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Today's Internet is no longer only controlled by a single stakeholder, e.g. a standard body or a telecommunications company.
Rather, the interests of a multitude of stakeholders, e.g. application developers, hardware vendors, cloud operators, and network operators, collide during the development and operation of applications in the Internet.
Each of these stakeholders considers different KPIs to be important and attempts to optimise scenarios in its favour.
This results in different, often opposing views and can cause problems for the complete network ecosystem.
One example of such a scenario are Signalling Storms in the mobile Internet, with one of the largest occurring in Japan in 2012 due to the release and high popularity of a free instant messaging application.
The network traffic generated by the application caused a high number of connections to the Internet being established and terminated.
This resulted in a similarly high number of signalling messages in the mobile network, causing overload and a loss of service for 2.5 million users over 4 hours.
While the network operator suffers the largest impact of this signalling overload, it does not control the application.
Thus, the network operator can not change the application traffic characteristics to generate less network signalling traffic.
The stakeholders who could prevent, or at least reduce, such behaviour, i.e. application developers or hardware vendors, have no direct benefit from modifying their products in such a way.
This results in a clash of interests which negatively impacts the network performance for all participants.
The goal of this monograph is to provide an overview over the complex structures of stakeholder relationships in today's Internet applications in mobile networks.
To this end, we study different scenarios where such interests clash and suggest methods where tradeoffs can be optimised for all participants.
If such an optimisation is not possible or attempts at it might lead to adverse effects, we discuss the reasons.
Purpose: A study of real-time adaptive radiotherapy systems was performed to test the hypothesis that, across delivery systems and institutions, the dosimetric accuracy is improved with adaptive treatments over non-adaptive radiotherapy in the presence of patient-measured tumor motion. Methods and materials: Ten institutions with robotic(2), gimbaled(2), MLC(4) or couch tracking(2) used common materials including CT and structure sets, motion traces and planning protocols to create a lung and a prostate plan. For each motion trace, the plan was delivered twice to a moving dosimeter; with and without real-time adaptation. Each measurement was compared to a static measurement and the percentage of failed points for gamma-tests recorded. Results: For all lung traces all measurement sets show improved dose accuracy with a mean 2%/2 mm gamma-fail rate of 1.6% with adaptation and 15.2% without adaptation (p < 0.001). For all prostate the mean 2%/2 mm gamma-fail rate was 1.4% with adaptation and 17.3% without adaptation (p < 0.001). The difference between the four systems was small with an average 2%/2 mm gamma-fail rate of <3% for all systems with adaptation for lung and prostate. Conclusions: The investigated systems all accounted for realistic tumor motion accurately and performed to a similar high standard, with real-time adaptation significantly outperforming non-adaptive delivery methods.
In recent years, cloud gaming has become a popular research topic and has claimed many benefits in the commercial domain over conventional gaming. While, cloud gaming platforms have frequently failed in the past, they have received a new impetus over the last years that brought it to the edge of commercial breakthrough. The fragility of the cloud gaming market may be caused by the high investment costs, offered pricing models or competition from existing "à la carte" platforms. This paper aims at investigating the costs and benefits of both platform types through a twofold approach. We first take on the perspective of the customers, and investigate several cloud gaming platforms and their pricing models in comparison to the costs of other gaming platforms. Then, we explore engagement metrics in order to assess the enjoyment of playing the offered games. Lastly, coming from the perspective of the service providers, we aim to identify challenges in cost-effectively operating a large-scale cloud gaming service while maintaining high QoE values. Our analysis provides initial, yet still comprehensive reasons and models for the prospects of cloud gaming in a highly competitive market.
This paper concerns the an intelligent mobile application for spatial design support and security domain. Mobility has two aspects in our research: The first one is the usage of mobile robots for 3D mapping of urban areas and for performing some specific tasks. The second mobility aspect is related with a novel Software as a Service system that allows access to robotic functionalities and data over the Ethernet, thus we demonstrate the use of the novel NVIDIA GRID technology allowing to virtualize the graphic processing unit. We introduce Complex Shape Histogram, a core component of our artificial intelligence engine, used for classifying 3D point clouds with a Support Vector Machine. We use Complex Shape Histograms also for loop closing detection in the simultaneous localization and mapping algorithm. Our intelligent mobile system is built on top of the Qualitative Spatio-Temporal Representation and Reasoning framework. This framework defines an ontology and a semantic model, which are used for building the intelligent mobile user interfaces. We show experiments demonstrating advantages of our approach. In addition, we test our prototypes in the field after the end-user case studies demonstrating a relevant contribution for future intelligent mobile systems that merge mobile robots with novel data centers.
Athletes adapt their training daily to optimize performance, as well as avoid fatigue, overtraining and other undesirable effects on their health. To optimize training load, each athlete must take his/her own personal objective and subjective characteristics into consideration and an increasing number of wearable technologies (wearables) provide convenient monitoring of various parameters. Accordingly, it is important to help athletes decide which parameters are of primary interest and which wearables can monitor these parameters most effectively. Here, we discuss the wearable technologies available for non-invasive monitoring of various parameters concerning an athlete's training and health. On the basis of these considerations, we suggest directions for future development. Furthermore, we propose that a combination of several wearables is most effective for accessing all relevant parameters, disturbing the athlete as little as possible, and optimizing performance and promoting health.