Low-priority Users Research Articles

Resource optimization-based network selection model for heterogeneous wireless networks

<p class="Abstract"><span lang="EN-US">The internet of things (IoT) environment prerequisite seamless connectivity for meeting real-time application requirements; thus, required efficient resource management techniques. Heterogeneous wireless networks (HWNs) have been emphasized for providing seamless connectivity with high quality of service (QoS) performance to provision IoT applications. However, the existing resource allocation scheme suffers from interference and fails to provide a quality experience for low-priority users. As a result, induce bandwidth wastage and increase handover failure. In addressing the research issues this paper presented the resource-optimized network selection (RONS) method for HWNs. The RONS method employs better load balancing to reduce handover failure and maximizes resource utilization through dynamic slot optimization. The RONS method assures tradeoffs between high performance to high priority users and quality of experience (QoE) for low priority users. The experiment outcome shows the RONS achieves very good performance in terms of throughput, packet loss, and handover failures in comparison with existing resource selection methods.</span></p>

Online Radio Access Technology Selection Algorithms in a 5G Multi-RAT Network

In today's wireless networks, a variety of Radio Access Technologies (RATs) are present. However, each RAT being controlled individually leads to suboptimal utilization of network resources. Due to the remarkable growth of data traffic, interworking among different RATs is becoming necessary to overcome the problem of suboptimal resource utilization. Users can be offloaded from one RAT to another based on loads of different networks, channel conditions and priority of users. We consider the optimal RAT selection problem in a Fifth Generation (5G) New Radio (NR)-Wireless Fidelity (WiFi) network where we aim to maximize the total system throughput subject to constraints on the blocking probability of high priority users and the offloading probability of low priority users. The problem is formulated as a Constrained Markov Decision Process (CMDP). We reduce the effective dimensionality of the action space by eliminating the provably suboptimal actions. We propose low-complexity online heuristics for RAT selection which can operate without the knowledge regarding the statistics of system dynamics. Network Simulator-3 (ns-3) simulations reveal that the proposed algorithms outperform traditional RAT selection algorithms under realistic network scenarios including user mobility.

Admission Control in Priority Queueing System With Servers Reservation and Temporal Blocking Admission of Low Priority Users

Admission Control in Priority Queueing System With Servers Reservation and Temporal Blocking Admission of Low Priority Users

Mathematical Analysis of Priority Bi-serial Queue Network Model

One of the most comprehensive theories of stochastic models is queueing theory. Through innovative analytical research with broad applicability, advanced theoretical models are being developed. In the present research, we would like to investigate at a queuing network model with low and high priority users and different server transition probabilities. The two service channels used in this study, <img src=image/13428051_01.gif> and <img src=image/13428051_02.gif>, are connected to the same server, <img src=image/13428051_03.gif>. Customers with low and high priorities are invited by the server <img src=image/13428051_04.gif>. The objective of the research is to design a model that helps in minimizing congestion in different systems. Poisson distribution is used to characterize both the arrival and service patterns. The functioning of this system takes place in a stochastic domain. The differential difference equations have been established, and the consistency of behaviour of the system has been examined. The generating function approach, the law of calculus, and a statistical formula are used to assess the model's performance. Numerical analyses and graphical presentations are used to show the model's outcomes. The results of the model are displayed graphically and through numerical analyses. This model can be used in a number of real situations, including administration, manufacturing, hospitals, banking systems, etc. In such situations, the present study is quite beneficial for understanding the system and redesigning it.

Spectrum sensing and resource allocation for 5G heterogeneous cloud radio access networks

In this paper, the problem of opportunistic spectrum sharing for the next generation of wireless systems empowered by the cloud radio access network (C-RAN) is studied. More precisely, low-priority users employ cooperative spectrum sensing to detect a vacant portion of the spectrum that is not currently used by high-priority users. The authors' aim is to maximize the overall throughput of the low-priority users while guaranteeing the quality of service of the high-priority users. This objective is attained by optimally adjusting spectrum sensing time, with respect to target probabilities of detection and false alarm, as well as dynamically allocating C-RAN resources, that is, powers, sub-carriers, remote radio heads, and base-band units. To solve this problem, which is non-convex and NP-hard, a low-complex iterative solution is proposed. Numerical results demonstrate the necessity of sensing time adjustment as well as effectiveness of the proposed solution.

PRICE BASED TRAFFIC CONGESTION CONTROL IN THE UPCOMING 5G DEPLOYMENT

The demand for data in the 4G (Fourth Generation networks) and 5G (Fifth Generation networks) is becoming excessively high and the solution is being investigated to effectively utilize the available spectrum at the physical layer across different protocols to speed-up access from 2.5 to 10 times. Furthermore, the current proposals for 5G systems is envisaged to increase spectrum efficiency which brings about customer satisfaction, network density and operational efficiency, using newly 3.5 GHz NCC auctioned spectrum bands. The CPU processing power and cloud computing are expected to be the key driving factors in the evolution of wireless Network from 1G to 5G. These support wide range of new technologies like IoT, smart cities and Cyber and information Security as well as broadband penetration using entirely new Network architectural concept as a total transformation. This paper presents 5G network tariff implementation strategies and proposes a model of revenue generation which would enable a market mechanism that would allow the customer to communicate with the 5G Network and negotiate a contract based on some QoS (Quality of Service) parameters like blocking probabilities of High Priority Users (HPUs) and Low Priority Users (LPUs) , delay, and price. The percentage Improvement in Cumulative Revenue (CR) generated by the proposed model over the existing models is 10. Recommendations were made on the way forward for the optimum 5G tariffs in the Nigerian context

A User-Priority-Driven Multi-UAV Cooperative Reconnaissance Strategy

This paper considers a reconnaissance scenario where multiple unmanned aerial vehicles (UAVs) provide services cooperatively for multiple users with different priorities. Although users all expect to acquire their needed information in a short time, the degree of urgency to meet their demands is different when taking their diverse priorities into account. A priority-driven multiuser satisfaction model is designed, where users’ satisfaction is quantified based on their different priorities, information acquisition demands, and the time they obtain their desired information. To ensure high priority users’ fast information acquisition while avoiding excessive delay in low priority users’ information acquisition, a batchwise information backhaul strategy is adopted. In each batch, a UAV is selected as the data ferry through a consultative mechanism to carry information back to users. This reconnaissance process is formulated as a cooperative path planning problem, where the optimization objective is maximizing users’ total satisfaction, while an intelligent algorithm is proposed to solve this problem effectively. The simulation results show that compared with traditional path planning algorithms without considering user satisfaction, our proposed algorithm can guarantee faster information acquisition for users with higher priorities, which leads to higher satisfaction. In addition, the applicability of our proposed reconnaissance strategy and path planning algorithm in different situations is also analyzed.

Random Multiple Access With Hierarchical Users

Classical random access protocols support prioritized user groups by allowing a high priority user to transmit with a relatively high probability. However, when a high priority user competes for the channel with a large number of low priority users, transmission success probability of the high priority user can still diminish to zero. In this paper, a distributed medium access control (MAC) framework is proposed to support hierarchical user groups in a random multiple access system in the following senses. First, when the number of primary users is small, the MAC framework guarantees that channel availability should stay above a pre-determined threshold no matter how many secondary users are competing for the channel. Second, when the number of primary users is large, the MAC framework drives transmission probabilities of the secondary users to zero but does not reject channel access to the primary users. These properties are achieved in a distributed environment without direct message exchange between users, without knowledge on the number of users, and without knowing whether each transmission should belong to a primary or a secondary user. The MAC framework is also extended to systems where each user can be equipped with multiple transmission options.

Throughput analysis of 2-D OCDMA/pure ALOHA networks with access control and two user classes of variable length for multimedia traffic

In a previous research, the throughput of a 2-D optical code-division multiple-access (OCDMA)/unslotted ALOHA (U-ALOHA)/channel load sensing protocol network using an optical hard limiter and channel code was analyzed. This scheme assumed a fixed message length and one user class. However, the current and future themes of networks is multimedia traffic with variable message length and two different user classes of real-time and non-real-time. In this paper, we propose a 2-D OCDMA/U-ALOHA network with access control and two user classes of variable message length. We assume that the number of fixed-length packets in a message is geometrically distributed and perform access control by assigning two user classes with different access permission probabilities. The numerical results show the high priority user class (e.g. real-time data traffic) can maintain maximum system throughput under the heavy load at the expense of low priority user class (e.g. non-real-time data traffic). The proposed network protocol could obtain 100 Gbps and be a promising alternative for local area networks (LANs) and broadband optical access networks for larger capacity in response to fast growing of multimedia data traffic.

A multi-stage graph based algorithm for survivable Service Function Chain orchestration with backup resource sharing

Network softwarisation introduces flexibility in network management by enabling the deployment of network functions as software modules running on virtual machines. However, this creates new concerns for service availability and reliability due to multiple sources of failures at both software and hardware levels, potentially resulting in service degradations and penalties due to Service Level Agreement (SLA) violations. The survivability of critical services can best be guaranteed by pro-actively provisioning dedicated backup resources for these services, but at the cost of a high resource consumption. Aware of the divergent requirements of future services, a promising alternative is envisaged, allowing non-critical users to use the unused backup resources of high priority users. However, this approach poses a stringent challenge if a critical service disruption occurs, requiring the computation of a traffic rerouting solution for the non-critical requests when preempted from their borrowed resources. In this paper we first propose a generic multi-stage graph based algorithm as an alternative algorithm for Service Function Chain (SFC) deployments. Simulation results demonstrate that the proposed algorithm is optimized in terms of resource utilization, resulting in a 10% improvement in terms of acceptance ratio compared to a given state of the art algorithm, and within a 4% margin of the optimal solution. Based on the mentioned algorithm, we propose a new migration-aware algorithm for the mapping of non-critical services, enabling the non-critical services to borrow the unused backup resources from the critical services while minimizing the probability of preemption they could experience. The migration-aware algorithm results in more than an 8% resource saving, in most scenarios, compared to a dedicated backup strategy, and more than a 70% performance improvement in terms of the number of service preemptions, compared to a cost based algorithm. Additionally, whenever low priority users are preempted from their borrowed resources, we propose a new QoS-aware global-rerouting algorithm for remapping those users, reducing the impact of the service interruption thanks to avoiding the migration of surviving VNFs and virtual links when feasible. The proposed algorithm is shown to outperform a service restoration strategy based on local rerouting, in terms of successful service restoration and resource consumption.

Security Improvement With QoS Provisioning Using Service Priority and Power Allocation for NOMA-IoT Networks

Non-orthogonal multiple access (NOMA) has gained attention as a promising multiple access scheme for the Internet of Things (IoT). A typical setting of user ordering in NOMA networks with user priority difference allows a service priority for solely low-rate high-priority users. In contrast, the diverse quality of service (QoS) requirements and service priorities are prerequisite features of users in the IoT. In this paper, we consider a downlink transmission scenario for NOMA-IoT networks in which the base station (BS) simultaneously serves the two users with a priority difference. To tackle the requirements of the IoT, we consider two schemes: a service priority scheme for high-priority user (SP-HP), and a service priority scheme for low-priority user (SP-LP). Meanwhile, the BS adopts a power allocation strategy to realize the desirable QoS provision for high-priority user and optimize the outage experience of low-priority user in an opportunistic manner. It is novel and interesting to extend the NOMA-IoT framework for a malicious attempt of a passive eavesdropper. To investigate the efficiency and security performances of both schemes, the connection and secrecy outage probabilities of both users are characterized, and their closed-form expressions are derived over Rayleigh fading channels. An effective secrecy throughput (EST) is presented to holistically characterize the performance of the system. Numerical results validate the accuracy of the theoretical results. The results suggest that the transmit power of both users in each scheme can be optimized for the maximum EST, and a selection of an optimal scheme for the reliable and secure transmissions of both users is possible under certain channel conditions.

Spectrum utilization efficiency in the cognitive radio enabled 5G-based IoT

The cognitive radio enabled cooperative communication is envisioned to be a vital part of the 5G-based Internet of Things (IoT). Since IoT contains billions of resource constrained devices, spectrum utilization efficiency (SUE) becomes a significant problem in order to accommodate such a large number of devices within the scarce spectrum. Therefore, in this paper, SUE of cognitive radio networks (CRNs) is investigated in terms of channel availability and service completion probability. We propose a spectrum efficient CRN (SE-CRN) that employs a hybrid underlay-interweave (UI) mode of CRNs for secondary users (SUs) under cooperative communication. Two types of SUs, with low and high priority levels, are considered. Moreover, a multi-attribute based approach for service determination for low priority users’ interruption is proposed that ensures the optimal channel availability for high priority users. SE-CRN is composed of two algorithms, namely, spectrum efficient dynamic spectrum access (SE-DSA) and spectrum efficient dynamic channel reservation (SE-DCR). SE-DSA dynamically assigns available channels to primary and secondary users based on their priority levels. SE-DCR dynamically keeps a number of channels reserved to support interruption of ongoing services. We utilize continuous time Markov chain (CTMC) for modeling and also form mathematical expressions for a number of QoS parameters. The scheme is evaluated under varying levels of network traffic loads and multiple rates of channel failure. We show through numerical results that SUE can be reasonably enhanced by SE-CRN.

Load Management, Power and Admission Control in Downlink Cellular OFDMA Networks

We present a resource management framework for load-coupled downlink cellular OFDMA networks considering the load factor of an individual base station (BS) per resource block (RB), i.e., the number of adjacent sub-carriers (SCs), as the variable of interest in the resource management problem. The load factor of a BS per RB, which corresponds to the fraction of active SCs in the BS per RB, is an indicator of the level of resource consumption, and it affects the interference caused to that RB reused in other BSs, and thereby, results in a load-coupled OFDMA system. We first propose two distributed schemes to minimize: (i) the total load factor of the BSs (which would in turn increase the number of supportable users in the system), and (ii) the total downlink transmit power level of the BSs. Then, we derive the necessary and sufficient conditions for checking the feasibility of given target-rate requirements (also referred to as demand vector) for users. Accordingly, an iterative and distributed scheme is proposed to check the feasibility of a given demand vector. Next, for a priority-based load-coupled network, we propose a priority-based gradual removal algorithm to support the maximal number of low-priority users while satisfying the demands of the high-priority users. To evaluate the performance of our proposed schemes for resource management and admission control in load-coupled OFDMA networks, the theoretical investigations are complemented with Monte Carlo simulations.

Performance Analysis of Multiuser FSO/RF Network Under Non-Equal Priority With $P$ -Persistence Protocol

This paper presents and analyzes a novel multiuser network based on hybrid free-space optical (FSO)/radio-frequency (RF) transmission system, where every user is serviced by a primary FSO link. When more than one FSO link fail, the central node services these corresponding users of non-equal priority by using a common backup RF link according to a $p$ persistence servicing protocol. A novel discrete-time Markov chain model is developed for the proposed network, where different transmission rates over RF and FSO links are assumed. We investigate the throughput from central node to the user, the average size of the transmit buffer allocated for every user, the frame queuing delay in the transmit buffer, the efficiency of the queuing system, the frame loss probability, and the RF link utilization. Numerical examples show that transmitting a data frame with probability $p$ when using the common backup RF link achieves considerable network performance improvement while ensuring high-priority users enjoy better performance. Meanwhile, the performance of low-priority users approaches the performance when using equal priority protocol to serve all the remote users.

Physical Impairment Aware Virtual Optical Network Construction Algorithm with Service Differentiation in Elastic Optical Networks

Background: Elastic optical networks can support high data bit rates efficiently with its flexible wavelength grid, and with virtual optical networks, network resources can be managed simply. However, the signal may be deteriorated by the physical impairments. Therefore, service differentiation techniques have to consider the physical impairments. Objective: We propose a novel virtual optical network construction algorithm that provides service differentiation. Moreover, the effect of physical impairments is considered before constructing a virtual optical network. The goal of the proposed algorithm is to provide service differentiation in terms of the rejection rate of virtual optical network requests. Here, we consider the on-line scenario where the traffic is not known in advance. Methods: In the proposed method, each virtual optical network comprises two nodes and a lightpath between the two nodes. In our proposed method, service differentiation is provided by giving a higher (lower) acceptance rate for high (low) priority users. This method consists of four mechanisms; signaling mechanism, physical impairment estimation mechanism, resource check mechanism, and retransmission mechanism. Numerical Results: We evaluate by simulation the performance of the proposed method in NSFNET and European topologies. Analysis of the rejection rate as function of network load, impact of the network load on the number of retransmissions, and impact of network topology were discussed. Numerical results show that our method not only provides service differentiation but also reduces the overall rejection rate. Conclusion: We can conclude that our method is efficient compared to the conventional methods considering the scenario and topologies analyzed.

On Secure QoS-based NOMA Networks with Multiple Antennas and Eavesdroppers over Nakagami-m Fading

In this paper, we study the physical layer security of a downlink multi-input single-output non-orthogonal multiple access (NOMA) system, in which transmit antenna selection (TAS) scheme, users’ quality of service (QoS) requirements, Nakagami-m fading channel, and user selection solution are considered for secure NOMA transmission. Specifically, we investigate the scenario that a base station (BS) (source) communicates with two legitimate user (LU) clusters with different priority depending on their QoS requirements in the presence of multiple passive eavesdroppers over Nakagami-m fading. To enhance the secrecy performance, we examine a TAS scheme and a user selection method. In this context, prior to transmission, a transmit antenna and a user in high-priority LU cluster are jointly selected to maximize the channel quality of the link from the BS to the selected user. Furthermore, together with the selected high-priority user, a user in low-priority LU cluster, which has the best channel condition, is chosen for performing two-user NOMA. In order to evaluate the secrecy performance, tight and asymptotic closed-form expressions of secrecy outage probability for selected LUs and overall system are derived. Our theoretical results confirmed by Monte–Carlo simulation show that in QoS-based NOMA system, high-priority users cause the higher effects on the overall secrecy performance in comparison with low-priority users. Finally, these results also indicate that our proposed communication protocol achieves the secrecy performance greater than conventional protocol.

Performance Analysis of D2D Underlying Cellular Networks Based on Dynamic Priority Queuing Model

In this paper, we develop a spatiotemporal mathematical model for analyzing the performance of prioritized data transmissions in the device-to-device (D2D) underlaying cellular network. A dynamic interference model of a D2D user is constructed by exploiting thinned Poisson point process to model the D2D user location with data stored in the buffer. A dynamic priority queuing model is adapted to analyze the performance of multiple types of traffic, in which the priority jump strategy is proposed to provide increased transmission opportunity for low-priority user packets. Then, we employ a two-dimensional Geo/G/1 Markov chain to describe a queue model with priority jump and evaluate it using quasi-birth-and-death process approach. An iterative solution is used to compute the steady-state probability distribution and the expressions of performance metrics are obtained. The simulation results show the validity of the theoretical analysis. Moreover, by comparing the dropping probability of the priority queuing model with and without the jump strategy, the rationality of the introduced model is confirmed.

Context-aware and priority-based user association and resource allocation in heterogeneous wireless networks

Heterogeneous wireless networks (HWNs) are usually characterized by the integration of cellular networks and wireless local area networks (WLANs) to meet user requirements and enhance system capacity. This paper proposes a user association and downlink resource allocation algorithm in HWNs with users having different priorities. The proposed solution employs contextual information related to the preferences of the users, their requested data rate, and the characteristics of networks. The user preference is translated through a profit function that is based on the received signal quality and the power consumption at mobile terminals (MTs). Accordingly, an optimization problem is formulated to maximize the overall user satisfaction for each priority level. The formulated problem throws firm restrictions to prevent low-priority users from allocating resources utilized by other users with higher priorities. We then propose a novel heuristic approach with polynomial-time complexity to approximate the formulated problem. Furthermore, the system architecture is discussed and a new solution management strategy is proposed to limit the complexity of the algorithm. Simulation results show that the proposed approximation method maintains the nearest performance to the optimal solution.

Stable Throughput Regions of Opportunistic NOMA and Cooperative NOMA With Full-Duplex Relaying

In this paper, we consider downlink non-orthogonal multiple access (NOMA) transmission with dynamic traffic arrival for spatially random users of different priorities. By exploiting limited channel state information, we propose an opportunistic NOMA scheme to enable NOMA for high- and low-priority users when high-priority users experience good channel conditions. Opportunistic NOMA improves the transmission opportunities of low-priority users while reducing the adverse effect of NOMA on high-priority users. Moreover, we propose a cooperative NOMA scheme with full-duplex relaying, where low-priority users act as full-duplex relays to assist the high-priority users. The high-priority user constructively combines the signal and its delayed version transmitted by the base station and a selected relay, respectively. The adopted relay selection scheme takes into account the users’ spatial distribution, queue status, and channel conditions. By using tools from queueing theory and stochastic geometry, we derive the stable throughput regions of both proposed schemes. Furthermore, we derive the conditions under which the proposed NOMA schemes achieve larger stable throughput regions than orthogonal multiple access (OMA). At the expense of a higher implementation complexity and with appropriate parameter setting, cooperative NOMA with full-duplex relaying achieves a larger stable throughput region than opportunistic NOMA, which in turn outperforms OMA.

Performance Study of Queuing Delay in CRN Using Different Proposed Spectrum Handoff Approaches

Spectrum handoff in cognitive radio networks is to have a seamless switch between channels consequently, a high quality of service for the secondary users. This paper proposes three techniques for spectrum handoff. The first proposed one based on the low priority user leaves the channel to another channel. The second proposed model based on the low priority user stays on the same channel with resuming its transmission when the high priority user finished its transmission. Finally, the third proposed model based on the low priority user stays on the same channel with restarting its transmission when the high priority user finished its transmission. The obtained results indicate that the three proposed system models give different queuing delay performances for each user. The techniques of the models and the obtained results are important for evaluating the total system time, service time and queuing delay for secondary users. Consequently, the quality of service for the secondary users and hence the useful for cognitive radio network design and optimization will be obtained.