arbitrarily close as variance decreases.