QoS Routing and Scheduling in TDMA basedWireless Mesh Backhaul Networks

Chi-Yao HongDept. of Comp. Sci. & Info. Engr.

National Taiwan UniversityTaipei, 106, Taiwan, R.O.C.

Email: cyhong@newslab.csie.ntu.edu.tw

Ai-Chun PangGraduate Institute of

Networking and MultimediaDept. of Comp. Sci. & Info. Engr.

National Taiwan UniversityEmail: acpang@csie.ntu.edu.tw

Jean-Lien C. WuDept. of Electronic Engr.

National Taiwan University of Sci. and Tech.Taipei, 106, Taiwan, R.O.C.

Email: jcw@mail.ntust.edu.tw

Abstract— With the advance of wireless technologies, wirelessmesh backhaul networks (WMBNs) are emerging an alternativeto conventional wired backbones for metropolitan areas. Asreal-time applications (e.g., voice over IP and video streaming)rapidly grow, provisioning quality-of-service (QoS) guarantees isone of the most important issues for WMBNs. In this paper,we consider the QoS problem for routing and scheduling inTDMA-based WMBNs. We propose an integrated routing andscheduling mechanism to provides QoS guarantees to real-timeservices with unrestricted topologies for TDMA-based WMBNs.A linear programming optimization is devised to solve the amountof non-collision bandwidth for a path according to the availableresource and the interference. A simulation model is developedto investigate the performance of our proposed mechanism.Through the developed simulation, a series of experiments areconducted to show the capabilities of our proposed mechanism.

I. INTRODUCTION

With the advance of wireless technologies, wireless meshbackhaul networks (WMBNs) are emerging an alternative toconventional wired backbones for metropolitan areas. Com-pared with the wired networks, WMBNs are more reliable,scalable, cost-effective, and can be easily built in the areaswhere the deployment of the wired backhaul is difficult orcost-prohibitive [1]. Figure 1 depicts an example of WMBNs,where the solid, dashed and dotted lines respectively representthe wired, wireless and wired/wireless connections. A WMBNcomprises mesh routers (MR), and the MRs are responsibleto provide Internet accesses for its serving access networkssuch as WiFi, WiMAX, cellular and sensor networks. SomeMRs are equipped with the wired network interfaces, and actas gateways to connect to the Internet backbone. In such anetwork, user packets practically flow to or from Internet (i.e.,Internet-connected gateway) passing through one or more MRsin a single-hop or multihop fashion [1], [2].

As real-time applications (e.g., voice over IP and videostreaming) rapidly grow, provisioning quality-of-service (QoS)guarantees is one of the most important issues for WMBNs [3].However, the non-deterministic channel access of contention-based medium access control (MAC) protocols, such as IEEE802.11a/b/e/g, makes it impossible to ensure hard QoS guaran-tees for WMBNs. As compared with contention-based MAC,TDMA-based channel access could provide fine-granularity

Internet

Wireless mesh backhaul

Mesh routerwith gatewayMesh router

Base station Base station

sink

WiFi networksCellular networks WiMAX networks

Sensor networks

Clients

Mesh routerMesh router

with gatewayMesh router

Mesh routerMesh routerMesh routerMesh router

Access point

Fig. 1. An example of wireless mesh backhaul networks

resource/admission control. Moreover, the centralized controlof gateways for TDMA-based WMBNs facilitates the useof QoS-aware scheduling and routing. In this study, wepresent an integrated mechanism for real-time applicationsover TDMA-based WMBNs, and propose QoS-aware routingand scheduling algorithms under the integrated mechanism.Our routing and scheduling algorithms can work with any typeof network topologies, and the link capacity and interferenceare taken into account to guarantee QoS required by the real-time applications.

Designs of routing and scheduling algorithms havebeen extensively investigated in mobile ad hoc networks(MANETs) [4]–[7]. However, the traffic flows generated byMANETs and WMBNs are not similar. Each node in anMANET exchanges data packets with the other MANET nodeswhile all traffics generated for the WMBN nodes deliverto/from the gateways. Also, the gateways of WMBNs act asthe coordinators to provide the centralized resource/admissioncontrol. For the proposing of routing and scheduling algo-rithms in WMBNs, existing solutions mainly considered best-effort traffics without QoS requirements [1], [8]–[11]. Specifi-cally, Lee et al. [12] investigated the QoS routing problem byconstructing a tree-based topology. However, the tree topologyfor a WMBN limits the number of subsets of simultaneouslyactive links (see [8], [13]), and thus the network performancedegrades with a lower degree of spatial reuse.

1525-3511/07/$25.00 ©2007 IEEE

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The remainder of the paper is organized as follows. Section2 describes the motivation and contribution of our work. InSection 3, a WMBN system model is presented, and ourQoS-aware routing and scheduling algorithms are proposedin Section 4. Section 5 shows the simulation results of theproposed algorithms. Finally, we conclude the paper with abrief summary and some pointers to future work.

II. MOTIVATION AND CONTRIBUTION

For WMBNs, an appropriate routing algorithm needs to findone or more feasible routes for each pair of source and desti-nation nodes such that 1) QoS requirements of the applicationsare satisfied and 2) global resource efficiency is maximized.To achieve this, firstly, the routing algorithm should be awareof the interference. The value of signal-to-interference-and-noise ratio (SINR) of a transmission has a large impact onthe occurrence of transmission error. In order to alleviate theinfluence of the interference, our routing algorithm shall selectthe routes with the consideration of the interference. Secondly,the selected routed paths shall meet certain QoS require-ments such as guaranteed bandwidth. For real-time services,insufficient bandwidth will cause unexpected delay or jitter.To fulfill the bandwidth requirement, a linear-programmingoptimization technique is used to calculate the achievable non-collision bandwidth of the routing path. With this information,whether a bandwidth request is accepted, rejected or just partlyaccepted can be determined.

Also, the routes shall not be restricted by a particulartopology, e.g., tree, star or ring. A topology-unrestricted rout-ing algorithm will find more-optimal routes than those fora specific topology since the routing paths for the specifictopology are usually confined to its physical/logical placement.Finally, the actual traffic demand of an MR varies as dependingon application needs of its serving clients, and thus a dynamicrouting strategy should be considered. In addition to anappropriate routing algorithm, packet scheduling is necessaryfor a TDMA-based WMBN. With a QoS-aware schedulingalgorithm, each transmitting MR can adequately arrange itstime slots based on the information of bandwidth reservationgiven in the routing stage. Our scheduling algorithm is awareof the interference for collision avoidance. If any two links arefar enough to permit concurrently transmission, the concurrenttransmissions between these two links are allowed to achievehigher degree of spatial reuse and thus to effectively improveoverall network throughput. The scheduling algorithm coop-erates with our routing strategy to guarantee the promisingbandwidth for each service flow.

Based on the above discussions, the contributions of ourwork are two-folds. 1) We propose an integrated routing andscheduling mechanism to provides QoS guarantees to real-time services with unrestricted topologies for TDMA-basedWMBNs. To the best of our knowledge, this study has notbeen done before. 2) A linear programming optimization isdevised to solve the amount of non-collision bandwidth for apath according to the available resource and the interference.The details of our routing and scheduling algorithms will be

elaborated in the following section. Several experiments arealso conducted through our developed simulations to show thecapabilities of our QoS-aware routing and scheduling.

III. OUR PROPOSED MECHANISM

A. Assumptions

For simplicity, we consider a single-channel single-transceiver MAC. Our mechanism can be extended to a multi-channel multi-transceiver MAC with fewer modifications.Without loss of generality, we assume that there is only onegateway in the network. Also, packet loss is assumed to be ne-glected with a robust coding scheme. The TDD (time divisionduplexing) mode is chosen here for uplink and downlink trans-missions as it simplifies the frequency assignment problem.Since each MR is responsible for providing it serving clientsthe Internet service, we consider the downlink/uplink demandsof an MR is the aggregation of the downlink/uplink trafficdemands of its all serving clients. Based on the flexibility onbandwidth allocation provided by TDD, the traffic demandD[v] of an MR v is defined as

D[v] ={

0, if v is gatewayDdownlink[v] + Duplink[v], otherwise

(1)where Ddownlink[v] and Duplink[v] respectively represent thedownlink and uplink traffic demands of the MR v.

We consider IEEE 802.16 standard with orthogonal fre-quency division multiplexing (OFDM) as the underlyingphysical-layer technique [14]. The standard provides multipletransmission rates by applying different modulation schemesand coding rates. The receiver minimum input level sensitivity,RSS , is defined as

RSS = (−102) + SNRRX

+{

10 log[FS(

Nused

NFFT)(

Nsubchannels

16)]}

(2)

where SNRRX represents the receiver signal-to-noise ratio(SNR). Nused is the number of OFDM subcarriers, andNFFT = 2�log2(Nused)�. Also, Nsubchanels is the numberof allocated subchannels, and FS , the sampling frequency inMHz, is defined as

FS =⌊

η × BW

8000

⌋× 8000 (3)

where BW is the channel bandwidth and η is a constantsampling factor. On the other hand, RSS is also given by

RSS ≤ EIRP − PL − SLt − SLr + Gr − LM (4)

where EIRP is the effective isotropically-radiated power, i.e.,

EIRP = TxPower − PL + Gt (5)

Gt(dBi) and Gr(dBi) are the transmitter and receiver antennagain, respectively. SLt and SLr respectively represent thetransmitter and receiver loss. Also, TxPower(dBW ) is thetransmission power, the LM(dB) represents the link margin,and the PL(dB) is the transmission path loss. Since the MRs

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in WMBNs are assumed to be stationary and communicatewithout obstructions, the fading effects are negligible. Weadopt two-ray ground reflection model as our path loss model.By substituting (3), (4) and (5) into (2), we can calculate themaximal transmission ranges for different modulation schemeswith a certain SNRRX requirement.

In addition to the channel model, the interference is akey parameter that governs the degree of spatial reuse. TheProtocol model and the Physical model are both commonlyused as the interference model. Since it had been shownthat the Protocol model is equivalent to the Physical modelwhen path-loss exponents are greater than two, we adopt theProtocol model defined in [15] without considering SINR tosimplify the computation. In the Protocol model, when a nodet transmits to a node r, the transmission is successful if

d(i, r) ≤ (1 + α) × d(t, r) (6)

where d(t, r) is the distance between the nodes t and r. α is apower margin, and its value is always greater than zero. Thenode i is an arbitrary jammer that simultaneously transmits itsdata during the transmission period of the node t.

B. Flow of Our Proposed Mechanism

We use a flowchart shown in Figure 2 to describe ourproposed QoS-aware routing and scheduling mechanism. First,the gateway keeps listening the bandwidth requests issuedfrom its covering MRs. If there is any change on the trafficdemand of an MR, the MR sends a request to the gateway. Therequest will be piggybacked in the earliest data frame sent tothe gateway. Upon receipt of the request, the gateway checkswhether the bandwidth is requested to increase or not. If so,the gateway further checks if there is one or more existingroutes for the MR, or if there is any extra resource that canfulfill the request of the MR. If not, our routing and schedulingalgorithms will be triggered. Otherwise, our mechanism onlyperforms the scheduling algorithm.

On the other hand, the routing algorithm is activated to se-lect routes and to calculate the maximal bandwidth that couldbe granted to the MR along the selected routes. The selectioncriteria are the QoS requirements and interference as well asthe balancing degree. Then comparing the granted bandwidthwith that issued by the requesting MR, the gateway replieswhether the request is accepted, partly accepted or rejected.Based on the results of the routing algorithm, the gatewayupdates the uplink and downlink schedule, and distribute thetime slots to all MRs. In following, we describe the detail ofrouting algorithm, bandwidth calculation as well as schedulingalgorithm in the following subsections.

C. Routing Algorithm

We adopt multi-path routing to provide the gateway moreflexibility in dealing with variety of the traffic demands fromthe MRs [16]. In other words, the bandwidth requirement of anMR can be easily satisfied by aggregating the resources of themultiple paths. We slightly modify the Dijkstra’s algorithmto find a path from the gateway to a particular MR. The

START

Bandwidthrequest?

No

Yes

requesting router hascertain paths?

Yes

Traffic demands ofrequesting router can be satisfied

by former paths?

Yes

Scheduling AlgorithmDistribute timeslots tocorresponding node

No

No

Incrementalbandwidth request?

Yes

No

Routing Algorithm

Select routes forpending demands

B

C

A

B

B

Bandwidthcalculation

C

A

Fig. 2. Flowchart of our proposed mechanism

modifications do not complicate the routing algorithm, and thelink-state routing protocols are not affected by the modifica-tions. Instead of a fixed weight for a link in most of Dijkstra-based routing algorithms, the weights of wireless links inour routing algorithm could be changed as the alteration ofnetwork flows. The change of the wireless-link weights reflectsthe variation on the interference. Another modification is thatthe modified algorithm terminates immediately after the pathfrom the gateway to the target MR is discovered, and no furthercomputation is needed.

The pseudocode of our routing algorithm is shown inAlgorithm 1. A mesh network is modeled as an undirectedgraph G = (V,E), where MRs are represented by the verticesand wireless links are the edges. A wireless link (i, j) is anelement of E[G] if and only if node i and node j are withinthe maximum transmission range of each other. Let R[i, j] bethe bit rate of link (i, j) derived. B[i, j] denotes the availablebandwidth of link (i, j). D[v] be the traffic demand of routerv, and I[v], which is initially set by 0, represents the grantedbandwidth of router v. U [G] is a subset of the nodes whosedemands have not been satisfied, and P [G] is a subset ofthe wireless links along the selected path. Here, the controloverheads of control message are ignored, and thus B[i, j] isequal to R[i, j] in the beginning. In each iteration (the whileloop of lines 8-27 of Algorithm 1) , the gateway choosesa node v whose traffic demand D[v] is maximal in U [G].Such a greedy method is adopted to reduce the complexityof our routing algorithm. Then the gateway selects a routewith a minimal cost for v. After calculating the achievablebandwidth allocation along the path, the gateway subtracts theallocated bandwidth from the links along the selected path andfrom all of the interfered links of the path to avoid collisions.However, the subtracted quantities of bandwidth for theseinterfered links shall be differentiated since their link bit-ratesmight not be the same. Given that link (i, j) is delivering datawith the traffic demand D[i, j]. Let S[m,n] be the subtracted

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bandwidth quantity of link (m,n) interfered by link (i, j).Then we have S[m,n] = D[i,j]R[m,n]

R[i,j] . Furthermore, the weightof each wireless link is closely related to the optimality ofour routing results. We define the occupancy ratio of a link(i, j) as the weight W [i, j] of the link. The occupancy ratio ofthe link represents the allocated/occupied bandwidth under theinterference consideration. It not only denotes the utilizationof the link itself, but also represents an unusable ratio ofchannel bandwidth for the surrounding interfered links. A linkwith small occupancy ratio could contribute more resourcesthan a large one. Thus our modified Dijkstra’s algorithm willselect the path with high non-collision bandwidth under theinterference consideration. The way also boosts the balancingdegree of the network loading since selecting the links withheavy loading will be prevented.

Algorithm 1 Routing Algorithm1: if the routing algorithm has not been executed then2: for all link (i, j) ∈ E[G] do3: W [i, j] ⇐ small positive value4: B[i, j] ⇐ R[i, j]5: end for6: end if7: U [G] ⇐ V [G]8: while U [G] �= NIL do9: for all each link (i, j) ∈ E[G] do

10: if B[i, j] = 0 then11: W [i, j] ⇐ ∞12: end if13: end for14: choose v ∈ U [G] such that D[v] is maximized15: P [G] ⇐ MODIFIED DIJKSTRA’S ALGORITHM(G,W, v)16: if P [G] = NIL then17: Remove v from U [G]18: else19: D′[v] ⇐ BANDWIDTH CALCULATION(P,B,R)20: D′[v] ⇐ min(D[v] − I[v],D′[v])21: I[v] ⇐ I[v] + D′[v]22: for all link (m,n) is interfered by link (i, j) do23: B[m,n] ⇐ B[m,n] − D′[v] × R[m,n]/R[i, j]24: W [m,n] ⇐ W [m,n] + D′[v] × R[m,n]/R[i, j]25: end for26: end if27: end while

Once a path is selected by our routing algorithm, the non-collision bandwidth for the path can be then determined.We calculate the maximal achievable demand D′[v] via alinear programming formulation. The object is to maximizethe achievable traffic demand of router v, i.e.,

maximize D′[v] (7)

subject to the bandwidth constraint for each link

B[m,n] ≥ D′[v]×R[m,n]× ∑

∀link (i,j)∈P [G]

1R[i, j]

(8)

∀link (m,n) is interfered by ∀link (i, j) ∈ P [G]

Note that B[m,n] equals to B[n,m] for an undirected graphG.

D. Scheduling Algorithm

Since the paths with the granted bandwidth (e.g., I[v] ofrouter v) for each router can be determined in the routing stage,the traffic demands of these routers are mapped by the sched-uler to the corresponding time slots, i.e., the granted bandwidthD[i, j] of link (i, j). We define two parameters used as thelink situations in our scheduling algorithm. F [i, j] indicateswhether the demand of link (i, j) is already scheduled in thecurrent schedule period, i.e.,

F [i, j] ={

1, if D[i, j] is already scheduled0, otherwise

(9)

S[i, j] is a link-blocking parameter that indicates whether link(i, j) is interfered by any other active links, and we have

S[i, j] ={

1, if any link interfered link (i, j) is active0, otherwise

(10)Algorithm 2 shows the pseudocode of our scheduling. Themain part of the algorithm is given in the while loop of lines6-18. Let Q[G] be the subset of the links whose demands aresatisfied. The scheduling algorithm iteratively extracts non-blocking links from E[G] and adds it to Q[G] until Q[G] =E[G]. Until no links with S[i, j] = 0 are founded in E[G],the while loop of lines 7-11 terminates. Whenever a link isadded to the Q[G], one or more links might be avoid tobe scheduled presently in order to avoid collisions, and thusAlgorithm 3 updates S[i, j] for each link (i, j) in G. Note thatour scheduling algorithm can be easily extended to considerdifferent priorities by slightly modifying line 8 of Algorithm 2.

IV. PERFORMANCE EVALUATION

In this section, we evaluate the performance of our proposedintegrated QoS routing and scheduling mechanism through thedeveloped simulation experiments. Table I summaries the inputparameters used in the experiments. Based on the channelmodel derived in Section III-A, the bit rate and the maximaltransmission range corresponding to each modulation schemecan be found in Table II [17].

Our experimental WMBN is generated such that 20 MRsare randomly distributed in a 25 × 25 km2 area, and agateway is placed in the center of the area. To avoid thenetwork being partitioned, we use Dijkstra algorithm to checkits connectivity. The voice payload size is set according toITU-T Recommendation G.711 specification, and the packetoverheads conform to the RTP, UDP, IP and IEEE 802.16packet formats. Our event-driven simulation is implemented

This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the WCNC 2007 proceedings.

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Algorithm 2 Scheduling Algorithm

1: for all each link (i, j) ∈ E[G] do2: F [i, j] ⇐ 03: S[i, j] ⇐ 04: end for5: Q[G] ⇐ NIL6: while More than one link (i, j) ∈ E[G] do7: while More than one link (i, j) ∈ E[G]whereS[i, j] = 0

do8: Randomly select a link (i, j) ∈ E[G] such that

F [i, j] = 0 and S[i, j] = 09: Add link (i, j) to Q[G]

10: UPDATE NETWORK CONFIGURATION(G,E,Q, S)11: end while12: Select a link (i, j) ∈ Q[G] such that D[i, j]/R[i, j] is

minimal13: F [i, j] ⇐ 0 and D[i, j] ⇐ 014: for all link (m,n) ∈ Q[G] where D[m,n] �= 0 do15: D[m,n] ⇐ D[m,n] − D[i, j] × R[m,n]/R[i, j]16: end for17: UPDATE NETWORK CONFIGURATION(G,E,Q, S)18: end while

Algorithm 3 Update Network Configuration

1: for all link (i, j) ∈ E[G] do2: S[i, j] ⇐ 03: end for4: for all link (i, j) ∈ Q[G] do5: for all link(m,n) ∈ E[G] is interfered by link (i, j) do6: S[m,n] ⇐ 17: end for8: end for

TABLE I

PARAMETERS USED IN THE EXPERIMENTS

Parameter Value

Bandwidth 5MHz

Propagation model Two-ray ground reflection

η 1.152

Nused 200

Nsubchannels 16

Queue length 100 packets

Transciever loss 2dB

Link margin 15dB

Transmission power 30dBm

Antenna gain 20dBi

Antenna height 10 meter above ground

TABLE II

BIT RATES AND TRANSMISSION RANGES

ModulationCoding Receiver Transmission Bit rate

rate SNR (dB) range (Km) (Mbps)

BPSK 1/2 6.4 5.6454 1.89

QPSK1/2 9.4 4.7500 3.95

3/4 11.2 4.2825 6

16-QAM1/2 16.4 3.1746 8.06

3/4 18.2 2.8621 12.18

64-QAM2/3 22.7 2.2090 16.30

3/4 24.4 2.0030 18.36

0.9

1

1.1

1.2

1.3

1.4

1.5

0.05 0.075 0.1 0.125 0.15

Overall throughput (Mbps)

Per-MR traffic demand (Mbps)

Our mechanism, α=0.8Our mechanism, α=1.0Our mechanism, α=1.2

Basic mechanism, α=0.8

Fig. 3. Effect of traffic demand on system throughput

by C++ programs. The 95% confidence intervals for the datasets in the results conducted from independent experimentsare no more than 1% of their data values for each parameterconfiguration.

Figure 3 shows the effect of per-MR traffic demand onsystem throughput, where the power margin α is set to 0.8,1.0 and 1.2. The traffic demand for each MR follows Uniformdistribution, and its mean values range from 50 Kbps to 150Kbps. From this figure, as the traffic demand increases, theincrease of the system throughput gradually tends to be smallbecause the network resource has been exhausted. Also, theincrease of the power margin α results in the reduction of thesystem throughput. When α = 0.8, our proposed mechanismis compared with the basic mechanism that intuitively adoptsthe minimal-hop routing and conventional TDMA schedul-ing. In the circumstance of heavy loading, our mechanismgains much higher throughput than the basic mechanism. Thereason for this phenomenon is explained as follows. Firstly,our mechanism selects the paths that include the links withhigher non-collision bandwidth. Then the network load is morebalanced to avoid prematurely exhausting the resource of thecritical links. From this figure, we also observe that even witha large power margin, our mechanism still outperforms thebasic mechanism with a small one.

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0

50

100

150

200

250

300

350

5 10 15 20 25 30 35 40

Average end-to-end delay (ms)

Number of nodes

Our mechanism, α=0.8Our mechanism, α=1.0Our mechanism, α=1.2

Basic mechanism, α=0.8

Fig. 4. Average end-to-end delay versus the number of nodes, where themean traffic demand is set as 150 Kbps

Figure 4 indicates average end-to-end (i.e., MRs-to-gateway) delays under different numbers of MRs, wherethe mean traffic demand is set as 150 Kbps. In multi-hopwireless networks, the end-to-end delay is greatly affectedby the number of MRs. Because the multipath routing couldbring out-of-order packet delivery, the re-sequencing delayis also taken into account. In Figure 4, the increase of thenumber of MRs leads to the increase of average delay for allmechanisms under investigation. However, the delay increaseis nearly neglected for our proposed mechanism while thebasic mechanism has considerable increase as the number ofMRs increases. Specifically, for the case of more than 30MR nodes, the quality requirement of voice services in thebasic mechanism could not be fulfilled. On the other hand,we can see that even in a 40-MR-network, the delay of ourmechanism is about only 20 ms. We also observe that inour mechanism, average end-to-end delay is not affected bythe power margin α. This is because our routing/schedulingalgorithm is interference-aware and our bandwidth calculationoptimization can quantify the exact non-collision bandwidth.

V. ACKNOWLEDGMENTS

Pang’s work was sponsored in part by National ScienceCouncil under contracts NSC95-2219-E-002-016 and NSC95-2221-E-002-096-MY3, Intel and Chunghwa Telecom Co., Ltd.

VI. CONCLUSIONS

In this paper, we considered the QoS problem for routingand scheduling in TDMA-based WMBNs.We proposed anintegrated routing and scheduling mechanism to provides QoSguarantees to real-time services with unrestricted topologiesfor TDMA-based WMBNs. A linear programming optimiza-tion was devised to solve the amount of non-collision band-width for a path according to the available resource and theinterference. A simulation model was developed to investigatethe performance of our proposed mechanism. Through thedeveloped simulation, a series of experiments were conducted

to show the capabilities of our proposed mechanism. Theexperimental results indicated that our proposed mechanismoutperforms the basic mechanism with minimal-hop routingand conventional TDMA scheduling. For future research, weshall consider the possibility of scheduling slightly-interferedlinks for different QoS requirements.

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