Practical Resource Allocation Research Articles

Assistive technology as support for the exercise of legal capacity

Exercising legal capacity refers to engaging in legal transactions and relationships and is essential for the full inclusion of people with disabilities in society. The United Nations Convention on the Rights of Persons with Disabilities has enumerated the right to legal capacity on an equal basis and has created a state obligation to provide access to support for the exercise of legal capacity. This article examines the use of assistive devices as support for decision-making in exercising legal capacity for individuals with physical and cognitive impairments; for example, the use of voice recognition programmes, screen readers, and screen enlargement applications to support people with mobility and sensory impairments to use online portals essential for legal actions such as banking. It also discusses the experimental use of cognitive assistance, including computer or electrical assistive devices, to facilitate communication for people with cognitive impairments including those with no external signs of consciousness. It highlights the diversity of options for ‘support for the exercise of legal capacity’ showing how they can assist people with various disabilities. Finally, the article examines the boundaries of the state obligation to provide such support, including issues of practical implementation and resource allocation.

Energy-Efficient Resource Allocation in LTE-Based MIMO-OFDMA Systems With User Rate Constraints

In recent years, the enormous energy consumption of wireless communication systems has aroused universal concerns throughout the world. Hence, energy efficiency has become one of the central topics in today's wireless communication industry. In this paper, we study energy-efficient resource allocation for Long Term Evolution (LTE) cellular mobile systems. To be applicable in LTE systems, both multiple-input multiple-output (MIMO) orthogonal frequency-division multiple access (OFDMA) radio access network and resource blocks (RBs) for subchannel assignment are considered in this work, functioning as two distinguishing characteristics for LTE resource allocation. In particular, an optimization problem concerning joint RB assignment, and power allocation is formulated to maximize the energy efficiency measured by “bits-per-Joule” metric, under per-user quality-of-service (QoS) requirements in the form of user rate constraints. We first show that this energy-efficient resource allocation problem can be converted into a more tractable equivalent problem by which the fractional objective of energy efficiency is well settled. With the Lagrange dual method then, we decouple the RB assignment and power allocation on different subchannels using dual decomposition, which greatly simplifies the combinatorial RB assignment, and address the equivalent problem effectively via solving a series of dual optimization problems. Moreover, a computationally efficient but near-optimal algorithm is proposed to perform QoS-aware energy-efficient resource allocation in practice. Simulation results show that our proposed algorithm may not only improve energy efficiency significantly but fully satisfy users' rate requirements as well. Moreover, with MIMO-OFDMA and RB assignment being considered, the proposed algorithm may be more applicable in LTE systems than most existing schemes on energy-efficient resource allocation.

Novel Cross-Layer QoE-Aware Radio Resource Allocation Algorithms in Multiuser OFDMA Systems

The assurance of quality of experience (QoE) and provisioning of high throughput of the system represent the main goals of future wireless and mobile networks. This paper presents novel and practical cross-layer QoE-aware radio resource allocation (RRA) algorithms for the downlink of a heterogeneous orthogonal frequency division multiple access (OFDMA) system. The objective of the proposed algorithms is to assure the appropriate level of QoE for each user of the system by incorporating application-layer parameters and subjective human perception of quality into the RRA process. We propose two user-oriented joint subcarrier and power allocation algorithms with low complexity for real-time and interactive services. The first algorithm dynamically allocates resources by assuring the same level of QoE to all users of the system, whereas the second algorithm introduces the efficient trade-off between the user's QoE and the spectral efficiency of the system. By considering application-layer parameters and user's perception of quality, high users' QoE and explicit control of data rates can be achieved. The numerical results show that the proposed algorithms achieve significant increase in the level of QoE compared to previous works, a fair distribution of capacity among users and near to optimal solution of QoE for the OFDMA system.

Multiproject Resources Allocation Model under Fuzzy Random Environment and Its Application to Industrial Equipment Installation Engineering

This paper focuses on a multiproject resource allocation problem in a bilevel organization. To solve this problem, a bilevel multiproject resource allocation model under a fuzzy random environment is proposed. Two levels of decision makers are considered in the model. On the upper level, the company manager aims to allocate the company's resources to multiple projects to achieve the lowest cost, which include resource costs and a tardiness penalty. On the lower level, each project manager attempts to schedule their resource-constrained project, with minimization of project duration as the main objective. In contrast to prior studies, uncertainty in resource allocation has been explicitly considered. Specifically, our research uses fuzzy random variables to model uncertain activity durations and resource costs. To search for the optimal solution of the bilevel model, a hybrid algorithm made up of an adaptive particle swarm optimization, an adaptive hybrid genetic algorithm, and a fuzzy random simulation algorithm is also proposed. Finally, the efficiency of the proposed model and algorithm is evaluated through a practical case from an industrial equipment installation company. The results show that the proposed model is efficient in dealing with practical resource allocation problems in a bilevel organization.

A Practical Resource Allocation Approach for Interference Management in LTE Uplink Transmission

In this paper, we investigate power control and resource allocation for long-term evolution (LTE) uplink. We develop an efficient way to improve system performance, especially for those users at the edge of a cell, by taking interference to and from adjacent cells into consideration. Simulation results show that the spectrum efficiency for edge users is improved by about 20% over the independent resource allocation and by about 10% over the soft frequency reuse scheme.

User priority aware scheduling and dynamic resource allocation in orthogonal frequency division multiple access

In this study, new mathematical formulations and algorithms for joint scheduling and hybrid resource allocation are derived and investigated for a multi-user downlink orthogonal frequency division multiple access system. A three-sectored multi-cellular heterogeneous traffic environment is considered where users are randomly distributed and categorised under different priority levels. Traffic consists of time delay-sensitive and time delay-insensitive services. Three practical scheduling and resource allocation methods are proposed to address the balance between throughput, outage probability and resource efficiency under varying channel conditions. The proposed methods are based on the Lagrangian duality framework, and are formulated as mixed integer programming problems constrained by the total power of the base station and users' data rate while maintaining the quality of service for each user. Both dynamic and fixed resource allocation approaches are included in the main problem formulation. The complexity of the resource allocation problem is minimised by approximating the well-known water level. Simulation results show that the total system throughput is penalised for the method that aims to minimise the outage probability of the highest priority level. This is because of the severe channel conditions experienced by some users, whereas the alternatively proposed methods maintain system efficiency under a similar amount of constrained resources and required traffic.

Iterative power and subcarrier allocation in rate-constrained orthogonal multicarrier downlink systems based on hybrid harmony search heuristics

This paper presents a novel iterative hybrid algorithm for subcarrier and power allocation in a cognitive orthogonal frequency division multiple access (OFDMA) downlink. In the considered setup a primary base station forwards information to K distant receivers by using a single OFDM waveform, whereas a secondary base station – subject to stringent per-user rate constraints – interferes with the former by sending information from users to the same set of destinations. Power and user allocation at both base stations is jointly performed by the proposed algorithm to maximize the overall throughput of the setup while satisfying, at the same time, the imposed rate constraints. Our proposal, which stems from an hybridization of the harmony search (HS) and differential evolution (DE) algorithms along with a greedy local repair method, is shown – through computer simulations over the extended vehicular A ITU channel model – to be an effective and practical resource allocation procedure for cognitive OFDMA downlinks.

Decision Making for HIV Prevention and Treatment Scale up

Effectively controlling the HIV epidemic will require efficient use of limited resources. Despite ambitious global goals for HIV prevention and treatment scale up, few comprehensive practical tools exist to inform such decisions. We briefly summarize modeling approaches for resource allocation for epidemic control, and discuss the practical limitations of these models. We describe typical challenges of HIV resource allocation in practice and some of the tools used by decision makers. We identify the characteristics needed in a model that can effectively support planners in decision making about HIV prevention and treatment scale up. An effective model to support HIV scale-up decisions will be flexible, with capability for parameter customization and incorporation of uncertainty. Such a model needs certain key technical features: it must capture epidemic effects; account for how intervention effectiveness depends on the target population and the level of scale up; capture benefit and cost differentials for packages of interventions versus single interventions, including both treatment and prevention interventions; incorporate key constraints on potential funding allocations; identify optimal or near-optimal solutions; and estimate the impact of HIV interventions on the health care system and the resulting resource needs. Additionally, an effective model needs a user-friendly design and structure, ease of calibration and validation, and accessibility to decision makers in all settings. Resource allocation theory can make a significant contribution to decision making about HIV prevention and treatment scale up. What remains now is to develop models that can bridge the gap between theory and practice.

Solution of some convex separable resource allocation and production planning problems with bounds on the variables

In this paper, we consider the problems of minimizing convex separable functions of two specific forms over a feasible region defined by a linear inequality or linear equality constraint, and two-sided bounds on the variables (box constraints). These problems are interesting from both theoretical and practical point of view because they arise in some mathematical programming problems and in various practical problems, for example, resource allocation and production planning problems. Necessary and sufficient condition is proved for a feasible solution to be an optimal solution to a more general convex separable problem consisting in minimizing a strictly convex separable function subject to a linear inequality constraint and box constraints. Necessary and sufficient conditions for a feasible solution to be an optimal solution to the two problems under consideration are obtained as corollaries of this more general result. Iterative algorithms of polynomial complexity for solving such problems are proposed and their convergence is proved. Some examples and results of numerical experiments are also presented.

Evaluation of resource allocation and supply-demand balance in clinical practice with high-cost technologies

Japan has one of the highest numbers of high-cost medical devices installed relative to its population. While evaluations of the distribution of these devices traditionally involve simple population-based assessments, an indicator that includes the demand of these devices would more accurately reflect the situation. The purpose of this study was to develop an indicator of the supply-demand balance of such devices, using examples of magnetic resonance imaging scanners (MRI) and extracorporeal shockwave lithotripters (ESWL), and to investigate the relationship between this indicator, personnel distribution statuses and operating statuses at the prefectural level. Using data from nation-wide surveys and claims data from 16 hospitals, we developed an indicator based on the ratio of the supplied number of device units to the number of device units in demand for MRI and ESWL. The latter value was based on patient volume and utilization proportion. Correlation analyses were conducted between the supply-demand balances of these devices, personal distribution and operating statuses. Comparisons between our indicator and conventional population-based indicators revealed that 15% and 30% of prefectures were at risk of underestimating the availability of MRI and ESWL, respectively. The numbers of specialist personnel/device units showed significant, negative correlations with our indicators in both devices. Utilization-based analyses of health care resource placement and utilization status provide a more accurate indication than simple population-based assessments, and can assist decision makers in reviewing gaps between health policy and management. Such an indicator therefore has the potential to be a tool in helping to improve the efficiency of the allocation and placement of such devices.

Resource Allocation for Downlink Cellular OFDMA Systems—Part II: Practical Algorithms and Optimal Reuse Factor

In a companion paper (see ?Resource Allocation for Downlink Cellular OFDMA Systems-Part I: Optimal Allocation,? IEEE Trans. Signal Process., vol. 58, no. 2, pp. 720-734, Feb. 2010), we characterized the optimal resource allocation in terms of power control and subcarrier assignment, for a downlink sectorized OFDMA system impaired by multicell interference. In our model, the network is assumed to be one dimensional (linear) for the sake of analysis. We also assume that a certain part of the available bandwidth is likely to be reused by different base stations while that the other part of the bandwidth is shared in an orthogonal way between these base stations. The optimal resource allocation characterized in Part I is obtained by minimizing the total power spent by the network under the constraint that all users' rate requirements are satisfied. It is worth noting that when optimal resource allocation is used, any user receives data either in the reused bandwidth or in the protected bandwidth, but not in both (except for at most one pivot-user in each cell). We also proposed an algorithm that determines the optimal values of users' resource allocation parameters. As a matter of fact, the optimal allocation algorithm proposed in Part I requires a large number of operations. In the present paper, we propose a distributed practical resource allocation algorithm with low complexity. We study the asymptotic behavior of both this simplified resource allocation algorithm and the optimal resource allocation algorithm of Part I as the number of users in each cell tends to infinity. Our analysis allows to prove that the proposed simplified algorithm is asymptotically optimal, i.e., it achieves the same asymptotic transmit power as the optimal algorithm as the number of users in each cell tends to infinity. As a byproduct of our analysis, we characterize the optimal value of the frequency reuse factor. Simulations sustain our claims and show that substantial performance improvements are obtained when the optimal value of the frequency reuse factor is used.

Large-scale joint rate and power allocation algorithm combined with admission control in cognitive radio networks

In this paper, we investigate a dynamic spectrum sharing problem for the centralized uplink cognitive radio networks using orthogonal frequency division multiple access. We formulate a large-scale joint rate and power allocation as an optimization problem under quality of service constraint for secondary users and interference constraint for primary users. We also suggest admission control to find a feasible solution to the optimization problem. To implement the resource allocation on a large-scale, we introduce a notion of using the conservative factors α and β depending on the outage and violation probabilities. Since estimating instantaneous channel gains is costly and requires high complexity, the proposed algorithm pursues a practical and implementation-friendly resource allocation. Simulation results demonstrate that the large-scale joint rate and power allocation incurs a slight loss in system throughput over the instantaneous one, but it achieves lower complexity with less sensitivity to variations in shadowing statistics.

An Efficient Radio Resource Allocation Scheme for Minimum Outage Probability Using Cooperation in OFDMA Systems

Cooperation can increase the system performance by obtaining the spatial diversity. While most of the present works concentrate on the analysis of the cooperation based on the inter-user channel response and developing a scheme for higher cooperative diversity, in this paper, we focus on practical resource allocation in OFDMA systems. Since the user who uses the same center frequency can not receive the signal when transmitting, this constraint should be considered to apply the cooperation to OFDMA systems. In this paper, we propose the pair-based OFDMA frame structure that overcomes this constraint. Also in this frame structure to achieve the minimum outage probability of system, we select the best partner among the candidate neighbors and allocate the suitable subchannels to bandwidth requested users through a cooperative subchannel allocation (CSA) algorithm. In order to evaluate the proposed resource allocation scheme, we carry out simulations based on IEEE 802.16e. The simulation results show that our proposed algorithm offers smaller outage probability than one based on non-cooperative communications and we get the minimum outage probability when a threshold for selection of candidate neighbors is 10dB. We analyze that these results can be achieved by helping users located around the edge of the cell.

Sum Throughput Enhancements in Quality of Service Constrained Multiuser MIMO OFDM Systems

In many wireless applications, such as video streaming, data transfer or mobile Internet, user satisfaction is directly related to the transmission rates of the wireless channels in the physical layer. If the transmission rate of one user undercuts a certain level, the quality of the application becomes unacceptable. Furthermore network operators are interested in maximizing overall system throughput. However, this aim can usually not be achieved without violating these minimum rate constraints. In this article we therefore consider a practical resource allocation scheme for MIMO OFDM systems that achieves both aims without requiring computationally expensive optimization algorithms. The main part consists of a user classification. Users in one group will only be served with their minimum required rates. The remaining users can exploit the additional system resources more effectively for strong throughput increases and are therefore put in the other group. An iterative application of the proposed scheme enables additional throughput increases and the consideration of maximum transmission rates.

Optimal Testing Resource Allocation, and Sensitivity Analysis in Software Development

We consider two kinds of software testing-resource allocation problems. The first problem is to minimize the number of remaining faults given a fixed amount of testing-effort, and a reliability objective. The second problem is to minimize the amount of testing-effort given the number of remaining faults, and a reliability objective. We have proposed several strategies for module testing to help software project managers solve these problems, and make the best decisions. We provide several systematic solutions based on a nonhomogeneous Poisson process model, allowing systematic allocation of a specified amount of testing-resource expenditures for each software module under some constraints. We describe several numerical examples on the optimal testing-resource allocation problems to show applications & impacts of the proposed strategies during module testing. Experimental results indicate the advantages of the approaches we proposed in guiding software engineers & project managers toward best testing resource allocation in practice. Finally, an extensive sensitivity analysis is presented to investigate the effects of various principal parameters on the optimization problem of testing-resource allocation. The results can help us know which parameters have the most significant influence, and the changes of optimal testing-effort expenditures affected by the variations of fault detection rate & expected initial faults.

Decision-making and nurse case management: a philosophical perspective.

Decision-making related to resource allocation in home care case management practice is addressed from the unique perspective of nursing. The case management process stipulates the adherence to both client-centered and system-centered goals. Issues that emerge from this process include the ethical dilemma of deciding the equitable and fair distribution of resources related to the provision of appropriate levels of service; economic factors as they relate to limited financial resources; and the variance among case managers in their decision-making. Moderate realism, as compared to critical and feminist theory, provides a philosophical perspective that allows a practical interpretation of these issues.

Modelling of quality function deployment planning with resource allocation

Quality Function Deployment (QFD) is a well-known customer-oriented methodology, which is widely used to assist decision making in product design and development in various types of production. Determining how and to what extent certain characteristics or technical attributes (TAs) of products are to be met, with a view to gaining a higher level of overall customer satisfaction, is a key success factor in product design and development. An operational QFD planning problem with resource allocation is considered in this paper. The aim is to plan the attainment of TAs by allocating resources among the TAs with a view to achieving maximized overall customer satisfaction. Taking into account the technical and resource constraints, and the impact of the correlation among TAs, the operational QFD planning with resource allocation is formulated as a linear program and solved by a heuristics-combined Simplex Method. An overall procedure is presented to help a design team to implement this QFD design planning with resource allocation in practice. This model can bridge the gap and conflicts between the design targets at the strategic level, and resource allocations in the part deployment and operational process planning level.

Ethical conflicts reported by certified registered rehabilitation nurses.

The purpose of this study was to identify the types of ethical conflict reported by certified registered rehabilitation nurses (CRRNs) and their relationship to demographic, educational, and practice-setting variables. Ethical conflicts expressed by CRRNs in active practice in Maryland, Virginia, and the District of Columbia were analyzed according to four themes. Disagreements about medical or institutional practice, patients' rights, and payment issues were the most frequent practice contexts for ethical conflicts, reflecting these nurses' considerable underlying concerns about resource allocation in rehabilitation practice. Participants believed that 60% of the ethical conflicts were resolved, frequently through discussions with other team members and patients' family members. Ethics committees and consultants were used infrequently. There were no statistically significant relationships between the kinds of conflicts or their resolution and the participants' demographic, educational, and practice-setting variables.

On practical resource allocation for production planning and scheduling with period overlapping setups

Capacity requirements planning is normally based on long-term demand forecasts and part type mix estimates. In the execution of a production plan, it must often be recognized that the capacity assumptions previously made are no longer valid. This is because the part type mix, the operator or machine availability, or the existence of additional resources has changed. This may lead to underload as well as to overload situations for particular time periods. This paper presents a mixed 0–1 model and outlines a practical algorithm to schedule the production quantities. Our aproach takes into account all information available on the shop-floor level, such as: machine availability over the planning horizon, unit processing times for the part types, minor setup times (i.e., machine setups required when changing part types that belong to the same family), major setup times (i.e., machine setups required when changing part types that belong to different families), storable and non-storable resource availability and consumption, part type demand over the planning horizon, and bounds on production rate and backlogging. Furthermore, the model accounts correctly for costs corresponding to period overlapping setups. Also, the application of the model in some case studies is reported.