RESULTADOS OBJETIVO 3

Most of the legacy scheduling algorithms can be classified into this category. We will only discuss those that have been proposed and evaluated in WiMAX. Weighted Round Robin (WRR) and Deficit Round Robin (DRR) algorithms are evaluated on a WiMAX system in [12]. WRR is evaluated for the uplink traffic while DRR is evaluated for the downlink traffic. WRR is an extension of the Round Robin (RR) algorithm. It is a work-conserving algorithm in that it will continue allocating bandwidth to the SSs as long as they have backlogged packets. The WRR algorithm assigns weight to each SS and the bandwidth is then allocated according to the weights. The algorithm was originally proposed for ATM networks that have fixed size packets [13]. Since the

WRR [12] EDF+WFQ+FIFO [23] Cross-Layer [27] DRR [12] EDF+WFQ [24] O-DRR [28] EDF [15], [17] WRR+RR [25] Queuing-Theoretic [29] OFDMA scheduler [30] WFQ [15] WF2_{Q [19]} Modified EDF [22] MWFQ+MWRR+FIFO [26] TCP-traffic scheduler[31]

bandwidth is assigned according to the weights only, the algorithm will not provide good performance in the presence of variable size packets. It has been discussed in [12] that weight to a SS can be assigned to reflect its relative priority i.e. a higher weight assigned to SSs of the rtPS class compared to the weight assigned to SSs of the nrtPS and BE classes. DRR, a variation of RR, is also a work-conserving algorithm with a constant processing time [14]. DRR is similar to the RR algorithm in that a quantum of service is assigned to each SS. The difference between the two algorithms is that when a SS is not able to send a packet, the remainder quantum is stored in a deficit counter. The value of the deficit counter is added to the quantum in the following round. The algorithm is flexible enough as it allows provision of quanta of different sizes depending on the QoS requirements of the SSs. DRR is mostly suited for datagram networks where packet sizes vary. Since the DRR algorithm requires accurate knowledge of packet size, it is not suitable for the uplink traffic.

N. Ruangchaijatupon et al. [15] evaluate the performance of the Earliest Deadline

First (EDF) algorithm. EDF is a work conserving algorithm originally proposed for real- time applications in wide area networks [16]. The algorithm assigns deadline to each packet and allocates bandwidth to the SS that has the packet with the earliest deadline. Deadlines can be assigned to packets of a SS based on the SS’s maximum delay requirement. The EDF algorithm is suitable for SSs belonging to the UGS and rtPS scheduling services, since SSs in this class have stringent delay requirements. Since SSs belonging to the nrtPS service do not have a delay requirement, the EDF algorithm will schedule packets from these SSs only if there are no packets from SSs of UGS or rtPS

class. With a large number of SSs from the UGS or rtPS class, SSs from the nrtPS or BE class can potentially starve.

T. Tsai et al. [17] propose an uplink scheduling algorithm and a token bucket

based Call Admission Control (CAC) algorithm. The CAC algorithm assigns thresholds to each class to avoid starvation of lower priority classes. The EDF scheduling algorithm is used for the rtPS class. The scheduling algorithm first grants bandwidth to SSs of the UGS class. The algorithm will then allocate bandwidth to SSs of the rtPS class using the EDF algorithm and restricting the allocation to the maximum grant size. Finally, the algorithm will allocate minimum required bandwidth to SSs of the nrtPS and BE classes in order. Each SS is controlled by a token rate and bucket size. A mathematical model is proposed that estimates the appropriate token rate based on the queuing delay and the packet loss requirements, for both finite and infinite queue length.

N. Ruangchaijatupon et al. [15] also evaluate Weighted Fair Queuing (WFQ) for

the uplink traffic in WiMAX. WFQ is a packet-based approximation of the Generalized Processor Sharing (GPS) algorithm [18]. GPS is an idealized algorithm that assumes a packet can be divided into bits and each bit can be scheduled separately. This is an impractical assumption since a packet needs to be scheduled in its entirety. WFQ is a practical implementation of GPS as it assigns finish times to packets and selects packets in increasing order of their finish times. The finish times of packets of a SS are calculated based on the weight assigned to the SS and the size of the packets. The WFQ algorithm results in superior performance compared to the WRR algorithm in the presence of variable size packets. The finish time of a packet is essentially the time the packet would have finished service under the GPS algorithm. The disadvantage of the WFQ algorithm

is that it will service packets even if they wouldn’t have started service under the GPS algorithm. This is because the WFQ algorithm does not consider the start time of a packet.

Y. Shang and S. Cheng in [19] propose a hierarchical model for packet scheduling based on the proposal of J. Bennet and H. Zhang in [20]. The model is comprised of three scheduling servers: a hard-QoS scheduling server, a soft-QoS scheduling server and a best effort scheduling server. The UGS traffic is mapped to the hard-QoS server and the rtPS traffic is mapped to the soft-QoS server. The nrtPS traffic can be mapped to either the soft-QoS server or the best effort server. All the servers implement the Worst-case Fair Weighted Fair Queuing (WF2Q) scheduling algorithm [21]. WF2Q is another extension of GPS that addresses the issue of the WFQ algorithm servicing packets even if they wouldn’t have started service under the GPS scheme. O. Yang and J. Lu in [22] propose a joint CAC and scheduling algorithm based on the concept of EDF to satisfy the QoS requirements of real-time video applications in IEEE 802.16 networks. The algorithm claims to cover throughput requirement, delay constraint and maintain fairness among the SSs simultaneously.