IEEE 802.16 based last mile broadband wireless military networks with quality of service support

Wongthavarawat, Kitti; Ganz, Aura

doi:10.1109/milcom.2003.1290211

Cited by 110 publications

(71 citation statements)

References 10 publications

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“…Most proposed algorithms have applied some basic algorithms proposed in wired/wireless networks to WiMAX networks such as variations of RR and WFQ. For example, to schedule within a class, RR and WFQ are common approaches for nrtPS and BE and EDF for UGS and rtPS [52], [56]. The priority-based algorithm is commonly used for scheduling between the classes.…”

Section: A Channel-unaware Schedulersmentioning

confidence: 99%

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

So-In

Jain

Al-Tamimi

2009

IEEE J. Select. Areas Commun.

290

181

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Abstract-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.

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Section: A Channel-unaware Schedulersmentioning

confidence: 99%

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

So-In

Jain

Al-Tamimi

2009

IEEE J. Select. Areas Commun.

290

181

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“…As shown in our extensive survey of the IEEE 802.16e Mobile WiMAX schedulers [2], channel-unaware IEEE 802.16e schedulers have applied two techniques for UGS traffic: Weighted Round Robin (WRR), equally spread the allocation over all Mobile WiMAX frames (we call this averaging or AVG algorithm) and Earliest Deadline First (EDF) [3,4,5]. With the admission control, these techniques can achieve optimal throughput and meet deadlines; however, the delay jitter is not considered.…”

Section: Related Workmentioning

confidence: 99%

SWIM: A Scheduler for Unsolicited Grant Service (UGS) in IEEE 802.16e Mobile WiMAX Networks

2010

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Abstract. Most of the IEEE 802.16e Mobile WiMAX scheduling proposals for real-time traffic using Unsolicited Grant Service (UGS) focus on the throughput and guaranteed latency. The delay jitter and the effect of burst overhead have not yet been investigated. This paper introduces a new technique called Swapping Min-Max (SWIM) for UGS scheduling that not only meets the delay constraint with optimal throughput, but also minimizes the delay jitter and burst overhead.

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“…The UPS (Uplink Packet Scheduling) (Wongthavarawat and Ganz, 2003) and Deficit Fair Priority Queue (DFPQ) (Chen et al, 2005) employ service classes to meet differentiation and fairness. A simple mathematical approach for delay analysis for WiMax networks has been presented in (Sharieh et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

“…Petrinet approach to bandwidth allocation has been studied in (Raja and Kumanan, 2007). Liu et al (2005); Chen et al (2005) and Wongthavarawat and Ganz (2003) discuss complex schedulers such as Earliest Deadline First (EDF), Deficit Round Robin (DRR) (Shreedhar and Varghese, 1996), weighted fair queuing (WFQ) and worst case weighted fair queuing (W 2 FQ). Using a hierarchy of schedulers is a challenging task because per connection QoS must be translated into scheduler configuration at each level.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Bandwidth Allocation for Multiple Traffic Classes in IEEE 802.16e WiMax Networks: A Petrinet Approach

Geetha¹

2011

Journal of Computer Science

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Problem statement: WiMAX supports multiple types of traffic such as data, voice and video. Each flow requires a certain minimum bandwidth to achieve its QoS. Bandwidth allocation to traffic classes should be in such a way that fairness criteria is met with. Hence, we propose a dynamic bandwidth allocation mechanism to achieve fair and efficient allocation. Approach: We present a Generalized Stochastic Petri Net (GSPN) approach to model bandwidth allocation in Broadband Wireless Access (BWA) networks with multiple traffic classes. A dynamic weight assignment mechanism is proposed to enable fair bandwidth allocation among the competing traffic classes. Performance of the weight assignment mechanism is analytically evaluated using the GSPN model developed. Results: Results show performance improvement in terms of mean delay and normalized throughput of traffic classes compared to existing mechanisms. Simulation is carried out for different traffic rates. Analytical results are validated using simulations. Conclusion: Performance of the proposed system is evaluated in terms of mean delay and normalized system throughput. The model developed is generic and can be extended to any wireless network with multiple traffic classes.

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IEEE 802.16 based last mile broadband wireless military networks with quality of service support

Cited by 110 publications

References 10 publications

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

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

SWIM: A Scheduler for Unsolicited Grant Service (UGS) in IEEE 802.16e Mobile WiMAX Networks

Dynamic Bandwidth Allocation for Multiple Traffic Classes in IEEE 802.16e WiMax Networks: A Petrinet Approach

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