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Utilizing multiple access technologies such as 5G, 4G, and Wi-Fi within a coherent framework is currently standardized by 3GPP within 5G ATSSS. Indeed, distributing packets over multiple networks can lead to increased robustness, resiliency and capacity. A key part of such a framework is the multi-access proxy, which transparently distributes packets over multiple paths. As the proxy needs to serve thousands of customers, scalability and performance are crucial for operator deployments. In this paper, we leverage recent advancements in data plane programming, implement a multi-access proxy based on the MP-DCCP tunneling approach in P4 and hardware accelerate it by deploying the pipeline on a smartNIC. This is challenging due to the complex scheduling and congestion control operations involved. We present our pipeline and data structures design for congestion control and packet scheduling state management. Initial measurements in our testbed show that packet latency is in the range of 25 μs demonstrating the feasibility of our approach.
A Case Study of the Basic Learners’ Struggles in Guessing from Context to Retain Words Learned
(2022)
Guessing meaning from context is a challenging strategy for Second Language Learners (SLLs). In using the strategy, research found that poor students or low proficiency learners struggled in their attempts to use it. Mainly, it was reported that it was due to their vocabulary knowledge was limited. In another aspect, retaining vocabulary learnt is also important. Such is essential since learning vocabulary does not mean knowing the definition only. Yet, learners must also be able to use the vocabulary as they engage in language skills such as reading, writing, speaking and listening. The study aims at finding the hindrances faced among poor students’ using contextual clues in retaining vocabulary. The study employed a case study to collect data from two basic students studying at a tertiary level. The study found that their hindrances in guessing meaning contexts were due to their being confused in guessing meaning when reading a sentence. Also, it was found that they were not able to find clues since they lacked vocabulary to guess correctly. The study implied that guessing meaning from context required sizeable vocabulary knowledge. Therefore, more training is necessary to assist basic learners in being successful in guessing from contexts.
Utilizing multiple access networks such as 5G, 4G, and Wi-Fi simultaneously can lead to increased robustness, resiliency, and capacity for mobile users. However, transparently implementing packet distribution over multiple paths within the core of the network faces multiple challenges including scalability to a large number of customers, low latency, and high-capacity packet processing requirements. In this paper, we offload congestion-aware multipath packet scheduling to a smartNIC. However, such hardware acceleration faces multiple challenges due to programming language and platform limitations. We implement different multipath schedulers in P4 with different complexity in order to cope with dynamically changing path capacities. Using testbed measurements, we show that our CMon scheduler, which monitors path congestion in the data plane and dynamically adjusts scheduling weights for the different paths based on path state information, can process more than 3.5 Mpps packets 25 μs latency.
The article deals with the notion of internet aggression (cyber aggression). It considers the mentioned term from both psychological and communicative approaches. The paper also provides detailed analyses of the cyber aggression in political discourse. The provided ex-amples are taken from the speeches of politicians during the time of Covid pandemic. The author also identifies several types of cyber aggression.
Immersive virtual environments provide users with the opportunity to escape from the real world, but scripted dialogues can disrupt the presence within the world the user is trying to escape within. Both Non-Playable Character (NPC) to Player and NPC to NPC dialogue can be non-natural and the reliance on responding with pre-defined dialogue does not always meet the players emotional expectations or provide responses appropriate to the given context or world states. This paper investigates the application of Artificial Intelligence (AI) and Natural Language Processing to generate dynamic human-like responses within a themed virtual world. Each thematic has been analysed against humangenerated responses for the same seed and demonstrates invariance of rating across a range of model sizes, but shows an effect of theme and the size of the corpus used for fine-tuning the context for the game world.
This paper gives an overview of our recent activities in the field of satellite communication networks, including an introduction to geostationary satellite systems and Low Earth Orbit megaconstellations. To mitigate the high latencies of geostationary satellite networks, TCP-splitting Performance Enhancing Proxies are deployed. However, these cannot be applied in the case of encrypted transport headers as it is the case for VPNs or QUIC. We summarize performance evaluation results from multiple measurement campaigns. In a recently concluded project, multipath communication was used to combine the advantages of very heterogeneous communication paths: low data rate, low latency (e.g., DSL light) and high data rate, high latency (e.g., geostationary satellite).
Service orchestration requires enormous attention and is a struggle nowadays. Of course, virtualization provides a base level of abstraction for services to be deployable on a lot of infrastructures. With container virtualization, the trend to migrate applications to a micro-services level in order to be executable in Fog and Edge Computing environments increases manageability and maintenance efforts rapidly. Similarly, network virtualization adds effort to calibrate IP flows for Software-Defined Networks and eventually route it by means of Network Function Virtualization. Nevertheless, there are concepts like MAPE-K to support micro-service distribution in next-generation cloud and network environments. We want to explore, how a service distribution can be improved by adopting machine learning concepts for infrastructure or service changes. Therefore, we show how federated machine learning is integrated into a cloud-to-fog-continuum without burdening single nodes.
Time-to-Live (TTL) caches decouple the occupancy of objects in cache through object-specific validity timers. Stateof- the art techniques provide exact methods for the calculation of object-specific hit probabilities given entire cache hierarchies with random inter-cache network delays. The system hit probability is a provider-centric metric as it relates to the origin offload, i.e., the decrease in the number of requests that are served by the content origin server. In this paper we consider a user-centric metric, i.e., the response time, which is shown to be structurally different from the system hit probability. Equipped with the state-of-theart exact modeling technique using Markov-arrival processes we derive expressions for the expected object response time and pave a way for its optimization under network delays.