Overlay Graphs Research Articles

Electricity system optimisation based on python model for renewable electricity generation portfolio

100% renewable electricity scenarios have received great attention from industry and policy makers, this is due to its widespread need for technical, economical, and renewable integration action plans. In this research, a python model named WIBSS, is developed and tested for adequacy using sensitivity analysis and then used to simulate the Irish electricity system.In this investigation, the optimal cost was identified with the installed capacities needed for the electricity system for high electricity demand scenario, and the generation portfolios for the electricity system in Ireland is proposed.The electricity system parameters are determined and the levelised cost of electricity is optimised and tabulated. In this investigation, the optimal solution is identified to decrease curtailment and minimize the total cost. Overlay graphs are plotted, and the optimal renewable sources combinations are presented.This research of determining generation portfolios toward 100% renewable electricity systems demonstrates simulations of two different pathways for 2030 scenarios to meet electricity demand in Republic of Ireland. The renewable energy target appeared in the government climate action plan and the authors renewable energy target determined based on the simulation of the python model, with more than doubled photovoltaic installation, a significant reduction in offshore wind, and a substantial integration of battery capacity, the authors renewable energy target performs better than renewable energy target, the levelised cost of electricity were 57.22 €/mWh and 51.11 €/mWh respectively. The least cost pathway is extended to balance between electricity generation and electricity demand in 2040 scenario, and keys target were proposed for generation portfolios.

Pareto Optimization of GMDH-Type Neural Networks for Modelling and Prediction of Hoop Strain in Explosive Forming Process

In this paper, Evolutionary Algorithms (EAs) are deployed for multi-objective Pareto optimal design of Group Method of Data Handling (GMDH)-type neural networks that have been used for modelling of the effect of dynamic yield stress, thickness, charge mass, centre deflection and distance from centre on the hoop strain in explosive forming process using some input-output experimental data. In this way, EAs with a new encoding scheme is firstly presented to evolutionary design of the generalized GMDH-type neural networks in which the connectivity configurations in such networks are not limited to adjacent layers. Multi-objective EAs (non–dominated sorting genetic algorithm, NSGA-II) with a new diversity preserving mechanism are secondly used for Pareto optimization of such GMDH-type neural networks. The important conflicting objectives of GMDH-type neural networks that are considered in this work are, namely, Training Error (TE), Prediction Error (PE) and number of neurons (N) of such neural network. Different pairs of these objective functions are selected for 2-objective optimization processes. Therefore, optimal Pareto fronts of such models are obtained in each case which exhibit the trade-offs between the corresponding pair of conflicting objectives and, thus, provide different non-dominated optimal choices of GMDH-type neural networks models for the explosive forming process. Moreover, all the three objectives are also considered in a 3-objective optimization process which consequently lead to some more non-dominated choices of GMDH-type models representing the trade-offs among the training error, prediction error, and number of neurons (complexity of network), simultaneously. The overlay graphs of these Pareto fronts also reveal that the 3-objective results include those of the 2-objective results and, thus, provide more optimal choices for the multi-objective design of GMDH-type neural networks in terms of minimum training error, minimum prediction error and minimum complexity.

Multi-objective based superimposed optimization method for enhancement of l-glutaminase production by Bacillus subtilis RSP-GLU

l-Glutaminase (l-glutamine amidohydrolase, EC 3.5.1.2) is a deamiding enzyme that has current focus on a therapeutic potentials and flavor enhancement agent in food industry. It was noticed that the amidase production was depended on the bacterial growth. However, the enhancement of bacterial growth by other substrates suppress the secretion of l-glutaminase. Governing the growth as well as amidase production is challenging task. In this study a multi-objective based superimposed optimization method was employed to control the biomass as well as to enhance the production of l-glutaminase. Various parameters such as volume of medium, pH, incubation temperature, inoculum level, l-glutamine concentration and rpm were optimized. The interactive influence of these parameters with their effect on enzyme and biomass production was analyzed using fractional factorial central composite design (FFCCD). The coefficient of determination (R2) was calculated as 0.9862 and 0.9513 for l-glutaminase and biomass production respectively. Overlay graphs were plotted by superimposing the contours for the various response surfaces of biomass and enzyme production. Based on superimposing method the cultural conditions obtained was volume of media 85 mL, temperature 37 °C, pH 7.24, inoculum concentration 2.47 mL, l-glutaminase concentration 1.01 g/L and agitation speed of 109 rpm. At these conditions 225 U/mL l-glutaminase and 0.79 g/L biomass were obtained. The current study provides a good description for balanced optimization of fermentation process of multi response or objective systems by using FFCCD method.

Fast Distributed Consensus Through Path Averaging on Random Walks

Distributed computation of average consensus is an important function in numerous wireless sensor networks and ad-hoc networks applications. In light of the severe resource constraints characterizing these embedded networked systems, it is of paramount importance the design of effective algorithms with low computational, communication, and energy requirements. Randomized gossip are a category of network algorithms that entail communication and information exchange among nodes selected with probabilistic mechanisms. They are considered attractive solutions for solving consensus problems because of their decentralized nature, conceptual simplicity, and capability of adapting to structural network modifications. However, the number of iterations needed by randomized gossip to converge towards consensus is an issue to be addressed to reduce latency and to limit the impact of the algorithm on the lifetime of battery operated devices. Solutions to the problem have been proposed that make use of localization and greedy geographic routing to build overlay graphs on top of a randomized gossip protocol, thus enabling information averaging among non-neighbor nodes and accelerating convergence. The main drawback of this type of approach is that each node is required to know its position, which is not always affordable in terms of costs or not even possible because of the lack of GPS signal. In this article we propose a novel approach to the consensus averaging problem based on a random walk mechanism to identify nodes involved in a computation round, and on a path averaging technique to update more than two nodes into the same round. The resulting algorithm doesn’t rely on any positioning mechanism. Experimental results provide evidence of the improved performance of the proposed method with respect to standard randomized gossip, with considerable gain in terms of convergence speed.

Multi-objective optimization of oxidative desulfurization in a sono-photochemical airlift reactor

Response surface methodology (RSM) was employed to optimize ultrasound/ultraviolet-assisted oxidative desulfurization in an airlift reactor. Ultrasonic waves were incorporated in a novel-geometry reactor to investigate the synergistic effects of sono-chemistry and enhanced gas-liquid mass transfer. Non-hydrotreated kerosene containing sulfur and aromatic compounds was chosen as a case study. Experimental runs were conducted based on a face-centered central composite design and analyzed using RSM. The effects of two categorical factors, i.e., ultrasound and ultraviolet irradiation and two numerical factors, i.e., superficial gas velocity and oxidation time were investigated on two responses, i.e., desulfurization and de-aromatization yields. Two-factor interaction (2FI) polynomial model was developed for the responses and the desirability function associate with overlay graphs was applied to find optimum conditions. The results showed enhancement in desulfurization ability corresponds to more reduction in aromatic content of kerosene in each combination. Based on desirability approach and certain criteria considered for desulfurization/de-aromatization, the optimal desulfurization and de-aromatization yields of 91.7% and 48% were obtained in US/UV/O3/H2O2 combination, respectively.

Empirical Modeling and Multi-Response Optimization of Laser Transmission Welding of Polycarbonate to ABS

In present research, laser transmission welding of polycarbonate to ABS has been investigated through empirical modeling. The effect of laser power, welding speed, stand-off distance and clamp pressure on weld strength and track width is investigated using the empirical models developed by response surface methodology. Laser power and stand-off distance have shown the dominant effect on the weld strength and track width, respectively. Numerical and graphical optimization schemes are used to find out the optimal welding conditions which satisfy multiple objectives, simultaneously. The optimal welding parameter combinations are presented in favors of high welding strength and low track width. Overlay graphs are plotted by superimposing the contours for the various response surfaces. Optimal solutions are found that would improve the weld quality within the selected range of process parameters.

Crawler-Based Measurement of Large Scale P2P IPTV Systems

PDF HTML阅读 XML下载 导出引用 引用提醒 基于爬行器的大规模P2P IPTV 测量 DOI: 10.3724/SP.J.1001.2011.03849 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家高技术研究发展计划(863) (2008AA01Z407) Crawler-Based Measurement of Large Scale P2P IPTV Systems Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:为了解大规模P2P IPTV 系统中的用户行为特征和拓扑结构特征等内在信息,开发和部署了一个多协议P2P IPTV 爬行器TVCrawler,对3 个主流的P2P IPTV 系统——PPLive,PPStream 和UUSee 进行了大量的主动测量,并对P2P IPTV 系统中的用户行为和网络拓扑特征进行了分析和比较.主要发现包括:1) P2P IPTV 系统的频道在线人数中,有一半以上位于不可达的NAT 或者防火墙后面;2) 节点动态性的波动范围随频道人数的增加而增加,但是其取值范围具有幂律上限;3) 节点会话长度符合广延指数分布;4) PPLive 的入度分布属于具有指数截断的幂次分布,PPStream 的入度表现为某种分段幂律函数,UUSee 的入度接近威布尔分布;5) P2P IPTV 系统都是异配网络;6) P2P IPTV 系统都表现为小世界网络;7) PPLive 网络具有聚类特征,而PPStream 和UUSee 则不存在明显聚类特征;8) 3 个系统都表现出类似于无标度网络的鲁棒性特征,而与其他两个系统比较时,PPLive 具有更高的故障容错性和更明显的攻击脆弱性.这些测量研究和发现不仅有助于设计出更符合真实网络应用环境的系统或协议,也是实现对P2P IPTV 进行监测、引导、控制等方面的重要依据和基础. Abstract:In order to gain insight on the topology characteristics of P2P IPTV systems and their online user behavior characteristics, This paper develop and deploys a multiprotocol P2P IPTV network crawler, called TVCrawler, which enables users to launch an in-depth measurement and comparative research for several well-known P2P IPTV systems, including PPLive, PPStream, and UUSee. This paper presents results from experiments and research efforts on these large-scale P2P IPTV overlay graphs. Major findings include 1) more than 50% of online users are unreachable because they lie behind NAT or firewall; 2) fluctuation range of churn increases with the increase of the population of channel, and there exists a power-law upper bound for fluctuation range of churn; 3) session length of peer follows a stretched exponential distribution; 4) while the in-degree of PPLive follows the power-law distribution with exponential cutoffs, the in-degree of PPStream appears to have multiple separate power-law regimes with different exponents, and the in-degree of UUSee approaches Weibull distribution. 5) All of measured P2P IPTV overlay graphs appear as a disassortative mixing; 6) small-world networks are ubiquitous in measured P2P IPTV systems. 7) the PPLive overlay graph is clustering, but the others are not; 8) all of measured P2P IPTV overlay graphs have robustness similar to that of a power-law graph, but PPLive is more vulnerable to malicious attacks and more robust to random failures than the other. These research and findings Will be good for designing and optimizing of P2P IPTV protocols, but also for monitoring, directing, and dominating the P2P IPTV system. 参考文献 相似文献 引证文献

On the Topology Design of Integrated Wireless Networks

Topology clustering, constructing overlay graphs, adding relay nodes, or creating a “small-world” network by building some shortcuts etc, topology control schemes are able to achieve the scalability, resilience, and fault-tolerance for wireless communication networks. In this article, we take a different approach to reach such aim for heterogeneous integrated wireless networks by generating a topology such that the resulting network is “scale-free”. Thereby we propose a topology control algorithm based on the “scale-free” complex network concept and directed proximity graph theory for integrated wireless networks with non-uniform transmission ranges. In this algorithm, the topology is also generated by new nodes’ growth and preferential attachment procedure, but where each new node connects to the existing nodes in its directed attachable proximity in terms of certain probability at each time step. Each node’s directed attachable proximity graph is generated from its directed reachable proximity graph that is built by regulating its transmission power based on locally collected information. The simulation experiments are provided to validate our claims.

Understanding overlay characteristics of a large-scale peer-to-peer IPTV system

This article presents results from our measurement and modeling efforts on the large-scale peer-to-peer (p2p) overlay graphs spanned by the PPLive system, the most popular and largest p2p IPTV (Internet Protocol Television) system today. Unlike other previous studies on PPLive, which focused on either network-centric or user-centric measurements of the system, our study is unique in (a) focusing on PPLive overlay-specific characteristics, and (b) being the first to derive mathematical models for its distributions of node degree, session length, and peer participation in simultaneous overlays. Our studies reveal characteristics of multimedia streaming p2p overlays that are markedly different from existing file-sharing p2p overlays. Specifically, we find that: (1) PPLive overlays are similar to random graphs in structure and thus more robust and resilient to the massive failure of nodes, (2) Average degree of a peer in the overlay is independent of the channel population size and the node degree distribution can be fitted by a piecewise function, (3) The availability correlation between PPLive peer pairs is bimodal, that is, some pairs have highly correlated availability, while others have no correlation, (4) Unlike p2p file-sharing peers, PPLive peers are impatient and session lengths (discretized, per channel) are typically geometrically distributed, (5) Channel population size is time-sensitive, self-repeated, event-dependent, and varies more than in p2p file-sharing networks, (6) Peering relationships are slightly locality-aware, and (7) Peer participation in simultaneous overlays follows a Zipf distribution. We believe that our findings can be used to understand current large-scale p2p streaming systems for future planning of resource usage, and to provide useful and practical hints for future design of large-scale p2p streaming systems.

Distributed Network Formation for n-Way Broadcast Applications

In an n-way broadcast application, each one of n overlay nodes wants to push its own distinct large data file to all other n-1 destinations as well as download their respective data files. BitTorrent-like swarming protocols are ideal choices for handling such massive data volume transfers. The original BitTorrent targets one-to-many broadcasts of a single file to a very large number of receivers, and thus, by necessity, employs a suboptimized overlay topology. n-way broadcast applications, on the other hand, owing to their inherent complexity, are realizable only in small to medium scale networks. In this paper, we show that we can leverage this scale constraint to construct optimized overlay topologies that take into consideration the end-to-end characteristics of the network and as a consequence deliver far superior performance compared to random and myopic (greedy) approaches. We present the Max-Min and Max-Sum peer-selection policies used by individual nodes to select their neighbors. The first one strives to maximize the available bandwidth to the slowest destination, while the second maximizes the aggregate output rate. We design a swarming protocol suitable for n-way broadcast and operate it on top of overlay graphs formed by nodes that employ Max-Min or Max-Sum policies. Using measurements from a PlanetLab prototype implementation and trace-driven simulations, we demonstrate that the performance of swarming protocols on top of our constructed topologies is far superior to the performance of random and myopic overlays.

Engineering multilevel overlay graphs for shortest-path queries

An overlay graph of a given graph G = ( V , E ) on a subset S ⊆ V is a graph with vertex set S and edges corresponding to shortest paths in G . In particular, we consider variations of the multilevel overlay graph used in Schulz et al. [2002] to speed up shortest-path computation. In this work, we follow up and present several vertex selection criteria, along with two general strategies of applying these criteria, to determine a subset S of a graph's vertices. The main contribution is a systematic experimental study where we investigate the impact of selection criteria and strategies on multilevel overlay graphs and the resulting speed-up achieved for shortest-path computation: Depending on selection strategy and graph type, a centrality index criterion, selection based on planar separators, and vertex degree turned out to perform best.

Multi-objective evolutionary optimization of polynomial neural networks for modelling and prediction of explosive cutting process

In this paper, evolutionary algorithms (EAs) are deployed for multi-objective Pareto optimal design of group method of data handling (GMDH)-type neural networks which have been used for modelling an explosive cutting process using some input–output experimental data. In this way, multi-objective EAs (non-dominated sorting genetic algorithm, NSGA-II) with a new diversity-preserving mechanism are used for Pareto optimization of such GMDH-type neural networks. The important conflicting objectives of GMDH-type neural networks that are considered in this work are, namely, training error ( TE), prediction error ( PE), and number of neurons ( N) of such neural networks. Different pairs of theses objective functions are selected for 2-objective optimization processes. Therefore, optimal Pareto fronts of such models are obtained in each case which exhibit the trade-off between the corresponding pair of conflicting objectives and, thus, provide different non-dominated optimal choices of GMDH-type neural networks models for explosive cutting process. Moreover, all the three objectives are considered in a 3-objective optimization process, which consequently leads to some more non-dominated choices of GMDH-type models representing the trade-offs among the training error, prediction error, and number of neurons (complexity of network), simultaneously. The overlay graphs of these Pareto fronts also reveal that the 3-objective results include those of the 2-objective results and, thus, provide more optimal choices for the multi-objective design of GMDH-type neural networks in terms of minimum training error, minimum prediction error, and minimum complexity.

Dynamic Multi-level Overlay Graphs for Shortest Paths

Multi-level overlay graphs represent a speed-up technique for shortest paths computation which is based on a hierarchical decomposition of a weighted directed graph G. They have been shown to be experimentally efficient, especially when applied to timetable information. However, no theoretical result on the cost of constructing, maintaining and querying multi-level overlay graphs in a dynamic environment is known. In this paper, we show theoretical properties of multi-level overlay graphs that lead us to the definition of a new data structure for the computation and the maintenance of an overlay graph of G while weight decrease or weight increase operations are performed on G. Our solution is theoretically faster than the recomputation from scratch and allows queries that can be performed more efficiently than running Dijkstra’s shortest paths algorithm on G.

Multi-response optimization of CO 2 laser-welding process of austenitic stainless steel

Recently, laser welding of austenitic stainless steel has received great attention in industry. This is due to its widespread application in petroleum refinement stations, power plants, the pharmaceutical industry and also in households. Therefore, mechanical properties should be controlled to obtain good welded joints. The welding process should be optimized by the proper mathematical models. In this research, the tensile strength and impact strength along with the joint-operating cost of laser-welded butt joints made of AISI304 was investigated. Design-expert software was used to establish the design matrix and to analyze the experimental data. The relationships between the laser-welding parameters (laser power, welding speed and focal point position) and the three responses (tensile strength, impact strength and joint-operating cost) were established. Also, the optimization capabilities in design-expert software were used to optimize the welding process. The developed mathematical models were tested for adequacy using analysis of variance and other adequacy measures. In this investigation, the optimal welding conditions were identified in order to increase the productivity and minimize the total operating cost. Overlay graphs were plotted by superimposing the contours for the various response surfaces. The process parameters effect was determined and the optimal welding combinations were tabulated.

Software

Now available from SPSS is version 8.0 of SYSTAT, the Windows-based statistics and graphics software. The 32-bit package includes a number of additional features: a revised user interface; a spatial statistics capability that evaluates geostatistical models with 2D and 3D simulations; a map library that covers the world; and enhanced reporting and organizing facilities. The package allows users to overlay graphs from several files, model data using a range of options, import external map and data files, and publish results directly on the Web.

The application of ‘complexity analysis’ in selecting the optimum lathe for producing a defined component

In previous work (Brunn et al.[1]), it was shown that the floor to floor time for a turned component could be rapidly established. This time was dependant upon the type of lathe being investigated, for example, a part may require a 1 hr production cycle if allocated to a centre lathe, however, it is possible that the same part could be produced on a N.C. lathe in half this time. Thus the question arises, which machine is the most economic and in what way are the results affected by batch size. In this work the use of ‘complexity factor’ is shown to be the basis of a method which rapidly enables parts to be allocated to the machine which is the most economic for their production. A cost equation is used which encompasses production time, set-up time, batch size and factory dependant costs (such as overheads, labour and the like). This yields the overall cost per part. By the use of a computer program, the cost over a range of components and batch sizes is readily evaluated. This data is automatically plotted in a easily usable form. Using this approach, a series of overlay graphs is developed, this allows the performance of different lathes to be compared and hence the optimum selection made. The method is believed to be of considerable merit because its use enables the production planner to achieve the savings of machine optimisation at a low level of effort. This occurs because the time, and hence the cost of operating the system is negligible.