Admission Control for QoS Provision in Wireless Mesh Networks

Eduardo Pompeo da Silva Mineiro

MídiaCom Labs

Telecommunications Engineering Department

Federal Fluminense University

Niterói, Brazil

emineiro@midiacom.uff.br

Débora Christina Muchaluat-Saade

MídiaCom Labs

Computer Science Department

Federal Fluminense University

Niterói, Brazil

debora@midiacom.uff.br

Abstract— This work presents an admission control

mechanism for multi-hop wireless mesh networks based on the

IEEE 802.11 standard and the OLSR routing protocol. This

mechanism, called CAC-OLSR, aims at ensuring that traffic

flows with quality of service (QoS) requirements, especially

voice and video, are only admitted in the mesh network if it has

available resources in order to provide flow requirements. In

addition, QoS requirements of previously admitted traffic

flows cannot be violated. The proposal was evaluated with NS-

2 and Evalvid simulations.

Keywords-Quality of Service, QoS, admission control,

wireless mesh networks, OLSR, CAC-OLSR.

I. INTRODUCTION

Technological advances coupled with cost reduction have stimulated the implementation of wireless networks based on the IEEE 802.11 standard [1]. In addition, there is a growing trend in providing different services over IP networks, such as voice and video, which require a minimum level of quality of service (QoS). Some QoS mechanisms that have been widely disseminated and applied to wired networks need special treatment in wireless scenarios, especially because of bandwidth restrictions and huge channel quality variability.

Regarding quality of service in IEEE 802.11 wireless networks, it is important to consider the IEEE 802.11e amendment [2], which was incorporated into the original standard in 2007. This amendment established four traffic categories with different channel access priority, through the configuration of some parameters such as frame spacing, contention window size and transmission opportunity.

However, only traffic differentiation based on channel access priority is not sufficient to guarantee the quality of service required by some multimedia applications. For example, it does not avoid traffic congestion when many flows of the same access category are injected in the network. This will probably generate delay increase and throughput decrease observed by each flow.

In the case of voice transmission, for example, in order to guarantee quality of calls, network capacity must not be violated [3]. Unfortunately, this condition is not always satisfied when applying traffic differentiation only.

In this context, it is necessary to provide an admission control mechanism, which should be responsible for the entry of new network flows so that the quality of service required by them is met, without violating the requirements demanded by previously admitted flows.

The IEEE 802.11 standard suggests an admission control mechanism for wireless networks operating in the infrastructure mode. On the other hand, it does not define any admission control mechanism aimed at wireless mesh networks, where nodes communicate in ad hoc mode using multiple wireless hops.

This paper proposes an admission control mechanism for multi-hop wireless mesh networks based on the IEEE 802.11 distributed access mode. The proposed mechanism, called CAC-OLSR, is an extension to the OLSR [4] routing protocol (Optimized Link State Routing), which is widely used in wireless mesh networks [5, 6].

In addition to admission control, CAC-OLSR has the ability to reserve channel time resources for voice and video access categories. If those reserved resources are not fully used, they can be destined to other access categories in order to optimize network resource use.

The rest of the paper is structured as follows. Section II discusses related work. Section III proposes CAC-OLSR, an admission control mechanism for wireless mesh networks. Section IV presents a performance analysis through simulations made in Network Simulator (NS-2) [7]. Finally Section V covers the conclusions and future work.

II. RELATED WORK

The work of Yang and Kravets [8], referenced in many articles on the subject, proposed an admission control for ad hoc networks based on channel occupation. In summary, each node decides about the admission of a new flow by comparing the estimated occupation of the channel caused by the incoming traffic to the available channel resources, measured by carrier detection. If the former is smaller than the latter, the flow can be admitted.

In another article [9], Chakeres and Belding-Royer used the same principle of Yang and Kravets [8], but proposed a zone extension to be considered by each node when

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measuring channel occupation. This is due because of "hidden terminals", which can lead to false admissions. Both works did not take into account the IEEE 802.11e access categories. Also, they did not detail how their mechanisms would work in a multi-hop network.

Chakeres and Belding-Royer [9] suggested an association with reactive routing protocols, where the admission of new flows occurs during the route discovery process, but they did not mention how the mechanism could be applied to proactive protocols like OLSR [4]. Also, they did not consider intraflow interference, which will be addressed in the next section.

Lindgren and Belding-Royer [10] presented a treatment approach for intraflow interference. They proposed a factor called contention counter, which must be applied during the resource estimation to be consumed by a new flow. That work also proposed the admission control process during route discovery, a fact that excludes the application of the mechanism in networks whose routing protocol is proactive, such as OLSR [4]. They did not take into account the IEEE 802.11e access categories.

Ahn et al. [11] proposed a mechanism called SWAN, which means Service Differentiation in Stateless Wireless Ad Hoc Networks. SWAN does not depend on a specific routing protocol. It uses rate control for UDP and TCP best effort traffic, and sender-based admission control for UDP traffic. The admission control is always executed by the source node, which sends a probe to the destination node in order to check the available bandwidth in the network and to compare it with the bandwidth required by the new flow. SWAN did not take into account the IEEE 802.11e access categories.

Cerveira and Costa [12] proposed an extension to the AODV protocol [13] adding an admission control mechanism similar to those mentioned so far. However, it differentiates the channel time occupation between QoS and best-effort traffic, ignoring the latter in the process of admitting new flows. Through that strategy, best effort traffic will only occupy network resources not used by flows that demand QoS. The authors also considered the use of IEEE 802.11e access categories and assumed that best effort traffic uses TCP as the transport protocol. They also presented a treatment for intraflow interference.

Nguyen and Minet [14] presented an admission control proposal for the OLSR protocol [4]. In fact, the article proposed a modified version of OLSR, which considered bandwidth allocation and channel interference for route selection, besides admission control. The latter is based on two steps: feasibility and acceptability. In the first step, the incoming traffic node compares the bandwidth required by the flow with the available bandwidth on each node of the path (the available bandwidth of each node is disseminated via Hello messages). If the required bandwidth is smaller than the smallest available bandwidth among all nodes in the path, the flow may be accepted. In the acceptability step, there is a check for the interference caused by the new flow

in the vicinity of the nodes along the path. The proposal neither considered IEEE 802.11e, nor addressed the issue of intraflow interference.

Badis and Agha [15] proposed an admission control for the QOLSR [16] protocol. The scheme is based on sending preliminary messages called Check Request (CREQ) and Check Reply (CREP), which carry the incoming flow requirements in terms of bandwidth, delay and jitter. Each node in the path checks whether or not such requirements can be met and forwards the message along only in the positive case. If the CREQ node source receives a CREP, the corresponding flow is accepted. That work dealt with intraflow interference, but did not consider IEEE 802.11e.

As far as it was possible for the current work to investigate, the mechanism that will be presented in the following section is the first admission control mechanism, to be proposed for a proactive routing protocol, that addresses all the following features: considers a wireless network composed of multiple hops; considers the IEEE 802.11e access categories; presents a treatment for inter and intraflow interferences and deals with QoS violation.

Besides all the features above, this paper considers the reservation of channel time resources for voice and video access categories. If not used, those resources can be used by other categories. This is important because if it is not considered and, for example, the network capacity is fully used by previously admitted video flows, the admission control mechanism might not allow new voice flows, even though they belong to the highest priority category. CAC-OLSR, in this case, would stop the latest admitted video flow in order to admit voice traffic until the reserved resources for the voice category was reached. This issue is a new insight into the admission problem, as far as it was not considered by any of the mentioned related works.

III. CAC-OLSR

The CAC-OLSR proposal, which means Call Admission Control OLSR, uses as main criterion for flow admission the comparison between current channel time occupation and the estimated occupation demanded by a new flow. Furthermore, it uses the IEEE 802.11e access categories, treats inter and intraflow interference and deals with QoS violation.

In order to facilitate the mechanism understanding, this section is structured as follows. Section A presents the channel occupation measurement method, while Section B shows how the estimated occupation demanded by a new flow is done. Section C describes how inter and intra flow interferences are treated. QoS violation is discussed in Section D and Section E presents the admission policy.

A. Channel Occupation Measurement

In order to measure channel occupation, carrier detection is observed for a given period of time. This can be done in IEEE 802.11 by monitoring a function called PHYCS – PHY carrier sense, which indicates if the channel is idle or busy.

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However, this work proposes that channel is considered busy only if it is used by QoS traffic (voice and video). In other words, channel must be considered idle during transmission or reception of traffic without QoS (best effort and background). This strategy was adopted to prevent non-admission of QoS flows because of channel occupation with traffic without QoS. It is considered here, as adopted in [12], that the lower channel access priority and the use of TCP will automatically reduce best effort and background traffic category throughput in the presence of QoS traffic.

In summary, channel occupation measurement observes carrier detection periodically during a certain period (100 ms by default) and returns the percentage occupation caused by frames belonging to voice and video access categories. If the frame access category can not be identified, that frame is also considered for channel occupation measurement.

B. Channel Occupation Estimation for a New Flow

Channel occupation for a new flow can be estimated if the time required for one single frame transmission and the flow frame rate are known.

Based on IEEE 802.11, the time required to successfully transmit a frame, without RTS and CTS [1] procedures, is given by Equation (1).

Tframe = Data + SIFS + ACK + AIFS + Backoff (1)

In Equation (1), "Data" is the time required for a single data frame transmission; SIFS is the interframe spacing before an ACK transmission, which corresponds to the acknowledgment of the data frame previously sent; AIFS is the interframe spacing before the transmission of another data frame, depending on its access category. Finally, Backoff represents the time wasted with the contention process as described in IEEE 802.11.

SIFS and AIFS values can be easily obtained in IEEE 802.11 recommendations. Moreover, Data and ACK transmission time can be calculated with the frame size and transmission rate information.

Backoff time can be estimated based on the contention window average value multiplied by the duration of a time slot, which can also be obtained in IEEE 802.11 standard.

After estimating the time required for one data frame transmission (Equation 1), it is necessary to check the amount of frames sent by a given flow during an observation period. As a result, it is possible to estimate the percentage channel time occupation that will be consumed by that flow.

C. Interference

1) Interflow Interference

It is considered as interflow interference, one that happens among two or more different flows that compete for channel access. The correct treatment of this type of interference is very important to ensure that the admission of a new flow neither will interfere with previously admitted flows, nor will violate their QoS requirements.

To mitigate this problem, it is necessary to verify the available resources in terms of channel availability, both in the nodes along the path of the new flow, as well as in their neighbors that are located in the interference region.

CAC-OLSR combats interflow interference by propagating channel occupation observed by each node via OLSR Hello messages [4]. Each node that receives a Hello message stores the channel occupation information in its one and two-hop neighbor tables, which are already maintained by OLSR. This proposal considers that a node interference region consists of its one and two-hop neighbors only.

Thus, each node along the path can verify whether it has, as well as its one and two-hop neighbors have, the necessary resources to meet the new flow demand during the admission control process.

2) Intraflow Interference

Intraflow interference happens when nodes that forward packets of the same flow are interfering with each other. This will probably cause flow throughput decrease, even though each individual node has enough channel resource availability. To illustrate this phenomenon, Figure 1 shows a scenario where node 1 is transmitting a flow to node 5.

The filled circles represent the data transmission or reception range for each node, while the dashed one represents the carrier sensing range for node 3. Observe that node 3 is in the detection region of nodes 1, 2, 4 and 5, which prevents it from transmitting simultaneously with any of them. As a result, free time channel available resources should be reduced by a factor of 5. Thus, it is necessary to compute at each node, the number of nodes involved in the intraflow interference region in order to correctly estimate the resources that will be demanded by a new flow.

CAC-OLSR protocol considers that intraflow interference should be estimated by calculating a factor called Contention Counter (CC) [10]. This factor sums, in each node, the number of nodes belonging to the intraflow interference region, limited to a maximum of 5, i.e., the previous two, the two latter and the node itself. For example, the CC factor of node 3 in Figure 1 equals 5.

1

2

3

5

4

Figure 1. Intraflow interference.

Finally, this factor should be applied to estimate channel time occupation demanded by a new flow. For example, if after applying the method described in Section B, a value of 5% of occupation was reached, each node along the path must consider that the flow will consume 5% * CC of channel time capacity.

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D. QoS Violation

An admission control mechanism must deal with QoS violation, which may happen, for example, because of false admissions, node mobility, changes in a node neighborhood or due to variations in signal propagation conditions.

In CAC-OLSR, every node periodically monitors channel occupation with QoS flows. If one of them detects that occupation is greater than a threshold called “Violation Threshold”, the network is near congestion and one or more flows need to be stopped.

In this case, CAC-OLSR first checks if the reserved resources for video access category was violated. If so, an ICMP message is sent to the source node of the last admitted video flow in order to stop it. If not, voice access category reserved resources were violated. Then an ICMP message is sent to the source node of the last admitted voice flow in order to stop it. Figure 2 illustrates the proposed QoS violation mechanism.

Figure 2. QoS violation mechanism.

In order to avoid synchronization, each node starts to check channel occupation in a different time. Moreover there must be an interval of, at least, the observation period (100 ms) between measurements for resource update purposes.

The “Violation Threshold” must be a value greater than the one used by the admission control algorithm to admit new flows. Also, it must be neither too low to avoid unnecessary flow interruptions nor too high to avoid QoS violation.

E. Admission Policy

The admission policy includes the criteria to be used to decide if a new flow can be admitted in the network. These criteria are based on definitions and proposals presented in the previous sections. To make it clearer, Figure 3 shows a simplified flowchart of the proposed mechanism, which is explained below.

Upon receiving a data packet, CAC-OLSR checks whether it was originated in a client of the mesh node itself. If not, the packet is normally routed as in the original OLSR. Included in this action is the premise that if a node receives a packet to be forwarded, then it has already passed through the admission process at the source mesh node and therefore should be immediately forwarded.

If the packet was originated in a client of the mesh node itself, then it checks if it has associated QoS, i.e., whether it will be forwarded as voice or video categories. This checking

is done by consulting the IP header ToS (Type of Service) or DSCP (Differentiated Services Code Point) field. The ToS/DSCP value is used to map the packet to the appropriate IEEE 802.11e access category [2].

Figure 3. Admission flowchart.

If the packet does not demand QoS, i.e., if it belongs to best effort or background categories, then it should be normally forwarded, unless channel occupation with QoS traffic is over a configurable threshold. This threshold must be smaller than the “Violation Threshold”, as seen in the previous section. If channel occupation with QoS traffic is greater than the threshold chosen, the packet is discarded, avoiding network congestion.

It is important to observe that traffic without QoS will pass through CAC-OLSR admission control mechanism only if the network is not congested. That traffic lower channel access priority and the use of TCP in most cases regulate traffic injection into the network by itself.

Back to the flowchart in Figure 3, if the flow has associated QoS (voice and video categories), then the source mesh node will check whether it has previously been admitted and still has an entry in the admission table. If so, the packet is immediately sent. If not, a new admission process is started.

In fact, before starting a new admission process, it checks if the flow has already been rejected within a minimum time interval required for a new admission process to be initiated. If so, the flow should again be rejected.

It is worth to notice that it was necessary to create a flow table in each node database with the admission, accepted and rejected flows. Each entry in that table has a timer. Flows without packet transmission for a given time will be excluded and will have to pass through the admission process again. Rejected flows will remain on the table until the timer times out and a new admission attempt will not be allowed for them during this period.

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After the previous step, the node checks if channel occupation with QoS traffic is smaller than the threshold value and if it is smaller than the reserved resources value for the access category of the new flow. If both conditions are not satisfied, the flow must be rejected. On the other hand, if one of them is met the node sends a CREQ – Check Request – message, which must be answered by the destination with a CREP – Check Reply. It is import to notice that if only the second condition is met and the channel occupation with QoS traffic is higher than the threshold, it means that the other access category exceeded its reserved resources and its latest flow must be interrupted (QoS violation).

CREQ and CREP aims at avoiding inter and intraflow interference problems, as already explained. Each node in the path, upon receiving a CREQ, checks the channel occupation perceived by itself and all its one and two-hop neighbors. Those occupations are compared to the value estimated for the new flow, which includes the CC factor. If the node itself or any of its neighbors has no available resources, CREQ should be discarded. On the other hand, if all nodes have the necessary resources, CREQ must be forwarded to next node in the path until the destination node is reached.

The destination node must process CREQ and send a CREP, which will cross the path in the reverse way. Again, each node will check for available resources before forwarding CREP. If the source node receives CREP, it will process the message and finally admit the flow if it has available resources. The source node has a timer for receiving the corresponding CREP. After timeout, the flow is considered rejected.

IV. PERFOMANCE ANALYSIS

In order to analyze the performance of CAC-OLSR, simulations were done using Network Simulator - NS-2 version 2.34 [7] and Evalvid [20]. The results were compared with the standard OLSR protocol [4] and with SWAN [11] admission control mechanism. SWAN [11] was chosen because an RFC draft was written based on it and because its NS-2 code was available [17].

A. Simulation Scenario

For evaluation of CAC-OLSR, a mesh network scenario composed of 10 nodes randomly placed in an area of 500m x 500m was configured in NS-2 [7]. The random position was provided by the setdest tool, available in NS-2.

All simulations described here were performed using the standard OLSR protocol, CAC-OLSR and SWAN control admission mechanism.

As the NS-2 version employed did not have an implementation of OLSR, the code developed by the University of Murcia, UM-OLSR, version 0.8.7 [18], which is totally adherent to RFC 3626 [4], was used.

The IEEE 802.11e access categories were considered only for OLSR and CAC-OLSR evaluation, since SWAN did not consider them. These access categories were

developed for NS-2 by TKN group [19] and the parameters for each one were set up according to the IEEE 802.11 standard suggestion [1].

All simulations were done without the use of RTS/CTS [1]. All scenarios used IEEE 802.11g in ad-hoc mode and the TwoRayGround propagation model. The transmission range was set to 250 m, while the carrier sensing range, to 550 m.

Network traffic was generated as follows: to model voice and video flows, two CBR (Constant Bit Rate) traffic sources were respectively implemented, one with 160-byte packet size sent every 20ms (64 Kbps) and another with 1280-byte packet size transmitted every 10ms (1024 Kbps). Best effort and background traffic were modeled as FTP with 1300 and 1500-byte packet sizes respectively. At each 20s, a new flow from each type (voice, video, best effort and background) was randomly injected in the network. The first four flows, however, began after 30s of simulation, to ensure the correct routing protocol convergence. The total simulation time was 431s. The threshold values adopted were 95% for QoS violation and 90% for the admission process. The reserved channel time resources values for QoS categories were 55% for voice and 35% for video.

For each simulation, the following metrics were computed: average end-to-end delay, average throughput per flow and average aggregate throughput. In addition to these metrics, the average number of admitted flows and the additional control overhead injected into the network were also measured for CAC-OLSR.

A second test was done in order to evaluate the quality of a real video transmission. The same scenario described above was set in NS-2 with some differences in the network traffic. In this test, one flow from each type (voice, video, best effort and background) was injected every 10s, starting after 30s. Besides that, a real video called “News” [20] was injected after 50s. “News” is a QCIF video with average throughput of 310 Kbps and duration of 12s. This video was encoded and prepared for transmission in NS-2 using Evalvid tool set. The video was repeated four times, so it lasted 48s. Source and destination was randomly selected. In the destination, each received video frame PSNR was calculated and converted to a MOS grade.

Finally, for the purpose of evaluating CAC-OLSR QoS violation recovery, a particular scenario was employed, as showed in Figure 4.

Figure 4. QoS violation recovery scenario.

Voice and video flows, with the same traffic model defined before, were started every 20s from nodes 0 and 3 to

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nodes 2 and 5 respectively. Nodes 0 to 2 and 3 to 5 were separated by a distance of 1000 m. After 300s of simulation, nodes 3 to 5 moved horizontally and stopped 10 m away from nodes 0 to 2. Average end-to-end delay was measured.

B. Results

The results were obtained from an average of 30 simulations for each mechanism, SWAN, OLSR+802.11e and CAC-OLSR+802.11e, with a 95% confidence interval.

1) Average End-to-end Delay

This metric considers the average end-to-end delay suffered by packets sent in each 20s interval. Figures 5 and 6 show average delay results for voice and video flows.

Observing Figure 5, it can be seen that voice flows average delay reached almost 15s with the OLSR+802.11e and 25s with SWAN. On the other hand, CAC-OLSR was able to keep average delay of all voice flows bellow 150ms, an acceptable value for voice applications. Considering video flows, CAC-OLSR maintained the delay below 500ms.

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Figure 5. Average end-to-end delay for voice flows.

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Figure 6. Average end-to-end delay for video flows.

2) Average throughput per flow

The average throughput per flow corresponds to the average bits per second transmitted per flow at each 20s interval. Figures 7 and 8 show throughput results for voice and video flows.

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Figure 7. Average throughput per flow for voice flows.

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Figure 8. Average throughput per flow for video flows.

Only CAC-OLSR was able to deliver the required average throughput per flow, i.e., 64 Kbps for voice and 1024 Kbps for video.

3) Average aggregate throughput

The average aggregate throughput corresponds to the average bits per second transmitted by all traffic flows at each 20s time interval. Figure 9 shows the average aggregated throughput for QoS traffic, while Figure 10 shows throughput for non-QoS traffic.

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Figure 9. Average aggregate throughput for QoS traffic.

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Figure 10. Average aggregate throughput for non-QoS traffic.

In the case of aggregate throughput for QoS traffic, CAC-OLSR presented the best result, as shown in Figure 9, probably because of less time spent with MAC retransmissions. For non-QoS traffic, as shown in Figure 10, CAC-OLSR also presented better results, although after 271s the average aggregate throughput remained below 50 Kbps for all mechanisms.

4) Admitted Flows

Figure 11 shows the average number of voice and

video admitted flows. OLSR+802.11e does not have an

admission control mechanism. So, with 431s of simulation,

there were 21 voice and 21 video flows in the network.

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Figure 11. Admitted Flows.

SWAN admitted an average of 9 voice and 11 video flows. As SWAN could not satisfy QoS metric requirements for all flows, it admitted more flows than network capacity was able to support. This is probably due to the fact that the mechanism does not consider traffic between transmission and carrier sensing ranges when admitting a new flow.

CAC-OLSR admitted an average of 8 voice and almost 2 video flows after 431s of simulations. In addition to satisfying QoS requirements for all admitted flows, CAC-OLSR also presented better results in terms of aggregate throughput. So, the proposed mechanism admitted an appropriate number of flows.

5) Admission Control Overhead

One concern about adopting CAC-OLSR is the

additional overhead introduced into the network, mainly

because of CREQ and CREP messages. However, as shown

in Table I, this increase was, on average, less than 6%

considering the number of packets. Considering an average

of 8343.10 control packets sent by CAC-OLSR, 464.57

were CREQ or CREP messages, which represent 5.57% of

the total. It is noteworthy that the other packets are usually

sent by the original OSLR protocol [4] (Hello, topology

control messages - TC, among others). With respect to the

additional amount of bytes injected into the network

because of CREQ and CREP, the simulations showed an

increase of only 4.04%.

TABLE I. CAC-OLSR ADITIONAL OVERHEAD

Description CREQ or CREP Control Packets %

Sent Packets 464.57 8343.10 5.57%

Amount of bytes 44311.40 1097641.40 4.04%

6) Real Video Transmission

Using the Evalvid tool set,, the percentage number of

frames classified in each MOS grade was calculated.

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Bad (1) Poor (2) Fair (3) Good (4) Excelent (5)

Figure 12. Received frames per MOS.

As shown in Figure 12, CAC-OLSR presented the best

results, with almost 100% of received frames classified as

“Excellent”, as the original video. On the other hand, OLSR

received only 30% of the frames as “Good” and “Excelent”,

while SWAN received most of frames with “Bad” quality.

7) QoS Violation Recovery

The scenario proposed to evaluate QoS violation recovery, as previously described, is extremely severe. The two groups of nodes are put together when each one has almost 100% of its channel resources consumed by voice and video flows. This evaluation was done only with CAC-OLSR, with and without the QoS violation recovery mechanism.

Figures 13 and 14 showed that with the QoS violation recovery, voice and video end-to-end average delay were reestablished after a severe neighborhood change. The same did not happen without the violation mechanism.

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Figure 13. Average end-to-end voice delay.

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Figure 14. Average end-to-end video delay.

V. CONCLUSIONS

This paper presented CAC-OLSR, an admission control mechanism for IEEE 802.11e wireless mesh networks, using the OLSR routing protocol. The proposal considered available channel time resources in order to admit a new flow and presented an approach to deal with inter and intraflow interferences. CAC-OLSR also dealt with QoS violation and provided the ability to reserve channel time resources for voice and video access categories.

Performance results provided by CAC-OLSR were quite satisfactory compared to those produced by SWAN and by the original OLSR protocol using the IEEE 802.11e access categories. There was a significant reduction in the end-to-end average delay and an increase in the aggregate throughput. Moreover, CAC-OLSR was able to maintain the throughput demanded by voice and video flows. The additional-control-byte overhead introduced by the admission mechanism was less than 5%.

As future works, CAC-OLSR is going to be implemented in openwrt-based mesh routers in order to be evaluated in a real network. Also, scalability needs to be investigated in a scenario with a large number of mesh nodes and flows, as well as the mechanism´s behavior with node mobility. Another future work is the improvement of channel occupation estimation for a new flow using a statistical approach.

REFERENCES

[1] IEEE P802.11-2007 IEEE Standard for Information Technology Telecommunications and Information Exchange between Systems - Local and Metropolitan Area Networks - Specific Requirements - Part 11: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications. June 2007.

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[3] Conceição, A. F., Li, J. and Florêncio, D. A., “Voice transmission over IEEE 802.11 networks: main issues and restrictions”, in WebMedia '06 Proceedings of the 12th Brazilian Symposium on Multimedia and the web, Natal-RN, Brazil, November 2006.

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