Interest in broadband wireless access (BWA) has been growing due to increased user mobility and the need for data access at all times. IEEE 802.16e based WiMAX networks promise the best available quality of experience for mobile data service users. Unlike wireless LANs, WiMAX networks incorporate several quality of service (QoS) mechanisms at the Media Access Control (MAC) level for guaranteed services for data, voice and video. The problem of assuring QoS is basically that of how to allocate available resources among users in order to meet the QoS criteria such as delay, delay jitter and throughput requirements. IEEE standard does not include a standard scheduling mechanism and leaves it for implementer differentiation. Scheduling is, therefore, of special interest to all WiMAX equipment makers and service providers. This paper discusses the key issues and design factors to be considered for scheduler designers. In addition, we present an extensive survey of recent scheduling research. We classify the proposed mechanisms based on the use of channel conditions. The goals of scheduling are to achieve the optimal usage of resources, to assure the QoS guarantees, to maximize goodput and to minimize power consumption while ensuring feasible algorithm complexity and system scalability.

https://www.cse.wustl.edu/~jain//papers/ftp/sched.pdf

Scheduling in IEEE 802.16e mobile WiMAX networks: key issues and a survey

In this chapter, we focus on the management of resource allocation and scheduling in IEEE 802.16e based mobile WiMAX networks. Since mobile WiMAX uses orthogonal frequency division multiple access (OFDMA), the scheduling issues can apply for other OFDMA-based networks as well. Unlike wireless LANs, WiMAX networks incorporate several Quality of Service (QoS) mechanisms at the media access control (MAC) layer for guaranteed services for data, voice, and video. The problem of assuring QoS is basically that of how to allocate available resources among users in order to meet the QoS criteria such as delay, delay jitter, and throughput requirements. IEEE standard does not include a standard scheduling mechanism and leaves it for vendor differentiation. Scheduling is, therefore, of special interest to all WiMAX equipment makers and service providers. This chapter mainly discusses the key issues and design factors to be considered for scheduler design. Before discussing the scheduling disciplines in detail, the three main services-voice, video, and data are discussed. Understanding the nature of traffic classes gives an insight on how to design the scheduler to guarantee the service. Moreover, the capacity limitation of each service is analyzed not only for capacity planning but also for simulation validation purposes. Finally, we present a brief survey of recent scheduling research. We classify the proposed mechanisms based on the use of channel conditions. The goals of scheduling are to achieve the optimal usage of resources, to assure the QoS guarantees, to maximize goodput, and to minimize power consumption while ensuring feasible algorithm complexity and system scalability. The organization of this chapter, shown in Table 1, is as follow: In Section 1 we give an overview to WiMAX in order to give readers better understanding of WiMAX characteristics such as physical (PHY) and MAC. In Section 2 the capacity limitation of each service is analyzed not only for capacity planning but also for simulation validation purposes. Then, we emphasize key issues such as two-dimensional downlink mapping (Section 3) and bandwidth request mechanism (Section 4) in order to design the scheduling disciplines, and then we discuss the key factors that the scheduling designer needs to consider as well as a brief survey on WiMAX scheduling in Section 5. We revisit open issues and potential research areas in Section 6. Table 1: Structure of Chapter 1-Introduction: PHY and MAC, registration process-Capacity estimation-Downlink mapping-Bandwidth request mechanisms-QoS schedulers: channel-aware and channel-unaware-Conclusions and open research issues Table 2: …

https://www.cse.wustl.edu/~jain/books/ftp/wimax_ra.pdf

Resource Allocation in IEEE 802.16 Mobile WiMAX

Comparison and analysis of the revenue-based adaptive queuing models

This paper introduces an embedded fuzzy expert system for Adaptive Weighted Fair Queueing (AWFQ) located in the network traffic router to update weights for output queues. WFQ algorithm allows differentiated service for traffic classes according to Quality of Service (QoS) requirements. Link sharing and packet scheduling methods are the most critical factors when guaranteeing QoS. There are many different scheduling mechanisms but adequate and adaptive QoS aware scheduling solutions are still in a phase of development due to the rapid growth of multimedia in the Internet. The proposed AWFQ model in this work simplifies the link sharing to two service classes: one for UDP and another for TCP. The implementation of the model is based on adaptive change of weight coefficients that determine the amount of allowed bandwidth for the service class. New weight coefficients are calculated periodically on routers according to developed embedded fuzzy expert system. It is shown through simulations that the AWFQ model is more stable and reacts faster to different traffic states than the traditional WFQ scheduler. The embedded expert system adjusts the weights of AWFQ with two parameters that are based on the share of the UDP and TCP input traffic data rate and the change of the share of the UDP and TCP input data rate.

Embedded fuzzy expert system for Adaptive Weighted Fair Queueing

This article presents a cross-layer packet scheduler to provide end-to-end QoS guarantees for Digital Video Broadcasting-Second Generation (DVB-S2) broadband satellite systems. The scheduler design is based on a cross-layer mechanism defined between the physical and the network layer. It includes an algorithm to guarantee the required QoS specifications established in the service level agreement. The algorithm calculation depends basically on two parameters: the available bandwidth present in a DVB-S2 satellite link and the QoS requirements of each traffic class defined by the satellite operator. The cross-layer scheduler's operation is demonstrated using the NS-2 simulator tool. The results show that the proposed mechanism maximizes the bandwidth utilization while enforcing the priority level of each service class when an extreme reduction of bandwidth caused by rain events is experienced.

Cross-layer packet scheduler for QoS support over Digital Video Broadcasting-Second Generation broadband satellite systems

This paper proposes a model to maximize revenue while serving customers with different quality-of-service (QoS) requirements. A providers' goal is to share resources between active customers to ensure all QoS requirements. At the same time, a provider is interested in maximizing the revenue. Since the amount of active users varies a provider functioning can be optimized by allocating different portions of resources. The proposed model is based on the weighted fair queue policy, which is extended so that the usage-based revenue criterion can be used to dynamically adapt weights. The model is flexible in that different services are grouped into service classes and are given different performance characteristics. It guarantees the QoS requirements and maximizes the revenue by manipulating weights of the WFQ model. The simulation of the proposed model considers a single node with several service classes. It is shown that the total revenue can be significantly improved when compared to a non-adaptive approach.

An adaptive approach to WFQ with the revenue criterion

This paper presents an adaptive resource allocation model that is based on the WRR queuing discipline. The model ensures QoS requirements and tries to maximize a service provider's revenue by manipulating weights of the WRR scheduler. To adjust the weights, it is proposed to use the revenue criterion, which controls the allocation of free resources. The simulation considers a single node with the implemented model that serves several classes with different QoS requirements and traffic characteristics. It is shown that the total revenue can be increased due to the allocation of unused resources to more expensive service classes. Furthermore, the adaptive model eliminates the need to find the optimal static weight values as they are calculated dynamically.

Adaptive scheduling using the revenue-based weighted round robin

In this work, the problem of efficient configuration and management of adaptive routers is considered. Adaptive routers use intellectual models to change dynamically the parameters of the queuing policies based on various criteria. By now, the policy-based information model can be used to provide configuration data for these routers. However, the existent scheme fails to provide a set of classes for adaptive queuing models. Thus, a creation of an extension to the policy-based information model is considered and a set of possible classes is highlighted. Furthermore, an example is given that considers how parameters of an adaptive queuing model can be represented as a set of policy classes and used within the DiffServ framework.

J. Joutsensalo

Papers

An adaptive approach to WFQ with the revenue criterion

Adaptive scheduling using the revenue-based weighted round robin

Extension of the QoS policy information model to support adaptive queuing techniques