A new CAC and packet scheduling scheme for mobile WiMAX networks

TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES Trans. Emerging Tel. Tech. 2014; 25:981–992 Published online 16 August 2013 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/ett.2689

RESEARCH ARTICLE

A new CAC and packet scheduling scheme for mobile WiMAX networks Ahlem Saddoud1,2 , Lamia Chaari Fourati1,2* and Lotfi Kamoun1,2 1 Sfax National Engineering School (ENIS), University of Sfax, Sfax, Tunisia 2 Laboratory of Electronics and Information Technology (LETI), University of Sfax, Sfax, Tunisia

ABSTRACT As the wireless network technology evolves, IEEE 802.16 standard, also known WiMAX (Worldwide Interoperability for Microwave Access) appears as a great competitor to GSM, 3G, even IEEE 802.11 networks. The coverage of this technology is expanded up to 50 km. It is claimed to provide a transmission rate up to 70 Mbps while respecting the QoS (Quality of Service) mechanism. However, the call admission control (CAC), scheduling and bandwidth allocation mechanisms were not defined and left as an open issue. In this paper, we introduce a CAC scheme and a scheduling algorithm for IEEE 802.16e Mobile W I MAX. An efficient token bucket based CAC and uplink packet scheduling scheme is introduced in order to satisfy bandwidth guarantees to all service flow and delay guarantees to real time service flows. The proposed solution is practical and compatible to the IEEE 802.16 standard as it provides the QoS of different traffic classes especially best effort traffic by avoiding its starvation as is specified in major previous works. An analytical model and simulation results are developed in order to validate the proposed CAC scheme and the scheduling algorithm. By numerical results, we show that our proposed scheme is compatible to the IEEE 802.16 standard as it performs significantly the best effort traffic without violating QoS performance of other service classes. Copyright © 2013 John Wiley & Sons, Ltd. *Correspondence L. C. Fourati, Computer Science, Computer Science and Multimedia Higher Institute at SFAX University, Sfax, Tunisia. E-mail: [email protected] Received 17 January 2013; Revised 9 June 2013; Accepted 24 June 2013

1. INTRODUCTION The Institute of Electrical and Electronics IEEE 802.16 standard is a real revolution in wireless metropolitan area networks that enables high-speed access to data, video and voice services. The IEEE 802.16 is mainly aimed at providing broadband wireless access. Thus, it complements existing last mile wired networks such as cable modem and xDSL (Digital Subscriber Line). Its main advantage is fast deployment, which results in cost saving. The IEEE 802.16 standard [1] provides network access to buildings through external antennas connected to radio base station (BS). Basically, two ways for sharing wireless media are defined by the medium access control (MAC) layer: point to multipoint (PMP) and mesh mode. The main difference between the PMP and the optional mesh modes is that in the PMP mode, traffic only occurs between the BS and subscriber stations (SSs), whereas in the mesh mode traffic, it can be routed through other SSs and can occur directly between SSs. PMP mode is mainly applied in WiMAX as it is a centralised architecture where all data traffic are Copyright © 2013 John Wiley & Sons, Ltd.

controlled by the serving base BS [2]. Two types of traffic are supported by the WiMAX networks: uplink (UL) channel where data are sent from the SSs to the BS and downlink (DL) channel where data bursts are sent from BS to all SSs. When the system uses time-division multiplexing, for UL and DL transmissions, the frame is subdivided into an UL sub-frame and a DL sub-frame. In IEEE 802.16e2005 [3], both frequency division duplexing (FDD) and time division duplexing (TDD) are allowed. In the case of FDD, the UL and DL sub-frames are transmitted simultaneously on different carrier frequencies; in the case of TDD, the UL and DL sub-frames are transmitted on the same carrier frequency at different times. In broadband wireless communications, QoS is still an important criterion. The WiMAX standard is designed to provide QoS through classification of different types of connections as well as scheduling. Although extensive bandwidth (BW) allocation and QoS mechanisms are provided, the details of scheduling and reservation management are left not standardised. In fact, the standard supports scheduling only for fixed-size realtime service flows. The admission control and scheduling 981

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of both variable-size real-time and non-real-time connections are not considered in the standard. Thus, WiMAX QoS is still an open field of research and development for both constructors and academic researchers. The standard should also maintain connections for mobile users and guarantee a certain level of QoS. In this paper, we focus on the QoS in WiMAX network through a new call admission control (CAC) scheme and an UL packet scheduling algorithm in order to satisfy both BW and delay. An efficient token bucket based CAC scheme is introduced in order to satisfy BW guarantees to all service flow and delay guarantees to real-time flows. ErtPS (extended real-time polling service) request is considered to be the same as rtPS (real-time polling service) connections because both connections have the same QoS parameters. Therefore, by an efficient token bucket model, the proposed solution improves the QoS of best effort (BE) traffic by avoiding its starvation without violating QoS performance of other service classes. The rest of this paper is organised as follows. In the next section, we introduce the IEEE802.16 air interface and QoS architecture. After a presentation of related works in the literature in Section III, we give a detailed description of the proposed model in Section IV. In order to show the benefits of the proposed scheme, we evaluated our proposed model using the continuous time Markov chain. Therefore, we describe the analytical model of the proposed scheme in Section V. Simulation results of our proposed scheme are validated in Section VI. Finally, the conclusion and future works are drawn in Section VII.

2. IEEE 802.16 AIR INTERFACE AND QUALITY OF SERVICE ARCHITECTURE 2.1. IEEE 802.16 air interface : The principle technologies behind the physical(PHY) layer of WiMAX are orthogonal frequency division multiplexing (OFDM) and orthogonal frequency division multiple access. Both TDD and FDD are specified in the IEEE 802.16 standard [4]. TDD is a technique in which the system receives and transmits within the same frequency channel, whereas in FDD mode, two separate frequencies are required to transmit and receive. The PHY layer specification operates in a framed format. Each frame consists of a DL sub-frame and an UL sub-frame. TDD framing is illustrated in Figure 1: The UL and DL transmissions share the same frequency while being allocated in each TDD frame according to an adaptive threshold. The UL sub-frame structure using TDD mode is illustrated in Figure 2. The MAC layer of IEEE 802.16 is designed to serve sparsely distributed stations with high data rates, where the SSs are not required to listen to the other stations like the MAC in IEEE 802.11. The BS schedules the transmissions of the corresponding SSs in advance. The SSs need 982

to contend only when they access the channel for the first time at the admission control stage. The reservation-based resource allocation allows the BS to serve a large number of SSs as well as the guarantee of QoS in the connection level for both UL and DL traffic. 2.2. IEEE 802.16 quality of service architecture: The WiMAX is designed to support QoS. The MAC, which is based on the concept of service flows, specifies a QoS signalling mechanism for both BW request and BW allocation in the UL and DL channels. In computer networks, admission control and scheduling are very necessary to allocate sufficient resources for users while satisfying the QoS. Admission control is responsible for accepting or rejecting the connection according to the available BW that satisfies the connection and guarantees the required QoS without degrading the QoS for other existing connections. UL packet scheduling, which is found on the BS side, controls all UL packet transmissions. The IEEE 802.16 MAC layer enables classification of traffic flow and maps them to connections with specific scheduling services. Each connection is associated with a single scheduling data service, and each data service is associated with a set of QoS parameters that quantify aspects of its behaviour. Five types of scheduling services are defined by the IEEE 802.16e standard: [5] (1) UGS (Unsolicited grant service): This service is designed to support fixed-size data packets at a constant bit rate like flows such as voice over Internet Protocol. The mandatory service flow parameters that define this service are maximum sustained traffic rate, maximum latency, tolerated jitter and request/transmission policy. BW request is not required for this service. For the UL scheduler, BS determines the Information Elements (IEs) for the UL-MAP; it allocates a fixed numbers of time slots in each time frame. (2) rtPS: This class is designed to support real-time service flows, such as moving picture experts group video, that generate variable-size data packets on a periodic basis. Applications have specific BW requirements as well as the maximum delay (deadline). The BW request is used only in the contention free mode. The current queue size that represents the current BW demand is included in the BW request. Late packets with expired deadline will be useless. (3) ertPS: This service is basically identical to UGS, except that ertPS can change the allocated BW dynamically depending on the traffic characteristics. On detecting that the allocated BW is insufficient to serve packets in time, the SS requests an additional BW by piggybacking its amount on the packet header. Otherwise, if the connection becomes inactive or traffic input rate decreases, the SS can request stopping or decreasing the BW allocation. ThereTrans. Emerging Tel. Tech. 25:981–992 (2014) © 2013 John Wiley & Sons, Ltd. DOI: 10.1002/ett

A. Saddoud, L. C. Fourati and L. Kamoun

Figure 1. Time division duplex (TDD) framing. SS Transition Gap

Initial ranging opps UIUC=2

Collision

Access Burst

Requestcontention opps UIUC=1

SS1 scheduled data UIUC=i

…..

SSn scheduled data UIUC=i

BS Rx/Tx Transition Gap (RTG)

Collision

Bandwidth Request

Figure 2. Uplink sub-frame structure.

fore, the ertPS is suitable for real-time variable bit rate traffic and Voice over Internet Protocol traffic with silence suppression. (4) nrtPS (non-real-time polling service): This service is designed to support delay-tolerant data streams, such as an file transfer protocol, that require variable-size data grants at a minimum guaranteed rate. The mandatory service flow parameters to define this service are minimum reserved traffic rate, maximum sustained traffic rate, traffic priority and request/transmission policy. BW request uses either contention free mode or contention mode. Current queue size (the current BW demand) is included in the BW request. (5) BE service: This service is designed to support data streams, such as web browsing, that do not require a minimum service-level guarantee. The applications Trans. Emerging Tel. Tech. 25:981–992 (2014) © 2013 John Wiley & Sons, Ltd. DOI: 10.1002/ett

in this service flow receive the available BW after the BW is allocated to the previous four service flows. The BW request uses only contention mode. Current queue size is included in the BW request. We summarise QoS specification of different service class in the following Table I.

3. RELATED WORKS 3.1. WiMAX enhancements : Recent researches aimed at enhancing WiMAX PHY layer performances[6][7] as well as MAC mechanisms[8][9]. In [10], a novel blind timing offset estimation method was proposed for OFDM systems based on cyclic structure. A cyclic prefix is appended to each OFDM symbol in order 983

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Table I. Quality of service data service types. Class

Applications

QoS specifications

UGS

VoIP

rtPS

Streaming audio, video

ertPS

Voice with activity detection (VoIP)

nrtPS

FTP

Maximum sustained rate Maximum latency tolerance Jitter tolerance minimum reserved rate Maximum sustained rate Maximum latency tolerance Traffic priority Minimum reserved rate Maximum sustained rate Maximum latency tolerance Jitter tolerance Traffic priority Minimum reserved rate Maximum sustained rate Traffic priority Maximum sustained rate Traffic priority

BE

Data transfer, web browsing

to eliminate the intersymbol interference as well as intercarrier interference. In [6], a novel frequency offset estimation technique for the OFDMA based WiMAX system was proposed, it is based on exploiting periodicity in the preamble’s time domain signal. In additive white Gaussian noise channel, the scheme improved the performance of the channel estimation by up to 8 dBs over the conventional method based on using the cyclic prefix. The handover procedure can have a negative impact on the quality of service because of the short break in the connection. In [9], authors propose a modification of the hard handover procedure to enable reduction of the handover interruption time by exploiting the results of a handover prediction. The decrease of the handover interruption duration is accomplished by utilisation of the results of handover target BS prediction. Moreover, the proposed mechanism fast predicted handover enables to meet the requirements on IEEE802.16m for frames with longer duration in comparison with the IEEE802.16e. Multihop wireless systems outperform single-hop ones in terms of coverage extension and throughput enhancement, in this field many works [8] [11] were carried out. In [8], a dynamic group management scheme at the MAC layer based on RS (relay station) position, with dynamic RS selection. Its goal is the fast creation of routes at the MAC layer that allows upper layers to identify mobile node groups from the RSs they are associated to. Multicast multimedia communications was improved compared with the conventional scheme. In [11], a path selection method called optimal path relay association was proposed. In this method, each RS in the mobile multihop relay network is capable of finding its optimal path by considering the following metrics available: link BW, signal-to-noise ratio and hop count. 984

3.2. WiMAX scheduling and admission control: Recent researches in QoS field aimed at providing new scheduling algorithms and new admission control mechanisms. In [12], a new DL resource allocation scheme in the IEEE 802.16 standard based on the orthogonal frequencydivision multiple access PHY layer was proposed. The objective is to allocate the DL frequency-time slots and transmission power to different users with the purpose to maximise the total throughput. The main contribution was to model the overloaded system by an unbalanced transportation problem with the dissatisfaction of users’ rate reflected in the cost of getting slots from the dummy band. Therefore, by solving the problem the total power is minimised, whereas the proportional rates are considered simultaneously. In [13], authors formulated an integrated algorithm capable of providing accurate predictive CAC and resource reservation techniques with optimal resource utilisation. The algorithm has been developed using the concept of adaptive filtering using normalised least mean square adaptive filtering to estimate the source traffic characteristics. In [14], resource allocation in the UL of OFDMA systems was investigated. The problem of ergodic utility maximisation with discrete rates is formulated and solved using dual Lagrangian techniques. Suboptimal algorithms based on equal power allocation over the subcarriers are proposed. In [15] and [16], the authors proposed an UL-scheduling algorithm and an admission control policy for IEEE 802.16 fixed WiMAX. A hierarchical QoS architecture is defined. This architecture consists of two layers. A strict priority is used in the first layer, where the entire BW is Trans. Emerging Tel. Tech. 25:981–992 (2014) © 2013 John Wiley & Sons, Ltd. DOI: 10.1002/ett

A. Saddoud, L. C. Fourati and L. Kamoun

distributed between the different service flows. UGS has the highest priority, then rtPS, nrtPS and finally BE. In the second level of this hierarchal architecture, different mechanisms are used to control the QoS for each class of service flow. In [17], a QoS-supported UL scheduling and CAC mechanism similar to [15] are proposed. BW needed by real-time flows can be correctly reserved while promising their delay requirements. The authors proposed a model to convert Poisson traffic flow into token bucket based connection. The CAC scheme proposed is based on the estimation of BW usage while the delay requirement of rtPS flows will be met. To do that, the BW required by an rtPS flow is estimated using token bucket parameters and the delay. In [18], an efficient token bucket based CAC scheme for IEEE 802.16e mobile WiMAX is proposed. The proposed CAC scheme satisfies BW guarantees to all service flows and delay guarantees to rtPS flows. It provides higher priority to handoff connections because it is more annoying to drop an ongoing connection than blocking a newly originated connection. Also, UGS connections are given higher priority as it is the most common service used in everyday life. A priority-based fair scheduling algorithm for WiMAX UL traffic is presented in [19] for SSs to serve a mixture of UL traffic from different scheduling services. The proposed model provides a tractable method for operators to manage and dimension their WiMAX systems for UL multimedia traffic. In [20], utility-based dynamic BW allocation algorithm in IEEE 802.16 networks to minimise the average queuing delay. In this algorithm, a network utility function, which is related to the average queuing delay of each SS node, is constructed; for QoS consideration, weight factors are introduced for different type of services. This algorithm takes into consideration the QoS requirements of different traffic types and makes use of a utility function to minimise the average queuing delay. In [21], a statistical CAC mechanism is introduced; it is named modified complete sharing because it is based on complete sharing mechanism taking into consideration the variability of the traffic. Thus, in order to avoid the QoS degradation, the proposed CAC mechanism considers the traffic variability and overflow. The authors reserve an additional BW for service whose traffic is variable to avoid the QoS degradation caused by traffic variability. Another CAC algorithm combined with a packet-scheduling scheme is introduced in [22]. An adaptive CAC is provided using a fixed guard channel admission policy, whereby new connections beyond some specified guard channel are blocked. The proposed CAC reserves an adaptive temporal channel BW for mobile SSs based on most recent requests to assure seamless handoff of connections. It is shown that, when the system is moderately loaded, the proposed CAC performs better than a fixed guard channel scheme in terms of reducing handoff dropping and new call blocking probabilities. In [23] , an adaptive BW allocation and admission control mechanism based on game theory for WiMAX are Trans. Emerging Tel. Tech. 25:981–992 (2014) © 2013 John Wiley & Sons, Ltd. DOI: 10.1002/ett

proposed. Delay and throughput are the QoS performances that need to be guaranteed for real-time and non-real-time polling services. The authors formulated a non-cooperative two-person general-sum game. Nash equilibrium was used in order to obtain the candidate strategies, and the decision of the game is made on the basis of the presence of admissible strategy pair. The game theoretic formulation provides the amount of BW allocated to a new connection. The payoffs for the game model are obtained on the basis of a radio link level queuing model considering adaptive modulation and coding in the physical layer and burstiness in the traffic arrival process. The performance of the proposed scheme was evaluated and compared against the performances of traditional schemes (i.e. static and adaptive schemes). By simulation, the authors prove that the proposed scheme can maintain the QoS performances at the required level. In [24], the authors proposed a dynamic BW request mechanism for variable bit rate real-time traffic in IEEE 802.16 networks. In order to maximise the efficiency of wireless channel, the amount of requested BW was calculated dynamically using the notion of target delay, a tolerable delay for real-time service without violating delay requirement. Because of the dual feedback architecture, the proposed scheme responds quickly to the variation of traffic load. The stability of the proposed scheme was analysed on the basis of a systematic approach. Using this analysis, the authors derived a simple design guideline for the proposed algorithm and proved that the rate-based control in BW request is essential for stability. The simulation results confirm that the proposed algorithm strikes a balance between efficiency and QoS and that it provides a control knob for the delay by using the target delay. In our previous work [25], we have proposed and analysed the performances of an CAC and BW allocation scheme based on strict priority between traffics. This scheme is suitable for real-time applications as it gives it more priority than non-real-time service classes. In this paper, we introduce a new CAC mechanism and an UL packet-scheduling method that aim to avoid the starvation of the BE traffic because we have penalised the BE traffic in our previous study [25]. In this work, we propose an efficient token bucket method that increases significantly the number of accepted connections for BE traffic and maintains also a delay guarantees to real-time traffics. Thus, our proposition takes into account the QoS of different service classes connections for IEEE 802.16e Mobile WiMAX network. In the following, we present the model associated with the behaviour of our proposed scheme.

4. PROPOSED MODEL We consider a PMP mode where one BS serves multiple connections from different SSs. A connection is presented by a separate queue where all new packets arrive from the corresponding service flows. For each service class, we take into consideration the handoff flows and the originated connections. The handoff connections are those handoffed 985

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from neighbouring cells to the current cell, and the originated calls are newly generated from the current cell. ErtPS connections are considered to be the same as rtPS connections, because both connections have the same QoS parameters and differ only by the way of request/transmission policy. In our model, the handoff calls are given higher priority than the originated calls. We assume that the arrival process for all the different service class follows a Poisson distribution. Therefore, the duration of a connection request follows an exponential distribution. We give the following QoS parameters of each connection (the arrival, service and frame duration. . . ) used in the remainder of the paper.  C = Total amount of bandwidth available at the BS for              

uplink Connections (Mbps). BUGS = total capacity allocated for current UGS connections (Kbps). BrtPS = average capacity allocated for current rtPS connections (Kbps). BnrtPS = average capacity allocated for current nrtPS connections (Kbps). BBE = average capacity allocated for current BE connections (Kbps). BNRT = BnrtPS + BBE = C - BUGS - BrtPS . di = maximum delay requirement for rtPS connections (ms). f = duration of a time frame which includes downlink and uplink sub-frames (ms). ri = token arrival rate (average data rate) of a connection i (Kbps). bi = token bucket size of a connection i (Kbits). mi = di /f , mi must be an integer. i = number of UGS connections admitted into the network. j = number of rtPS connections admitted into the network. k= number of nrtPS connections admitted into the network. l = number of BE connections admitted into the network.

It is important to show that we use two conditions mention and proved in [15] for the choice of the frame duration: (1) f < min.d i =2/; (2) f must be the divisor of the delay requirement di In order to guarantee the delay of an admitted rtPS connection, we believe in the following equation proved in [15]: h  bi > .mi  1/  1 C BNRT =B

rtPS



i  1  ri  f (1)

In addition, the amount of BW requested by a new connection is estimated as the token rate ri. 986

Figure 3. Relationship between call admission control and uplink scheduler.

We give in the following a detailed description of the admission control process and the UL packet scheduling mechanism for our system.

4.1. Call admission control description: When a mobile station send a request to the BS with a certain QoS parameters for a new connection, the BS will check whether it can provide the required QoS for that connection. If the request was accepted, the BS verifies whether the QoS of all the ongoing connections can be maintained. On the basis of this, it will take a decision on whether to accept or reject the connection. The process described previously is called as CAC mechanism. Thus, CAC restricts the access to the network in order to prevent network congestion or service degradation for already accepted users.The most important concern for providing CAC in WiMAX networks is to guarantee QoS of connections. In Figure 3, we illustrate the relationship between the CAC module and the UL scheduler detailed in the following subsection. The proposed CAC scheme ensures that a connection is accepted into the network only if its QoS requirements can be satisfied as well as the performance of existing connections in the network is not deteriorated. CAC algorithm determines the amount of BW to be allocated for different services by giving several priorities between them. We provide higher priority to handover connections. In addition, the priority between the various service flows (UGS > rtPS > nrtPS>BE) is also maintained. Therefore, the priority order of different types of service flows is H-UGS > O-UGS > H-rtPS > O-rtPS> H-nrtPS> O-nrtPS > H-BE > O-BE, where H stands for handoff and O stand for newly originated connections, respectively. The principle of our CAC algorithm is described as follows: Firstly, we calculate the remaining UL BW: Brem , Brem = C-BUGS - BrtPS - BnrtPS -BBE . Secondly, we compare Brem to the BW requested by a new connection. If there are enough resources, the system will check whether the delay guarantees of the existing rtPS connection are satisfied or not using Equation (1). If the delay is satisfied, the system accepts the incoming flow, otherwise the connection will be denied. Trans. Emerging Tel. Tech. 25:981–992 (2014) © 2013 John Wiley & Sons, Ltd. DOI: 10.1002/ett

A. Saddoud, L. C. Fourati and L. Kamoun

4.2. Uplink packet scheduling One of the most important tasks of a scheduling scheme is to satisfy the quality of service requirements of its users while efficiently utilising the available BW. For the UL traffic, the scheduling algorithm has to work in tandem with CAC to satisfy the QoS requirements. The proposed UL packet scheduling is based on a hierarchical structure of BW allocation. The overall BW is allocated according to strict priority between all types of service flows (UGS, rtPS, nrtPS and BE). The UGS class has the highest priority, and the BE class has the lowest priority. We use a token bucket for each service flow except the UGS because it has a fixed BW, and so no need of token bucket. The token arrival process follows a Poisson distribution with rate ri. If the bucket is full of tokens, new tokens are thrown away. When a packet arrives for a BW request, it will be accepted if there are a number of tokens in the bucket at least equal to the number of bytes in the packet. If there are not enough tokens in the bucket, the packet will be thrown away. Furthermore, we serve a rtPS call if there is rtPS token and no UGS request, then we serve nrtPS call if there is nrtPS token and no rtPS request and so on. The proposed token bucket mechanism described below is illustrated in Figure 4. The principle concept of the UL scheduler is described as follows: We calculate the number of rtPS packets that need to be sent during each frame. Then, we grant all the UGS connection based on their fixed BW requirements as it is already defined by the IEEE 802.16 standard. For rtPS connections, we applied the earliest deadline first service discipline. Packet with the earliest deadline will be served first if there are enough rtPS token and no UGS requests. After that, we check if there are no rtPS requests and an available nrtPS tokens exist. Thus, we schedule nrtPS packets based on weight fair queue. Finally, we verify if there are no nrtPS requests and enough BE tokens. The remaining BW is allocated to each BE connection.

5. ANALYTICAL MODEL We have presented our CAC and UL packet-scheduling model based on the token bucket mechanism in the previous section. In this section, we propose a mathematical model based on the continuous time Markov chain in order to determine QoS parameters (new call blocking probability, handoff call blocking probability and BW utilisation). The analytical model is developed using the following assumptions. The arrival process of the handoff and originated UGS, rtPS, nrtPS and BE connections is Poisson with rates hu , ou , hr , or , hn , on , hB , oB , respectively. The service times of UGS, rtPS, nrtPS and BE are exponentially distributed with mean 1/u , 1/r , 1/n and 1/B , respectively. Markov chain is adopted to analyse the problem. Each Markov chain state is defined by four parameters (i, j, k, l) Trans. Emerging Tel. Tech. 25:981–992 (2014) © 2013 John Wiley & Sons, Ltd. DOI: 10.1002/ett

Figure 4. Proposed uplink scheduler with token bucket mechanism.

where i (respectively j, k, l) is the number of UGS (respectively rtPS, nrtPS, BE) connections admitted into the network. The state space of the Markov chain is obtained on the basis of our proposed scheme. We suppose that the steady state probability of the state s= ( i, j, k, l) is represented by .i ; j ; k; l/. The state space S for our model is obtained by the following equation: S D fs D .i ; j ; k; l/ ji :BUGS C j :BrtPS Ck:BnrtPS C l:BBE 6 C g

(2)

From a state s = ( i, j, k, l), a transition occurs when a new request (originated or handoff) for connection admission is accepted at the BS or an ongoing connection terminates. The general state transition diagram for a given state s is shown in Figure 5. The state balance equation for a given state s is obtained by Equation (3). .tu :Q.i C 1; j ; k; l/ C t r :Q.i ; j C 1; k; l/ C tn :Q.i ; j ; k C 1; l/ C tB :Q.i ; j ; k; l C 1/ C i :u Q.i  1; j ; k; l/ C j :r Q.i ; j  1; k; l/ C k:n : Q.i ; j ; k  1; l/Cl:B Q.i ; j ; k; l  1//:.i ; j ; k; l/D0  1; .i ; j ; k; l/S Q.i ; j ; k; l/ D 0; otherwise (3) 8 < hu C ou if .i C 1/:BUGS C j :BrtPS Ck:BnrtPS C l:BBE > C tu D : otherwise hu 987

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)

.i C 1/:BUGS C j :BrtPS C k:BnrtPS Cl:BBE > C P

 CBP-rtPS =

(5)

(i, j, k, l)

s2S1

( s D .i ; j ; k; l/

where S1 D

k )

i :BUGS C .j C 1/:BrtPS C k:BnrtPS Cl:BBE > C  CBP-nrtPS=

P

(6)

(i, j, k, l)

s2S1

( Figure 5. The continuous time Markov chain.

t r

s D .i ; j ; k; l/

where S1 D

k )

i :BUGS C j :BrtPS C .k C 1/:BnrtPS Cl:BBE > C

8 < hr C or if i :BUGS C .j C 1/:BrtPS Ck:BnrtPS C l:BBE > C D : otherwise hr

 CBP-BE=

P

(7)

(i, j, k, l)

s2S1

( 8 < hn C on if i :BUGS C j :BrtPS C.k C 1/:BnrtPS C l:BBE > C tn D : otherwise hn

tB

8 < hB C oB if i :BUGS C j :BrtPS Ck:BnrtPS C .l C 1/:BBE > C D : otherwise hB

The steady state probabilities of all states in S can be obtained by solving the aforementioned equation. The resolution of Equation (3) is performed with the normalised condition: X

.i ; j ; k; l/ D 1

(4)

s2S

5.1. Call blocking probability: P

(i, j, k, l)

s2S1

( where S1 D

988

s D .i ; j ; k; l/

i :BUGS C j :BrtPS C k:BnrtPS C.l C 1/:BBE > C

k ) (8)

5.2. Bandwidth utilisation: The BU is the average ratio of used BW to the total BW. The BU expression is given by the following equation: BU D

X

.i :BUGS C j :BrtPS C k:BnrtPS C l:BBE /

s2S

.i ; j ; k; l/=C

(9)

6. SIMULATION RESULTS

From the steady state probabilities, we calculate the QoS parameters: call blocking probability and bandwidth utilisation (BU).

 CBP-UGS =

where S1 D

s D .i ; j ; k; l/

k

6.1. Performance of the call admission control and uplink scheduling scheme: We describe the simulation results in this section. We validate our CAC and UL packet scheduling, and we show the simulation results about our delay, the call blocking probability and BU. The simulations are carried out on MATLAB. Our calculation results are obtained from Equations (5), (6), (7), (8) and (9) detailed in the previous section. The parameters of different service classes are listed in Table II. Trans. Emerging Tel. Tech. 25:981–992 (2014) © 2013 John Wiley & Sons, Ltd. DOI: 10.1002/ett

A. Saddoud, L. C. Fourati and L. Kamoun

Table II. Quality of service parameters. bi (kbit)

di (ms)

rtPS nrtPS BE

512 512 300

25 25 15

30 -

Next, we compare the performance of the proposed CAC and packet scheduling scheme with that proposed in [25]. Actually, in our previous study [25], we have analysed the QoS performance of each service classes using the strict priorities mechanism between the traffics. By numerical measures, we show that our proposed scheme improves

The T cycle is 10 ms: it is the time interval of each request-and-grant round in IEEE 802.16 networks, it is equal to frame duration. The frame duration f is taken as 10 ms, and the total UL capacity available at the BS is 70 Mbps. In order to evaluate the performance of the proposed model, we compute the call blocking probability under different service classes. In Figures 6 and 7, we have computed the call blocking probabilities for respectively H-UGS, O-UGS, H-rtPS, O-rtPS, H-nrtPS, O-nrtPS, H-BE and O-BE traffics by varying the arrival rate (in Figure 6) and the number of SS (in Figure 7. We have represented all the traffics in the same figures, and we have noticed that the call blocking probability increases as the number of SSs increases and so as the total arrival rate increases. Indeed, we have shown that the blocking probabilities respect the priority between the traffics. Namely, the blocking probabilities for UGS are less than rtPS, nrtPS and BE traffics. In other words, the call blocking probability of BE traffic increases more rapidly, the following is nrtPS traffic then rtPS and finally UGS. This is because the priorities given between service classes. The BU of the total system (BT otal / is the sum of the BU of different service classes (BUGS , BrtPS , BnrtPS , BBE /. In Figure 8, we have represented BT otal , BUGS , BrtPS , BnrtPS , BBE for all the traffics in the same figure, whereas in Figure 9, we give the average delay for all traffics. In both figures, the priority between the traffics is respected. Indeed, we have shown that the call blocking probability, the BU and the delay respect the priority between the traffics.

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Figure 9. Average delay of different service classes.

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Figure 10. Call blocking probability for real-time polling service traffic.

Figure 12. Call blocking probability for best effort traffic.

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Figure 11. Call blocking probability for non-real-time polling service traffic.

the blocking probabilities for BE traffic without degrading those other traffics. In Figures 10,11 and 12, call blocking probabilities are computed for rtPS, nrtPS and BE traffics by varying the number of SS, respectively. In this figures, we present the call blocking probabilities in the case of using the strict priority mechanism and in the case of our proposed scheme. We notice that the call blocking probabilities is improved for different service classes. Actually, we can see in Figure 10 that the call blocking probability for BE traffic decreases by 25%. These results validate our method based on token bucket mechanism by improving the overall QoS of accepted connections. Thus, we can consider that our model is very efficient as it increases the number of accepted BE connections without violating the QoS performance of other connections in the system. In Figures 13, 14 and 15, we represent all the traffics in the same figures. In fact, Figure 13 shows that the call blocking probabilities respect the priority between the traffics. Namely, the call blocking probabilities for rtPS are less than nrtPS and BE traffics in the case of considering our proposed scheme based on token bucket mechanism. In Figure 14, we give the call blocking probabilities for all 990

Figure 13. Call blocking probability of all traffics with strict priority.

the considered traffics where the strict priority between the traffics is respected. In order to show that our proposed scheme improves the call blocking probabilities for BE traffic without degrading those other traffics, we give in Figure 15 the call blocking probabilities for all traffics in the case where we consider our scheme based on token bucket mechanism and with considering the strict priority mechanism. Thus, the main objective of this scheme is to ensure the QoS performance of the BE traffics without violating the satisfaction of others traffics. We can conclude through the obtained results that our CAC and packet scheduling mechanism improves the quality of service of all traffic by solving the BE traffic starvation without penalising other traffics.

7. CONCLUSION The majority of classical CAC and packet scheduling schemes proposed in the literature have provided more QoS performance for real-time traffics without ensuring a minimum QoS for non-real time especially BE traffic. Thus, by penalising low priority traffics, we can easily degrade the QoS performance of such schemes. In this Trans. Emerging Tel. Tech. 25:981–992 (2014) © 2013 John Wiley & Sons, Ltd. DOI: 10.1002/ett

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REFERENCES

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Figure 14. Call blocking probability of all traffics with our token bucket model.

Figure 15. Call blocking probability of all traffics with different methods.

paper, we have proposed a new CAC mechanism and an UL packet scheduling method that take into account the QoS of different service classes connections. Our proposed scheme, based on QoS requirements, satisfies both BW and delay guarantees for the real time admitted connections in the network and improves also the QoS of BE traffic. To achieve this goal, we have proposed a new CAC and scheduling scheme, which is based on token bucket mechanism for rtPS, nrtPS and BE traffic classes in the purpose of limiting the number of accepted rtPS and nrtPS connections and to increase considerably the number of accepted BE connections without violating real time QoS performances. A mathematical model is developed based on continuous time Markov chain in order to evaluate the performance of our scheme. From analytical results, we can conclude that our proposition could be a better choice in Mobile WiMAX. Further research will focus on a simulation of another admission control schemes and scheduling policy employed in WiMAX networks with fixed and mobile technologies. Trans. Emerging Tel. Tech. 25:981–992 (2014) © 2013 John Wiley & Sons, Ltd. DOI: 10.1002/ett

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Trans. Emerging Tel. Tech. 25:981–992 (2014) © 2013 John Wiley & Sons, Ltd. DOI: 10.1002/ett