Fast Hole Tunneling Times in Germanium Hut Wires Probed by Single-Shot Reflectometry

Heavy holes confined in quantum dots are predicted to be promising candidates for the realization of spin qubits with long coherence times. Here we focus on such heavy-hole states confined in Germanium hut wires. By tuning the growth density of the latter we can realize a T-like structure between two neighboring wires. Such a structure allows the realization of a charge sensor, which is electrostatically and tunnel coupled to a quantum dot, with charge-transfer signals as high as 0.3e. By integrating the T-like structure into a radio-frequency reflectometry setup, single-shot measurements allowing the extraction of hole tunneling times are performed. The extracted tunneling times of less than 10$\mu$s are attributed to the small effective mass of Ge heavy-hole states and pave the way towards projective spin readout measurements

A data mining approach for location prediction in mobile environments

Cataloged from PDF version of article.Mobility prediction is one of the most essential issues that need to be explored for mobility management in mobile computing systems. In this paper, we propose a new algorithm for predicting the next inter-cell movement of a mobile user in a Personal Communication Systems network. In the first phase of our threephase algorithm, user mobility patterns are mined from the history of mobile user trajectories. In the second phase, mobility rules are extracted from these patterns, and in the last phase, mobility predictions are accomplished by using these rules. The performance of the proposed algorithm is evaluated through simulation as compared to two other prediction methods. The performance results obtained in terms of Precision and Recall indicate that our method can make more accurate predictions than the other methods. 2004 Elsevier B.V. All rights reserved

SiGe quantum dots for fast hole spin Rabi oscillations

We report on hole g-factor measurements in three terminal SiGe self-assembled quantum dot devices with a top gate electrode positioned very close to the nanostructure. Measurements of both the perpendicular as well as the parallel g-factor reveal significant changes for a small modulation of the top gate voltage. From the observed modulations we estimate that, for realistic experimental conditions, hole spins can be electrically manipulated with Rabi frequencies in the order of 100MHz. This work emphasises the potential of hole-based nano-devices for efficient spin manipulation by means of the g-tensor modulation technique

Cost-efficient Low Latency Communication Infrastructure for Synchrophasor Applications in Smart Grids

With the introduction of distributed renewable energy resources and new loads, such as electric vehicles, the power grid is evolving to become a highly dynamic system, that necessitates continuous and fine-grained observability of its operating conditions. In the context of the medium voltage (MV) grid, this has motivated the deployment of Phasor Measurement Units (PMUs), that offer high precision synchronized grid monitoring, enabling mission-critical applications such as fault detection/location. However, PMU-based applications present stringent delay requirements, raising a significant challenge to the communication infrastructure. In contrast to the high voltage domain, there is no clear vision for the communication and network topologies for the MV grid; a full fledged optical fiber-based communication infrastructure is a costly approach due to the density of PMUs required. In this work, we focus on the support of low-latency PMU-based applications in the MV domain, identifying and addressing the trade-off between communication infrastructure deployment costs and the corresponding performance. We study a large set of real MV grid topologies to get an in-depth understanding of the various key latency factors. Building on the gained insights, we propose three algorithms for the careful placement of high capacity links, targeting a balance between deployment costs and achieved latencies. Extensive simulations demonstrate that the proposed algorithms result in low-latency network topologies while reducing deployment costs by up to 80% in comparison to a ubiquitous deployment of costly high capacity links

Seamless Support of Low Latency Mobile Applications with NFV-Enabled Mobile Edge-Cloud

Emerging mobile multimedia applications, such as augmented reality, have stringent latency requirements and high computational cost. To address this, mobile edge-cloud (MEC) has been proposed as an approach to bring resources closer to users. Recently, in contrast to conventional fixed cloud locations, the advent of network function virtualization (NFV) has, with some added cost due to the necessary decentralization, enhanced MEC with new flexibility in placing MEC services to any nodes capable of virtualizing their resources. In this work, we address the question on how to optimally place resources among NFV- enabled nodes to support mobile multimedia applications with low latency requirement and when to adapt the current resource placements to address workload changes. We first show that the placement optimization problem is NP-hard and propose an online dynamic resource allocation scheme that consists of an adaptive greedy heuristic algorithm and a detection mechanism to identify the time when the system will no longer be able to satisfy the applications’ delay requirement. Our scheme takes into account the effect of current existing techniques (i.e., auto- scaling and load balancing). We design and implement a realistic NFV-enabled MEC simulated framework and show through ex- tensive simulations that our proposal always manages to allocate sufficient resources on time to guarantee continuous satisfaction of the application latency requirements under changing workload while incurring up to 40% less cost in comparison to existing overprovisioning approaches

Cost-Efficient NFV-Enabled Mobile Edge-Cloud for Low Latency Mobile Applications

Mobile edge-cloud (MEC) aims to support low la- tency mobile services by bringing remote cloud services nearer to mobile users. However, in order to deal with dynamic workloads, MEC is deployed in a large number of fixed-location micro- clouds, leading to resource wastage during stable/low work- load periods. Limiting the number of micro-clouds improves resource utilization and saves operational costs, but faces service performance degradations due to insufficient physical capacity during peak time from nearby micro-clouds. To efficiently support services with low latency requirement under varying workload conditions, we adopt the emerging Network Function Virtualization (NFV)-enabled MEC, which offers new flexibility in hosting MEC services in any virtualized network node, e.g., access points, routers, etc. This flexibility overcomes the limitations imposed by fixed-location solutions, providing new freedom in terms of MEC service-hosting locations. In this paper, we address the questions on where and when to allocate resources as well as how many resources to be allocated among NFV- enabled MECs, such that both the low latency requirements of mobile services and MEC cost efficiency are achieved. We propose a dynamic resource allocation framework that consists of a fast heuristic-based incremental allocation mechanism that dynamically performs resource allocation and a reoptimization algorithm that periodically adjusts allocation to maintain a near- optimal MEC operational cost over time. We show through ex- tensive simulations that our flexible framework always manages to allocate sufficient resources in time to guarantee continuous satisfaction of applications’ low latency requirements. At the same time, our proposal saves up to 33% of cost in comparison to existing fixed-location MEC solutions

Information-aware access network selection

Mobile devices are increasingly presented with multiple connectivity options, including WiFi hotspots, micro-/macro-cells or even other devices in device-to-device (D2D) communications. By and large, connectivity management for mobile devices has primarily focused on contention, congestion and wireless medium conditions. In this paper, we assess the role of information-centrism in mobile device connectivity management. Motivated by the increasing availability of content and services in in-network caches and micro-data centres, we design an access network selection scheme that takes into account information availability within each connectivity option. Our simulations show that information-awareness results in a significant increase of cache hit ratios by up to 115% in certain scenarios

Information-centric networking for machine-to-machine data delivery: A case study in smart grid applications

Largely motivated by the proliferation of content-centric applications in the Internet, information-centric networking has attracted the attention of the research community. By tailoring network operations around named information objects instead of end hosts, ICN yields a series of desirable features such as the spatiotemporal decoupling of communicating entities and the support of in-network caching. In this article, we advocate the introduction of such ICN features in a new, rapidly transforming communication domain: the smart grid. With the rapid introduction of multiple new actors, such as distributed (renewable) energy resources and electric vehicles, smart grids present a new networking landscape where a diverse set of multi-party machine-to-machine applications are required to enhance the observability of the power grid, often in real time and on top of a diverse set of communication infrastructures. Presenting a generic architectural framework, we show how ICN can address the emerging smart grid communication challenges. Based on real power grid topologies from a power distribution network in the Netherlands, we further employ simulations to both demonstrate the feasibility of an ICN solution for the support of real-time smart grid applications and further quantify the performance benefits brought by ICN against the current host-centric paradigm. Specifically, we show how ICN can support real-time state estimation in the medium voltage power grid, where high volumes of synchrophasor measurement data from distributed vantage points must be delivered within a very stringent end-to-end delay constraint, while swiftly overcoming potential power grid component failures. © 1986-2012 IEEE