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APCC 2010 31 October - 3 November 2010 Langham Hotel, Auckland, New Zealand Youn-Soon Shin, Kang-Woo Lee and Jong-Suk Ahn Dongguk Univ.

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Presentation on theme: "APCC 2010 31 October - 3 November 2010 Langham Hotel, Auckland, New Zealand Youn-Soon Shin, Kang-Woo Lee and Jong-Suk Ahn Dongguk Univ."— Presentation transcript:

1 APCC October - 3 November 2010 Langham Hotel, Auckland, New Zealand Youn-Soon Shin, Kang-Woo Lee and Jong-Suk Ahn Dongguk Univ.

2 Table of Contents. Multiple Queues for IEEE Analytical Performance Model. Experiments. Conclusion. Introduction 2/17

3 Contributions and Motivations Two contributions –proposes multiple transmission queues for IEEE –investigates the effects of adopting the multiple queues for improving Quality of Service(QoS) Motivations – cannot prioritize important frames such as GTS requests –When a node wants to send data over a CFP it should reserve the CFP time slots by sending a GTS request frame with CSMA/CA during CAP intervals in advance –Our multiple queue model is one of the feasible platform candidates for time-sensitive applications such as medical/health- care systems CFP (Contention Free Period) GTS (Guaranteed Time Slot) 3/17 Introduction(1/2 ) CAP (Contention Access Period) CSMA/CA (Carrier Sensing Multiple Access/Collision Avoidance)

4 IEEE Standard alternates the sleep period and active period to minimize wasting energy Active period is further divided into –Contention Access Period which each node randomly chooses the sending time by CSMA/CA with BEB algorithm –Contention Free Period is slotted into small fixed GTS which a future sender should reserve in advance BEB (Binary Exponential Backoff) 4/17 Introduction(2/2 )

5 Differences from the previous models –Our model abstracts the multi-queue system faithfully where each node runs a scheduler resolving virtual collisions among its multiple queues –Our model further augments the conventional models by adding two important features of such as maximum transmission retries limit If a frame collides after max. number of retransmissions, it should be dropped. deferment behaviors When a frames transmission cannot be completed within a given CAP, the transmission should be delayed to the next CAP Previous models –can only evaluate networks where each node is assumed to keep sending frames of one traffic class among available traffic classes –do not include the deferment and transmission retries behaviors Differences from the Previous Models 5/17 Multiple Transmission Queues for IEEE (1/4)

6 Queue 0 Queue N -1 backoff module Contention Window Class N -1 Class 0 Scheduler to resolve virtual collisions backoff module Classifier MAC PHY Multiple Priority Queue Algorithm Once a frame arrives at the head of queue –the associated backoff module is executed Each queues transmission priority –is distinguished by associating different contention window parameters When the backoff timeouts of two or more different priority queues on the same node are the same, –the scheduler resolves this virtual collision by offering the right of channel access to the frame in higher priority queue For the other frames with the equal backoff delay, –scheduler invokes corresponding backoff modules to recalculate their new backoff delay because they are considered to collide virtually 6/17 Multiple Transmission Queues for IEEE (2/4)

7 Complete Markov Chain Block Diagram ( 1- p g,c ) successful 0 -th CSMA/CA with BEB and Deferment frame discard … a new frame arrival Idle qs g … 1-qs g qe g 1-qe g p g,c collision i -th CSMA/CA with BEB and Deferment R -th CSMA/CA with BEB and Deferment p g,c collision transmission (1-p g,c ) successful p g,c collision transmission abstracts CSMA/CA of running on class g with transmission retries limit When a frame of class g is generated with probability qe g from the idle state –node tries to transmit the frame by CSMA/CA with BEB algorithm A CSMA/CA with BEB and Deferment algorithm has three possible outcomes –Successful transmission –Collision runs the next CSMA/CA until the number of retransmissions reaches R where R represents the max. number of retransmissions –Frame discard A frame from class g should be dropped after max. of channel capture failure after (R + 1 )-th collision 7/17 Multiple Transmission Queues for IEEE (3/4)

8 g,j,-1 g,j,W g,j -2 g,j,0g,j,W g,j -1g,j,1 … 11 g,j-1,-1 1/W g,j Df (1- p d )α g pdpd 1 (1- p d )(1-α g ) 1-β g βgβg βgβg Df g,j,0,Rt-1 g,j,0,Rt-2 g,j,0,0 … pdpd Tx (b) (a) [Fig. 3] presents a discrete Markov chain describing the detail behaviors of each small box –labeled as i-th CSMA/CA with BEB and deferment in [Fig. 2] Deferment scheme –[Fig. 3-(a)] adds a small box labeled as Df –When a frames transmission cannot be completed within a given CAP with probability p d, the transmission of that frame should be delayed to the next CAP –It loops back to the current stage to pick up a new backoff delay when the subsequent CAP starts 8/17 Multiple Transmission Queues for IEEE (4/4) Discrete Markov Chain including Deferment Behaviors

9 Probabilities of Frame Discards and Collisions the collision probability two frame discard probabilities We modified the second term, to accommodate the effect of virtual collision resolution to exclude lower priority queues than class g in the same node from the competition over underlying physical channel. 9/17 Analytical Performance Model(1/3) previous models

10 Delay Model for with Multiple Queues the total delay taken to send a frame successfully including the delay wasted for discarded frames due to transmission retries 10/17 Analytical Performance Model(2/3)

11 Throughput Model for with Multiple Queues The successful transmission probability differs from the previous ones since they did not consider virtual collision resolution Higher priority frames should be transmitted before lower ones in the same node even though they have the same backoff delay Lower priority classes' transmission will not affect the throughput of higher priority class. The throughput of class g : the fraction of the time that spent on the channel for successful transmission of frames in a unit time span 11/17 Analytical Performance Model(3/3) previous models

12 Experiments ParameterValue Data, GTS request Frame Payload70 Bytes PHY + MAC header13 Bytes ACK11 Bytes Channel Bit Rate250 Kbps duty cycle100% macMinBE1,2,3,4 macMaxBE5 macMaxCSMA4 aMaxFrameRetries3 Superframe Order2,3,9 The simulation modules for are developed using ns Each classs priority is adjusted with macMinBE which determine the size of the contention window 12/17 Experiments(1/4)

13 Delay Variations due to Deferment [Fig. 4] illustrates the effect of deferments to the average channel access delay when the number of nodes and SO vary The value of SO determines the size of CAP interval The effect of deferments becomes apparent when SO is set to 3 or 2, leading to 14.5% difference of access delays at maximum from the model without deferments 13/17 Experiments(2/4) 14.5%

14 Access Delays of Single Queue, Class0, Class1 [Fig. 5] shows the effect of dual queues employed in , where the class 1 is for GTS request frames with higher priority and the class 0 is for data frames with lower priority macMinBE for class0and1 are set to 3 and 1, respectively This graph illustrates that class 1 takes much less average channel access delays by around 45% at maximum at the expense of 5% of delay increase over class 0 compared to the delays of the single queue system 14/17 Experiments(3/4) 45% 5%

15 Throughput of Single Queue, Class0, Class1 [Fig. 6] plots the throughputs as a function of offered load λ g when the nodes with dual queues contend for the wireless channel The throughput of the class 1 exceeds that of class 0 as the offered load becomes heavy while the throughputs of two classes are mostly the same when the load is light The throughputs evaluated by the analytical model are different by 7% at maximum from those of simulations 15/17 Experiments(4/4)

16 Summary and Future Plan This paper –expands the traditional model to incorporate multiple queues for supporting QoS services –proposes an enhanced analytical model for by including deferment behaviors and transmission retries –proves that the deferment and transmission retries behaviors should be included for accurate forecast of delays the multi-queue system can deliver data of higher priority classes rapidly without sacrificing the delays of lower priority classes Future research –develop the performance model applicable to bursty traffic 16/17 Conclusion

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