In this paper, we propose Transmission Control Protocol (TCP)-aware cross layer scheduling algorithms in a multipoint-to-point network such as the uplink of an IEEE 802.16 (WiMAX) network. Inadequate bandwidth allocation to a TCP flow may lead to timeout and since TCP source drops its congestion window ( @math ) immediately after a timeout, it may affect the average throughput adversely. On the other hand, since the TCP source increases its @math only linearly upon the availability of bandwidth, any excess assignment of bandwidth may remain underutilized. The proposed scheduling algorithms address this by allocating the resources based on @math and TCP timeout. Moreover, since we focus on uplink scheduling, we consider that only flow level resource requirement is communicated to the Base Station ( @math ) instead of per packet information. The schedulers also take into account the wireless channel characteristics and are thus cross layer in nature. Through exhaustive simulations, we demonstrate that the proposed schedulers exhibit enhanced throughput and fairness properties when compared to that of Round Robin (RR) scheduler under different shadowing. We demonstrate a gain between 3.5 to 15 in throughput and 15 to 25 in channel utilization over RR scheduler under different shadowing.
In @cite_0 , the authors have proposed a Token Bank Fair Queuing (TBFQ) @cite_2 based scheduler for the downlink flows of an IEEE 802.16 network. It considers location dependent channel errors while scheduling and employs credit behavior of a flow to determine a priority index. Though this scheme provides fairness, it does not guarantee any delay while scheduling. @cite_31 proposes an adaptive selective Automatic Repeat reQuest based scheduling scheme for @math applications and uses an analytical model for parameter manipulation. Though it provides a trade-off between utilization and throughout, it is more suitable for the downlink scheduling in WiMAX networks,
@cite_0 @cite_31 @cite_2
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SUMMARY The token bank fair queuing algorithm (TBFQ) is a novel scheduling algorithm that is suitable for wireless multimedia services. The bandwidth allocation mechanism integrates the leaky bucket structure with priority handling to address the problem of providing quality-of-service (QoS) guarantees to heterogeneous applications in the next generation packet-switched wireless networks. Scheduling algorithms are often tightly integrated with the wireless medium access control (MAC) protocol. However, when heterogeneous wireless systems need to be integrated and interoperate with each other, it is desirable from the QoS provisioning standpoint to decouple scheduling algorithm from the MAC protocol. In this paper we propose a framework of seamless QoS provisioning and the application of TBFQ for uplink and downlink scheduling in wireless networks. We study its performance under a generic medium access framework that enables the algorithm to be generalized to provide QoS guarantees under various medium access schemes. We give a brief analysis of the algorithm and compare its performance with common scheduling algorithms through simulation. Our results demonstrate that TBFQ significantly increases wireless channel utilization while maintaining the same QoS, unlike many fair queuing algorithms, TBFQ does not require timestamping information of each packet arrival an impractical feature in an already resource scarce environment. This makes TBFQ suitable for wireless multimedia communication. Copyright # 2004 John Wiley & Sons, Ltd. Fair scheduling of delay and rate-sensitive packet flows over a wireless channel is not addressed effectively by most contemporary wireline fair-scheduling algorithms because of two unique characteristics of wireless media: (1) bursty channel errors and (2) location-dependent channel capacity and errors. Besides, in packet cellular networks, the base station typically performs the task of packet scheduling for both downlink and uplink flows in a cell; however, a base station has only a limited knowledge of the arrival processes of uplink flows. We propose a new model for wireless fair-scheduling based on an adaptation of fluid fair queueing (FFQ) to handle location-dependent error bursts. We describe an ideal wireless fair-scheduling algorithm which provides a packetized implementation of the fluid mode, while assuming full knowledge of the current channel conditions. For this algorithm, we derive the worst-case throughput and delay bounds. Finally, we describe a practical wireless scheduling algorithm which approximates the ideal algorithm. Through simulations, we show that the algorithm achieves the desirable properties identified in the wireless FFQ model. Quality of Service (QoS) is provided in IEEE 802.11e protocol by means of HCF Controlled Channel Access (HCCA) scheduler which is efficient for supporting Constant Bit Rate (CBR) applications. Numerous researches have been carried out to enhance the HCCA scheduler attempting to accommodate the needs of Variable Bit Rate (VBR) video traffics which probably demonstrates a non-deterministic profile during the time. This paper presents an adaptive TXOP assignment mechanism for supporting the transmission of the prerecorded video traffics over IEEE 802.11e wireless networks. The proposed mechanism uses a feedback about the size of the subsequent video frames of the uplink traffic to assist the Hybrid Coordinator (HC) accurately assign TXOP according to the fast changes in the VBR profile. The simulation results show that our mechanism reduces the delay experienced by VBR traffic streams comparable to HCCA scheduler due to the accurate assignment of the TXOP which preserve the channel time for data transmission. We consider the problem of resource allocation in downlink OFDMA systems for multi service and unknown environment. Due to users' mobility and intercell interference, the base station cannot predict neither the Signal to Noise Ratio (SNR) of each user in future time slots nor their probability distribution functions. In addition, the traffic is bursty in general with unknown arrival. The probability distribution functions of the SNR, channel state and traffic arrival density are then unknown. Achieving a multi service Quality of Service (QoS) while optimizing the performance of the system (e.g. total throughput) is a hard and interesting task since it depends on the unknown future traffic and SNR values. In this paper we solve this problem by modeling the multiuser queuing system as a discrete time linear dynamic system. We develop a robust H∞ controller to regulate the queues of different users. The queues and Packet Drop Rates (PDR) are controlled by proposing a minimum data rate according to the demanded service type of each user. The data rate vector proposed by the controller is then fed as a constraint to an instantaneous resource allocation framework. This instantaneous problem is formulated as a convex optimization problem for instantaneous subcarrier and power allocation decisions. Simulation results show small delays and better fairness among users.