Fair Resource Allocation Research Articles

Error Estimate and Fairness in Resource Allocation With Inaccurate Information Sharing

In resource allocation systems, inaccurate information sharing situations are such that users can be aware, up to a small error, about the other users’ demands and the available global resource (which can be insufficient to meet the overall demand). Consequently, given an allocation rule, users can predict an allocation that will not necessarily coincide with the actual one. In this letter, we provide an estimation of the error for a number of allocation rules and compare their robustness in inaccurate information sharing settings.

Wireless Powered ALOHA Networks With UAV-Mounted-Base Stations

In this letter, we study wireless powered communication networks (WPCNs) with base stations (BSs) mounted on unmanned aerial vehicles (UAVs). For implementation simplicity and uncoordinated access, the energy harvesting (EH) users (EHUs) employ slotted ALOHA to transmit information at a fixed rate to a common UAV-mounted BS. The UAV flying along a circular trajectory facilitates a line of sight (LoS) between the BS and each EHU, and also mitigates the adverse double near-far effect as it periodically comes close to the EHUs. Due to the periodicity of the LoS channels, the channel can be tracked without performing energy-costly channel estimation, and the channel attenuation can be compensated to avoid channel outages. For such a WPCN, we optimize the UAV radius, the channel access probability, and the rate of each EHU to enable proportionally fair resource allocation. Our solution reveals that, when a certain UAV altitude is exceeded, proportional fairness is attained when the UAV is in the hovering mode.

A moderated mediation model of the relationship between organizational justice and turnover intention

PurposeThe purpose of this study is to examine the mediating role of organizational identification (OI) on the relationship between organizational justice (OJ) and turnover intention (TI), as well as the moderating role of psychological contract fulfillment (PCF) in those relationships.Design/methodology/approachData were collected from 339 employees of a financial institution in Turkey. Regression analyses were conducted to investigate a moderated mediation model.FindingsThis study found that OI was partially mediated the relationship between OJ and TI. The results also indicated that the indirect effect of OJ on TI through OI was moderated by PCF.Research limitations/implicationsThe generalizability of the findings is limited. As this study is cross-sectional, causal inferences cannot be inferred regarding the hypothesized relationships.Practical implicationsTo reduce TI, organizations should ensure the fair allocation of resources and rewards among employees. Moreover, organizations should pay attention to the expectations of employees and the promises made to them in an attempt to fulfill psychological contract obligations.Originality/valueThis study explores the mediating role of OI in the relationship between OJ and TI. In addition, this research sheds light on the moderating role of PCF in this mediation model.

Neuro-Fuzzy based Call Admission Control for next Generation Mobile Multimedia Networks

As the demand of the mobile users are increasing day by day, wireless/mobile multimedia networks still need advancement in terms of, reliable traffic performance, link availability, efficient bandwidth utilization, and user mobility, that can attain extremely consistent wireless communication and data transmission over the networks. Due to the emerging demand of multimedia services a high-speed network and call admission control (CAC) scheme is required, which not only guarantees the quality of services (QoS) for new and handoff calls but also results in optimum resource utilization in bursty traffic network environments. The main objective of this integrated neural fuzzy based CAC scheme is to improve QoS with decent resource allocation, such that it minimizes the probability of call dropping and call blocking in mobile multimedia networks. The proposed neural fuzzy CAC scheme is a hybrid approach that integrates the semantic rule ability of fuzzy logic (FL) controller and self-training capability of a neural network (NN) which is further enhanced to construct an efficient computational model for traffic control and fair radio resources allocation for new calls and handoff calls. The simulation results conclude that a neural fuzzy based CAC can achieve minimal call dropping probabilities and maximum resource utilization in high-speed networks as compared to fuzzy logic based CAC and conventional CAC or existing CAC schemes

Estimating local need for mental healthcare to inform fair resource allocation in the NHS in England: cross-sectional analysis of national administrative data linked at person level.

Equitable access to mental healthcare is a priority for many countries. The National Health Service in England uses a weighted capitation formula to ensure that the geographical distribution of resources reflects need. To produce a revised formula for estimating local need for secondary mental health, learning disability (intellectual disability) and psychological therapies services for adults in England. We used demographic records for 43 751 535 adults registered with a primary care practitioner in England linked with service use, ethnicity, physical health diagnoses and type of household, from multiple data-sets. Using linear regression, we estimated the individual cost of care in 2015 as a function of individual- and area-level need and supply variables in 2013 and 2014. We sterilised the effects of the supply variables to obtain individual-need estimates. We aggregated these by general practitioner practice, age and gender to derive weights for the national capitation formula. Higher costs were associated with: being 30-50 years old, compared with 20-24; being Irish, Black African, Black Caribbean or of mixed ethnicity, compared with White British; having been admitted for specific physical health conditions, including drug poisoning; living alone, in a care home or in a communal environment; and living in areas with a higher percentage of out-of-work benefit recipients and higher prevalence of severe mental illness. Longer distance from a provider was associated with lower cost. The resulting needs weights were higher in more deprived areas and informed the distribution of some 12% (£9 bn in 2019/20) of the health budget allocated to local organisations for 2019/20 to 2023/24.

Detecting Sybil nodes in stationary wireless sensor networks using learning automaton and client puzzles

A well-known harmful attack against wireless sensor networks (WSNs) is the Sybil attack. In a Sybil attack, WSN is destabilised by a malicious node which forges a large number of fake identities to disrupt network protocols such as routing, data aggregation, and fair resource allocation. In this study, the authors suggest a new algorithm based on a composition of learning automaton (LA) model and client puzzles theory to identify Sybil nodes in stationary WSNs. In the proposed algorithm, each node sends puzzles to its neighbours periodically during the network lifetime and tries to identify Sybil nodes among them, considering their response time (puzzle solving time). In this algorithm, each node equipped with a LA to reduce the communication and computation overhead of sending and solving puzzles. The proposed algorithm has been simulated using J-SIM simulator and simulation results have shown that the proposed algorithm can detect 100% of Sybil nodes and the false detection rate is about 5% on average. Also, the performance of the proposed algorithm has been compared to a wellknown neighbour-based algorithm through experiments and the results have shown that the proposed algorithm is significantly better than this algorithm in terms of detection and false detection rates.

A heuristic for fair dynamic resource allocation in overloaded OFDMA systems

OFDMA is a popular coding scheme for mobile wireless communications. In OFDMA, one must allocate the available resources (bandwidth and power) dynamically, as user requests arrive and depart in a stochastic manner. Several exact and heuristic methods exist to do this, but they all perform poorly in the “over-loaded” case, in which the user demand is close to or exceeds the system capacity. To address this case, we present a dynamic local search heuristic. A particular feature of our heuristic is that it takes fairness into consideration. Simulations on realistic data show that our heuristic is fast enough to be used in real-time, and consistently delivers allocations of good quality.

A Hierarchical Resource Allocation Scheme Based on Nash Bargaining Game in VANET

Due to the selfishness of vehicles and the scarcity of spectrum resources, how to realize fair and effective spectrum resources allocation has become one of the primary tasks in VANET. In this paper, we propose a hierarchical resource allocation scheme based on Nash bargaining game. Firstly, we analyze the spectrum resource allocation problem between different Road Side Units (RSUs), which obtain resources from the central cloud. Thereafter, considering the difference of vehicular users (VUEs), we construct the matching degree index between VUEs and RSUs. Then, we deal with the spectrum resource allocation problem between VUEs and RSUs. To reduce computational overhead, we transform the original problem into two sub-problems: power allocation and slot allocation, according to the time division multiplexing mechanism. The simulation results show that the proposed scheme can fairly and effectively allocate resources in VANET according to VUEs’ demand.

Improve MPTCP with SDN: From the perspective of resource pooling

Multipath TCP (MPTCP) is proposed by IETF to support concurrent multipath transmission between multihomed hosts. Resource pooling principle, which treats network as a single pooled resource, is applied in the design of MPTCP schemes, and provides guidelines for MPTCP's control to achieve resource utilization and fair resource allocation. However, randomized routing solution and load balancing without global network information in MPTCP have become obstacles to achieve these objectives, which is validated through our measurements. To address above problems, we propose S-MPTCP, which realizes coupling control to MPTCP connections in network based on SDN technology providing global network information. Leveraging collected topology information, a key parameter, expected throughput, is calculated for each subflow ensuring the efficiency and fairness in resource exploration and allocation, and according to it, routing and load balancing modules are improved. Under S-MPTCP's control, subflow's throughput will stabilize around its expected throughput, and meanwhile congestion can be alleviated effectively. Experimental results show that S-MPTCP achieves significant enhancement of bandwidth utilization and fair resource allocation, and the time needed for load balancing is shortened considerably.

A Game Theoretic Approach for Distributed and Coordinated Channel Access Control in Cooperative Vehicle Safety Systems

Fairness and efficiency are two key requirements that have to be guaranteed in channel resource allocation in cooperative vehicle safety systems. Existing channel access control strategies, however, rely on each individual node to adjust networking parameters independently according to its locally measured state information, thus leading to unfairness. Although some coordinated strategies have been proposed to resolve this issue, they pay little attention to the efficiency. In order to achieve the tradeoff between fairness and efficiency, in this paper, we propose a utility function in terms of inter-packet reception time required to capture the performance of consecutive successful packets' reception under various vehicle densities. A channel access control problem among vehicles is then formulated as a non-cooperation game model. This model utilizes a punishment function to penalize a node that monopolizes the channel resources and hence can enable nodes to coordinate with each other to achieve desired fairness and efficiency. Next, a distributed decision-making scheme for channel access control is designed. It adjusts transmission rate in a coordinated manner and can guide each node to reach a Pareto-optimal Nash equilibrium point. The experimental results validate that the proposed strategy can result in fair channel resource allocation and ensure high-tracking accuracy for each vehicle under dynamic traffic conditions.

Severity as a Priority Setting Criterion: Setting a Challenging Research Agenda

Priority setting in health care is ubiquitous and health authorities are increasingly recognising the need for priority setting guidelines to ensure efficient, fair, and equitable resource allocation. While cost-effectiveness concerns seem to dominate many policies, the tension between utilitarian and deontological concerns is salient to many, and various severity criteria appear to fill this gap. Severity, then, must be subjected to rigorous ethical and philosophical analysis. Here we first give a brief history of the path to today’s severity criteria in Norway and Sweden. The Scandinavian perspective on severity might be conducive to the international discussion, given its long-standing use as a priority setting criterion, despite having reached rather different conclusions so far. We then argue that severity can be viewed as a multidimensional concept, drawing on accounts of need, urgency, fairness, duty to save lives, and human dignity. Such concerns will often be relative to local mores, and the weighting placed on the various dimensions cannot be expected to be fixed. Thirdly, we present what we think are the most pertinent questions to answer about severity in order to facilitate decision making in the coming years of increased scarcity, and to further the understanding of underlying assumptions and values that go into these decisions. We conclude that severity is poorly understood, and that the topic needs substantial further inquiry; thus we hope this article may set a challenging and important research agenda.

Policy and Ethical Considerations for Widespread Utilization of Generic Orthopedic Implants.

In 2015, the United States spent $3.2 trillion on healthcare, representing 18% of the nation’s gross domestic product [1]. As prices continue to climb, physicians, healthcare policymakers, and industry leaders alike have sought varied means to lower costs while maintaining the quality of care. Coverage expansion, shifts toward bundled care payments, and the implementation of Medicare Payment Reform (Medicare Access and Children’s Health Insurance Program Reauthorization Act of 2015 [MACRA]) are indicative of shifting dynamics in the American healthcare system prioritizing outcomes, value, and cost-containment over the fee-for-service model [2], [3]. Orthopedic implant expenditures are considerable in the overall cost of care for surgical patients. The cost of total joint arthroplasty implants between 1996 and 2006 increased an estimated 130%. Implant and medical device costs comprise up to 60% of hospital reimbursements for primary procedures [4]. Most implants are proprietary in nature and vary substantially in their price and features depending on the industry manufacturer [5], [6], [7]. Control of implant costs is thus a necessary focus for cost containment in orthopedic surgery. To that end, as patents on many brand name implants begin to expire, “generic” implants present a unique opportunity to improve the value of orthopedic care. Although generic drugs have been used for decades in the pharmaceutical industry, the use of generic implants has only recently been considered in the field of orthopedic surgery [8], [9], [10]. In the pharmaceutical sector, an estimated $33 billion has been saved by Medicare in the United States through utilization of generic medications [11]. There could be potential for an analogous substantial reduction in healthcare expenditures via the use of generic orthopedic implants. There is some literature describing the favorable economic possibilities for use of generic orthopedic implants [9], [10], [12]. However, the ethical issues, policy implications, and potential unanticipated consequences of such a paradigm shift have not been investigated. This article discusses the pros and cons of generic implant usage from economic, clinical, and ethical perspectives.

Organizational justice and work stress: The mediating role of negative, but not positive, emotions

Organizational justice involves employees' perceptions of the fairness of resource allocation in an organization. The negative emotional impact of justice perceptions leads to an attitudinal and behavioral response by employees that can seriously affect the effectiveness of the organization. From organizational psychology, an attempt has been made to explain the possible relationship between inequity and well-being, conceptualizing organizational justice as part of the stress phenomenon. The purpose of this study was to examine whether emotions played a role as mediators in the relationship between organizational justice perceptions and work stress in a sample (N = 465) of employees who work in different Spanish organizations. Results indicated that emotions mediated the relationship between employees' justice perceptions and work stress. The mediation models of organizational justice perceptions (distributive, procedural and interactional) and work stress mediated by emotions were quite similar. In all three cases, the mediation role of emotions consists of a higher frequency of negative emotions. Moreover, the indirect effect of procedural justice through positive emotions was also statistically significant. The findings are discussed in order to suggest interventions and future research avenues.

Justice in Dementia Care Resource Allocation: How Should We Plan for Dementia Services?

Dementia care resources in Taiwan have not been allocated taking into account patients’ needs and the distance between service users and providers. The objective of this study was to use two newly developed indicators; profit willing distance (PWD) and tolerance limited distance (TLD), to profile the service availability and accessibility of the 22 administrative areas in Taiwan and facilitate justice-based resource allocation by the central government. The study employed secondary data analysis by using a geographic information system (GIS) and geocoding to identify distances between service users and providers. The study samples were drawn from the databank of the National Disability Eligibility Determination System and grouped by the acuteness of registrants’ needs. Both the PWD and TLD were found in 15 of the administrative areas, and neither was found in three areas (Penghu, Kinmen, and Lienchiang County). Either the PWD or TLD (but not both) were found in four areas (only have PWD: Hsinchu and Chiayi City; only have TLD: Yunlin and Taitung County). How the priorities should be set for dementia service allocation based on these findings was also addressed. We conclude that the indicators of PWD and TLD can add value to the policy decision-making process, help set priorities, and facilitate efficient and fair resource allocation by defining specifics of the resources needed.

QoS-Constrained Semi-Persistent Scheduling of Machine-Type Communications in Cellular Networks

The dramatic growth of machine-to-machine (M2M) communication in cellular networks brings the challenge of satisfying the quality of service (QoS) requirements of a large number of M2M devices with limited radio resources. In this paper, we propose an optimization framework for the semi-persistent scheduling of M2M transmissions based on the exploitation of their periodicity with the goal of reducing the overhead of the signaling required for connection initiation and scheduling. The goal of the optimization problem is to minimize the number of frequency bands used by the M2M devices to allow fair resource allocation of newly joining M2M and human-to-human communications. The constraints of the problem are delay and periodicity requirements of the M2M devices. We first prove that the optimization problem is NP-hard and then propose a polynomial-time heuristic algorithm employing a fixed priority assignment according to the QoS characteristics of the devices. We show that this heuristic algorithm provides an asymptotic approximation ratio of 2.33 to the optimal solution for the case where the delay tolerances of the devices are equal to their periods. Through extensive simulations, we demonstrate that the proposed algorithm performs better than the existing algorithms in terms of frequency band usage and schedulability.

Stable multi‐player evolutionary game for two‐choice resource allocation problems

The authors consider the problem of multi-player evolutionary game with two strategies and an arbitrary number of players. A randomised probabilistic access model is considered where the users randomly select the strategies. The strategies are a selection between two radio access technologies to receive service from. For a fair resource allocation between a number of users, the payoff function of each player is considered to be inversely proportional to the number of players choosing a strategy. It is valid for the radio access technology selection problem where resources are divided fairly between the users. The necessary and sufficient conditions for the existence and uniqueness of a mixed Nash equilibrium point of the game is provided. In addition, it is proved that the mixed Nash equilibrium point of the game is globally asymptotically stable and also evolutionarily stable strategy.

Optimal Transmission Scheduling in Small Multimodal Underwater Networks

We describe a scheduling protocol for multimodal networks of relatively limited size, whose nodes encompass various underwater communication technologies. For such a case, we show that significant improvement in the network operations is possible when the transmission schedule is set to jointly utilize all communication technologies. Our solution is based on per-technology time-division multiple access frames, whose time slots are determined optimally to maximize the overall channel utilization while preserving flow limitations and maintaining fairness in resource allocation. Our numerical simulations and experimental results for multimodal networks with several acoustic technologies show that, while maintaining a fair resource allocation, our scheduling solution provides both high throughput and low packet delivery delay.

Resource allocation in ICU: ethical considerations.

Increasing scarcity of resources on the background of ever improving medical care and prolonged life expectancy has placed a burden on all aspects of health care. In this article we examine the current problems with resource allocation in intensive care and question whether we can find guidance on appropriate resource allocation through ethical models. The problem of fair and ethical resource allocation has perpetually plagued health care. Recent work has looked at value for money, benefits of therapies and how we define futility, but these still fall victim to the same problems that classical schools of ethical thought have tried to tackle. Many ethical principles provide a framework on which to allocate resources to certain cohorts of patients, however, most appear too rigid to be fully and primarily utilized for intensive care admission. We suggest a collaboration of principles be applied to achieve a moral, ethical and common sense approach to this issue. Over resourcing and under resourcing is also suggested to be problematic for patients and healthcare workers alike.

A bibliometric analysis of comparative research on the evolution of international and Chinese ecological footprint research hotspots and frontiers since 2000

The ecological footprint (EF) methodology, which is a tool for evaluating the natural resource use level and regional carrying capacity, has been extensively used to measure the capacity to reach both an ecological supply and demand balance and a level of sustainable development. In this study, to systematically sort and analyse the distribution of EF research, its hot areas and the evolution of its fronts, papers with “ecological footprint” as the subject term in the Web of Science Core Collection Database and the China Knowledge Resource Integrated Database Core Journals since 2000 are visually analysed using CiteSpace. The characteristics of these papers, including the quantity trend, quality, author group, affiliated institution type and journal type, are summarized, and keyword co-appearance and paper co-citation knowledge maps are produced. The results show the following: (1) Chinese researchers have been closely following international research fronts and steadily improving their research results. (2) Hotspots such as carbon dioxide emissions, the carbon footprint (CF), water footprint (WF) and sustainable use have been receiving attention both in China and internationally. International researchers focus on hot topics such as public satisfaction, land and resource use, spatial equity and policy analysis. In comparison, Chinese researchers prefer to modify and improve relevant methods, such as the three-dimensional EF (3D EF) and footprint family methods. (3) The research frontier of EF is based on improving the EF accounting method, which is aimed at assessing and monitoring the relationship between ecology and the economic society on a multi-scale basis, establishing an index system that can evaluate the demand for natural resources and environmental pressure, and explore the issues of mechanisms of regional ecology resource allocation fairness, and market-led and government-led ecological governance efficiency.

An Effective Spectrum Handoff Based on Reinforcement Learning for Target Channel Selection in the Industrial Internet of Things.

The overcrowding of the wireless space has triggered a strict competition for scare network resources. Therefore, there is a need for a dynamic spectrum access (DSA) technique that will ensure fair allocation of the available network resources for diverse network elements competing for the network resources. Spectrum handoff (SH) is a DSA technique through which cognitive radio (CR) promises to provide effective channel utilization, fair resource allocation, as well as reliable and uninterrupted real-time connection. However, SH may consume extra network resources, increase latency, and degrade network performance if the spectrum sensing technique used is ineffective and the channel selection strategy (CSS) is poorly implemented. Therefore, it is necessary to develop an SH policy that holistically considers the implementation of effective CSS, and spectrum sensing technique, as well as minimizes communication delays. In this work, two reinforcement learning (RL) algorithms are integrated into the CSS to perform channel selection. The first algorithm is used to evaluate the channel future occupancy, whereas the second algorithm is used to determine the channel quality in order to sort and rank the channels in candidate channel list (CCL). A method of masking linearly dependent and useless state elements is implemented to improve the convergence of the learning. Our approach showed a significant reduction in terms of latency and a remarkable improvement in throughput performance in comparison to conventional approaches.