Poor Fairness Research Articles

Optimal Allocation of Resources for the Integrated Medical Care and Elderly Care Model under Dynamic Monitoring

Aiming at the problems of poor fairness of resource allocation and long time-consuming allocation of traditional methods, a method of resource optimization allocation under dynamic monitoring of medical care combined with elderly care mode is proposed. The integrated medical and elderly care model is analyzed, the role of dynamic monitoring in the optimal allocation of resources in the integrated medical and elderly care model is discussed, and a general model for optimal allocation of medical and elderly resources based on the analysis results is established. Based on the criterion of “minimum variance of estimation error,” a combined prediction model is established to obtain the combined prediction results. The investment objects of the optimal allocation of resources in the elderly care model are clustered in advance by using the clustering method, and the investment objects of the optimal allocation of resources in the elderly care model are comprehensively evaluated by using the principal component analysis method. According to the actual results of the comprehensive evaluation, the improved whale algorithm is used to allocate pension resources reasonably, and the fairness and applicability of the allocation results are analyzed experimentally. The results show that the method proposed in this paper has strong rationality and can effectively realize the rational distribution of pensions.

A Deflection-Based Deadlock Recovery Framework to Achieve High Throughput for Faulty NoCs

Deadlock is a critical issue in faulty Networks-on-Chips (NoCs). Existing deadlock-free approaches on faulty NoCs suffer from low throughput and poor fairness when the network becomes oversaturated. This problem hinders their practical use as oversaturation scenarios are more frequent on faulty NoCs. To address this issue, a deflection-based deadlock recovery framework is proposed for higher oversaturation performance on faulty NoCs. First, we observe the low oversaturation performance of existing deadlock recovery approaches, and analyze the positive feedback loop that can amplify the negative impact of deadlocks and congestions, which necessitate handling both deadlocks and congestions in a deadlock recovery framework. Second, we propose a novel deadlock recovery framework, which includes an accurate, timely deadlock detection and a highly efficient deadlock recovery. Both the deadlock detection and recovery reduce the average packet traversal latency, thereby improving the average oversaturation throughput. Third, we propose a distributed implementation to make the entire network enter and exit the deflection mode, which is conducted by broadcasting special messages via a bufferless subnetwork. An average oversaturation throughput improvement of 1.1 ~ 8.1× over state-of-the-art approaches is achieved. In terms of fairness, the minimal oversaturation throughput is improved from near zero to half of the peak throughput.

The Determinants of Out-of-Pocket Expenditure in IBD Italian Patients. Results from the AMICI Survey.

Decision makers are used to consider Out-of-Pocket Expenditure (OOPE) within a health technology assessment framework in order to account for an indicator relying on the level of fairness and on the quality of care of a health system. In this paper, we provide estimates on the determinants of OOPE in Italy by using data coming from an observational cross-sectional study that enrolled a sample of 2526 patients suffering from inflammatory bowel diseases. We explore the association between OOPE and: (1) geographical location; (2) income effects; (3) performances in delivering healthcare. A regression model was used. Individuals’ age were in the range of 18–88 (mean 44 ± 14.55). Forty-six percent were females, 54% were married and 19% held a bachelor degree. Ninety-six percent of respondents declared an OOPE >0 whose mean value was €960 ± €950. Individuals belonging to low-income and low-performance regions were more likely to declare an OOPE >0 (99%). Regression findings suggest that increases in OOPE could be considered as a response from patients aiming to compensate for lacks and inefficiencies in the public healthcare offers. Policymakers should consider increases in OOPE in patients with Inflammatory Bowel Diseases (IBDs) as an indicator of poor quality of care and poor fairness.

Voting-Based Decentralized Consensus Design for Improving the Efficiency and Security of Consortium Blockchain

Since its emergence, blockchain technology has received great attention because of its advantages in terms of decentralization, transparency, traceability, and the ability to be tamper proof. These advantages help blockchain become a better option for fields, such as digital currency and information storage. Specifically, consortium blockchain is preferred by researchers because it provides a certain degree of access control and a supervisory mechanism. However, in real-world applications, blockchain platforms pervasively show bottlenecks, such as ultrahigh energy consumption, time inefficiency, low transaction throughput, vulnerability to targeted attacks, and poor fairness of user profits, which seriously influence the performance of this technology and thus hinder its development and adoption. In this article, we try to enhance the performance of blockchain platforms by optimizing the quality of its core module, known as the consensus algorithm. To do so, we introduce proof of assets and proof of reputation to design a voting-based decentralized consensus (VDC) algorithm for consortium blockchain. Combined with the verifiable random function (VRF), VDC realizes better fairness of user profits and time efficiency with acceptable energy consumption and without sacrificing security. The simulation results show that the proposed algorithm achieves a faster consensus process and better user fairness than existing algorithms while still maintaining a negligible energy cost and adequate security.

Length of stay control: Is it a fair inventory management strategy in hotel market?

According to past revenue management (RM) research, length of stay control (LOSC) plays a significant role in building effective RM systems and increasing revenues in the hotel industry. While LOSC has been widely implemented in the hotel’s online booking systems, little attention has been paid to this important non-pricing RM practices. Thus, the current study aims to provide a holistic view of customers’ perceptions toward hotel’s LOSC practice. In particular, this study (1) investigates the impact of LOSC practice on customers’ perceived fairness and subsequent behaviors and (2) tests the moderating role of customers’ membership status on perceived fairness. A between-subjects factorial design and partial least squares structural equation modeling (SEM) analysis were employed to test the structured relationships. Research findings demonstrate that customers perceive LOSC as unfair, such poor fairness perceptions leading to negative word-of-mouth and a decrease in willingness to book. Hotels’ loyalty program members are likely to perceive LOSC as much more unfair than those who are not. The current study is the first study to reveal the critical roles of hotels’ LOSC practice and loyalty membership on customers’ perceived fairness and subsequent behavior intentions.

Short trading cycles: Paired kidney exchange with strict ordinal preferences

I study kidney exchange with strict ordinal preferences and with constraints on the lengths of the exchange cycles. Efficient deterministic mechanisms have poor fairness properties in this environment. Instead, I propose an individually rational, ordinally efficient and anonymous random mechanism for two-way kidney exchange based on Bogomolnaia and Moulin’s (2001) Probabilistic Serial mechanism. Individual rationality incentivizes patient–donor pairs who are compatible with each other to participate in the exchange, thus increasing the overall transplantation rate. Finally, individual rationality, ex-post efficiency and weak strategyproofness are incompatible for any mechanism.

Urgency-Based Fair Scheduling for LTE to Improve Packet Loss and Fairness: Design and Evaluation

Classic scheduling algorithms for the LTE uplink in the literature may cause severe packet loss, poor fairness, and inefficient resource allocation. To alleviate packet loss, delay budget rather than channel condition plays a key factor in our proposed algorithm that allows the user equipment (UE) with the least left delay budget to be scheduled first. Besides, the UEs with fewer allocated resources can be served earlier to improve fairness. For reaching efficient resource utilization, our proposed algorithm further poses a constraint in sequential resource allocation. Via extensive simulations, we successfully demonstrate that our proposed algorithm significantly outperforms the closely related algorithms in terms of packet loss ratio and fairness index at the cost of raised end-to-end delay but still within the delay bound. For our proposed algorithm, it also gains improvement in throughput due to its reduction in the packet loss ratio and bounded relaxation in the end-to-end delay.

Opportunistic Spectrum Access with Dynamic Users: Directional Graphical Game and Stochastic Learning

This paper investigates the channel selection problem with dynamic users and the asymmetric interference relation in distributed opportunistic spectrum access systems. Since users transmitting data are based on their traffic demands, they dynamically compete for the channel occupation. Moreover, the heterogeneous interference range leads to asymmetric interference relation. The dynamic users and asymmetric interference relation bring about new challenges such as dynamic random systems and poor fairness. In this article, we will focus on maximizing the tradeoff between the achievable utility and access cost of each user, formulate the channel selection problem as a directional graphical game and prove it as an exact potential game presenting at least one pure Nash equilibrium point. We show that the best NE point maximizes both the personal and system utility, and employ the stochastic learning approach algorithm for achieving the best NE point. Simulation results show that the algorithm converges, presents near-optimal performance and good fairness, and the directional graphical model improves the systems throughput performance in different asymmetric level systems.

Optimising channel assignment to prevent flow starvation and improve fairness for planning single radio WMNs in built environments

Wireless mesh networks (WMNs) have many attractive characteristics, such as auto-configuration, self-management, and self-healing. With newer and farther reaching applications being developed in built environments, such as smart grids and intelligent transportation systems, users expect high quality of service and thus fairness is an important issue to be addressed. Channel assignment (CA) is the mechanism for allocating radio resources to the nodes and therefore plays a key role in managing fairness in WMNs. Fairness in WMNs depends on how wireless resources are allocated among the nodes. We examine interference models used in existing CA algorithms and find that CA algorithms using these models yield poor fairness because they only reflect local interference between a link and its interfering links. However, flow starvation is due to network wide interference (i.e. global) involving border links and middle links. We propose a novel anti-starvation channel assignment algorithm (ASCA) for planning single radio WMNs. Such ASCA algorithm leverages a new interference model that takes into account both local and global interference. Simulation results show the ASCA algorithm effectively alleviates flow starvation and improves fairness up to 62% compared with the best result from clique-based CA benchmarks. To the best of our knowledge, the proposed ASCA is the first one to optimise CA algorithms with consideration of both local and global interference.

Throughput Modeling of Distributed Reservation Protocol

To evaluate the performance of distributed medium access control (MAC) layer of emerging ultra wideband (UWB) and 60-GHz millimeter wave (mmWave) wireless personal area networks (WPANs) based on distributed reservation protocol (DRP) of ECMA-368 and ECMA-387 standards, we provide an analytical model for the probability distribution of steady state throughput as a function of the network dimensions size, number of devices, antenna beamwidth, transmission range, bit error rate (BER), antenna disturbance rate (ADR), aggregation length, payload size, and incoming frame rate. Using this model, the optimal payload size is computed as an example of optimization problem. We also propose a formula for the starvation and fairness and using them, we found a major flaw in DRP, i.e., its poor fairness. We develop a fair DRP (FDRP) protocol and modify our model to cover it. The models are evaluated by simulation of ad-hoc network scenarios and results show that the average error is less than 2 percent.

How penalty leads to improvement: A measurement study of wireless backoff in IEEE 802.11 networks

Despite much theoretical work, different modifications of backoff protocols in 802.11 networks lack empirical evidence demonstrating their real-life performance. To fill the gap we have set out to experiment with performance of exponential backoff by varying its backoff factor. Despite the satisfactory results for throughput, we have witnessed poor fairness manifesting in severe capture effect. The design of standard backoff protocol allows already successful nodes to remain successful, giving little chance to those nodes that failed to capture the channel in the beginning. With this at hand, we ask a conceptual question: Can one improve the performance of wireless backoff by introducing a mechanism of self-penalty, when overly successful nodes are penalized with big contention windows? Our real-life measurements using commodity hardware demonstrate that in many settings such mechanism not only allows to achieve better throughput, but also assures nearly perfect fairness. We further corroborate these results with simulations and an analytical model. Finally, we present a backoff factor selection protocol which can be implemented in access points to enable deployment of the penalty backoff protocol to consumer devices.

Improving Fairness without Outage Performance Deterioration in Selection Cooperation

The traditional selection cooperation scheme selects the relay with best instantaneous receive signal-to-noise ratio to forward the message and achieves good outage performance, which may however cause poor fairness among relays. In this letter, we propose two practical selection cooperation schemes in Decode-and-Forward (DF) fashion to improve the fairness of relay selection. Numerical results suggest that both of the proposed schemes can achieve fairness close to the strict fairness scheme without outage performance deterioration. It is also validated that these schemes have lower complexities than traditional ones and therefore are practical for real networks.

QTCP: Improving Throughput Performance Evaluation with High-Speed Networks

High-speed TCP (HSTCP) is one of the several popular variants of TCP aimed at the optimization of TCP for high-speed networks. Like all other variants, HSTCP also fails to take full shared bandwidth utilization and offers low throughput rate, high packet loss rate and poor fairness. To overcome these problems, a new adaptive congestion control algorithm with high-speed delay product network named, the Quick Transport Control Protocol (QTCP) has been designed through this research. The basic idea of QTCP has been inspired by the HSTCP and CUBIC, which supported to enhance the algorithm. Three main component of QTCP window control algorithm are α phase, β phase and multiplicative decrease. An experimental setup was designed for the evaluation of QTCP. In this experiment, the QTCP was evaluated based on average throughput and fairness between multiple flows with the same RTT. QTCP performs tuning of the sender side modification based on slow start and AIMD algorithms of HSTCP and CUBIC. QTCP provides higher throughput and enhanced fairness as compared to most of the currently available TCP variants for high-speed networks. The improved throughput and fairness remains intact even in the presence of background traffic. NS-2 simulator-based results with different configurations are presented, discussed in detail, and evaluated with other popular algorithms.

Analysis, Simulation, and Implementation of VCP: A Wireless Profiling

Every congestion-control protocol operating in wireless networks is potentially faced with two major challenges of performance degradation. These sources are: 1) the coupling of fairness and efficiency; and 2) not properly differentiating between congestion-caused loss associated with network buffering and error-caused loss associated with fading effects. In this paper, we provide a Variable-structure Congestion-control Protocol (VCP)-based cross-layer framework of congestion control that can address both challenges noted. As a part of our framework, we introduce a loss differentiation heuristic algorithm that can be used with a variety of congestion-control protocols. Then, using analysis, simulation, implementation, and emulation, we profile the performance of a number of congestion-control alternatives in wireless networks. We describe the first implementation of VCP as a collection of loadable kernel modules along with fine-tuned implementations of XCP and TCP / AQM + ECN in Linux. We utilize NS2 as our simulation tool and a wired Linux testbed emulating wireless link effects as our experimental tool. We implement a finite-state Markov chain in both NS2 and our testbed in order to model error-caused loss over wireless links. We further use link-layer forward error correction (FEC) codes on a per-packet basis to compensate against such loss. Our profiling results demonstrate that VCP equipped with our loss differentiation heuristic and link-layer FEC represents a well-performing yet practical alternative of wireless congestion control. We also identify some of the shortcomings of VCP, including its oscillatory behavior in the presence of link estimation errors and poor fairness characteristic in multibottleneck networks.

Capacity and fairness tradeoff in multiuser scheduling system with reduced feedback

Multiuser diversity is an effective technique to increase the capacity of wireless networks. However, the poor fairness among the mobile stations (MSs) and the heavy feedback load as the number of MSs increases are the main problems in implementing multiuser diversity. We propose a new scheduling scheme with opportunistic feedback. Specifically, the schedule for multiple users is based on two different criteria such as the absolute SNR and the normalized SNR. Simulation result shows that the tradeoff between capacity and fairness can be fine-tuned through the proposed scheduling scheme.

Parallel Proportion Fair Scheduling in DAS with Partial Channel State Information

A parallel multiplexing scheduling (PMS) scheme is proposed for distributed antenna systems (DAS), which greatly improves average system throughput due to multi-user diversity and multi-user multiplexing. However, PMS has poor fairness because of the use of the “best channel selection” criteria in the scheduler. Thus we present a parallel proportional fair scheduling (PPFS) scheme, which combines PMS with proportional fair scheduling (PFS) to achieve a tradeoff between average throughput and fairness. In PPFS, the “relative signal to noise ratio (SNR)” is employed as a metric to select the user instead of the “relative throughput” in the original PFS. And only partial channel state information (CSI) is fed back to the base station (BS) in PPFS. Moreover, there are multiple users selected to transmit simultaneously at each slot in PPFS, while only one user occupies all channel resources at each slot in PFS. Consequently, PPFS improves fairness performance of PMS greatly with a relatively small loss of average throughput compared to PFS.

Enhanced Fair Scheduling for IEEE 802.11e Wireless LANs

As wireless LANs are gaining popularity, the demand for supporting multimedia and QoS-sensitive applications becomes more important than before. Although enhancements to the legacy IEEE 802.11 MAC to support QoS mechanisms have been proposed, they suffer from unfair allocation of bandwidth between high and low priority traffic. We propose a distributed enhanced fair scheduling (EFS) scheme that can conquer the above problem. With a fast backoff mechanism in the backoff timer decrement state and by dynamically adjusting backoff intervals according to the network load, we can enhance the performance of the EFS. We have evaluated the performance of the EFS through simulation. Experimental results show that the proposed EFS has better throughput performance than DFS by 13%, lower average MAC delay than DFS by 6% and the two have nearly equal fairness. Although the enhanced distributed channel access (EDCA) in IEEE 802.11e has better throughput and delay performance than EFS and DFS, it has very poor fairness. The contention free burst (CFB) mechanism in EDCA is the main factor that results in good throughput performance, lower average MAC delay and poor fairness. Our EFS is very suitable for applications that need strict fair bandwidth allocation, such as pay services.

Fairness enforcement in switch on event multithreading

The need to reduce power and complexity will increase the interest in Switch On Event multithreading (coarse-grained multithreading). Switch On Event multithreading is a low-power and low-complexity mechanism to improve processor throughput by switching threads on execution stalls. Fairness may, however, become a problem in a multithreaded processor. Unless fairness is properly handled, some threads may starve while others consume all of the processor cycles. Heuristics that were devised in order to improve fairness in simultaneous multithreading are not applicable to Switch On Event multithreading. This paper defines the fairness metric using the ratio of the individual threads' speedups and shows how it can be enforced in Switch On Event multithreading. Fairness is controlled by forcing additional thread switch points. These switch points are determined dynamically by runtime estimation of the single threaded performance of each of the individual threads. We analyze the impact of the fairness enforcement mechanism on aggregate IPC and weighted speedup. We present simulation results of the performance of Switch On Event multithreading. Switch On Event multithreading achieves an average aggregate IPC increase of 26% over single thread and 12% weighted speedup when no fairness is enforced. In this case, a sixth of our runs resulted in poor fairness in which one thread ran extremely slowly (10 to 100 times slower than its single-thread performance), while the other thread's performance was hardly affected. By using the proposed mechanism, we can guarantee fairness at different levels of strictness and, in most cases, even improve the weighted speedup.

Tradeoffs Between Low Complexity, Low Latency, and Fairness With Deficit Round-Robin Schedulers

Deficit Round-Robin (DRR) is a scheduling algorithm devised for providing fair queueing in the presence of variable length packets. The main attractive feature of DRR is its simplicity of implementation: in fact, it can exhibit O(1) complexity, provided that specific allocation constraints are met. However, according to the original DRR implementation, meeting such constraints often implies tolerating high latency and poor fairness. In this paper, we first derive new and exact bounds for DRR latency and fairness. On the basis of these results, we then propose a novel implementation technique, called Active List Queue Method (Aliquem), which allows a remarkable gain in latency and fairness to be achieved, while still preserving O(1) complexity. We show that DRR achieves better performance metrics than those of other round-robin algorithms such as Pre-Order Deficit Round-Robin and Smoothed Round-Robin. We also show by simulation that the proposed implementation allows the average delay and the jitter to be reduced.