Chapter 2 Related Work
2.5 Discussion
Through the necessary simulations, as these mechanisms described above are designed in purpose, most of them reach the goal they were designed for. EDCA provides service differentiation which not provided by original DCF; AEDCF lower the collision rate and increase total throughput especially when the channel is highly load, compare to EDCA; AFEDCF performs better fairness between the same priority flows while maintaining high throughput and service differentiation; IDFQ provides higher total throughput of all flows than EDCA and service differentiation for different flows in proportion to their weights, while achieving weighted fairness between different priority flows, especially.
As to comparison under different consideration angle and different protocols, in total throughput, AEDCF, AFEDCF and IDFQ prefer better than EDCA, and AFEDCF prefers better than AEDCF. In the view of fairness, AFEDCF and IDFQ should prefer better than EDCA and AEDCF, but AFEDCF and IDFQ just achieve different kind of fairness because the method they adopted in protocols.
However, all the four mechanisms do not mention about absolute fair share of residual bandwidth among all applications, including flows of different priorities.
Even IDFQ provides only weighted fairness, i.e. relative fairness, regardless of usage or residual bandwidth. In other words, these mechanisms cannot provide global fairness. In fact, EDCA even perform better than AEDCF in this aspect.
Besides, no mechanism consider QoS demand in the aspect of transmission rate, which describes the real applications’ demand more precisely than to just define the priorities relationship. Guaranteeing that the high priority flows will get higher probability than lower priority flow may be not enough if the high priority flows demand is too high compare to the priority relation predefined, on the contrary, these
Table 2.5-1. Characteristic summation of QoS enhancement mechanisms
EDCA AEDCF AFEDCF IDFQ
Service differentiation based on priority
● ● ● ●
Service differentiation based on QoS satisfaction
○ ○ ○ ○
Total throughput improvement ○ ● ● ● Fairness between the same
priority flows
○ ○ ● ○
Weighted fairness between different priority flows
○ ○ ○ ●
Absolute fairness between all flows
○ ○ ○ ○
●: support, ○: not support
mechanism may be too unfair for the low priority flows, especially if the high priority flows’ demand are not far more the lower ones’. The characteristic analysis of mechanisms above is organized in Table 2.5-1. below.
According to the observations above, in the next chapter, I will introduce a new mechanism based on the satisfaction of applications’ transmission rate demand, and it will also achieve better global fairness among all the applications, while maintaining high total throughput.
Chapter 3
Satisfaction-based Media Access Control Scheme
In this chapter, the proposed media access control scheme is described, named Satisfaction-based Enhanced DCF (SEDCF). In the following, the description of SEDCF is separated to characteristic and assumption, parameters, and algorithm.
3.1 Characteristic and Assumption
SEDCF is capable of providing QoS guarantee for multimedia flows in the view of transmission rate satisfaction, and it ensures the global fairness among all flows while maintaining high total throughput.
In SEDCF concept, all the flows must provide their QoS demand by specifying their requirement transmission rate, not just specifying AC and get the information about priority relationships, and if the average transmission rate is higher than the required transmission rate previous defined, the flow is said to be satisfied. After a flow is satisfied, any other transmission of this flow is extra gift, regardless what AC this flow is. The concept of global fairness SEDCF provide is once the QoS flows are satisfied, the total residual bandwidth is shared fairly among all the flows, including QoS flows and best effort flows.
There are some assumptions and definitions below:
A) A node cannot transmit and receive frames simultaneously.
B) Mobility is not under consideration in SEDCF.
C) Every QoS flows must provide their QoS demand by specifying their
requirement transmission rate, not just specifying AC.
3.2 Parameters
Here are some basic parameters in SEDCF need to specify:
A) Usage
Usage means the bandwidth which s already used by a QoS flow, measure in transmission rate.
B) Minima Required transmission rate (MR)
Every QoS flow must specify MR, which represent the QoS level of this flow more precisely than just specifying AC. As to best effort flows, MR is set to be zero, that is, best effort flows are always considered to be satisfied.
C) Measuring Time Interval (Tupdate)
In every system defined Tupdate, the situations of bandwidth allocation of all flows are measured in share degree, defined below.
D) Smoothing Factor (α)
The smoothing factor is to adjust the portion of importance degree of latest estimated share degree, defined below.
E) Share Degree (SD)
In every Tupdate, Share Degree (SD) of every flow is computed. SD means how well this flow has been treated except the minima request, which also represent how much residual bandwidth this flow has used. The SD of flow i at measuring time interval j [ ] is computed by the following equation: SD ij flow i at measuring time interval j, respectively, and BW means the total j
network available bandwidth at measuring time interval j. The value is definitely between (-1, 1), and positive means the flow is satisfied at time interval j, while the negative value means the flow is not satisfied at j, which must be compensated later to ensure fairness.
j[ ]
Like measuring the network collision rate in AEDCF, in order to alleviate the impact of transient collisions, SEDCF also adopt EWMA mechanism to smoothen the estimated values. That is,
( )
1 interval j and j+1, respectively, and α is the smoothing factor here. The will be used in contention window adjustment and backoff timer decreasing procedure later.3.3 Algorithm
The SEDCF scheme is separate to two phases below: contention window adjustment and backoff timer decreasing procedure, while the detail algorithm is described in these sub-sections below.
3.3.1 Phase 1 – Contention Window Adjustment Procedure
As in EDCA, contention window needs to be adjusted only after a successful transmission or an unsuccessful transmission. Hence, the whole contention window adjusting procedure is shown as follows.
1) Adjusting CW after each successful transmission
After each successful transmission, say flow i, in the original EDCA concept, the value of contention window must be reset to CWmin[i], but in SEDCF, only the flows which are not satisfied yet ( is less than zero) have this right to do so and get more opportunity to transmit packet more, hoping for getting compensated. As to those flows which have already satisfied ( is larger than or equal to zero), basically, their contention window should be decrease slower than unsatisfied flows’
to release the transmission opportunity to other flow. Of course the decreasing potion of these satisfied flows’ CW should refer to their , CWmin[i] and CWmax[i]. Finally, the computed CW value should still be bounded between (CWmin[i], CWmax[i]), hence, the whale CW adjusting formula is derived below:
j [ ]
( )
2) Adjusting CW after each unsuccessful transmission
After each unsuccessful transmission, say flow i, on the contrary to the situation after successful transmission, as long as this flow is satisfied ( is larger than or equal to zero) now, its CW should be set to CWmax[i] to release the transmission opportunity to other flows. As to the unsatisfied flows ( is less than zero), although it should get more transmission opportunity, its CW still should increase to avoid further collision base on the basic concept of IEEE 802.11 MAC scheme. Hence, the CW of unsatisfied flows should increase slowly, and the increasing potion is computed according to their , CWmin[i] and CWmax[i]. Finally, the bounded procedure of CW is still necessary to keep CW would not be larger than CWmax[i]. The whale adjusting formula is in (16).
j [ ]
3.3.2 Phase 2 – Backoff Timer Decreasing Procedure
After the contention window is computed, if the flow i is in collision state or deferring state, the backoff timer should be randomly chosen from [1, 1+CW[i]] and start the decreasing procedure while sensing the channel is idle longer than AIFS[i], and the flow cannot attempt to transmit packet only after the backoff timer is decreasing to zero. Unlike AEDCF, in order to maintain the global fairness between all flows, even in backoff timer decreasing procedure, those unsatisfied flows ( is less than zero) should decrease their BT[i] faster to zero, which can make more opportunity to transmit next time. In SEDCF, the FCR mechanism is used on unsatisfied flows, which decreasing BT[i] exponentially, that is
j [ ]
average
SD i
(
averagej [ ] 0 , [ ])
[ ] / 2if SD i < BT i =BT i . (17)
As to satisfied flows ( is larger than or equal to zero), their BT[i]
decrease slowly than unsatisfied flows do, which the reason is that they have already get their minima request and should release the media to other flows. Hence their BT[i]
still decrease linearly as the EDCA mechanism, which the formula is
j [ ]
average
SD i
(
averagej [ ] 0 , [ ])
[ ]if SD i ≥ BT i =BT i −SlotTime. (18)
Chapter 4
Performance Evaluation
In this chapter, the performance evaluations of SEDCF, AEDCF and AFEDCF will be proposed by using ns-2 simulator [11].
4.1 Simulation Environment
Besides using ns-2 simulator, other simulation environment is described as follows. IEEE 802.11a is adopted as the PHY layer, and detailed parameters are listed in Table 4.1-1, including total data rate, Slot_time, which is significant to the proposed mechanism.
Because SEDCF, AEDCF and AFEDCF are proposed based on EDCA of IEEE 802.11e, all the parameters used in IEEE 802.11e MAC layer to provide service differentiation are in Table 4.1-2 for the general simulations later. We generate three classes of traffic in our simulations, i.e., phone, video, and best effort flows, respectively. These three types of flows represent the highest, the second, and the lowest priority, accordingly. All three classes of flows send data with constant data rates of 160 bytes per 20 ms, 1280 bytes per 10 ms, and 200 bytes per 12.5 ms, respectively. The simulation time is 12 seconds. We assume that all flows are backlogged during the simulation time. We set the QoS demands for phone and video flows are both 50% transmission successful rate. That is, to be satisfied, the minima transmission rate requirement for phone and video flows are 32 Kbps and 512Kbps, respectively. Furthermore, based on [4], the smoothing factor and Tupdate is set to 0.8 and 5000 Slot_time, accordingly.
In order to increasing the network load, the number of nodes will increase
gradually to simulation. All the nodes locate in the same Basic Service Set (BSS), and the diagram of the traffic is shown in Fig. 4.1-1, which is that every node sends three distinct flows to next node, and all the traffics are one-hop.
Table 4.1-1. Parameter settings of PHY layer
SIFS 16μs Preamble Length 20μs
RxTxTurnaround time 1μs PLCP header length 4μs
Table 4.1-2. Parameter settings of IEEE802.11e MAC layer
Parameters Phone
Figure 4.1-1. Simulation scenario
4.2 Performance Metrics
The performance metrics measured in the simulation include the network throughput, satisfaction index, and fairness index, which extended from [12] as defined below:
A) Network throughput (ϕ)
The summation of all flows’ Usage, i.e., ( ),
i
Usage i i F
ϕ=∑ ∀ ∈ , (19) where F is the set of all flows, Usage i( ) is the usage of flow i.
B) Satisfaction index (η)
It only counts for QoS flows and is used to indicate the satisfaction degree. Its definition is
MR i are the usage and the minima required transmission rate of flow i.
The concept is, say flow i, once , it is said satisfied, for satisfaction index, how much the media is over used by this flow is meaningless, so we do not have to consider to compute
[ ] [ ] Uasge i ≥MR i
( )
Usage i x ; while for the unsatisfied i flows, how much more the usage needs for them to satisfy is very important, for satisfaction index, and the closer x to 1, the closer this flow is satisfied. And i the final value of η is between 0 and 1 after indexing normalization. The larger the value η is, the better the overall satisfaction degree of QoS flows is.
C) Fairness index (κ)
It counts all flows and is to show how fair share about the residual bandwidth. Its definition is
MR i are the usage and the minima required transmission rate of flow i. On the contrary concept of satisfaction index, for any unsatisfied flow, the difference between its usage and its minima required transmission rate is not important, because fairness index is about residual bandwidth. As to satisfied flows, how much usage a flow over used is very significant, and the fairness we attempt is among all flows regardless of priority, so yi is not concern about MR i in [ ] denominator. The larger difference between all flows’ leads the worse fair share among all flows. After the indexing normalization, the final value of κ is also between 0 and 1. The larger the value κ is, the more fairly share of the residual bandwidth among all flows.
yi
D) Mean Delay (δ)
The mean end-to-end delay is the time difference of a QoS packet from source to destination, i. e.,
_ ( ), Mean Delay i i F
δ = ∀ ∈ (22) where F is the set of all flows, Mean Delay i is the average value of all the _ ( ) end-to-end delay of flow i.
4.3 Simulation Result
In order to understand the performance of SEDCF precisely, the simulation results will be apart to phase by phase. That is, in the following sub-section, I will propose the baseline comparison of those related works, performance comparison of SEDCF phase 1 vs. AEDCF, and then SEDCF phase 1 vs. SEDCF phase 1+2, SEDCF phase 1 vs. AFEDCF, the delay comparison, finally is SEDCF phase 1 vs. AFEDCF.
4.3.1 Baseline Comparison of Related Works
First of all, we propose the baseline comparison of related works, which is include EDCA, AEDCF and AFEDCF, and IDFQ is not included because it is based on WFQ, which is totally different concept from others.
Fig. 4.3-1 shows the throughput of EDCA, AEDCF and AFEDCF. We can see that the throughput lines increase before there are 15 nodes, and decrease after that, because after there are 15 nodes, the total available bandwidth is not enough to handle
0 500 1000 1500 2000 2500
5 10 15 20 25 30 35 40
Number of nodes
Overall throughput (KB/s)
EDCA AEDCF AFEDCF
Figure 4.3-1. Overall throughput of EDCA, AEDCF and AFEDCF
0.7 0.75 0.8 0.85 0.9 0.95 1 1.05
5 10 15 20 25 30 35 40
Number of nodes
Overall satisfaction index
EDCA AEDCF AFEDCF
Figure 4.3-2. Overall satisfaction index of EDCA, AEDCF and AFEDCF
all the traffic. After there are 15 nodes, AFEDCF performs outstandingly in the related works.
There are overall satisfaction index and overall fairness index comparison shown in Fig. 4.3-2 and Fig 4.3-3. In the overall satisfaction index, it includes all the QoS flows, which mean it does not include best effort flows. All the satisfaction indexes start to degrade after there are 20 nodes, and EDCA and AEDCF have no big difference while AFEDCF is the outstanding method (over 0.9 even when there are 40 nodes) again.
0 0.2 0.4 0.6 0.8 1
5 10 15 20 25 30 35 40
Number of nodes
Overall fairness index
EDCA AEDCF AFEDCF
Figure 4.3-3. Overall fairness index of EDCA, AEDCF and AFEDCF
As to overall fairness index, after there are 15 nodes, AEDCF performs worst in three protocols, while EDCA and AFEDCF performs overall satisfaction index over 0.4. AFEDCF performs satisfaction index about 0.6 by indirectly achieving inter class fairness after there are 30 nodes.
4.3.2 SEDCF phase 1 vs. AEDCF
Since SEDCF phase 1 and AEDCF are similar to adjust contention window by a periodically estimated factor, and neither adapt the original backoff timer decreasing procedure, we propose their performance comparison first.
The throughputs of SEDCF phase 1 and AEDCF are shown in Fig. 4.3-4. We found that SEDCF phase 1 has better video-type flow and overall throughput than that of AEDCF. The reason is we lower the sending failure rate of QoS flows by adjusting the CW of satisfied flows more flexibly. And the throughout of phone–type flow is maintained the same as that of AEDCF. Furthermore, as the number of nodes
0 500 1000 1500 2000 2500
5 10 15 20 25 30 35 40
Number of nodes
Throughput (KB/s)
Phone-SEDCF p1 Video-SEDCF p1 BE-SEDCF p1 Overall-SEDCF p1 Phone-AEDCF Video-AEDCF BE-AEDCF Overall-AEDCF
Figure 4.3-4. Throughput of SEDCF phase 1 and AEDCF
increasing, the throughput of phone-type flows keeps increasing; contrarily, the throughput of video-type flows starts to decreasing when the number of nodes is larger than 15. The reason is that in such a case that 15 nodes are backlogged to send data, the total required bandwidth to satisfy their QoS demands almost equals to the available bandwidth. Thus, more number of nodes, more number of the highest-priority flows (i.e., phone-type flows). In such situation, to guarantee phone-type flows’ QoS demands, best effort-type and even video-type flows should sacrifice to release some bandwidth.
0.7 0.75 0.8 0.85 0.9 0.95 1 1.05
5 10 15 20 25 30 35 40
Number of nodes
Satisfaction index
Phone-SEDCF p1 Video-SEDCF p1 Overall-SEDCF p1 Phone-AEDCF Video-AEDCF Overall-AEDCF
Figure 4.3-5. Satisfaction index of SEDCF phase 1 and AEDCF
Fig. 4.3-5 shows the satisfaction index of SEDCF phase 1 and AEDCF. We found both phone-type traffics of SEDCF phase 1 and AEDCF have same high value satisfaction index, however, the other satisfaction index of both SEDCF phase 1 and AEDCF are slightly decreasing while the number of nodes increase because the available bandwidth is no longer enough to satisfy the QoS demand of those Video-type flows. But because we take account of SD into CW adjustment, most of the flow satisfaction index of SEDCF phase 1 aggregate better than those of AEDCF, which leads the higher overall and video-type flow satisfaction index.
0
Figure 4.3-6. Fairness index of SEDCF phase 1 and AEDCF
The measured fairness index is shown in Fig. 4.3-6 Similar to satisfaction index, flows of phone-type have the best fairness index (more than 0.98) than others. As to the other flows of AEDCF, the fairness index is decreasing distinctly after the number of node is more than 15. While the other flows of SEDCF phase 1 have generally constant fairness indexes, which result from taking SD into account in adjusting CW provides well intra-class (local) and inter-class (global) fairness. But there is an exception while there are 25 nodes in topology, at this time, the available bandwidth can just no longer provide the video-type QoS demand (529.99 kbits/s per flow, which is very close to the require transmission rate 512 kbits/s per flow), which leads to the residual bandwidth of video-type flows distributed separately, and the fairness index is lower. But while the number of nodes keeps growing, the residual bandwidth of video-type flows aggregated soon although the QoS demand is no longer satisfied, so the fairness indexes afterward go back to higher value.
0
Figure 4.3-7. Throughput of SEDCF phase 1 and SEDCF phase 1+2
4.3.3 SEDCF phase 1 vs. SEDCF phase 1+2
After tuning of the contention window, the performance of adding the new backoff timer decreasing procedure should be evaluated. Fig. 4.3-7 shows the throughput comparison of SEDCF phase 1 and SEDCF phase 1+2. The phone-type flow throughput is still increasing gradually and stably while the number of node increase. As to video-type flows, after there are 20 nodes, the throughput of SEDCF phase 1+2 video-type flows start decreasing because of the total available bandwidth is running out for the total QoS demand of QoS flows, which makes the total throughput of SEDCF phase 1+2 reached high peak about 2200 KB/s, even higher than SEDCF phase 1 at all time. The reason is for the unsatisfied flows, SEDCF phase 1+2 provide even better protection by counting their backoff timer faster than satisfied flows, and since the best effort are always considered as satisfied, they can never benefited from the mechanism and start sacrifice to maintain QoS flows demand
0.7
Figure 4.3-8. Satisfaction index of SEDCF phase 1 and SEDCF phase 1+2
earlier, which makes the highest throughput ever.
The satisfaction index of SEDCF phase 1 and SEDCF phase 1+2 are shown in Fig. 4.3-8. SEDCF phase 1+2 also performs well at this part. The satisfaction indexes
The satisfaction index of SEDCF phase 1 and SEDCF phase 1+2 are shown in Fig. 4.3-8. SEDCF phase 1+2 also performs well at this part. The satisfaction indexes