Transmission cost allocation using cooperative game theory: a comparative study

In this paper is presented a Game Theory based methodology to allocate transmission costs, considering cooperation and competition between producers. As original contribution, it finds the degree of participation on the additional costs according to the demand behavior. A comparative study was carried out between the obtained results using Nucleolus balance and Shapley Value, with other techniques such as Averages Allocation method and the Generalized Generation Distribution Factors method (GGDF). As example, a six nodes network was used for the simulations. The results demonstrate the ability to find adequate solutions on open access environment to the networks.

Dynamic power- and failure-aware cloud resources allocation for Sets of independent tasks

Cloud computing is increasingly being adopted in different scenarios, like social networking, business applications, scientific experiments, etc. Relying in virtualization technology, the construction of these computing environments targets improvements in the infrastructure, such as power-efficiency and fulfillment of users’ SLA specifications. The methodology usually applied is packing all the virtual machines on the proper physical servers. However, failure occurrences in these networked computing systems can induce substantial negative impact on system performance, deviating the system from ours initial objectives. In this work, we propose adapted algorithms to dynamically map virtual machines to physical hosts, in order to improve cloud infrastructure power-efficiency, with low impact on users’ required performance. Our decision making algorithms leverage proactive fault-tolerance techniques to deal with systems failures, allied with virtual machine technology to share nodes resources in an accurately and controlled manner. The results indicate that our algorithms perform better targeting power-efficiency and SLA fulfillment, in face of cloud infrastructure failures.

Comparison of allocation approaches in soybean biodiesel life cycle assessment

This work shows the influence of using different allocation approaches when modelling the inventory analysis in a soybean biodiesel life cycle assessment (LCA). Results obtained using mass, energy and economic based allocations are compared, focusing on the following aspects: normalised potential environmental impact (PEI) categories, total PEI and relative contributions to the total PEI from each life cycle stage and environmental impact category. Similar results are obtained either using economic and energy based allocations. However, different results are obtained when mass based allocation is used when compared with the other two. This study also illustrates that using different allocation approaches in biodiesel LCA may influence the final conclusions, especially in comparative assertions, emphasising the need to perform a sensitivity analysis in the LCA interpretation step.

An Explicit GTS allocation algorithm for IEEE 802.15.4

The IEEE 802.15.4 standard provides appealing features to simultaneously support real-time and non realtime traffic, but it is only capable of supporting real-time communications from at most seven devices. Additionally, it cannot guarantee delay bounds lower than the superframe duration. Motivated by this problem, in this paper we propose an Explicit Guaranteed time slot Sharing and Allocation scheme (EGSA) for beacon-enabled IEEE 802.15.4 networks. This scheme is capable of providing tighter delay bounds for real-time communications by splitting the Contention Free access Period (CFP) into smaller mini time slots and by means of a new guaranteed bandwidth allocation scheme for a set of devices with periodic messages. At the same the novel bandwidth allocation scheme can maximize the duration of the CFP for non real-time communications. Performance analysis results show that the EGSA scheme works efficiently and outperforms competitor schemes both in terms of guaranteed delay and bandwidth utilization.

Bandwidth allocation in hexagonal wireless sensor networks for real-time communications

We present an algorithm for bandwidth allocation for delay-sensitive traffic in multi-hop wireless sensor networks. Our solution considers both periodic as well as aperiodic real-time traffic in an unified manner. We also present a distributed MAC protocol that conforms to the bandwidth allocation and thus satisfies the latency requirements of realtime traffic. Additionally, the protocol provides best-effort service to non real-time traffic. We derive the utilization bounds of our MAC protocol.

GTS allocation analysis in IEEE 802.15.4 for real-time wireless sensor networks

The IEEE 802.15.4 protocol proposes a flexible communication solution for Low-Rate Wireless Personal Area Networks including sensor networks. It presents the advantage to fit different requirements of potential applications by adequately setting its parameters. When enabling its beacon mode, the protocol makes possible real-time guarantees by using its Guaranteed Time Slot (GTS) mechanism. This paper analyzes the performance of the GTS allocation mechanism in IEEE 802.15.4. The analysis gives a full understanding of the behavior of the GTS mechanism with regards to delay and throughput metrics. First, we propose two accurate models of service curves for a GTS allocation as a function of the IEEE 802.15.4 parameters. We then evaluate the delay bounds guaranteed by an allocation of a GTS using Network Calculus formalism. Finally, based on the analytic results, we analyze the impact of the IEEE 802.15.4 parameters on the throughput and delay bound guaranteed by a GTS allocation. The results of this work pave the way for an efficient dimensioning of an IEEE 802.15.4 cluster.

Energy and delay trade-off of the GTS allocation mechanism in IEEE 802.15.4 for wireless sensor networks

The IEEE 802.15.4 protocol proposes a flexible communication solution for Low-Rate Wireless Personal Area Networks (LR-WPAN) including wireless sensor networks (WSNs). It presents the advantage to fit different requirements of potential applications by adequately setting its parameters. When in beaconenabled mode, the protocol can provide timeliness guarantees by using its Guaranteed Time Slot (GTS) mechanism. However, power-efficiency and timeliness guarantees are often two antagonistic requirements in wireless sensor networks. The purpose of this paper is to analyze and propose a methodology for setting the relevant parameters of IEEE 802.15.4-compliant WSNs that takes into account a proper trade-off between power-efficiency and delay bound guarantees. First, we propose two accurate models of service curves for a GTS allocation as a function of the IEEE 802.15.4 parameters, using Network Calculus formalism. We then evaluate the delay bound guaranteed by a GTS allocation and express it as a function of the duty cycle. Based on the relation between the delay requirement and the duty cycle, we propose a power-efficient superframe selection method that simultaneously reduces power consumption and enables meeting the delay requirements of real-time flows allocating GTSs. The results of this work may pave the way for a powerefficient management of the GTS mechanism in an IEEE 802.15.4 cluster.

Cost Allocation Model for Distribution Networks Considering High Penetration of Distributed Energy Resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitiveenvironment of electricity markets impose the use of new approaches in several domains. The networkcost allocation, traditionally used in transmission networks, should be adapted and used in the distribu-tion networks considering the specifications of the connected resources. The main goal is to develop afairer methodology trying to distribute the distribution network use costs to all players which are usingthe network in each period. In this paper, a model considering different type of costs (fixed, losses, andcongestion costs) is proposed comprising the use of a large set of DER, namely distributed generation(DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehi-cles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). Theproposed model includes three distinct phases of operation. The first phase of the model consists in aneconomic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen’s andBialek’s tracing algorithms are used and compared to evaluate the impact of each resource in the net-work. Finally, the MW-mile method is used in the third phase of the proposed model. A distributionnetwork of 33 buses with large penetration of DER is used to illustrate the application of the proposedmodel.

The role of dispersion into assets allocation

Dispersion of returns has gained a lot of attention as a measure to distinguish good and bad investment opportunities time. In the following dissertation, the cross-sectional returns volatility is analyzed over a fifteen year period across the S&P100 Index composition. The main inference drawn from the data sample is that the canonical measure of dispersion is highly macro-risk driven and therefore more biased towards returns volatility rather than its correlation component.

Impact of clinical practice guidelines on priorisation for intensive care beds allocation in high-risk acute coronary syndrome patients: does age play a role?

QUESTION UNDER STUDY: To assess which high-risk acute coronary syndrome (ACS) patient characteristics played a role in prioritising access to intensive care unit (ICU), and whether introducing clinical practice guidelines (CPG) explicitly stating ICU admission criteria altered this practice. PATIENTS AND METHODS: All consecutive patients with ACS admitted to our medical emergency centre over 3 months before and after CPG implementation were prospectively assessed. The impact of demographic and clinical characteristics (age, gender, cardiovascular risk factors, and clinical parameters upon admission) on ICU hospitalisation of high-risk patients (defined as retrosternal pain of prolonged duration with ECG changes and/or positive troponin blood level) was studied by logistic regression. RESULTS: Before and after CPG implementation, 328 and 364 patients, respectively, were assessed for suspicion of ACS. Before CPG implementation, 36 of the 81 high-risk patients (44.4%) were admitted to ICU. After CPG implementation, 35 of the 90 high-risk patients (38.9%) were admitted to ICU. Male patients were more frequently admitted to ICU before CPG implementation (OR=7.45, 95% CI 2.10-26.44), but not after (OR=0.73, 95% CI 0.20-2.66). Age played a significant role in both periods (OR=1.57, 95% CI 1.24-1.99), both young and advanced ages significantly reducing ICU admission, but to a lesser extent after CPG implementation. CONCLUSION: Prioritisation of access to ICU for high-risk ACS patients was age-dependent, but focused on the cardiovascular risk factor profile. CPG implementation explicitly stating ICU admission criteria decreased discrimination against women, but other factors are likely to play a role in bed allocation.

Using genetic algorithms for the single allocation hub location problem

Hub location problem is an NP-hard problem that frequently arises in the design of transportation and distribution systems, postal delivery networks, and airline passenger flow. This work focuses on the Single Allocation Hub Location Problem (SAHLP). Genetic Algorithms (GAs) for the capacitated and uncapacitated variants of the SAHLP based on new chromosome representations and crossover operators are explored. The GAs is tested on two well-known sets of real-world problems with up to 200 nodes. The obtained results are very promising. For most of the test problems the GA obtains improved or best-known solutions and the computational time remains low. The proposed GAs can easily be extended to other variants of location problems arising in network design planning in transportation systems.

Multi-Objective Genetic Algorithms for the Single Allocation Hub Location Problem

Hub Location Problems play vital economic roles in transportation and telecommunication networks where goods or people must be efficiently transferred from an origin to a destination point whilst direct origin-destination links are impractical. This work investigates the single allocation hub location problem, and proposes a genetic algorithm (GA) approach for it. The effectiveness of using a single-objective criterion measure for the problem is first explored. Next, a multi-objective GA employing various fitness evaluation strategies such as Pareto ranking, sum of ranks, and weighted sum strategies is presented. The effectiveness of the multi-objective GA is shown by comparison with an Integer Programming strategy, the only other multi-objective approach found in the literature for this problem. Lastly, two new crossover operators are proposed and an empirical study is done using small to large problem instances of the Civil Aeronautics Board (CAB) and Australian Post (AP) data sets.

Le financement des municipalités par le gouvernement fédéral au Canada et aux États-Unis: transferts et facteurs d'allocation.

Rapport de recherche

Fair Production and Allocation of an Excludable Nonrival Good

We study fairness in economies with one private good and one partially excludable nonrival good. A social ordering function determines for each profile of preferences an ordering of all conceivable allocations. We propose the following Free Lunch Aversion condition: if the private good contributions of two agents consuming the same quantity of the nonrival good have opposite signs, reducing that gap improves social welfare. This condition, combined with the more standard requirements of Unanimous Indifference and Responsiveness, delivers a form of welfare egalitarianism in which an agent's welfare at an allocation is measured by the quantity of the nonrival good that, consumed at no cost, would leave her indifferent to the bundle she is assigned.