To cope with increasing energy consumption in mobile devices, the mobile cloud offloading has received considerable attention from its ability to offload processing tasks of mobile devices to cloud ...servers, and previous studies have focused on single type tasks in fixed network environments. However, real network environments are spatio-temporally varying, and typical mobile devices have not only various types of tasks, e.g., network traffic, cloud offloadable/nonoffloadable workloads but also capabilities of CPU frequency scaling and network interface selection between WiFi and cellular. In this paper, we first jointly consider the following three dynamic problems in real mobile environments: 1) cloud offloading policy, i.e., determining to use local CPU resources or cloud resources; 2) allocation of tasks to transmit through networks and to process in local CPU; and 3) CPU clock speed and network interface controls. We propose a DREAM algorithm by invoking the Lyapunov optimization and mathematically prove that it minimizes CPU and network energy for given delay constraints. Trace-driven simulation based on real measurements demonstrates that DREAM can save over 35% of total energy than existing algorithms with the same delay. We also design DREAM architecture and demonstrate the applicability of DREAM in practice.
This paper presents a quantitative study on the performance of 3G mobile data offloading through WiFi networks. We recruited 97 iPhone users from metropolitan areas and collected statistics on their ...WiFi connectivity during a two-and-a-half-week period in February 2010. Our trace-driven simulation using the acquired whole-day traces indicates that WiFi already offloads about 65% of the total mobile data traffic and saves 55% of battery power without using any delayed transmission. If data transfers can be delayed with some deadline until users enter a WiFi zone, substantial gains can be achieved only when the deadline is fairly larger than tens of minutes. With 100-s delays, the achievable gain is less than only 2%-3%, whereas with 1 h or longer deadlines, traffic and energy saving gains increase beyond 29% and 20%, respectively. These results are in contrast to the substantial gain (20%-33%) reported by the existing work even for 100-s delayed transmission using traces taken from transit buses or war-driving. In addition, a distribution model-based simulator and a theoretical framework that enable analytical studies of the average performance of offloading are proposed. These tools are useful for network providers to obtain a rough estimate on the average performance of offloading for a given WiFi deployment condition.
Cellular networks are facing severe traffic overloads due to the proliferation of smart handheld devices and traffic-hungry applications. A cost-effective and practical solution is to offload ...cellular data through WiFi. Recent theoretical and experimental studies show that a scheme, referred to as delayed WiFi offloading, can significantly save the cellular capacity by delaying users' data and exploiting mobility and thus increasing chance of meeting WiFi APs (Access Points). Despite a huge potential of WiFi offloading in alleviating mobile data explosion, its success largely depends on the economic incentives provided to users and operators to deploy and use delayed offloading. In this paper, we study how much economic benefits can be generated due to delayed WiFi offloading, by modeling the interaction between a single provider and users based on a two-stage sequential game. We first analytically prove that WiFi offloading is economically beneficial for both the provider and users. Also, we conduct trace-driven numerical analysis to quantify the practical gain, where the increase ranges from 21% to 152% in the providers revenue, and from 73% to 319% in the users surplus.
This article proposes a precise identification scheme of an interior permanent-magnet synchronous motor (IPMSM) flux linkage through experimental tests considering motor nonlinearities, such as the ...magnetic saturation and spatial harmonics. In the proposed scheme, the flux linkage is identified based on the voltage equation of IPMSM. The fundamental and harmonic electromotive force in the rotor reference frame is obtained in real time by applying a discrete Fourier transform with the phase compensation of the time delay due to digital control and pulsewidth modulation. The effect of the inverter nonlinearity is compensated using an experimentally obtained lookup table. Based on the identified flux-linkage map, a flux-based IPMSM model that accurately simulates motor behavior can be constructed. The effectiveness of the proposed flux-linkage identification scheme is verified through the comparison of simulation and experimental results.
This paper analyzes the convergence of signal-injection sensorless control (SISC) especially for heavily saturated interior permanent-magnet synchronous motors (IPMSMs). In the analysis, it is ...revealed that the harmonic inductance and the operating current variation are critical factors in determining the operational limit of SISC. The clear boundary of SISC for an IPMSM can be obtained through the proposed convergence analysis. Based on this analysis, a control algorithm is proposed to extend the operational limit of SISC. With the proposed method, the torque capability under SISC can be maximized. Simulations and experiments are performed to verify the proposed method.
In this paper, we propose a prediction algorithm, the combination of Long Short-Term Memory (LSTM) and attention model, based on machine learning models to predict the vision coordinates when ...watching 360-degree videos in a Virtual Reality (VR) or Augmented Reality (AR) system. Predicting the vision coordinates while video streaming is important when the network condition is degraded. However, the traditional prediction models such as Moving Average (MA) and Autoregression Moving Average (ARMA) are linear so they cannot consider the nonlinear relationship. Therefore, machine learning models based on deep learning are recently used for nonlinear predictions. We use the Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) neural network methods, originated in Recurrent Neural Networks (RNN), and predict the head position in the 360-degree videos. Therefore, we adopt the attention model to LSTM to make more accurate results. We also compare the performance of the proposed model with the other machine learning models such as Multi-Layer Perceptron (MLP) and RNN using the root mean squared error (RMSE) of predicted and real coordinates. We demonstrate that our model can predict the vision coordinates more accurately than the other models in various videos.
In this work, a flat-evaporator loop heat pipe (FELHP) having a flexible heat transport path was constructed and tested. The operating characteristics were investigated in terms of the operating ...temperatures and various thermal resistances using different working fluids (e.g. ethanol, acetone, and distilled water) and at different elevations. Regarding the effect of the working fluid, acetone showed the lowest thermal resistance at lower heat loads (e.g., 0.25 KW
−1
±0.07 KW
−1
at 60 W), whereas the water-filled FELHP resulted in the widest operating range with the lowest thermal resistance of 0.25 KW
−1
±0.05 KW
−1
at 320 W. A significant effect of elevation change was observed due to the prevailing hydrostatic head loss over the frictional pressure loss; the lowest thermal resistances at different elevations varied from 0.64 KW
−1
±0.11 KW
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to 0.11 KW
−1
±0.03 KW
−1
with decreasing elevation.
The recent discovery of diffuse dwarf galaxies that are deficient in dark matter appears to challenge the current paradigm of structure formation in our universe. We describe numerical experiments to ...determine if so-called dark matter deficient galaxies (DMDGs) could be produced when two gas-rich, dwarf-sized galaxies collide with a high relative velocity of ∼300 km s−1. Using idealized high-resolution simulations with both mesh-based and particle-based gravito-hydrodynamics codes, we find that DMDGs can form as high-velocity galaxy collisions and separate dark matter from the warm disk gas, which subsequently is compressed by shock and tidal interaction to form stars. Then using the large simulated universe IllustrisTNG, we discover a number of high-velocity galaxy collision events in which DMDGs are expected to form. However, we did not find evidence that these types of collisions actually produced DMDGs in the TNG100-1 run. We argue that the resolution of the numerical experiment is critical to realizing the "collision-induced" DMDG formation scenario. Our results demonstrate one of many routes in which galaxies could form with unconventional dark matter fractions.
In this paper, we aim to obtain the optimal tradeoff between the average delay and the average power consumption in a communication system. In our system, the arrivals occur at each timeslot ...according to a Bernoulli arrival process, and are buffered at the transmitter waiting to be scheduled. We consider a finite buffer and allow the scheduling decision to depend on the buffer occupancy. In order to capture the realism in communication systems, the transmission power is assumed to be an increasing and convex function of the number of packets transmitted in each timeslot. This problem is modeled as a constrained Markov decision process (CMDP). We first prove that the optimal policy of the Lagrangian relaxation of the CMDP is deterministic and threshold-based. We then show that the optimal delay-power tradeoff curve is convex and piecewise linear, and the optimal policies of the original problem are also threshold-based. Based on the results, we propose an algorithm to obtain the optimal policy and the optimal tradeoff curve. We also show that the proposed algorithm is much more efficient than using general methods. The theoretical results and the algorithm are validated by linear programming and simulations.
Histones are subjected to extensive covalent modifications that affect inter-nucleosomal interactions as well as alter chromatin structure and DNA accessibility. Through switching the corresponding ...histone modifications, the level of transcription and diverse downstream biological processes can be regulated. Although animal systems are widely used in studying histone modifications, the signalling processes that occur outside the nucleus prior to histone modifications have not been well understood due to the limitations including non viable mutants, partial lethality, and infertility of survivors. Here, we review the benefits of using Arabidopsis thaliana as the model organism to study histone modifications and their upstream regulations. Similarities among histones and key histone modifiers such as the Polycomb group (PcG) and Trithorax group (TrxG) in Drosophila, Human, and Arabidopsis are examined. Furthermore, prolonged cold-induced vernalization system has been well-studied and revealed the relationship between the controllable environment input (duration of vernalization), its chromatin modifications of FLOWERING LOCUS C (FLC), following gene expression, and the corresponding phenotypes. Such evidence suggests that research on Arabidopsis can bring insights into incomplete signalling pathways outside of the histone box, which can be achieved through viable reverse genetic screenings based on the phenotypes instead of direct monitoring of histone modifications among individual mutants. The potential upstream regulators in Arabidopsis can provide cues or directions for animal research based on the similarities between them.
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