Deutsche Telekom

About: Deutsche Telekom is a company organization based out in Welwyn Garden City, United Kingdom. It is known for research contribution in the topics: Telecommunications network & Terminal (electronics). The organization has 3473 authors who have published 5208 publications receiving 65429 citations. The organization is also known as: DTAG & German Telecom.

BUBBLE Rap: Social-Based Forwarding in Delay-Tolerant Networks

Abstract: The increasing penetration of smart devices with networking capability form novel networks Such networks, also referred as pocket switched networks (PSNs), are intermittently connected and represent a paradigm shift of forwarding data in an ad hoc manner The social structure and interaction of users of such devices dictate the performance of routing protocols in PSNs To that end, social information is an essential metric for designing forwarding algorithms for such types of networks Previous methods relied on building and updating routing tables to cope with dynamic network conditions On the downside, it has been shown that such approaches end up being cost ineffective due to the partial capture of the transient network behavior A more promising approach would be to capture the intrinsic characteristics of such networks and utilize them in the design of routing algorithms In this paper, we exploit two social and structural metrics, namely centrality and community, using real human mobility traces The contributions of this paper are two-fold First, we design and evaluate BUBBLE, a novel social-based forwarding algorithm, that utilizes the aforementioned metrics to enhance delivery performance Second, we empirically show that BUBBLE can substantially improve forwarding performance compared to a number of previously proposed algorithms including the benchmarking history-based PROPHET algorithm, and social-based forwarding SimBet algorithm

ThinkAir: Dynamic resource allocation and parallel execution in the cloud for mobile code offloading

Abstract: Smartphones have exploded in popularity in recent years, becoming ever more sophisticated and capable. As a result, developers worldwide are building increasingly complex applications that require ever increasing amounts of computational power and energy. In this paper we propose ThinkAir, a framework that makes it simple for developers to migrate their smartphone applications to the cloud. ThinkAir exploits the concept of smartphone virtualization in the cloud and provides method-level computation offloading. Advancing on previous work, it focuses on the elasticity and scalability of the cloud and enhances the power of mobile cloud computing by parallelizing method execution using multiple virtual machine (VM) images. We implement ThinkAir and evaluate it with a range of benchmarks starting from simple micro-benchmarks to more complex applications. First, we show that the execution time and energy consumption decrease two orders of magnitude for a N-queens puzzle application and one order of magnitude for a face detection and a virus scan application. We then show that a parallelizable application can invoke multiple VMs to execute in the cloud in a seamless and on-demand manner such as to achieve greater reduction on execution time and energy consumption. We finally use a memory-hungry image combiner tool to demonstrate that applications can dynamically request VMs with more computational power in order to meet their computational requirements.

Coordinated multipoint: Concepts, performance, and field trial results

Abstract: Coordinated multipoint or cooperative MIMO is one of the promising concepts to improve cell edge user data rate and spectral efficiency beyond what is possible with MIMOOFDM in the first versions of LTE or WiMAX. Interference can be exploited or mitigated by cooperation between sectors or different sites. Significant gains can be shown for both the uplink and downlink. A range of technical challenges were identified and partially addressed, such as backhaul traffic, synchronization and feedback design. This article also shows the principal feasibility of COMP in two field testbeds with multiple sites and different backhaul solutions between the sites. These activities have been carried out by a powerful consortium consisting of universities, chip manufacturers, equipment vendors, and network operators.

ElasticTree: saving energy in data center networks

Abstract: Networks are a shared resource connecting critical IT infrastructure, and the general practice is to always leave them on. Yet, meaningful energy savings can result from improving a network's ability to scale up and down, as traffic demands ebb and flow. We present ElasticTree, a network-wide power1 manager, which dynamically adjusts the set of active network elements -- links and switches--to satisfy changing data center traffic loads.We first compare multiple strategies for finding minimum-power network subsets across a range of traffic patterns. We implement and analyze ElasticTree on a prototype testbed built with production OpenFlow switches from three network vendors. Further, we examine the trade-offs between energy efficiency, performance and robustness, with real traces from a production e-commerce website. Our results demonstrate that for data center workloads, ElasticTree can save up to 50% of network energy, while maintaining the ability to handle traffic surges. Our fast heuristic for computing network subsets enables ElasticTree to scale to data centers containing thousands of nodes. We finish by showing how a network admin might configure ElasticTree to satisfy their needs for performance and fault tolerance, while minimizing their network power bill.