Cross-layer Scheduling Research Articles

Packet scheduling in MIMO satellite long term evolution networks

Summary This paper deals with the performance evaluation of different packet scheduling schemes for Long Term Evolution mobile satellite systems based on the adoption of a multi-user MIMO technique. The major breakthrough of MIMO technology in terrestrial networks has motivated the interest here for the adoption of MIMO in mobile satellite systems as well. In particular, a land mobile dual-polarized GEO satellite system has been considered in this work. The aim of this paper is to propose new cross-layer packet scheduling schemes that achieve a good trade-off among throughput, QoS and fairness and to conduct performance comparisons with other scheduling schemes in the literature. This is the reason why this paper also proposes a new performance index that can be used to evaluate the overall performance of each scheduler. The work shows that the new cross-layer scheduler, called channel-based queue sensitive scheduler, attains the best performance in terms of the new comprehensive performance index, thus representing an interesting solution for future mobile satellite systems. Copyright © 2015 John Wiley & Sons, Ltd.

Energy Efficient Medium Access Control Protocol for Clustered Wireless Sensor Networks with Adaptive Cross-Layer Scheduling.

This paper presents an Energy Efficient Medium Access Control (MAC) protocol for clustered wireless sensor networks that aims to improve energy efficiency and delay performance. The proposed protocol employs an adaptive cross-layer intra-cluster scheduling and an inter-cluster relay selection diversity. The scheduling is based on available data packets and remaining energy level of the source node (SN). This helps to minimize idle listening on nodes without data to transmit as well as reducing control packet overhead. The relay selection diversity is carried out between clusters, by the cluster head (CH), and the base station (BS). The diversity helps to improve network reliability and prolong the network lifetime. Relay selection is determined based on the communication distance, the remaining energy and the channel quality indicator (CQI) for the relay cluster head (RCH). An analytical framework for energy consumption and transmission delay for the proposed MAC protocol is presented in this work. The performance of the proposed MAC protocol is evaluated based on transmission delay, energy consumption, and network lifetime. The results obtained indicate that the proposed MAC protocol provides improved performance than traditional cluster based MAC protocols.

Utility-Based Optimized Cross-Layer Scheme for Real-Time Video Transmission Over HSDPA

In this paper we first build an accurate and general transmission distortion model for H.264/AVC video streams to estimate the importance of each packet. Then, a utility-based optimized cross-layer resource allocation, MCS selection, and packet scheduling algorithm for real-time video transmission over HSDPA is studied. The utility here refers to the packet utility which is defined as a function of the packet urgency and the packet importance . Transmitting the packets with greater utility values firstly in each TTI can provide a higher level of video quality for the users. Thus, we formulate an optimization problem with the objective of maximizing the aggregate packet utility over all the users under the HSDPA physical resource constraints . In order to obtain an optimal transmission strategy, a dynamic programming -based cross-layer algorithm (DPCLA) is proposed. In view of its high complexity, we further develop a greedy-based cross-layer algorithm (GCLA) to find a suboptimal solution. Simulation results show that the proposed utility-based optimized cross-layer scheme, including the proposed transmission distortion model and the algorithms of DPCLA and GCLA, can provide higher received video quality than the existing ones for video transmission over HSDPA.

Joint transmission in cellular networks with CoMP—Stability and scheduling algorithms

Due to the current trend towards smaller cells, an increasing number of users of cellular networks reside at the edge between two cells; these users typically receive poor service as a result of the relatively weak signal and strong interference. Coordinated Multi-Point (CoMP) with Joint Transmission (JT) is a cellular networking technique allowing multiple Base Stations (BSs) to jointly transmit to a single user. This improves the users’ reception quality and facilitates better service to cell-edge users. We consider a CoMP-enabled network, comprised of multiple BSs interconnected via a backhaul network. We formulate the OFDMA Joint Scheduling (OJS) problem of determining a subframe schedule and deciding if and how to use JT in order to maximize some utility function. We show that the OJS problem is NP-hard. We develop optimal and approximation algorithms for specific and general topologies, respectively. We consider a time dimension and study a queueing model with packet arrivals in which the service rates for each subframe are obtained by solving the OJS problem. We prove that when the problem is formulated with a specific utility function and solved optimally in each subframe, the resulting scheduling policy is throughput-optimal. Via extensive simulations we show that the bulk of the gains from CoMP with JT can be achieved with low capacity backhaul. Moreover, our algorithms distribute the network resources evenly, increasing the inter-cell users’ throughput at only a slight cost to the intra-cell users. This is the first step towards a rigorous, network-level understanding of the impact of cross-layer scheduling algorithms on CoMP networks.

Fair Scheduling for Energy Harvesting Nodes

This letter considers the problem of scheduling in the multiple input multiple output (MIMO) multiple-access wireless channel, where the transmitters are energy harvesting nodes (EHNs) that are powered by renewable energy sources (RESs). In this letter the conventional scheduling objective of maximizing rate is augmented by two other objectives, regulating fairness, and stabilization of the stored energy processes of the EHNs. This problem is formulated as a network of energy queues, which represent the batteries. Considering the stochastic nature of the wireless channel and the energy harvesting processes, this letter employs Lyapunov drift plus penalty technique to develop a cross-layer scheduler that operates in a slotted-time and distributed manner. At each epoch it selects an EHN for transmission and computes the transmit power. As an added advantage, the power control algorithm still retains the optimal water-filling solution. Through simulations, the proposed solution is compared against a conventional max-rate scheduler and is shown to better enforce fairness, stabilize the battery levels, and minimize the required battery capacity.

An IP cross-layer scheduler with closed-loop control for QoS provisioning in NGNs

Next-generation networks (NGNs) will support quality of service over a mixed wired and wireless IP-based infrastructure. A relative model of service differentiation in differentiated services architecture is a scalable solution for delivering multimedia traffic. However, considering the dynamic nature of radio channels specifically, it is difficult to achieve a given service provisioning working at the IP and lower layers separately as in the classical approach without a run-time adaptation of the system towards the target quality. This work describes an IP cross-layer scheduler able to support a Proportional Differentiation Model (PDM) for delay guarantees also over wireless. The key idea is to leverage feedbacks from the lower layers about the actual delays experienced by packets in order to tune at run-time the priority of the IP service classes in a closed-loop control with the objective of supporting a PDM at the interface on the whole, considering the cumulative latency across multiple layers, as relevant for the end-user. A simulation analysis demonstrates the prominent improvements in reliability and robustness of the proposal in the case of time-variant performance of the MAC and PHY layers with respect to the classical non-cross-layer approach and open-loop control. Furthermore, considerations on the required functionality and likely deployment scenarios highlight the scalability and backward compatibility of the designed solution, addressing a sustainable approach and smooth migration to NGNs.

Optimal TDMA Scheduling in Tree-Based Power-Line Communication Networks

The large amount of differentiated quality-of-service traffic generated by modern smart grids necessitates efficient scheduling schemes for the uplink traffic. This paper proposes a cross-layer time-division multiple access scheduling scheme destined for broadband power-line communications (BB-PLC)-access networks. The scheme determines the topology of the smart-grid communications (SGC) PLC trees formed across the power grid, identifies the noninterfering segments in the tree graph, and schedules the uplink transmission. The scheme is based on appropriately adjusting the injected power of the SGC tree nodes following a graph-based distributed approach in the attempt to enhance slot reuse. The scheme has been tested and assessed for typical SGC networks deployed in rural and urban areas, considering both aggregated and nonaggregated SGC traffic. The relevant simulations verify that by reducing the interference due to PLC transmission, the proposed adaptive power-control-based scheme can significantly minimize the injected power, enhance throughput, and reduce delay on an SGC cell basis. The reduction in schedule length depends drastically on the maximum-allowed injected power and the topology of the SGC tree and may reach 70% when combined with data aggregation.

New scheduling scheme for green communications in long term evolution networks

Green communications has been paid much attention recently, to provide energy efficient networks with a high level of quality of service (QoS). In this study, the authors propose a cross-layer scheduling scheme for the downlink of long-term evolution networks, considering the buffer state which may be empty in some times. Their target is to minimise energy consumption under the constraints of limited average transmitting power in the base station, and maximum tolerable delay as QoS of heterogeneous users. In the proposed scheme, the authors use an effective capacity link layer model to consider the data link layer characteristics, such as probability of non-empty buffer and probability of maximum delay, along with the physical layer parameters. Simulation results show more than 48% reduction of energy consumption in peak traffic loads.

Two Time-Scale Cross-Layer Scheduling for Cellular/WLAN Interworking

In this paper, we investigate uplink resource allocation for wireless local area network and cellular network interworking to provide multi-homing voice and data services. The problem is formulated based on the physical layer and medium access control layer technologies of the two networks to ensure that the resource allocation decisions are feasible and can be executed at the lower layers. Furthermore, to efficiently utilize users' equipment (UEs) battery power, the power distribution among multiple network interfaces of the UEs is included in the problem formulation. The optimal resource allocation problem is a multiple time-scale Markov decision process (MMDP) as the two networks operate at different time-scales and due to voice and data service requirements. We derive decision policies for the upper and the lower levels of the MMDP by decomposing each resource allocation problem over multiple time slots to a set of resource allocation problems for individual time slots and solving the resource allocation problems corresponding to individual time slots using convex optimization techniques. To reduce the time complexity, we further propose a heuristic resource allocation algorithm by deriving the decision policies based on a single system state. The system state consists of average square channel gains for dual variable calculation and instantaneous channel gains for resource allocation based on the calculated dual variables. Simulation results demonstrate the achievable throughput and service quality improvements by employing these two algorithms.

Cross-layer scheduling design for multimedia applications over cognitive ad hoc networks

Cross-layer scheduling design for multimedia applications over cognitive ad hoc networks

Multimedia over cognitive radio networks: Towards a cross-layer scheduling under Bayesian traffic learning

Mobility and spectrum change of the cognitive radio networks (CRNs), make the traffic information exchange among the secondary users (SUs) a high-overhead task. In order to quickly estimate the queuing delay in the multimedia over CRN applications without exchanging traffic information among SUs, we are the first group to propose the use of Dirichlet-prior based fully Bayesian model in each individual SU to automatically update its statistical distribution on other SUs’ Non-Contiguous (NC)-OFDM subcarrier selection strategy. Such a statistical distribution is used to estimate the probability of queuing delay being less than a threshold. In addition, we introduce a new concept called the Time Window, to accurately determine how many packets can be transmitted simultaneously over multiple subcarriers. Then, we propose a comprehensive, intelligent cross-layer scheduling scheme that can generate the optimal subcarrier selection, power and modulation allocation for each multimedia packet. Our experiments on real video transmission validate our intelligent cross-layer scheduling schemes. The simulation results match with theoretical analysis very well, and the reconstructed video quality using our proposed scheduling scheme is superior to four other popularly used schemes.

A CROSS-LAYER SCHEDULER WITH CHANNEL STATE INFORMATION FOR GUARANTEED QUALITY OF SERVICE

WiMAX networks are deployed for commercial use because of its nature high bandwidth. This requirement invokes the application level changes i n QoS provisioning techniques. The objective of the broadband wireless technologies is to ensure th e end to end Quality of Service (QoS) for the service classes. WiMAX is a revolution in wireless networks, which could support real time multimedia services. In order to provide QoS suppor t and efficient usage of system resources an intelligent scheduling algorithm is needed. The des ign of the detailed scheduling algorithm is a major focus for researchers and service providers. In thi s study, a channel aware cross-layer scheduling algorithm for WiMAX networks has been proposed. This scheme employs the Signal to Noise Ratio (SNR) value, which allocates the bandwidth based on the information about the quality of the channel and the service requirements of each connection. Th e proposed algorithm is described in detail and evaluated, through a series of simulations. The QoS parameters of throughput, bandwidth efficiency and transmission efficiency have been measured in s imulation.

Cross-layer Scheduling with Feedback for QoS Support

Next-Generation Networks (NGNs) will support Quality of Service (QoS) over a mixed wired and wireless IP-based infrastructure. A relative model of service differentiation in Differentiated Services architecture is a scalable solution for delivering multimedia traffic. However, considering the dynamic nature of radio channels typically, it is difficult to achieve a given service provisioning working at the IP and lower layers separately as in the classical approach, without a run-time adaptation of the system towards the target quality. This work describes an IP cross-layer scheduler able to support a Proportional Differentiation Model (PDM) for delay guarantees with content-awareness, also over wireless. The key idea is to leverage feedbacks from the lower layers about the actual delays experienced by packets in order to tune at run-time the priority of the IP service classes in a closed-loop control with the objective of supporting a PDM at the network node on the whole, considering the cumulative latency in crossing the first three layers of the protocol stack, as relevant for the end-user. A simulation analysis demonstrates the prominent improvements in reliability and robustness of the proposal in the case of time-variant performance of the MAC and PHY layers with respect to the classical non-cross-layer approach and the open- loop control. Furthermore, considerations on the required functionality and likely deployment scenarios highlight the scalability and backward compatibility of the designed solution in supporting the concept of network transparency for the delivering of critical applications, as of the e-health domain.

Cross-Layer Scheduling and Resource Allocation for Heterogeneous Traffic in 3G LTE

3G long term evolution (LTE) introduces stringent needs in order to provide different kinds of traffic with Quality of Service (QoS) characteristics. The major problem with this nature of LTE is that it does not have any paradigm scheduling algorithm that will ideally control the assignment of resources which in turn will improve the user satisfaction. This has become an open subject and different scheduling algorithms have been proposed which are quite challenging and complex. To address this issue, in this paper, we investigate how our proposed algorithm improves the user satisfaction for heterogeneous traffic, that is, best-effort traffic such as file transfer protocol (FTP) and real-time traffic such as voice over internet protocol (VoIP). Our proposed algorithm is formulated using the cross-layer technique. The goal of our proposed algorithm is to maximize the expected total user satisfaction (total-utility) under different constraints. We compared our proposed algorithm with proportional fair (PF), exponential proportional fair (EXP-PF), and U-delay. Using simulations, our proposed algorithm improved the performance of real-time traffic based on throughput, VoIP delay, and VoIP packet loss ratio metrics while PF improved the performance of best-effort traffic based on FTP traffic received, FTP packet loss ratio, and FTP throughput metrics.

Resource Management Technique Based on Lightweight and Compressed Sensing for Mobile Internet of Things

In mobile Internet of Tings, based on cross-layer design and resource-aware scheduling, the combination of light weight coding and compressed sensing is used to improve the real-time performance of acquisition of system resource and reliability of resource management in this paper. Compressed sensing scheme based on the adaptive frame format definition of lightweight coding is able to set up the parameters such as sample signal, signal and hops. The nonlinear relationship matrixes between resource information of sensors or system and quality of services are built to manage the global or local network resource scheduling. Experimental results show that the proposed scheme is better than the traditional scheme or resource management based on compressed sensing alone scheme, which can make the system be able to achieve optimal resource allocation.

COMPARISON FOR WIMAX SCHEDULING ALGORITHMS AND PROPOSAL QUALITY OF SERVICE IMPROVEMENT IN WIMAX NETWORKS

The objective of the broadband wireless technologie s is to ensure the end to end Quality of Service (Q oS) for service classes. Wimax is a revolution in wirel ess networks which could support real time multimedia services. In order to provide QoS suppor t and efficient usage of system resources an intelligent scheduling algorithm is needed. The des ign of detailed scheduling algorithm is a major focus for researchers and service providers. In thi s study, a channel aware cross-layer scheduling algorithm for Wimax networks has been proposed. This scheme employs Signal to Noise Ratio (SNR) value which allocates bandwidth based on the inform ation about the quality of the channel and service requirements of each connection. The proposed algor ithm is described in detail and evaluated through series of simulation. The simulation results prove that the proposed algorithm reduces the packet loss rate and delay and thus improves throughput by 12.8 %.

Delay-Guaranteed Cross-Layer Scheduling in Multihop Wireless Networks

In this paper, we propose a cross-layer scheduling algorithm that achieves a throughput “ ε-close” to the optimal throughput in multihop wireless networks with a tradeoff of O([1/(ε)]) in average end-to-end delay guarantees. The algorithm guarantees finite buffer sizes and aims to solve a joint congestion control, routing, and scheduling problem in a multihop wireless network while satisfying per-flow average end-to-end delay constraints and minimum data rate requirements. This problem has been solved for both backlogged as well as arbitrary arrival rate systems. Moreover, we discuss the design of a class of low-complexity suboptimal algorithms, effects of delayed feedback on the optimal algorithm, and extensions of the proposed algorithm to different interference models with arbitrary link capacities.

QoS-Based Cross-Layer Scheduling for Wireless Multimedia Transmissions with Adaptive Modulation and Coding

It is challenging to design effective scheduling algorithms for multimedia transmissions over wireless channels that employ adaptive modulation and coding (AMC). On the one hand, it is desirable for the overall system throughput to be enhanced by taking advantage of multi-user diversity. On the other hand, fairness or QoS guarantees need to be maintained for individual users, especially in the case of multimedia applications that have strict delay requirements. In this paper, we propose a novel scheduling algorithm called QoS-based cross-layer scheduling (QoS-CLS) to achieve a good design tradeoff. To maximize the system throughput, the algorithm takes into account the information on both the physical layer and the data link layer to schedule user transmissions. Using cross-layer information, the scheduling problem is formulated as a Markov Decision Process and the optimal decision policy (based on the channel status, traffic state, and buffer status of each traffic flow) is pre-calculated by linear programming. This policy is then stored in the system for scheduling in real-time. Simulation results show that QoS-CLS can greatly enhance the channel throughput compared to existing algorithms because of its cross-layer QoS consideration and the optimization method. Moreover, it can provide QoS guarantees while achieving efficient resource sharing among different traffic flows.

Delay-Aware Two-Hop Cooperative Relay Communications via Approximate MDP and Stochastic Learning

In this paper, a low-complexity delay-aware cross-layer scheduling algorithm for two-hop relay communication systems is proposed. The complex interactions of the queues at the source node and the M relay nodes (RSs) are modeled as an infinite horizon average reward Markov decision process (MDP), whose state space involves the joint queue state information (QSI) of the queues at the source node and the M RSs as well as the joint channel state information (CSI) of all S-R and R-D links. To address the curse of dimensionality, an equivalent MDP formulation is first proposed, where the system state depends only on global QSI. Furthermore, using approximate MDP and stochastic learning, an auction-based distributed online learning algorithm is derived, where each node iteratively estimates a per-node value function based on real-time observations of the local CSI and local QSI as well as signaling between relays. The combined distributed learning converges almost surely to a global optimal solution for large arrivals. Finally, it is showed by simulations that the proposed scheme achieves significant gain compared with various baselines such as the conventional CSIT-only control and the throughput optimal control (in stability sense).

Downlink cross-layer scheduling strategies for long-term evolution and long-term evolution-advanced systems

The most recent trend in the Information and Communication Technology world is toward an ever growing demand of mobile heterogeneous services that imply the management of different quality of service requirements and priorities among different type of users. The long-term evolution LTE/LTE-advanced standards have been introduced aiming to cope with this challenge. In particular, the resource allocation problem in downlink needs to be carefully considered. Herein, a solution is proposed by resorting to a modified multidimensional multiple-choice knapsack problem modeling, leading to an efficient solution. The proposed algorithm is able to manage different traffic flows taking into account users priority, queues delay, and channel conditions achieving quasi-optimal performance results with a lower complexity. The numerical results show the effectiveness of the proposed solution with respect to other alternatives. Copyright © 2013 John Wiley & Sons, Ltd.