A Multi-Objective Approach for VNE: Problems using multiple ILP formulations

Network Virtualization is a key technology for the Future Internet, allowing the deployment of multiple independent virtual networks that use resources of the same basic infrastructure. An important challenge in the dynamic provision of virtual networks resides in the optimal allocation of physical resources (nodes and links) to requirements of virtual networks. This problem is known as Virtual Network Embedding (VNE). For the resolution of this problem, previous research has focused on designing algorithms based on the optimization of a single objective. On the contrary, in this work we present a multi-objective algorithm, called VNE-MO-ILP, for solving dynamic VNE problem, which calculates an approximation of the Pareto Front considering simultaneously resource utilization and load balancing. Experimental results show evidences that the proposed algorithm is better or at least comparable to a state-of-the-art algorithm. Two performance metrics were simultaneously evaluated: (i) Virtual Network Request Acceptance Ratio and (ii) Revenue/Cost Relation. The size of test networks used in the experiments shows that the proposed algorithm scales well in execution times, for networks of 84 nodes

Modelo para distribuição de recursos nos municípios brasileiros baseado na lei de diretrizes orçamentárias, análise multicritério e programação linear

The municipal management in any country of the globe requires planning and allocation of resources evenly. In Brazil, the Law of Budgetary Guidelines (LDO) guides municipal managers toward that balance. This research develops a model that seeks to find the balance of the allocation of public resources in Brazilian municipalities, considering the LDO as a parameter. For this using statistical techniques and multicriteria analysis as a first step in order to define allocation strategies, based on the technical aspects arising from the municipal manager. In a second step, presented in linear programming based optimization where the objective function is derived from the preference of the results of the manager and his staff. The statistical representation is presented to support multicriteria development in the definition of replacement rates through time series. The multicriteria analysis was structured by defining the criteria, alternatives and the application of UTASTAR methods to calculate replacement rates. After these initial settings, an application of linear programming was developed to find the optimal allocation of enforcement resources of the municipal budget. Data from the budget of a municipality in southwestern Paraná were studied in the application of the model and analysis of results.

Physical Design Methodologies for Low Power and Reliable 3D ICs

As the semiconductor industry struggles to maintain its momentum down the path following the Moore's Law, three dimensional integrated circuit (3D IC) technology has emerged as a promising solution to achieve higher integration density, better performance, and lower power consumption. However, despite its significant improvement in electrical performance, 3D IC presents several serious physical design challenges. In this dissertation, we investigate physical design methodologies for 3D ICs with primary focus on two areas: low power 3D clock tree design, and reliability degradation modeling and management. Clock trees are essential parts for digital system which dissipate a large amount of power due to high capacitive loads. The majority of existing 3D clock tree designs focus on minimizing the total wire length, which produces sub-optimal results for power optimization. In this dissertation, we formulate a 3D clock tree design flow which directly optimizes for clock power. Besides, we also investigate the design methodology for clock gating a 3D clock tree, which uses shutdown gates to selectively turn off unnecessary clock activities. Different from the common assumption in 2D ICs that shutdown gates are cheap thus can be applied at every clock node, shutdown gates in 3D ICs introduce additional control TSVs, which compete with clock TSVs for placement resources. We explore the design methodologies to produce the optimal allocation and placement for clock and control TSVs so that the clock power is minimized. We show that the proposed synthesis flow saves significant clock power while accounting for available TSV placement area. Vertical integration also brings new reliability challenges including TSV's electromigration (EM) and several other reliability loss mechanisms caused by TSV-induced stress. These reliability loss models involve complex inter-dependencies between electrical and thermal conditions, which have not been investigated in the past. In this dissertation we set up an electrical/thermal/reliability co-simulation framework to capture the transient of reliability loss in 3D ICs. We further derive and validate an analytical reliability objective function that can be integrated into the 3D placement design flow. The reliability aware placement scheme enables co-design and co-optimization of both the electrical and reliability property, thus improves both the circuit's performance and its lifetime. Our electrical/reliability co-design scheme avoids unnecessary design cycles or application of ad-hoc fixes that lead to sub-optimal performance. Vertical integration also enables stacking DRAM on top of CPU, providing high bandwidth and short latency. However, non-uniform voltage fluctuation and local thermal hotspot in CPU layers are coupled into DRAM layers, causing a non-uniform bit-cell leakage (thereby bit flip) distribution. We propose a performance-power-resilience simulation framework to capture DRAM soft error in 3D multi-core CPU systems. In addition, a dynamic resilience management (DRM) scheme is investigated, which adaptively tunes CPU's operating points to adjust DRAM's voltage noise and thermal condition during runtime. The DRM uses dynamic frequency scaling to achieve a resilience borrow-in strategy, which effectively enhances DRAM's resilience without sacrificing performance. The proposed physical design methodologies should act as important building blocks for 3D ICs and push 3D ICs toward mainstream acceptance in the near future.

Teoria de carteiras e a alocação de parques eólicos offshore

The consumption of energy on the planet is currently based on fossil fuels. They are responsible for adverse effects on the environment. Renewables propose solutions for this scenario, but must face issues related to the capacity of the power supply. Wind energy offshore emerging as a promising alternative. The speed and stability are greater winds over oceans, but the variability of these may cause inconvenience to the generation of electric power fluctuations. To reduce this, a combination of wind farms geographically distributed was proposed. The greater the distance between them, the lower the correlation between the wind velocity, increasing the likelihood that together achieve more stable power system with less fluctuations in power generation. The efficient use of production capacity of the wind park however, depends on their distribution in marine environments. The objective of this research was to analyze the optimal allocation of wind farms offshore on the east coast of the U.S. by Modern Portfolio Theory. The Modern Portfolio Theory was used so that the process of building portfolios of wind energy offshore contemplate the particularity of intermittency of wind, through calculations of return and risk of the production of wind farms. The research was conducted with 25.934 observations of energy produced by wind farms 11 hypothetical offshore, from the installation of 01 simulated ocean turbine with a capacity of 5 MW. The data show hourly time resolution and covers the period between January 1, 1998 until December 31, 2002. Through the Matlab R software, six were calculated minimum variance portfolios, each for a period of time distinct. Given the inequality of the variability of wind over time, set up four strategies rebalancing to evaluate the performance of the related portfolios, which enabled us to identify the most beneficial to the stability of the wind energy production offshore. The results showed that the production of wind energy for 1998, 1999, 2000 and 2001 should be considered by the portfolio weights calculated for the same periods, respectively. Energy data for 2002 should use the weights derived from the portfolio calculated in the previous time period. Finally, the production of wind energy in the period 1998-2002 should also be weighted by 1/11. It follows therefore that the portfolios found failed to show reduced levels of variability when compared to the individual production of wind farms hypothetical offshore

Transmission loss allocation based on optimal power flow and sensitivity analysis

This paper presents a new approach to the transmission loss allocation problem in a deregulated system. This approach belongs to the set of incremental methods. It treats all the constraints of the network, i.e. control, state and functional constraints. The approach is based on the perturbation of optimum theorem. From a given optimal operating point obtained by the optimal power flow the loads are perturbed and a new optimal operating point that satisfies the constraints is determined by the sensibility analysis. This solution is used to obtain the allocation coefficients of the losses for the generators and loads of the network. Numerical results show the proposed approach in comparison to other methods obtained with well-known transmission networks, IEEE 14-bus. Other test emphasizes the importance of considering the operational constraints of the network. And finally the approach is applied to an actual Brazilian equivalent network composed of 787 buses, and it is compared with the technique used nowadays by the Brazilian Control Center. (c) 2007 Elsevier Ltd. All rights reserved.

Transmission costs allocation based on optimal re-dispatch

Congestion management of transmission power systems has achieve high relevance in competitive environments, which require an adequate approach both in technical and economic terms. This paper proposes a new methodology for congestion management and transmission tariff determination in deregulated electricity markets. The congestion management methodology is based on a reformulated optimal power flow, whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the transactions resulting from market operation. The proposed transmission tariffs consider the physical impact caused by each market agents in the transmission network. The final tariff considers existing system costs and also costs due to the initial congestion situation and losses. This paper includes a case study for the 118 bus IEEE test case.

Effects of brood manipulation costs on optimal sex allocation in social hymenoptera.

In eusocial Hymenoptera, queens and workers are in conflict over optimal sex allocation. Sex ratio theory, while generating predictions on the extent of this conflict under a wide range of conditions, has largely neglected the fact that worker control of investment almost certainly requires the manipulation of brood sex ratio. This manipulation is likely to incur costs, for example, if workers eliminate male larvae or rear more females as sexuals rather than workers. In this article, we present a model of sex ratio evolution under worker control that incorporates costs of brood manipulation. We assume cost to be a continuous, increasing function of the magnitude of sex ratio manipulation. We demonstrate that costs counterselect sex ratio biasing, which leads to less female-biased population sex ratios than expected on the basis of relatedness asymmetry. Furthermore, differently shaped cost functions lead to different equilibria of manipulation at the colony level. While linear and accelerating cost functions generate monomorphic equilibria, decelerating costs lead to a process of evolutionary branching and hence split sex ratios.

Optimal switch allocation for automatic load transfer in distribution substations

This work proposes a methodology for optimized allocation of switches for automatic load transfer in distribution systems in order to improve the reliability indexes by restoring such systems which present voltage classes of 23 to 35 kV and radial topology. The automatic switches must be allocated on the system in order to transfer load remotely among the sources at the substations. The problem of switch allocation is formulated as nonlinear constrained mixed integer programming model subject to a set of economical and physical constraints. A dedicated Tabu Search (TS) algorithm is proposed to solve this model. The proposed methodology is tested for a large real-life distribution system. © 2011 IEEE.

Optimal Power Allocation for Multiuser Secure Communication in Cooperative Relaying Networks

We consider a cooperative relaying network in which a source communicates with a group of users in the presence of one eavesdropper. We assume that there are no source-user links and the group of users receive only retransmitted signal from the relay. Whereas, the eavesdropper receives both the original and retransmitted signals. Under these assumptions, we exploit the user selection technique to enhance the secure performance. We first find the optimal power allocation strategy when the source has the full channel state information (CSI) of all links. We then evaluate the security level through: i) ergodic secrecy rate and ii) secrecy outage probability when having only the statistical knowledge of CSIs.

The optimal sample allocation problem for mapped outputs

Abstract not available

Optimal Budget-Constrained Sample Allocation for Selection Decisions with Multiple Uncertain Attributes

A decision-maker, when faced with a limited and fixed budget to collect data in support of a multiple attribute selection decision, must decide how many samples to observe from each alternative and attribute. This allocation decision is of particular importance when the information gained leads to uncertain estimates of the attribute values as with sample data collected from observations such as measurements, experimental evaluations, or simulation runs. For example, when the U.S. Department of Homeland Security must decide upon a radiation detection system to acquire, a number of performance attributes are of interest and must be measured in order to characterize each of the considered systems. We identified and evaluated several approaches to incorporate the uncertainty in the attribute value estimates into a normative model for a multiple attribute selection decision. Assuming an additive multiple attribute value model, we demonstrated the idea of propagating the attribute value uncertainty and describing the decision values for each alternative as probability distributions. These distributions were used to select an alternative. With the goal of maximizing the probability of correct selection we developed and evaluated, under several different sets of assumptions, procedures to allocate the fixed experimental budget across the multiple attributes and alternatives. Through a series of simulation studies, we compared the performance of these allocation procedures to the simple, but common, allocation procedure that distributed the sample budget equally across the alternatives and attributes. We found the allocation procedures that were developed based on the inclusion of decision-maker knowledge, such as knowledge of the decision model, outperformed those that neglected such information. Beginning with general knowledge of the attribute values provided by Bayesian prior distributions, and updating this knowledge with each observed sample, the sequential allocation procedure performed particularly well. These observations demonstrate that managing projects focused on a selection decision so that the decision modeling and the experimental planning are done jointly, rather than in isolation, can improve the overall selection results.

Online Supplement to ‘Myopic Allocation Policy with Asymptotically Optimal Sampling Rate’

This document is the Online Supplement to ‘Myopic Allocation Policy with Asymptotically Optimal Sampling Rate,’ to be published in the IEEE Transactions of Automatic Control in 2017.

Optimal resource allocation and budgeting in libraries

Libraries since their inception 4000 years ago have been in a process of constant change. Although, changes were in slow motion for centuries, in the last decades, academic libraries have been continuously striving to adapt their services to the ever-changing user needs of students and academic staff. In addition, e-content revolution, technological advances, and ever-shrinking budgets have obliged libraries to efficiently allocate their limited resources among collection and services. Unfortunately, this resource allocation is a complex process due to the diversity of data sources and formats required to be analyzed prior to decision-making, as well as the lack of efficient integration methods. The main purpose of this study is to develop an integrated model that supports libraries in making optimal budgeting and resource allocation decisions among their services and collection by means of a holistic analysis. To this end, a combination of several methodologies and structured approaches is conducted. Firstly, a holistic structure and the required toolset to holistically assess academic libraries are proposed to collect and organize the data from an economic point of view. A four-pronged theoretical framework is used in which the library system and collection are analyzed from the perspective of users and internal stakeholders. The first quadrant corresponds to the internal perspective of the library system that is to analyze the library performance, and costs incurred and resources consumed by library services. The second quadrant evaluates the external perspective of the library system; user’s perception about services quality is judged in this quadrant. The third quadrant analyses the external perspective of the library collection that is to evaluate the impact of the current library collection on its users. Eventually, the fourth quadrant evaluates the internal perspective of the library collection; the usage patterns followed to manipulate the library collection are analyzed. With a complete framework for data collection, these data coming from multiple sources and therefore with different formats, need to be integrated and stored in an adequate scheme for decision support. A data warehousing approach is secondly designed and implemented to integrate, process, and store the holistic-based collected data. Ultimately, strategic data stored in the data warehouse are analyzed and implemented for different purposes including the following: 1) Data visualization and reporting is proposed to allow library managers to publish library indicators in a simple and quick manner by using online reporting tools. 2) Sophisticated data analysis is recommended through the use of data mining tools; three data mining techniques are examined in this research study: regression, clustering and classification. These data mining techniques have been applied to the case study in the following manner: predicting the future investment in library development; finding clusters of users that share common interests and similar profiles, but belong to different faculties; and predicting library factors that affect student academic performance by analyzing possible correlations of library usage and academic performance. 3) Input for optimization models, early experiences of developing an optimal resource allocation model to distribute resources among the different processes of a library system are documented in this study. Specifically, the problem of allocating funds for digital collection among divisions of an academic library is addressed. An optimization model for the problem is defined with the objective of maximizing the usage of the digital collection over-all library divisions subject to a single collection budget. By proposing this holistic approach, the research study contributes to knowledge by providing an integrated solution to assist library managers to make economic decisions based on an “as realistic as possible” perspective of the library situation.

Influence of the Operational Constraints in the Active Transmission Losses Allocation via Lagrange Multipliers

This paper presents an approach for the active transmission losses allocation between the agents of the system. The approach uses the primal and dual variable information of the Optimal Power Flow in the losses allocation strategy. The allocation coefficients are determined via Lagrange multipliers. The paper emphasizes the necessity to consider the operational constraints and parameters of the systems in the problem solution. An example, for a 3-bus system is presented in details, as well as a comparative test with the main allocation methods. Case studies on the IEEE 14-bus systems are carried out to verify the influence of the constraints and parameters of the system in the losses allocation.