Low-priority Users Research Articles

Priority-Based Resource Scheduling in Hybrid-Access LTE Femtocell

Femtocell technology is an emerging solution that is promising for improving indoor coverage problems and enhancing cell capacity. In a femtocell network, the overall system performance depends on the access method utilized, which specifies whether a specific user equipment can connect to the femtocell network. Three access methods are defined for long-term evolution (LTE) femtocell networks: open access, closed access and hybrid access. For fair and effective use of resources, hybrid access is preferred. Because some of the resources are shared among nonregistered users, it is essential to regulate their scheduling schemes. This study investigates resource scheduling for femtocell networks in hybrid access mode, which gives preferential access to the high-priority traffic of nonsubscribers. High-priority traffic metric (THP) is calculated for high-priority users, and low-priority traffic metric (TLP) is calculated for low-priority users. Then, individual sorted lists are formed for (THP) and (TLP). Nonsubscribers from the (THP) list are allocated initially, after which UEs from the (TLP) list are chosen for allocation based on resource availability, thereby increasing the overall average throughput of high-priority users in a network.

Increasing public safety broadband network resiliency through traffic control

Long Term Evolution (LTE)-based cellular networks are being deployed around the world to provide public safety with enhanced capabilities and access to broadband technology. In the United States, the First Responder Network Authority (FirstNet) is on the verge of deploying a nationwide network called the National Public Safety Broadband Network (NPSBN). Commercial networks typically aim at maximizing network capacity, i.e. the aggregate data rate, in order to increase revenue. However, in public safety networks, coverage, not capacity, is paramount, especially during an outage when sites are down. Through traffic control and preemption, the service level of low-priority users is reduced or denied, freeing up resources to restore coverage to high-priority users, e.g. users responding to an incident. In this study, we examine the effect of outages on network coverage and throughput. As our main contribution, we propose three traffic-control schemes that exploit variable modulation and coding, a feature that LTE enhances with respect to its 3G predecessors. The schemes differ based on the proportion of low- and high-priority users preempted. We show that the network coverage can be restored significantly and we investigate the tradeoff between the three schemes. Finally, we perform sensitivity analysis to confirm the effectiveness of the schemes across a wide range of scenarios.

Scheduling for telemedicine traffic transmission over WLANs

The major disadvantage of the Enhanced Distributed Channel Access (EDCA, the contention-based channel access function of 802.11e) is that it is unable to guarantee priority access to higher priority traffic in the presence of significant traffic loads from low priority users. This problem is enhanced by the continuously growing number of multimedia applications and the popularity of Wireless Local Area Networks (WLANs). Hence, solutions in scheduling multimedia traffic transmissions need to take into account both the Quality of Service (QoS) requirements and the Quality of Experience (QoE) associated with each application, especially those of urgent traffic, like telemedicine, which carries critical information regarding the patients’ condition. In this work, we propose an easy-to-implement token-based and self policing-based scheduling scheme combined with a mechanism designed to mitigate congestion. Our approach is shown to guarantee priority access to telemedicine traffic, to satisfy its QoS requirements (delay, packet dropping) and to offer high telemedicine video QoE while preventing bursty video nodes from over-using the medium.

Modeling and Analysis of Non-Orthogonal MBMS Transmission in Heterogeneous Networks

Broadcasting/multicasting is an efficient mechanism for multimedia communications due to its high spectrum efficiency, which achieves point-to-multipoint transmission on the same radio resources. To satisfy the increasing demands for multimedia broadcast multicast service (MBMS), we present a power domain non-orthogonal MBMS transmission scheme in a K-tier heterogeneous network (HetNet). Firstly, the system model, usage scenarios, and fundamentals of the presented scheme are discussed. Next, a tractable framework is developed to analyse the performance of non-orthogonal MBMS transmission, by using stochastic geometry. Based on this framework, the analytical expressions for the signal-to-interference-plus-noise ratio (SINR) coverage probability, average number of served users, and sum rate are derived. Furthermore, synchronous non-orthogonal MBMS transmission to further improving the system performance is also studied. The results demonstrate that non-orthogonal MBMS transmission can achieve better performance than the conventional one, in which non-orthogonal multirate one can fully utilize channel conditions to achieve a significant rate gain, while non-orthogonal multi-service one can efficiently use power resources to guarantee the quality of service (QoS) of high priority users, and also provide services for low priority users simultaneously.

Adaptive Service Rate and Vacation Length for Energy-Efficient HeNB Based on Queueing Analysis

To improve the energy efficiency of small-cell networks, in this paper, we analyze the operating procedure of home base stations, i.e., Home evolved Node B (HeNB), in femtocells, by introducing an MAP/PH/1/k queueing model. In this analytical model, the HeNB's power on/off is represented as the alternative service and vacation periods. In addition, the hybrid-access mode defined in Third-Generation Partnership Project (3GPP) Release 9 is considered, which involves both high-priority and low-priority users. Based on the analytical results, an adaptive service rate and vacation length (ASV) method is proposed to maximize the HeNB's energy efficiency while satisfying its quality-of-service (QoS) requirements, such as blocking probability and user waiting time. Simulation results demonstrate that the proposed ASV method is more effective in improving energy efficiency compared with its counterpart.

Biomedical nemesis? Critical deliberations with regard to health and social care integration for social work with older people

This article questions ongoing moves towards integration into health care for social work with older people in the United Kingdom. While potentially constructing clearer pathways to support, integration risks reducing welfare provisions for a traditional low priority user group, while further extending the principles of privatisation. Integration models also understate the ideological impact of biomedical perspectives within health and social care domains, conflate roles and undermine the potential positive role of ‘holistic’ multi-agency care. Constructive social work for older people is likely to further dilute within aggressive integrated models of welfare, which will be detrimental for meeting many of the complex needs of ageing populations.

Energy Efficiency Versus Performance in Cognitive Wireless Networks

Energy efficiency is a critical issue in wireless networks, not only due to the technological limitations on energy supplies, but also due to the environmental impact caused by the information and communication technologies. This work discusses performance tradeoffs related to the energy efficiency, providing insightful results on the intricate relationship between system parameters. We propose a new parametrization to study a network in which users with different priorities to access the network resources can interfere and cooperate among themselves. A non-cooperative model is analyzed under three different spectrum sharing schemes, and we discuss important tradeoffs between energy efficiency and throughput, and between energy efficiency and the spectrum sensing accuracy. We also propose a cooperative model, in which a low-priority user relays packets for the high-priority user as repayment for interference. The energy-throughput tradeoff is analyzed in the case of cooperation, both in the case of half-duplex and full-duplex relays with different degrees of self-interference cancellation.

Admission Control Over Internet of Vehicles Attached With Medical Sensors for Ubiquitous Healthcare Applications.

Wireless technologies and vehicle-mounted or wearable medical sensors are pervasive to support ubiquitous healthcare applications. However, a critical issue of using wireless communications under a healthcare scenario rests at the electromagnetic interference (EMI) caused by radio frequency transmission. A high level of EMI may lead to a critical malfunction of medical sensors, and in such a scenario, a few users who are not transmitting emergency data could be required to reduce their transmit power or even temporarily disconnect from the network in order to guarantee the normal operation of medical sensors as well as the transmission of emergency data. In this paper, we propose a joint power and admission control algorithm to schedule the users' transmission of medical data. The objective of this algorithm is to minimize the number of users who are forced to disconnect from the network while keeping the EMI on medical sensors at an acceptable level. We show that a fixed point of proposed algorithm always exists, and at the fixed point, our proposed algorithm can minimize the number of low-priority users who are required to disconnect from the network. Numerical results illustrate that the proposed algorithm can achieve robust performance against the variations of mobile hospital environments.

Near-Optimal Downlink Precoding for Two-Tier Priority-Based Wireless Networks

In this paper, we study a two-tier priority-based wireless cellular network in which the primary base station (BS) has multiple antennas and the other terminals have a single antenna. We assume that we have two classes of users: high priority users and low priority users. We consider a rate maximization problem of the low priority users under signal-to-interference-plus-noise-ratio constraints on the high priority user to guarantee a certain quality-of-service for the high priority user. Since the interference due to the low priority users which communicate with each other via direct transmission may severely degrade the performance of the high priority user, we propose a BS-aided two-way relaying approach in which the BS helps relay the low priority users' signals instead of allowing them to communicate with each other via a direct path between them. In addition, an algorithm to find a near-optimal beamforming solution at the BS is proposed. The asymptotic results in the high power regime are derived to verify the average sum rate performance in the proposed scheme. Finally, based on some selected numerical results, we show that the proposed scheme outperforms the direct transmission scheme over a wide transmit power range.

A tale of two rivers: Pathways for improving water management in the Jordan and Colorado River basins

This paper considers two river systems that have been subject to significant development during the last 60 years: the Jordan River in the Middle East and the Colorado River in the western United States. Both play major roles in serving the demands of growing populations, and climate change models predict both semi-arid to arid regions to become hotter and/or drier in the future. The Jordan River basin, shared by five nations, is already experiencing a critical level of environmental damage. Its lower stretch is practically a sewage canal with less than 10% of its natural base-flow. Due to its unique historical, religious and environmental role, restoration efforts have gained momentum and wide public support. In the Colorado River Basin, water law is characterized by the “Law of the River” and water use is managed through regional allocation constraints. The Colorado River, shared by seven U.S. states and Mexico, is highly managed and over-allocated. Shortage declarations have serious implications for low priority users, with the Central Arizona Project being among the lowest. This makes large population centers and agricultural users vulnerable to curtailment of deliveries. We argue that there are common factors with respect to the policy and management options of these two basins that may provide insights into the similarities and divergences of their respective future pathways. These factors are: regional water supply and demand pressures, water governance, transboundary issues and demand for environmental flows. With a particular focus on the Israel and Arizona portions of these respective river basins, we address synergies and tradeoffs between groundwater and surface water usage, sectoral allocation strategies, public vs. private water ownership and legality, transboundary sharing, technical options for addressing growing regional water scarcity, and economic considerations. Difficult and bold decisions are required in both regions.

Dynamic Spectrum Access with Prioritized Secondary Users in Cognitive Radio Networks

Dynamic Spectrum Access (DSA) has got tremendous attention and research, but most of the existing dynamic spectrum access schemes assume that all Secondary Users (SUs) are of the same priority. In this paper, prioritized SU traffic is considered. The SU traffic in the system is classified into two priority classes based on Quality of Service (QoS) requirements, namely delay-sensitive SU and delay-insensitive SU. Considering that the higher priority users can preempt the transmission of the lower priority users, we develop the analytical model by applying Preemptive Repeat Priority (PRP) M/G/1 queueing theory. Based on the model, we evaluate the overall system time of the prioritized SUs and separately design different spectrum access strategies for them. The results demonstrate that the proposed dynamic spectrum access schemes can simultaneously reduce the overall system time of SUs with different priority classes significantly.

Distributed Priority-Based Power and Admission Control in Cellular Wireless Networks

A distributed priority-based power and admission control algorithm is presented to address the priority-based gradual removal problem in cellular wireless networks. We assume that there exist two classes of priority for users (high-priority users versus low-priority users) and minimal number of low-priority users should be gradually removed, subject to the constraint that all high-priority users are supported with their target signal-to-interference-plus-noise ratios (SINRs) which is assumed feasible. In our proposed algorithm, each high-priority user rigidly tracks its target-SINR by employing the conventional target-SINR tracking power control algorithm, and each transmitting low-priority user tracks its target-SINR as long as its required transmit power is below a threshold, otherwise it temporarily removes itself. Each removed low-priority user resumes its transmission if the required transmit power to reach its target-SINR goes below a given threshold which is different from the former. Of these two thresholds, whose values are analytically obtained, the former is provided by the base station and the latter is obtained in a distributed manner as a function of the former. We show that the distributed power-update function corresponding to our proposed algorithm has at least one fixed-point which is not unique in general. The convergence point, where our proposed algorithm potentially converges to, depends on initial transmit power levels of users. We also show that our proposed algorithm, at each of its fixed-points, not only provides all high-priority users with their (feasible) target-SINRs but also guarantees that no low-priority user is erroneously removed (i.e., no additional low priority user can be supported along with currently supported users). Furthermore, for the special case of tracking a common target-SINR by all low-priority users, we show that our proposed algorithm minimizes the outage-ratio of low-priority users subject to zero-outage-ratio of high-priority users. Simulation results confirm our analytical developments and show that our proposed priority-based power and admission control algorithm solves the priority-based gradual removal problem efficiently.

SRAG: A Priority-Based Rate Adaptation Scheme Using Game Theory for Vehicular Networks

Rate adaptation is critical to the system performance of Wireless Local Area Networks (WLANs). Existing rate adaptation schemes mostly make use of packet statistics or the signal strengths of received packets to adapt transmission rates, regardless of the packet priorities. In this paper, we first find out that it is beneficial for rate adaptation schemes to consider packet priorities when adapting transmission rates. We then propose a novel priority-based rate adaptation scheme for vehicular networks named SRAG (Stackelberg Rate Adaptation Game) which jointly considers channel conditions and packet priorities using game theory. In SRAG, rate adaptation is modeled as a game which consists of different priorities of users and each user tries to select an optimal transmission rate that maximizes its utility regardless of others' utilities. SRAG adopts a Stackelberg game model to regulate behaviors of self-interested users and gives priority to high priority users in order to achieve better overall performance. Extensive ns-2 simulations demonstrate that SRAG can provide much better performance for high priority users than existing rate adaptation schemes, while maintaining good performance for low priority users.

Dynamic spectrum allocation with admission control based on cognitive radio for QoS support in multiple wireless network

Cognitive radio is an emerging technology in wireless access, aimed at vastly improving the way radio spectrum is utilized. In this article, we investigate the performance improvement gained by applying cognitive radio to a multiple wireless service providers (WSPs). We consider several WSPs and two types of users: primary (licensed) and secondary (unlicensed) users. Two different schemes are proposed for unlicensed users to manage their handoff. These two schemes are different in the sense that one allows to each WSP to give more priority to his own unlicensed users by dropping low priority users, while the other does not allow that. The system is modeled by a Markov process, with continuous time and finite state space. Due to the very large number of states, we propose a robust method to approximate the stationary probability distribution vector of Markov process. Based on this approximation, we develop several performance metrics, blocking and dropping probabilities for both kinds of unlicensed users. Numerical results show that this approximation is very close to the exact solution. Finally, we show that spectrum utilization of cognitive users increases with the proposed schemes especially in medium and high traffic.

Token- and Self-Policing-Based Scheduling for Multimedia Traffic Transmission Over WLANs

The worldwide popularity of wireless local area networks (WLANs) calls for efficient solutions in scheduling multimedia (voice, data, and video) traffic transmissions. Enhanced distributed channel access (EDCA), which is the contention-based channel access function of IEEE 802.11e, is unable to guarantee priority access to higher priority traffic in the presence of significant traffic loads from low-priority users. In this paper, we propose the use of a token- and self-policing-based scheduling scheme, which not only addresses this problem but also prevents bursty video nodes from overusing the medium and tackles the problem of idle time due to large transmission opportunities (TXOPs).

Potential Game Approach for Spectrum Sharing in Distributed Cognitive Radio Networks

In a spectrum sharing system, lower-priority users are allowed to spatially reuse the spectrum allocated to higher-priority users as long as they do not disrupt communications of the latter. Therefore, to improve spectrum utilization, an important requirement for the former users is to manage the interference and ensure that the latter users can maintain reliable communications. In the present paper, a game theoretic framework of joint channel selection and power allocation for spectrum sharing in distributed cognitive radio networks is proposed. First, a utility function that captures the cooperative behavior to manage the interference and the satisfaction level to improve the throughput of the lower-priority users is defined. Next, based on the defined utility function, the proposed framework can be formulated as a potential game; thus, it is guaranteed to converge to a Nash equilibrium when the best response dynamic is performed. Simulation results show the convergence of the proposed potential game and reveal that performance improvements in terms of network throughput of the lower-priority users and outage probability of the higher-priority users can be achieved by the introduction of an adaptive coefficient adjustment scheme in the proposed utility function at the expense of the convergence to the Nash equilibrium.

Differentiated Backoff Strategies for Prioritized Random Access Delay in Multiservice Cellular Networks

In this paper, a novel prioritization mechanism for random access strategies in cellular networks is proposed. The proposed prioritized random access strategy sets different retransmission probabilities to users, depending on their priorities. First, a mathematical analysis method for simultaneously evaluating throughput and access delay, considering an infinite population model and different retransmission policies, is developed. Most of the previous related research has been done, considering both finite population and saturation conditions where all the nodes in the system always have a packet ready to be transmitted, and the transmission queue of each station is assumed to be always nonempty. This assumption is a good approximation for a local area network working at full capacity. However, in a cellular system, the assumptions of a finite population and every node in a cell always having a packet to transmit are not very realistic. Here, the analytical results consider a Poisson arrival process-which is more suitable for the traffic model in a cellular system-for the users in the cells. Then, considering slotted ALOHA as a random access strategy and the developed analysis method, the case where two different types of service exist (low-and high-priority users) is mathematically analyzed. With the proposed prioritized random access strategy, the average access delay achieved for the high priority users is always lower than that for the low-priority users. Additionally, a mathematical expression for the throughput is derived with and without service differentiation. Finally, two approaches for finding the optimum retransmission probabilities are developed; in the first approach, the number of backlogged packets is required, whereas a simpler and efficient alternative method requires only the knowledge of the mean new packet arrival rate. For the performance analysis, four of the most common backoff algorithms are considered: (1) Uniform (UB); (2) Binary Exponential (BEB); (3) Negative Exponential (XB); and (4) Geometric (GB).

A Mitigation Technique of High-Power MAI in the Multimedia Optical CDMA System with the Optical Power Selector

In this paper, we propose a mitigation system of high-level multiple access interference (MAI) for multimedia optical Code-Division Multiple-Access (CDMA) systems using the optical power selector (OPS). The proposed system can eliminate high-intensity MAI at the receiver for low-priority users. Moreover, the proposed system can reduce by half the required number of code sequences compared to the conventional scheme. As a result, the proposed system can increase the number of weights at the same code-length and, thus, obtain higher code spreading gain. We analyze performances of the proposed system and show that both high-priority users and low-priority users achieve lower bit error rates in comparison to the conventional scheme.

A hybrid priority-based video-on-demand resource sharing scheme

Video-on-demand (VoD) environments frequently batch video requests to decrease I/O demand and increase throughput. Since users may leave due to waiting too long, a good video scheduling policy has to consider not only the batch size, but also the user defection probabilities and waiting times. Moreover, a practical VoD resource sharing scheme should endeavor to provide some free streams to serve a high-priority clients requests immediately, since the high-priority clients might pay for the requested video. To tackle these problems, this work proposes a hybrid resource sharing model that integrates controlled multicasting and batching. The proposed hybrid model applies a bandwidth borrowing and reserving scheme to give high-priority clients a prompt service, while still providing low-priority clients with a reasonable service. Furthermore, a novel probability model-based scheduling policy is proposed to alleviate the user defection behavior and unfairness issue. Experimental results demonstrate that the proposed resource sharing scheme is effective and feasible in terms of blocking probability of high-priority clients, the defection probability, service delay time and fairness to low-priority users.

Quality of Preventive Care for Diabetes: Effects of Visit Frequency and Competing Demands

We sought to determine the association between timely receipt of diabetes-related preventive services and the longitudinal pattern of outpatient service use as characterized by a novel taxonomy that prioritized visits based on the Oregon State Prioritized Health Services List. We performed a cross-sectional analysis of mail survey and automated health care data for a population-based sample of patients with diabetes enrolled in a health maintenance organization in Washington State (N = 4,463). Outcomes included American Diabetes Association-recommended preventive services, including regular hemoglobin A1C (HbA1C) monitoring, retinal examination, and microalbuminuria screening. Patients with fewer than 8 visits during the 2-year study period were considered infrequent users, while patients with 8 or more visits were classified as lower-priority users if most visits were for conditions of relatively low rank on the Oregon list and as higher-priority users otherwise. After adjustment for social, demographic, and clinical factors, and depression, infrequent users had significantly reduced odds of receiving at least 1 HbA1C test (odds ratio [OR] = 0.35, 95% confidence interval [CI], 0.24-0.51), retinal examination (OR = 0.74, 95% CI, 0.63-0.86), and microalbuminuria screening (OR = 0.75, 95% CI, 0.58-0.96) relative to higher-priority users during the previous year. Lower-priority users also had relatively reduced odds of receiving at least 1 HbA(1C) test (OR = 0.59, 95% CI, 0.35-1.01), retinal examination (OR = 0.68, 95% CI, 0.56-0.84), and microalbuminuria screening (OR = 0.79, 95% CI, 0.57-1.09) despite attending a similar mean number of total visits as higher-priority users. Patients who attend relatively few outpatient visits or who attend more frequent visits for predominantly lower-priority conditions are more likely to receive substandard preventive care for diabetes.