A dynamic bandwidth allocation scheme for interactive multimedia applications over cellular networks

Cellular networks played key role in enabling high level of bandwidth for users by employing traditional methods such as guaranteed QoS based on application category at radio access stratum level for various classes of QoSs. Also, the newer multimode phones (e.g., phones that support LTE (Long Term Evolution standard), UMTS, GSM, WIFI all at once) are capable to use multiple access methods simulta- neously and can perform seamless handover among various supported technologies to remain connected. With various types of applications (including interactive ones) running on these devices, which in turn have different QoS requirements, this work discusses as how QoS (measured in terms of user level response time, delay, jitter and transmission rate) can be achieved for interactive applications using dynamic bandwidth allocation schemes over cellular networks. In this work, we propose a dynamic bandwidth allocation scheme for interactive multimedia applications with/without background load in the cellular networks. The system has been simulated for many application types running in parallel and it has been observed that if interactive applications are to be provided with decent response time, a periodic overhauling of policy at admission control has to be done by taking into account history, criticality of applications. The results demonstrate that interactive appli- cations can be provided with good service if policy database at admission control is reviewed dynamically.

A Novel Power Allocation Scheme for Two-User GMAC with Finite Input Constellations

Constellation Constrained (CC) capacity regions of two-user Gaussian Multiple Access Channels (GMAC) have been recently reported, wherein an appropriate angle of rotation between the constellations of the two users is shown to enlarge the CC capacity region. We refer to such a scheme as the Constellation Rotation (CR) scheme. In this paper, we propose a novel scheme called the Constellation Power Allocation (CPA) scheme, wherein the instantaneous transmit power of the two users are varied by maintaining their average power constraints. We show that the CPA scheme offers CC sum capacities equal (at low SNR values) or close (at high SNR values) to those offered by the CR scheme with reduced decoding complexity for QAM constellations. We study the robustness of the CPA scheme for random phase offsets in the channel and unequal average power constraints for the two users. With random phase offsets in the channel, we show that the CC sum capacity offered by the CPA scheme is more than the CR scheme at high SNR values. With unequal average power constraints, we show that the CPA scheme provides maximum gain when the power levels are close, and the advantage diminishes with the increase in the power difference.

Obtaining single document summaries using latent dirichlet allocation

In this paper, we present a novel approach that makes use of topic models based on Latent Dirichlet allocation(LDA) for generating single document summaries. Our approach is distinguished from other LDA based approaches in that we identify the summary topics which best describe a given document and only extract sentences from those paragraphs within the document which are highly correlated given the summary topics. This ensures that our summaries always highlight the crux of the document without paying any attention to the grammar and the structure of the documents. Finally, we evaluate our summaries on the DUC 2002 Single document summarization data corpus using ROUGE measures. Our summaries had higher ROUGE values and better semantic similarity with the documents than the DUC summaries.

A GIS (geographical information system)-based spatial data mining approach for optimal location and capacity planning of distributed biomass power generation facilities: A case study of Tumkur district, India

This paper primarily intends to develop a GIS (geographical information system)-based data mining approach for optimally selecting the locations and determining installed capacities for setting up distributed biomass power generation systems in the context of decentralized energy planning for rural regions. The optimal locations within a cluster of villages are obtained by matching the installed capacity needed with the demand for power, minimizing the cost of transportation of biomass from dispersed sources to power generation system, and cost of distribution of electricity from the power generation system to demand centers or villages. The methodology was validated by using it for developing an optimal plan for implementing distributed biomass-based power systems for meeting the rural electricity needs of Tumkur district in India consisting of 2700 villages. The approach uses a k-medoid clustering algorithm to divide the total region into clusters of villages and locate biomass power generation systems at the medoids. The optimal value of k is determined iteratively by running the algorithm for the entire search space for different values of k along with demand-supply matching constraints. The optimal value of the k is chosen such that it minimizes the total cost of system installation, costs of transportation of biomass, and transmission and distribution. A smaller region, consisting of 293 villages was selected to study the sensitivity of the results to varying demand and supply parameters. The results of clustering are represented on a GIS map for the region.

Power allocation for interference channels

We propose power allocation algorithms for increasing the sum rate of two and three user interference channels. The channels experience fast fading and there is an average power constraint on each transmitter. Our achievable strategies for two and three user interference channels are based on the classification of the interference into very strong, strong and weak interferences. We present numerical results of the power allocation algorithm for two user Gaussian interference channel with Rician fading with mean total power gain of the fade Omega = 3 and Rician factor kappa = 0.5 and compare the sum rate with that obtained from ergodic interference alignment with water-filling. We show that our power allocation algorithm increases the sum rate with a gain of 1.66dB at average transmit SNR of 5dB. For the three user Gaussian interference channel with Rayleigh fading with distribution CN(0, 0.5), we show that our power allocation algorithm improves the sum rate with a gain of 1.5dB at average transmit SNR of 5dB.

Universal flame propagation behavior in packed bed of biomass

This article aims at seeking the universal behavior of propagation rate variation with air superficial velocity (V-s) in a packed bed of a range of biomass particles in reverse downdraft mode while also resolving the differing and conflicting explanations in the literature. Toward this, measurements are made of exit gas composition, gas phase and condensed phase surface temperature (T-g and T-s), and reaction zone thickness for a number of biomass with a range of properties. Based on these data, two regimes are identified: gasificationvolatile oxidation accompanied by char reduction reactions up to 16 +/- 1cm/s of V-s and above this, and char oxidationsimultaneous char oxidation and gas phase combustion. In the gasification regime, the measured T-s is less than T-g; a surface heat balance incorporating a diffusion controlled model for flaming combustion gives and matches with the experimental results to within 5%. In the char oxidation regime, T-g and T-s are nearly equal and match with the equilibrium temperature at that equivalence ratio. Drawing from a recent study of the authors, the ash layer over the oxidizing char particle is shown to play a critical role in regulating the radiation heat transfer to fresh biomass in this regime and is shown to be crucial in explaining the observed propagation behavior. A simple model based on radiation-convection balance that tracks the temperature-time evolution of a fresh biomass particle is shown to support the universal behavior of the experimental data on reaction front propagation rate from earlier literature and the present work for biomass with ash content up to 10% and moisture fraction up to 10%. Upstream radiant heat transfer from the ash-laden hot char modulated by the air flow is shown to be the dominant feature of this model.

Training for Antenna Selection in Time-Varying Channels: Optimal Selection, Energy Allocation, and Energy Efficiency Evaluation

Single receive antenna selection (AS) is a popular method for obtaining diversity benefits without the additional costs of multiple radio receiver chains. Since only one antenna receives at any time, the transmitter sends a pilot multiple times to enable the receiver to estimate the channel gains of its N antennas to the transmitter and select an antenna. In time-varying channels, the channel estimates of different antennas are outdated to different extents. We analyze the symbol error probability (SEP) in time-varying channels of the N-pilot and (N+1)-pilot AS training schemes. In the former, the transmitter sends one pilot for each receive antenna. In the latter, the transmitter sends one additional pilot that helps sample the channel fading process of the selected antenna twice. We present several new results about the SEP, optimal energy allocation across pilots and data, and optimal selection rule in time-varying channels for the two schemes. We show that due to the unique nature of AS, the (N+1)-pilot scheme, despite its longer training duration, is much more energy-efficient than the conventional N-pilot scheme. An extension to a practical scenario where all data symbols of a packet are received by the same antenna is also investigated.

A Markov Decision Theoretic Approach to Pilot Allocation and Receive Antenna Selection

This paper considers antenna selection (AS) at a receiver equipped with multiple antenna elements but only a single radio frequency chain for packet reception. As information about the channel state is acquired using training symbols (pilots), the receiver makes its AS decisions based on noisy channel estimates. Additional information that can be exploited for AS includes the time-correlation of the wireless channel and the results of the link-layer error checks upon receiving the data packets. In this scenario, the task of the receiver is to sequentially select (a) the pilot symbol allocation, i.e., how to distribute the available pilot symbols among the antenna elements, for channel estimation on each of the receive antennas; and (b) the antenna to be used for data packet reception. The goal is to maximize the expected throughput, based on the past history of allocation and selection decisions, and the corresponding noisy channel estimates and error check results. Since the channel state is only partially observed through the noisy pilots and the error checks, the joint problem of pilot allocation and AS is modeled as a partially observed Markov decision process (POMDP). The solution to the POMDP yields the policy that maximizes the long-term expected throughput. Using the Finite State Markov Chain (FSMC) model for the wireless channel, the performance of the POMDP solution is compared with that of other existing schemes, and it is illustrated through numerical evaluation that the POMDP solution significantly outperforms them.

Subchannel allocation and power control in femtocells to provide quality of service

Femtocells are a new concept which improves the coverage and capacity of a cellular system. We consider the problem of channel allocation and power control to different users within a Femtocell. Knowing the channels available, the channel states and the rate requirements of different users the Femtocell base station (FBS), allocates the channels to different users to satisfy their requirements. Also, the Femtocell should use minimal power so as to cause least interference to its neighboring Femtocells and outside users. We develop efficient, low complexity algorithms which can be used online by the Femtocell. The users may want to transmit data or voice. We compare our algorithms with the optimal solutions.

Oxy-steam gasification of biomass for hydrogen rich syngas production using downdraft reactor configuration

The paper focuses on the use of oxygen and steam as the gasification agents in the thermochemical conversion of biomass to produce hydrogen rich syngas, using a downdraft reactor configuration. Performance of the reactor is evaluated for different equivalence ratios (ER), steam to biomass ratios (SBR) and moisture content in the fuel. The results are compared and evaluated with chemical equilibrium analysis and reaction kinetics along with the results available in the literature. Parametric study suggests that, with increase in SBR, hydrogen fraction in the syngas increases but necessitates an increase in the ER to maintain reactor temperature toward stable operating conditions. SBR is varied from 0.75 to 2.7 and ER from 0.18 to 0.3. The peak hydrogen yield is found to be 104g/kg of biomass at SBR of 2.7. Further, significant enhancement in H-2 yield and H-2 to CO ratio is observed at higher SBR (SBR=1.5-2.7) compared with lower range SBR (SBR=0.75-1.5). Experiments were conducted using wet wood chips to induce moisture into the reacting system and compare the performance with dry wood with steam. The results clearly indicate the both hydrogen generation and the gasification efficiency ((g)) are better in the latter case. With the increase in SBR, gasification efficiency ((g)) and lower heating value (LHV) tend to reduce. Gasification efficiency of 85.8% is reported with LHV of 8.9MJNm(-3) at SBR of 0.75 compared with 69.5% efficiency at SBR of 2.5 and lower LHV of 7.4 at MJNm(-3) at SBR of 2.7. These are argued on the basis of the energy required for steam generation and the extent of steam consumption during the reaction, which translates subsequently in the LHV of syngas. From the analysis of the results, it is evident that reaction kinetics plays a crucial role in the conversion process. The study also presents the importance of reaction kinetics, which controls the overall performance related to efficiency, H-2 yield, H-2 to CO fraction and LHV of syngas, and their dependence on the process parameters SBR and ER. Copyright (c) 2013 John Wiley & Sons, Ltd.

Scientific and technological aspects of fixed bed biomass gasification

In recent years new emphasis has been placed on problems of the environmental aspects of waste disposal, especially investigating alternatives to landfill, sea dumping and incineration. There is also a strong emphasis on clean, economic and efficient processes for electric power generation. These two topics may at first appear unrelated. Nevertheless, the technological advances are now such that a solution to both can be combined in a novel approach to power generation based on waste-derived fuels, including refuse-derived fuel (RDF) and sludge power (SP) by utilising a slagging gasifier and advance fuel technology (AFT). The most appropriate gasification technique for such waste utilisation is the British Gas/Lurgi (BGL) high pressure, fixed bed slagging gasifier where operation on a range of feedstocks has been well-documented. This gasifier is particularly amenable to briquette fuel feeding and, operating in an integrated gasification combined cycle mode (IGCC), is particularly advantageous. Here, the author details how this technology has been applied to Britain's first AFT-IGCC Power Station which is now under development at Fife Energy Ltd., in Scotland, the former British Gas Westfield Development Centre.

Automatic Data Allocation and Buffer Management for Multi-GPU Machines

Multi-GPU machines are being increasingly used in high-performance computing. Each GPU in such a machine has its own memory and does not share the address space either with the host CPU or other GPUs. Hence, applications utilizing multiple GPUs have to manually allocate and manage data on each GPU. Existing works that propose to automate data allocations for GPUs have limitations and inefficiencies in terms of allocation sizes, exploiting reuse, transfer costs, and scalability. We propose a scalable and fully automatic data allocation and buffer management scheme for affine loop nests on multi-GPU machines. We call it the Bounding-Box-based Memory Manager (BBMM). BBMM can perform at runtime, during standard set operations like union, intersection, and difference, finding subset and superset relations on hyperrectangular regions of array data (bounding boxes). It uses these operations along with some compiler assistance to identify, allocate, and manage data required by applications in terms of disjoint bounding boxes. This allows it to (1) allocate exactly or nearly as much data as is required by computations running on each GPU, (2) efficiently track buffer allocations and hence maximize data reuse across tiles and minimize data transfer overhead, and (3) and as a result, maximize utilization of the combined memory on multi-GPU machines. BBMM can work with any choice of parallelizing transformations, computation placement, and scheduling schemes, whether static or dynamic. Experiments run on a four-GPU machine with various scientific programs showed that BBMM reduces data allocations on each GPU by up to 75% compared to current allocation schemes, yields performance of at least 88% of manually written code, and allows excellent weak scaling.

First and second law thermodynamic analysis of air and oxy-steam biomass gasification

Gasification is an energy transformation process in which solid fuel undergoes thermochemical conversion to produce gaseous fuel, and the two most important criteria involved in such process to evaluate the performance, economics and sustainability of the technology are: the total available energy (exergy) and the energy conserved (energy efficiency). Current study focuses on the energy and exergy analysis of the oxy-steam gasification and comparing with air gasification to optimize the H-2 yield, efficiency and syngas energy density. Casuarina wood is used as a fuel, and mixture of oxygen and steam in different proportion and amount is used as a gasifying media. The results are analysed with respect to varying equivalence ratio and steam to biomass ratio (SBR). Elemental mass balance technique is employed to ensure the validity of results. First and second law thermodynamic analysis is used towards time evaluation of energy and exergy analysis. Different component of energy input and output has been studied carefully to understand the influence of varying SBR on the availability of energy and irreversibility in the system to minimize the losses with change in input parameters for optimum performance. The energy and exergy losses (irreversibility) for oxy-steam gasification system are compared with the results of air gasification, and losses are found to be lower in oxy-steam thermal conversion; which has been argued and reasoned due to the presence of N-2 in the air-gasification. The maximum exergy efficiency of 85% with energy efficiency of 82% is achieved at SBR of 0.75 on the molar basis. It has been observed that increase in SBR results in lower exergy and energy efficiency, and it is argued to be due to the high energy input in steam generation and subsequent losses in the form of physical exergy of steam in the product gas, which alone accounts for over 18% in exergy input and 8.5% in exergy of product gas at SBR of 2.7. Carbon boundary point (CBP), is identified at the SBR of 1.5, and water gas shift (WGS) reaction plays a crucial role in H-2 enrichment after carbon boundary point (CBP) is reached. Effects of SBR and CBP on the H-2/CO ratio is analysed and discussed from the perspective of energy as well as the reaction chemistry. Energy density of syngas and energy efficiency is favoured at lower SBR but higher SBR favours H-2 rich gas at the expense of efficiency. Copyright (C) 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8-50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mgha(-1)) at spatial scales ranging from 5 to 250m (0.025-6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20-400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial ``dilution'' bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.