ABSTRACT 1. INTRODUCTION RESEARCH ARTICLE

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1 WIRELESS COMMUNICATIONS AND MOBILE COMPUTING Wrel. Commun. Mob. Comput. 2015; 15: Publshed onlne 5 May 2014 n Wley Onlne Lbrary (wleyonlnelbrary.com) RESEARCH ARTICLE Optmzed bandwdth allocaton n broadband wreless access networks Ndal Nasser 1 *, Red Mller 2, Amr Esmalpour 3, Abd-Elhamd M. Taha 1 and Tarek Bejaou 4 1 College of Engneerng, Alfasal Unversty, Ryadh, 11533, Saud Araba 2 Envronment Canada, Toronto, Ontaro, Canada 3 Electrcal and Computer Engneerng, Unversty of New Haven, West Haven, CT, U.S.A. 4 Faculty of Scences of Bzerte, Unversty of Carthage, Bzerte, 7000, Tunsa ABSTRACT Towards satsfyng the requrements of Internatonal Moble Telecommuncatons Advanced, both the Insttute of Electrcal and Electroncs Engneers (IEEE) and Thrd Generaton Partnershp Project (3GPP) ntroduced revolutonary wreless technologes, explotng advanced technologes and archtectures.both IEEE s (Worldwde Interoperablty for Mcrowave Access (WMAX)) and 3GPP s Long Term Evoluton have been ntroduced to accommodate the ncreasng demand for moble servces and applcatons. To realze the true potental of these technologes, however, opportunstc frameworks for rado resource management must be desgned to explot the adaptve nature of moble traffc. The utlty optmzed qualty-of-servce (QoS) framework proposed n ths paper for the moble WMAX networks acheves ths objectve. To mantan support for QoS guarantees, the framework captalzes on the adaptve nature of WMAX traffc by ndvdually lnkng connectons wth a utlty functon desgned to both uphold the end users perceved performance and determne bandwdth allocatons by a search tree maxmzaton algorthm. In dong so, bandwdth utlzaton s maxmzed for all actve connectons, and blockng and droppng probabltes for new and handover calls, respectvely, are mnmzed.the framework s evaluated through an extensve smulaton model and s shown to outperform state-of-the-art solutons. Copyrght 2014 John Wley & Sons, Ltd. KEYWORDS utlty functons; optmzaton; resource allocaton; QoS; moble WMAX *Correspondence Ndal Nasser, College of Engneerng, Alfasal Unversty, Ryadh, 11533, Saud Araba. E-mal: nnasser@alfasal.edu 1. INTRODUCTION The next generaton of wreless technology s promsng to satsfy the requrements of an ever expandng array of applcatons that greatly extend beyond the contemporary voce and data servces the de facto applcatons of thrd generaton (3G) networks. The Internatonal Telecommuncatons Unon Rado communcatons dvson (ITU-R) defnes the next generaton as one that surpasses the capabltes of 3G networks n many ways, ncludng deal data rates (up to 1 Gbps n the downlnk), sustaned rates at hgh moblty (up to km/h), and a strong and true convergence to all-internet protocol (IP) nfrastructure. Two revolutonary 3G technologes are makng the ITU-R expectatons of fourth generaton (4G) more tangble, namely moble Worldwde Interoperablty for Mcrowave Access (WMAX) and Long Term Evoluton. Both technologes explot several advances to enhance moble network operaton, ncludng the use of multcarrer access technologes, advanced antenna technques, and new access archtectures such as femtocells, relay statons, and so on. Moble WMAX was frst defned by the Insttute of Electrcal and Electroncs Engneers (IEEE) e amendment [1] and then by the aggregated IEEE document [2]. The successor to the moble WMAX that satsfes the ITU-R requrements for the next generaton of wreless networks has already been ratfed n the IEEE m standard and wll offer sgnfcantly more features compared wth the 3G-WMAX, ncludng voce over IP (VoIP), streamng applcatons, IP televson, and onlne gamng to name a few. More crtcally, however, users wll be able to access these servces anytme and anywhere to satsfy the requrement of 4G s ubqutous and pervasve networkng systems, from both moble and statonary devces. A challenge, however, wll reman wth the unqueness of the qualty-of-servce (QoS) requrements Copyrght 2014 John Wley & Sons, Ltd. 2111

2 Bandwdth allocaton broadband wreless networks N. Nasser et al. of dfferent users, whch s ndvdually descrbed usng attrbutes such as mnmum reserved and maxmum sustaned data rates, mnmum latency, and jtter. The vtal role played by dfferent modules of rado resource management (RRM) functonaltes n moble WMAX cannot therefore be overemphaszed. Specfcally, functonaltes such as admsson control (AC), bandwdth adaptaton (BA), and handover management (HM) are crucal to the operaton of moble WMAX, especally gven the lmted amount of avalable resources (.e., bandwdth, transmtters, power, etc.). An AC module regulates call admsson to the network and, together wth a BA module, allows the network to adapt to traffc varatons. Thus, the crtcal balancng act of an AC module weghs between admttng new users and the QoS mantaned for actve/current ones. In turn, BA modules vary allocatons to actve users based on both the nput from the AC module and the current network condtons. In nstances of low demand, users may acheve ther maxmum bandwdth requests, whle n nstances of ncreased demand, allocatons are gracefully reduced to the users ndvdual mnmum bandwdth requests. At a mnmum, an HM guarantees that a user does not lose connecton as t moves between dfferent cells by rasng the property of a moble user s call over a new one and by ensurng that suffcent resources are avalable n an arbtrary cell for handover connectons. Needless to say, the operaton of RRM functonaltes n a framework must be harmonzed. A serous drawback n exstng frameworks, however, s ther lack of adaptablty as they do not fully explot the adaptve nature that s characterstc of the majorty of wreless applcatons. Allowng for ths adaptablty can substantally ncrease both operator proftablty and user satsfacton. The operatve condton n ntroducng such adaptaton s to consstently uphold the user s servce level agreement. A leadng example of resource frameworks proposed for moble WMAX exercses ths constrant s the quadra-threshold bandwdth reservaton (QTBR) scheme [3]. QTBR utlzes a congeston avodance method to reduce the bandwdth of actve connectons. The QTBR framework, however, s lmted n ts mplementaton as t reles on a preset lnear scale factor n bandwdth allocaton. In operaton, ths scalng factor becomes ndfferent to the adaptve propertes of the connected applcatons and accordngly does not maxmze resource allocaton. Other bandwdth allocaton modules n the lterature, such as the hghest urgency frst (HUF) [4], lack any congeston avodance functonaltes. Meanwhle, exstng WMAX AC proposals [5 7] rely on nterclass threshold blockng polces. Such polces preemptvely block specfc servce classes from accessng the network, whch could be potentally devastatng to overall resource utlzaton. A vod therefore exsts n RRM framework desgn whereby the adaptve nature of WMAX traffc s fully utlzed, and WMAX s moblty requrement s fully satsfed through a dedcated handover management scheme. In ths paper, we propose an RRM framework that targets ths specfc vod. The proposed framework mantans the user s QoS requrements through actvely maxmzng the network resource utlzaton and mnmzng the blockng and handover droppng of ncomng call requests. Furthermore, the framework successfully desgn four objectves: (1) Mnmze ncomng connecton blockng and handover droppng probabltes; (2) Prortze handover connectons; (3) Maxmze bandwdth utlzaton; and (4) Mnmze mplementaton complexty. The remander of ths paper s organzed as follows. The next secton overvews the overall archtecture and operaton of WMAX networks before outlnng ts RRM framework requrements. It also provdes a revew of the lterature relevant to the proposal made heren. Secton 3 ntroduces our proposed framework, the utlty optmzed QoS (UOQoS), begnnng wth a descrpton of ts desgn and mplementaton objectves and gong through ts theoretcal bass of operaton. Detals of the smulaton model used n analyzng the performance of the UOQoS n comparson wth the QTBR are provded n Secton 4. Fnally, Secton 5 concludes the work. 2. BACKGROUND Ths secton provdes an overvew of WMAX aspects relevant to our proposals and provdes the motvatons for our work by revewng state-of-the-art solutons n lterature on RRM functonaltes proposed for WMAX networks WMAX networks WMAX networks enable robust wreless delvery of IP-based servces and applcatons. The network can transmt a theoretcal maxmum data rate of 120 Mb/s over a range of 50 km, provde mnmum QoS for multple servces, and has mproved non-lne-of-sght coverage for urban deployment [8]. WMAX network archtecture conssts of four man enttes: base staton (BS), core network (CN), moble subscrbers (MSs), and subscrber staton (SS). A typcal WMAX network ncludes one or more BSs provdng servce, relayed from the CN, to a coverage zone. SSs are statonary recevers and n turn provde ether wreless or wred connectvty to subordnate users and/or devces. MSs are connected users who are free to move around. Users may swtch servce between two BSs when they move from one servce area to another; the handover procedure performs the servce transfer from one BS to the next. The IEEE standards provde the physcal (PHY) and medum access control (MAC) layers for fxed and moble access n WMAX networks. They also defne fve servces classes for moble applcatons, namely unsolcted grant servce (UGS), extended real-tme pollng 2112 Wrel. Commun. Mob. Comput. 2015; 15: John Wley & Sons, Ltd.

3 N. Nasser et al. Bandwdth allocaton broadband wreless networks servce (ertps), real-tme pollng servce (rtps), non-realtme pollng servce (nrtps), and best effort (BE) [1]. Support for these servce classes s mandated for any RRM framework operatng n a WMAX network, although the standard does not detal specfc RRM technques, and leaves the desgn open for vendor and operator nnovaton Rado resource management for WMAX Satsfyng the QoS requrements of the dfferent WMAX servce classes entals the desgn of effcent RRM modules that facltate achevng network operaton objectves. Ths apples to the three man RRM modules dscussed n ths work: admsson control (AC), bandwdth allocaton (BA), and handover management (HM). Accommodatng dfferent applcaton types n a moble settng, these modules must balance the requests of the ndvdual servces classes whle consderng user demand and network condtons. Each of the fve servce classes noted earler has unque QoS connecton requrements, for example, n terms of delay, jtter, mnmum data rates, and maxmum data rate. The essental role of an AC module s decded upon whether to admt or deny a user s request to access network resource. In WMAX, an AC module s objectve s threefold: to satsfy the user s QoS requrements as defned by the fve servce classes, to maxmze network resource utlzaton, and to adapt to the varyng traffc demand. The qualty of an AC module s dentfed n terms of two connecton-level QoS metrcs called the new call blockng probablty (NCBP) and the handover call droppng probablty (HCDP). The latter metrc s sgnfcant when t comes to supportng moblty, especally as users are more senstve to call drops than blocks. One possble way to dfferentate user connecton requests s through statc bandwdth reservatons. In QTBR [6], the AC module makes ts decsons based on fxed resource utlzaton threshold defned for ndvdual servce classes. User connectons are prortzed based on ther servce classes, wth UGS havng the hghest prorty order, followed by ertps, rtps, nrtps, and, fnally, BE, wth BE havng the lowest prorty. A mnmum threshold s assgned for each servce class and s actvely compared wth the cell s bandwdth utlzaton. When the avalable bandwdth becomes less than the threshold for a certan servce class, all lower prorty connectons are blocked. Overall, the desgn approach for QTBR s acceptable, mantanng low blockng rates for UGS connectons and achevng up to 92$ resource utlzaton [6]. However, QTBR does exhbt a non-adaptve bas towards hgher prorty calls, even under low traffc demand, whch results n substantal resource underutlzaton. Another AC scheme ntroduced n [7] performs AC based on calculated expected NCBP. Blockng probabltes are calculated usng a Chernoff boundng method. AC decsons are made at the connecton level for UGS and BE servces, whch are consdered to requre a constant bandwdth rate. For rtps and nrtps servces wth varyng bandwdth requrements, the AC decsons are made at the burst level. A bnary search algorthm s used to quckly calculate the upper bound blockng probablty for each servce class. The search classfes four bandwdth threshold levels; each assocated wth a servce class. If the sum bandwdth provded to all connectons of a servce class exceeds ts threshold level, new connectons from ths class are blocked. Wthout consderaton for moble users and the ertps servce class, ths algorthm s not sutable for moble WMAX. In a generalzed RRM framework, a BA module s operaton s closely ted to packet schedulng (PS), whch s another RRM functonalty operatng at the packet level. Consderatons for a PS are made n our framework, although ts mplementaton detals are beyond the scope of ths paper. The nterested reader can kndly refer to other works that have dscussed WMAX PS n a more approprate detal [9 13]. In moble WMAX, a separaton s made between the downlnk (DL) and the uplnk (UL), wth the traffc of each lnk communcated over a dfferent channel. At a frame level, each connecton frame s separated nto DL and UL sub-frames. A proposal of nterest n ths regard s the HUF algorthm [4], whch consders traffc urgency, prorty, and farness when allocatng network resources. HUF dynamcally adjusts DL and UL allocatons based drectly on the ratos between ther respectve requests. HUF, however, s concerned prmarly wth offerng latency guarantees and does not address the need for adaptve congeston avodance n WMAX. Other BA methods deal wth bandwdth requests made by each applcaton per connecton. The authors n [14] propose a method to adjust allocatons accordng to channel qualty condtons at the burst level. The algorthm parttons bandwdth based on the requests made by actve connectons. Bandwdth s allocated such that the mnmum QoS requrements are met, and any remanng bandwdth s assgned to users wth better channel qualty. The remanng unassgned bandwdth s dstrbuted to connectons wth unfulflled maxmum bandwdth requests. Ths method guarantees that QoS requrements are met and sgnfcantly ncreases the total throughput. QTBR s QoS-aware BA [3] avods congeston by balancng the blockng and droppng probabltes, whch results n reducng the allocatons for actve connectons. Upon surpassng predetermned threshold levels of both blockng and droppng rates, the allocatons are reduced by a lnear factor. Ths reducton, however, negatvely affects bandwdth utlzaton n many common operatonal scenaros. For example, by couplng the blockng and droppng threshold levels, QTBR s flexblty s greatly lmted when dealng wth a varable traffc load. A case of smultaneous low droppng and hgh blockng, for nstance, would result n a consderable reducton n resource utlzaton. For moble WMAX, the mportance of an HM cannot be overstated as t s the key enabler for users to roam across the network geographcal terran whle mantanng contnuous access to network resources. At the connecton level, the HCDP measure s key. As noted earler, droppng Wrel. Commun. Mob. Comput. 2015; 15: John Wley & Sons, Ltd. 2113

4 Bandwdth allocaton broadband wreless networks N. Nasser et al. an actve user connecton results n greater user dssatsfacton wth the operator servce. Reducng HCDP s thus an essental HM desgn objectve, wth the understandng of the tradeoff between HCDP and NCBP. Bandwdth reservaton s a strategy that facltates ths desgn objectve. Statc reservatons, that s, reservatons ndfferent to magntude and type of demand, are easy to mplement but drectly affect network resource utlzaton. Dynamc reservatons, on the other hand, whle requrng some sgnalng overhead and processng durng operaton, offer superor resource use. Methods proposed n [15 17] employ predcton technques n reservng network allocatons for handover users as they move between coverage zones and trgger handover requests. Based on the predcted traffc demand, approprate resources are reserved at target BSs. The predctons are used to choose sutable bandwdth reservatons at the target BSs. When t s clear that a user wll soon transton between coverage zones, these algorthms attempt to reserve more resources to serve ncomng handovers. Movement predctons can be based on ether GPS nformaton from the user devce or other devce measurements such as sgnal strength [18 22]. 3. UOQoS THE UTILITY OPTIMIZED QUALITY-OF-SERVICE RRM FRAMEWORK WMAX networks support a wde range of applcatons, each wth unque resource requrements. Voce and vdeo streamng, TV broadcastng, and other applcatons have dfferent bandwdth adaptaton characterstcs. Some applcatons requre strct end-to-end bandwdth guarantees; others can tolerate and adapt to changng bandwdth levels. Bandwdth has a large mpact on the QoS experence by moble WMAX users. Despte the large data rates provded by WMAX, bandwdth s stll constraned by hgh demands of the resource ntensve applcatons, whch requres well managed resource dstrbuton n order to guarantee QoS to end users. The problem of allocatng fnte network resources s resolved by usng a resource management soluton wth adaptve BA. A resource management soluton s responsble for adaptng the network to traffc condtons, whch s acheved by combnng a par of adaptve BA and AC algorthms. Towards ths end, we propose the UOQoS RRM framework, whch nvolves dfferent resource management technques n balancng the ndvdual propertes of the dfferent servce classes. The prncple element of UOQoS s maxmzng applcatonspecfc utlty functons. The resource management modules employed are an AC module, a BA module, and an HM module. The system model for the framework s defned as follows. It s assumed that the system has n actve connectons and that the BS oversees acceptng or denyng new connecton requests and provdng servce to accepted requests by allocatng bandwdth. Each actve connecton s assumed to be usng an applcaton assocated wth one of WMAX s fve servce class (.e., UGS, rtps, ertps, nrtps, or BE). The servce s provded by a connecton to an external network, such as the Internet servce. The BS also oversees the allocaton of all avalable resources by guaranteeng mnmum QoS requrements to all actve users. In UOQoS, the AC accepts or denes new connecton requests, whle the BA s responsble for all ncreasng or decreasng allocatons for actve users. In the mplementaton of the framework, a PS module s also necessary to enforce tme-based guarantees (e.g., delay and jtter), as well as to ensure farness among connectons. In a way, the AC module preserves the qualty of ongong connectons by lmtng new admsson. Meanwhle, BA dynamcally allocates bandwdth to satsfy the varable demand on the network. In ths work, the BA employs a utlty-based multservce traffc model that dfferentates between user connectons based on the requrements of the dfferent servce classes. In dong so, t employs the adaptve characterstcs of certan traffc types. As both new and handover connectons are contendng for the same network resource, the makng of actve connectons n a congeston network may not be even. From the user s perspectve, droppng an actve call s less favorable than blockng a new connecton request. To account for ths prorty, a dynamc reservaton s employed whereby some resources are exclusve to handover users. Ths dynamc bandwdth reservaton s ntegrated n the AC and BA modules, as well as a negatng mechansm to reclam subscrbed bandwdth from the reserved resource pool Framework archtecture and components Fgure 1 llustrates the UOQoS framework archtecture. The BS connects all users wth the exstng network. Incomng connectons request resources from the AC, and based on network condtons retreved from the BA module, new connectons are accepted or rejected. When an ncomng connecton s accepted, the BA must allocate the bandwdth to all actve connectons. Fgure 1. UOQoS framework archtecture Wrel. Commun. Mob. Comput. 2015; 15: John Wley & Sons, Ltd.

5 N. Nasser et al. Bandwdth allocaton broadband wreless networks Adaptve bandwdth allocaton (ABA) module. In a tradtonal wreless network, once a connecton s admtted to the network, ts bandwdth requrements are fxed over ts lfetme. In a WMAX network wth a wde range of applcatons often wth low latency demands, however, an adaptve approach to BA (ABA) s more practcal. Wth an adaptve technque, the bandwdth usage of actve connectons can be modfed n order to permt a greater number of connectons. A utlty optmzed based resource management s ntroduced, applyng a multservce traffc model to ABA. The traffc model reflects the bandwdth adaptaton propertes of each applcaton type. WMAX provdes a set of traffc servce classes that group applcaton types together. The applcatons represented by each servce class share bandwdth adaptaton propertes. The ABA module uses a utlty functon (UF) to represent the utlzaton maxmzaton objectve, whch relates the bandwdth assgned to a connecton of a partcular WMAX servce class wth ts user satsfacton. End users are rarely concerned drectly wth the amount of bandwdth assgned to them, but rather wth ther perceved user experence. The needs of each servce class are reflected n the choce of UF Defnng UOQoS utlty functons. The use of utlty functons s central to the operaton of UOQoS. The desgn of the utlty functons s made such that they capture end-users bandwdth requrements and n addton to the adaptve nature of dfferent applcaton traffc. The use of utlty functons s certanly not new and has been wdely made n the desgn of other bandwdth adaptaton schemes [23 25]. In ths work, mappng for the utlty functons per-connecton curves s made between the allocated bandwdth and the performance of the allocaton as perceved by the end user. The functons employed are monotoncally non-decreasng, whch realzes the fact that the allocaton of hgher bandwdth does reduce performance. The functons are also defned over the nterval [0, 1], wth each connecton havng a unque maxmum bandwdth requrement that leads to a maxmum utlty of value 1. Ths s llustrated n Equaton (1). As t s mpractcal to a UF for ndvdual applcatons, we consder all applcatons wthn a sngle WMAX servce class to exhbt the same utlty characterstcs. In WMAX fve servces classes, UGS s the only servce class that mposes a hard real-tme (RT) UF, wth connectons havng a fxed bandwdth requrement. Over the lfetme of a UGS connecton, no adaptaton s consdered possble. Wth ths n mnd, a UGS connecton has a utlty.u /, bandwdth.b /, and mnmum bandwdth requrement b mn. The hard RT traffc s modeled as a Heavsde functon, ndcatng whether the maxmum or no bandwdth s suppled. 0, b < b u.b / D mn 1, b b mn (1) Applcatons wth flexble adaptve requrements comprse the rtps, ertps, and nrtps servce classes. An adaptve connecton has a mnmum bandwdth, b mn,andamaxmum sustaned bandwdth, b max. The UF for connecton has utlty u, bandwdth b, and constants k,1 and k,2,as shown n Equaton (2). u.b / D 1 e.k,1 b 2 /.k,2 Cb/ Constants, k,1 and k,2 are decded upon such that u.0/ D 0andu b max D u max. Ths equaton approaches but does not reach u max D 1. The relatonshp between k,1 and k,2 can thus be defned by Equaton (3): (2) k,1 D ln 1 u max k,2 C b max b max 2 (3) The pont b mn s defned where the UF has a pont of nflecton, swtchng from concave to convex. Ths occurs where the second dervatve of Equaton (2) s equal to zero:! d 2.k,1 b 2..k /,2 Cb / D 0 u.b / D 1 e The resultant functon s a cubc polynomal presented n Equaton (4): k,2 3 C b mn 2k,1 b mn 2 k,2 2 2k,1 k,2 b mn 3 k,1 b mn 4 D 0 (4) 2 Substtutng Equaton (3) nto Equaton (4) yelds Equaton (5): C 2ln 1 u max C C b mn C 2ln 1 u max C 2ln 1 u max 2ln 1 u max C ln 1 u max! 1 b mn 2 b max A k,2 3 2 b mn b max b mn 3!.b max / 2 k,2 2 3 b mn 4! b max C.b max / 2 k,2 2 4 b mn l b mn l 2.b max / D 0 Ths s a cubc polynomal n k,2, whch s solved usng the predetermned values for b mn, b max,andu mn k,1 s then calculated from Equaton (3). Non-RT (NRT) servce classes have exhbted a large delay tolerance and do not have strct bandwdth (5) Wrel. Commun. Mob. Comput. 2015; 15: John Wley & Sons, Ltd. 2115

6 Bandwdth allocaton broadband wreless networks N. Nasser et al. requrements. The BE servce class s the only class wth an NRT UF. NRT traffc has a large delay tolerance and lacks strct bandwdth requrements. BE s the only WMAX servce class usng an NRT-UF. It does not have a specfed b mn, and ts b max s determned by the servce provder. Any applcaton that can work wthout tme guarantees, such as Web browsng or fle transfer, falls nto ths servce class. The NRT UF s an exponental functon, calculated n Equaton (6): u.b / D 1 e k b. b max (6) The constant k can be determned usng the maxmum bandwdth and related utltes as n Equaton (7): k D ln 1 u max (7) Operaton of the UOQoS framework. The operaton of the BA module s based on a search tree algorthm. When an ncomng connecton s admtted by the AC nto the network, t s presumed to acqure both the mnmum requred and the maxmum sustaned bandwdth values, n addton to the type of WMAX servce class t follows. To satsfy the mnmum bandwdth requrements, the amount of bandwdth requred to sustan an acceptable level of performance for the end user must be mantaned. Meanwhle, the maxmum possble allocaton requested by a user s consdered to be ts nomnal bandwdth requrement. An approprate UF s chosen based on the connectons servce class. The bandwdth requrements nclude b max and b mn n the case of adaptve classes (rtps, nrtps, and ertps). The BA processes nformaton from both new and actve connectons to determne the resources to be allocated to each connecton. In a WMAX network, a BS s assumed to be assgned a maxmum bandwdth, denoted ˇ. The allocaton of the objectve s to maxmze the sum of the aggregate utlty for the n connectons n the network, as shown n Equaton (8), wth each connecton havng utlty u and bandwdth b. maxmze X n u.b / (8) D1 Subject to the constrant n Equaton (9): X n b ˇ (9) D1 Such a maxmzaton problem s non-determnstc polynomal-tme hard (NP-hard), renderng drect soluton methods mpractcal for mplementaton. To overcome ths complexty, a tree search-based quantzed optmzaton functon s used. The method offers a way to lnearly manage multple bandwdth levels through reducng the complexty of the search tree. Each UF s quantzed by dvdng ts range nto a number of equally szed utlty ntervals. In [26], t was shown that the loss n accuracy (.e., optmalty) s manageable for such tree search-based method. The accuracy, however, can be arbtrarly controlled through ncreasng or decreasng the number of steps. The quantzed UF of connecton s generally represented usng Equaton (10): u.b / D < b mn u mn < b max u max > >, < b mnc1 u mnc1 >, :::, (10) For n connectons, the utlty search tree can be represented usng the set S, as shown n Equaton (11). S D fu.b /j1 ng (11) The maxmum utlty of tree S, that s, max P b, can thus be found under the constrant presented n Equaton (12). X b ˇ ˇreserved (12) A greedy algorthm s used to carry out the sad maxmzaton. Allocatons are made by prortzng connecton usng what s called a utlty generaton rato. The result of ths generaton s a set of bandwdth profles, denoted b cur.at ntalzaton, b reserved equals ˇreserved. It should be noted, however, that ths may not always be practcally the case as the value of b reserved may take on addtonal values once ncomng handovers have taken place. In what follows, we detal the operaton of the algorthm. The algorthm starts wth a predetermned amount of unallocated bandwdth reserved for ncomng handovers. Allocatng the maxmum requred bandwdth to each connecton s then tred. If t s found possble, the objectve of maxmzng allocatons becomes redundant, and the algorthm concludes. If, however, the avalable resources are not suffcent for maxmzed allocatons, a search tree s ntalzed such that the lowest nodes n the three are occuped. The utlty generaton rato r cur and the requred bandwdth b req are then calculated for upgradng the connecton to the next hgher bandwdth level. In the next step, r max s deduced for every connecton by ncreasng the temporary allocaton b temp by one and calculatng each temporary generaton rato r temp. Meanwhle, the next bandwdth level b next s also chosen correspondng to the maxmum generaton rato. The algorthm then proceeds to compare b aval wth the maxmum requested bandwdth b req,max needed to upgrade each connecton. If b aval b req,max, then the remanng b aval s gven to the connecton wth the hghest current utlty generaton rato r cur, and the algorthm termnates. Next, the algorthm upgrades the bandwdth to the b next j f there s enough bandwdth avalable, and the temporary BA b temp s also upgraded to the next possble allocaton. If there s no enough bandwdth avalable, b aval s added to b curr j, and the algorthm termnates. The algorthm then updates connecton j based on the current and 2116 Wrel. Commun. Mob. Comput. 2015; 15: John Wley & Sons, Ltd.

7 N. Nasser et al. Bandwdth allocaton broadband wreless networks next possble BAs. Ths process s repeated untl the avalable resources are exhausted, whch s verfed ether when b aval b req,max or when b aval < b next j b curr for connecton j wth largest r max Admsson control. Inthecasewherem new ncomng connectons and n ongong connectons exst, the AC represents the search tree as S 0 D fu.b /j1 n C mg. If the mnmum bandwdth can be allocated to every connecton.e., b aval P ncm D1 breq, the same maxmzaton process used for S wll be used for S 0 to fnd new bandwdth levels. If the unallocated resources are nsuffcent, the new connecton s blocked Adaptve bandwdth allocaton wth reservaton. In the proposed statc bandwdth reservaton scheme, the bandwdth s reserved for handover connectons by the AC module; the bandwdth wll not be assgned unless t s exclusvely used for handlng ncomng handovers. If we consder the S 0 case presented n the prevous secton for BA purposes, the objectve becomes maxmzng P ncm D0 u.b /, subject to the constrant P n D0 b ˇ. The maxmzaton of S s shown n Algorthm 1. The reservaton steps are performed n steps 2 and 6 as ndcated later n the text. The reserved bandwdth b reserved s assgned to ncomng handovers by ths operaton and must be freed by another operaton. The process of restorng reserved bandwdth s descrbed n the followng sectons Reserved bandwdth restoraton. As the network contnues to operate, bandwdth may be freed by the completed connectons or outgong handovers. These events requre b reserved restoraton events, where the prevously consdered handover connectons become normal connectons and no longer draw upon reserved bandwdth. The bandwdth restoraton events occur before the dynamc BA algorthm s performed. The amount of bandwdth currently allocated s represented by b allocated. If there are stll reserved bandwdth n use and more avalable bandwdths to reassgn, the process attempts to assgn as much of b aval to b reserved as possble. 4. PERFORMANCE EVALUATION In the prevous secton, the reduced complexty at the core of the UOQoS framework demonstrates the feasblty of ts practcal mplementaton. Our nterest n ths secton s to evaluate whether the proposed framework acheves the remander of ts desgn objectves. Both UOQoS and QTBR [3,6] are evaluated n a smulaton envronment under two dstnct moblty scenaros, that s, pedestran Wrel. Commun. Mob. Comput. 2015; 15: John Wley & Sons, Ltd. 2117

8 Bandwdth allocaton broadband wreless networks N. Nasser et al. Table I. Connecton generaton detals and connecton rates. Servce Servce Connecton Connecton Max rate Mn rate class applcaton probablty duraton (s) (Kbps) (Kbps) UGS Dedcated UGS rtps MPEG vdeo ertps VoIP nrtps FTP (rate guaranteed) BE FTP (non-rate guaranteed) UGS, unsolcted grant servce; rtps, real-tme pollng servce; ertps, extended real-tme pollng servce; nrtps, non-real-tme pollng servce; BE, best effort; VoIP, voce over Internet protocol; FTP, fle transfer protocol. and vehcular, accordng to the performance metrcs that are dscussed later n the text Smulaton model To facltate our evaluaton, a smulaton envronment was desgned and mplemented usng network smulator verson 2 (ns-2) [27]. Two mult-rate MAC layers were added to the ns-2 orthogonal frequency-dvson multple access wreless PHY layer module to emulate the operaton of WMAX networks. Implementatons for both UOQoS and QTBR were also made. The smulated network models a WMAX network wth a group of cells, each cell wth a BS at ts center. A capacty of 40 Mbps s assumed n each cell s downstream. The MAC layers mplemented comprse an AC unt, a bandwdth management unt (BMU), and a schedulng unt (SU). The SU and BMU for the respectve frameworks are mplemented based on the prevous descrpton (for UOQoS) and the descrpton n [3,6] (for QTBR). The SU s adopted from [28]. The selected scheduler utlzes a weghted round-robn method between flows. For each frame, the assocate percentage factor s added to each class q 5, q 4, q 3, q 2, q 1, respectvely, related to the UGS, rtps, ertps, nrtps, and BE servce classes. For each class, the percentage factor dctates the porton of the total bandwdth t receves. At scheduler ntalzaton, the expected servng quantty.b type / of each classfcaton s calculated based on Equaton (13): B type D mn R type, B total q, 8 2 f1, 2, :::,5g, q 1 (13) where R type represents the total amount of requests per servce type and B total represents the total avalable bandwdth of the system. The scheduler then serves each remanng un-served connecton n prorty order; that s, class are only served when class C 1 are served. Ths process wll be repeated untl ether the bandwdth s completely allocated or all the remanng requestng connectons are served. Ths strategy guarantees that lower prorty traffc can stll obtan a mnmum bandwdth for transmsson f the traffc load s extremely heavy. The two smulated user envronments (pedestran and vehcular) enable separate testng of UOQoS and QTBR wth and wthout bandwdth reservaton. The pedestran envronment smulates pedestrans walkng at 3 km/h n a 500-m dameter cell; no bandwdth reservaton s used n UOQoS or QTBR for ths envronment because of low handover rates. (A typcal user may cross a cell boundary once every 5 mn.) UOQoS wthout bandwdth reservaton was descrbed n Secton 3, where handovers are treated lke new connecton requests. QTBR can be adjusted by varyng ts AC parameters. In the vehcular smulaton model connectons travellng at nter-cty speeds of 60 km/h n a 1000-m dameter cell, users may cross a cell boundary approxmately every 30 s. Because of the consderable handover rate, the UOQoS and QTBR algorthms are both used wth ther respectve bandwdth reservaton methods Traffc model The network comprses a group of cells, wth a BS at the center of each cell. Each BS s connected to the CN usng a 40-Mbps backhaul lnk wth a 25-ms delay. In turn, the CN s connected to the Internet wth a 100-Mbps lnk wth a 25- ms delay. Users connected va the CN and the Internet to a data server wth a 100-Mbps uplnk wth a 25-ms delay. For each user, the connecton lasts for a fxed duraton determned by the applcaton type and ndcated n Table I. In the network, users are randomly dstrbuted at ntalzaton. When the smulaton starts, each user assumes a lnear path and travels at a speed of ether 3 or 60 km/h, dependng on whether the pedestran or vehcular envronment s engaged. The generaton of connecton requests follows a Posson process wth a mean rate specfc to the cell n whch the call s orgnatng. In generatng the call requests, the applcaton type s selected based on a probablty shown n Table I. Fnally, Table I also shows the bandwdth requrements for each servce class, n addton to the correspondng connecton rates Results Smulatons are performed for both the pedestran and vehcular envronments. The average number of generated calls s controlled and s vared n the experments between 5 and 110 connectons per mnute (cpm) n ntervals of 5 cpm. For each result pont, the smulaton was repeated 10 tmes, each lastng for 500 s smulated tme. The smulaton results obtaned have a 95% confdence level, wth 5% 2118 Wrel. Commun. Mob. Comput. 2015; 15: John Wley & Sons, Ltd.

9 N. Nasser et al. Bandwdth allocaton broadband wreless networks Table II. UOQoS utlty functon and QTBR bandwdth adaptaton parameters. UOQoS QTBR Servce Max rate Mn rate Utlty Max rate Mn rate Utlty class Applcaton (Kbps, utl) (Kbps, utl) pont (Kbps) (Kbps) pont UGS Dedcated UGS (768, 1) rtps MPEG Vdeo (256, 1) (114, 0.3) ertps VoIP (256, 1) (114, 0.4) nrtps FTP (rate guaranteed) (512, 1) (226, 0.3) BE FTP (non-rate guaranteed) (16, 1) (4, 0.4) UOQoS, utlty optmzed qualty of servce; QTBR, quadra-threshold bandwdth reservaton; UGS, unsolcted grant servce; rtps, real-tme pollng servce; ertps, extended real-tme pollng servce; nrtps, non-real-tme pollng servce; BE, best effort; VoIP, voce over Internet protocol; FTP, fle transfer protocol. confdence ntervals. Table II ncludes UOQoS and QTBRs bandwdth rates determned by utlty functons. The maxmum and mnmum rates are shown wth ther respectve utlty ratng ponts Pedestran envronment. Ths envronment emulates users movng at a nomnal walkng speed. Both UOQoS and QTBR are evaluated wthout employng bandwdth reservatons and are adjusted by varyng AC parameters. Fgure 2 shows the effect of varyng the connecton arrval rate on bandwdth utlzaton. Both schemes exhbt a lnear ncrease n bandwdth utlzaton as the number of connecton requests rses. The lnear ncrease, however, saturates at around 50 cpm, at whch pont both algorthms respond to the lack of suffcent resources for maxmzed allocatons to all actve connectons. UOQoS wth reservatons utlzes nearly all of the avalable bandwdths. In allowng connectons from all class at all tmes, that s, wthout bas to servce classes wth hgher prorty, UOQoS acheves a better resource utlzaton than QTBR. In turn, n denyng lower classes access to network resources when resources are low, QTBR exhbts a lower overall bandwdth utlzaton. At hgher loads, QTBR partally reserves the bandwdth exclusvely for UGS connectons, wth the excess bandwdth not utlzed because of the low ncomng rate of UGS connectons n ths specfc scenaro. By blockng adaptve classes such as rtps, ertps, and nrtps, the QTBR model cannot take advantage of the adaptve bandwdth requrements. Ths shows that UOQoS has hgher bandwdth utlzaton than QTBR when low handover rates are encountered. Fgure 3 shows the effect of varyng the connecton arrval rate on new connecton request blockng probabltes. UOQoS does not block new connectons untl t s absolutely necessary at around 80 cpm. Ths s the pont at whch there s no enough bandwdth avalable to satsfy the mnmum bandwdth requrements of all actve connectons. However, QTBR starts blockng connectons much earler, at around 50 cpm. Fgure 2 shows that 60 cpm s the pont at whch not all connectons can be completely maxmzed. The QTBR algorthm begns blockng BE, nrtps, ertps, and rtps when a specfc bandwdth utlzaton level s reached. Fgure 2. Bandwdth utlzaton at dfferent connecton arrval rates n pedestran envronment. Fgure 3. Blockng probablty at dfferent connecton arrval rates n pedestran envronment. Next, we compare the effect of varyng the connecton arrval rate on connecton blockng probabltes for each connecton class. Fgures 4 and 5 show correspondng values for UGS servces, versus the adaptve classes, rtps, ertps, and nrtps, respectvely, whle Fgure 6 shows the same value for BE traffc. The connecton blockng of the UGS, rtps, and BE shows the dfferent approaches Wrel. Commun. Mob. Comput. 2015; 15: John Wley & Sons, Ltd. 2119

10 Bandwdth allocaton broadband wreless networks N. Nasser et al. Fgure 4. UGS blockng probablty at dfferent connecton arrval rates n pedestran envronment. Fgure 5. Adaptve class blockng probablty at dfferent connecton arrval rates n pedestran envronment. taken by the UOQoS framework and the QTBR algorthm. UOQoS slghtly reduces the chances of UGS connectons n order to allow more connectons from other classes, whle QTBR acts n opposte drecton, sacrfcng other connectons n favor of UGS. QTBR shows a local maxmum for ertps and nrtps near 70 cpm. Ths s caused by the threshold AC scheme used, where bandwdth utlzaton exceeds the rejecton thresholds for ertps and nrtps connectons. QTBR performs bandwdth reductons when UGS blockng probablty s hgh and when overall handover droppng s hgh. The UGS blockng probablty begns to ncrease as the connecton arrval rate approaches 80. At ths pont, QTBR begns reducng bandwdth to actve connectons, whch results n reducton of the blockng probabltes for ertps and nrtps traffc Vehcular envronment. The vehcular moblty envronment emulates users travellng at a speed of 60 km/h n a 1-km dameter cell. At Fgure 6. BE connecton blockng probablty at dfferent connecton arrval rates n pedestran envronment. ths speed, users may cross cell boundares (thus, trggerng a handover request) approxmately every 30 s. Ths results n a consderable handover rate and justfes the mplementaton of both UOQoS and QTBR wth an approprate bandwdth reservaton mechansm. When ncreasng the connecton arrval rate, both algorthms exhbted a lnear ncrease n bandwdth utlzaton. The bandwdth utlzaton, however, levels off at around 40 cpm, at whch pont both algorthms respond to bandwdth scarcty. As n the pedestran envronment, QTBR exhbts a bas towards hgher prorty servce classes. At a hgh aggregate load, QTBR reserves a certan amount of bandwdth exclusvely for UGS and handover connectons. Utlzaton thus drops as the rate of generatng UGS connecton requests s slow. As the aggregate load ncreases from 60 to 80 cpm, the reserved bandwdth s assgned to ncomng handovers, whch produces a smaller dfference n utlzaton dstrbutons than n the pedestran scenaro. By blockng new connectons from adaptve classes, QTBR becomes unable to explot the classes adaptablty. In turn, UOQoS exhbts hgher bandwdth utlzaton than QTBR when consderable handover rates are encountered. Fgure 7 shows the effect of varyng the connecton arrval rate on connecton blockng probablty n case of vehcular envronment. UOQoS only blocks new connectons at around 75 cpm, at the pont where there s no enough bandwdth to supply every actve connecton s mnmum requrements. There s a slght shft from 80 cpm n the pedestran envronment because of the extra bandwdth requred for handover reservaton. QTBR starts blockng connectons much earler, near 60 cpm. The blockng rate of QTBR begns to ncrease at 60 cpm, when the bandwdth to each adaptve connecton s dvded by 2. The dstnctve local mnmum of the QTBR dstrbuton s caused by the shft from provdng the ntermedary bandwdth to the mnmum bandwdth for all connectons. Fgures 8 and 9 compare the blockng probablty for each connecton class n case of vehcular envronment for UGS, the adaptve traffc classes (rtps, ertps, and nrtps), and the BE traffc. The connecton-blockng probabltes 2120 Wrel. Commun. Mob. Comput. 2015; 15: John Wley & Sons, Ltd.

11 N. Nasser et al. Bandwdth allocaton broadband wreless networks Fgure 7. Connecton blockng probablty at dfferent connecton arrval rates n vehcular envronment. Fgure 9. Adaptve class connecton blockng probablty at dfferent connecton arrval rates n vehcular envronment. Fgure 8. UGS connecton blockng probablty at dfferent connecton arrval rates n vehcular envronment. are qute dfferent for the UOQoS versus QTBR algorthms, just lke the case of pedestran envronment, where a balance between the demands of UGS versus non-ugs classes s desred. The local mnmum found at 56 cpm n case of QTBR s caused by the transton from ntermedary to mnmum bandwdth rates to actve connectons. At around 70 cpm, QTBR exhbts a smlar local maxmum for ertps and nrtps to that exhbted n the pedestran case. Also smlarly, ths behavor s a result of the threshold AC scheme utlzed by QTBR. It can also be observed that bandwdth utlzaton surpassed the rejecton threshold rates for both ertps and nrtps. Recall that QTBR reduces BA when UGS blockng probablty s hgh and when the aggregate handover droppng probablty s hgh. And although handovers n the vehcular envronment exhbt a hgher regularty than those of the pedestran envronment, QTBRs result n a low aggregate droppng probablty. At around 80 cpm, where the UGS blockng probablty s shown to ncrease, the QTBR begns to reduce BAs for actve connectons, resultng n a reduced blockng probablty for both adaptve and BE traffc. In experments explorng the effect of arrval rate on the UGS and rtps handover droppng probabltes, the droppng rate for UGS s unformly hgher for UOQoS than QTBR, n a smlar manner as n the case of connecton blockng probabltes. The droppng rate for rtps and the other adaptve classes s also hgher for UOQoS than QTBR; however, the dfference between the algorthms s much smaller. The bandwdth reservaton method found n UOQoS s better suted to handle the lower bandwdth requrements of the adaptve classes than those of the UGS class. Fnally, when comparng the blockng and droppng probabltes of UOQoS for the vehcular envronment scenaro and comparng the rates for rtps connectons, t was shown that UOQoS elevates treatment of ncomng handovers. Below 70 cpm, handovers and new ncomng connectons both receve equal and deal coverage. In the regon between 70 and 100 cpm, when meetng all actve connectons mnmum needs s dffcult to acheve, the handover blockng rate s lower than the ncomng connecton s droppng rate. These results clearly show that UOQoS prortzes handover connectons over new ncomng connectons Dscusson. The smulaton results show that UOQoS outperforms the QTBR algorthm n several areas. WMAX networks support both statonary and moble users. Therefore, two envronments, namely pedestran and vehcular envronments, were chosen n order to test both solutons under dfferent possble crcumstances. The pedestran network envronment tests how each method performs under low handover load, where the majorty of users are connectng usng a varety of servces. In ths scenaro, UOQoS acheved hgher overall bandwdth utlzaton and lower overall blockng probabltes. Ths s caused by the fact that n UOQoS method, the bandwdth s dynamcally reduced to actve connectons, whch results n more accepted ncomng connectons, and thus lowerng the connecton blockng probabltes. The vehcular envronment Wrel. Commun. Mob. Comput. 2015; 15: John Wley & Sons, Ltd. 2121

12 Bandwdth allocaton broadband wreless networks N. Nasser et al. was used to test the algorthms response to a hgher handover load envronment. QTBR responds to ths stuaton by reservng bandwdth for UGS and handover connectons, whle sacrfcng new or handover connectons from other classes. UOQoS on the other hand responds by tryng to mnmze overall droppng and blockng rates by admttng as many connectons as possble. UOQoS proves to provde better bandwdth utlzaton than QTBR. The results also show that UOQoS mantans a mnmum level of user requrements at all tmes, ncludng those of adaptve classes as well as UGS traffc. UOQoS balances the requests made by all servce classes ncludng the BE servces. The results ndcate that the combned AC and BA of UOQoS mnmze new connecton blockng and handover droppng rates. New connecton blockng probabltes are mnmzed by dynamcally reducng allocated bandwdth to actve connectons, thus freeng resources for future connectons. Handover droppng rates take advantage of resources freed by dynamc allocaton, as well as bandwdth reservaton used to ensure resource avalablty. UOQoS successfully prortzes handover connectons over new connectons, whch meets the requrement that actve handovers are gven prorty over new connecton attempts. It s also shown that UOQoS maxmzes bandwdth utlzaton whenever possble, showng superor performance to QTBR. Maxmum utlzaton s necessary to allocate as much resources as possble to actve and ncomng connectons. 5. CONCLUSIONS We proposed an RRM framework for moble WMAX networks that s low on complexty, explots the adaptve nature of the projected WMAX traffc, and enhances the overall moble experence. The proposed framework, called UOQoS, comprses an adaptve BA module and an AC module wth HM. It s AC module that takes advantage of the adaptve nature of traffc for VoIP, vdeo and voce streamng, Web browsng, and other RT applcatons. The adaptve BA module s bult on a utlty optmzaton tree that s used to balance the bandwdth requests of many users. Ths method ndcates how to reduce bandwdth supply based on the applcatons adaptve characterstcs and always mantans a maxmum bandwdth utlzaton. The proposed AC module s ntegrated wth the adaptve BA module and provdes the support for HM requred n moble WMAX networks. The framework forms a complete soluton to the resource management problem of WMAX networks, by meetng the overall goal of mnmzng connecton blockng and handover droppng by constantly adaptng the BA to each connecton. The performance of the UOQoS was verfed through smulaton. Results ndcate that the proposed framework ncreases the utlzaton of network resources and results n lower aggregate connecton blockng probabltes than QTBR a representatve framework chosen from the lterature for comparson. Furthermore, UOQoS was found capable of mantanng the handover droppng probablty lower than the new connecton blockng probablty. UOQoS also mantans actve BA such that the mnmum QoS requrements are always met. As an RRM framework, UOQoS performs well by lmtng congeston and enablng users of dfferent servce classes to access network classes wthout unjustfable bas. Areas of future work nclude ncorporatng operatonal enhancement mechansms such as handover predcton and nvolvng economc consderatons nto the RRM decson framework. Whle defnte gans can be argued for employng these methods, facltatng meanngful practcal mplementaton remans to be explored. REFERENCES 1. 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14 Bandwdth allocaton broadband wreless networks N. Nasser et al. the founder and Drector of the Wreless Networkng and Moble Computng Research Lab at Guelph (WNG: He has authored 129 journal publcatons and refereed conference publcatons and book chapters n the area of wreless communcaton networks and systems. He has also gven tutorals n major nternatonal conferences. Dr Nasser s currently servng as an assocate edtor of Wley s Internatonal Journal of Wreless Communcatons and Moble Computng, Wley s Internatonal Journal on Communcaton Systems, Wley s Securty and Communcaton Networks Journal and Internatonal Journal of Ad Hoc & Sensor Wreless Networks. He has been a member of the techncal programme and organzng commttees of several nternatonal IEEE conferences and workshops. Dr Nasser s a member of several IEEE techncal commttees. He receved the Fund for Scholarly and Professonal Development Award n 2004 from Queen s Unversty. He receved the Computng Faculty Apprecaton Award from the Unversty of Guelph- Humber. He receved the Best Research Paper Award at the ACS/IEEE Internatonal Conference on Computer Systems and Applcatons (AICCSA 08), at the Internatonal Wreless Communcatons and Moble Computng Conference (IWCMC 09), at the Internatonal Wreless Communcatons and Moble Computng Conference (IWCMC 11), and at the Internatonal Conference on Computng, Management and Telecommuncatons (ComManTel 13). Red Mller studed Computng Informaton Scence and Theoretcal Physcs at The Unversty of Guelph. Hs personal research s currently focused on dgtal audo sgnal processng. He s now employed by Envronment Canada and prmarly works towards developng dssemnaton technques for clmatologcal and meteorologcal data. Amr Esmalpour s an Assstant Professor n the Department of Electrcal and Computer Engneerng (ECE) and Computer Scence at the Unversty of New Haven n Connectcut, USA, where he s teachng advanced courses n networkng and wreless communcaton and networks. Hs area of research s n Qualty of Servce provsonng and Rado Resource Management (RRM) for the 4G wreless technologes. Pror to that, he was a postdoctoral fellow at the Department of ECE at the Unversty of Toronto, n Toronto, Canada, where he was performng research on the fourth generaton of wreless networks. Dr Esmalpour receved hs PhD from the Unversty of Guelph, n Guelph, Canada, and he has been teachng wreless network courses at dfferent colleges and unverstes n Canada and the USA. Abd-Elhamd M. Taha s currently an Assstant Professor at Alfasal Unversty n Ryadh, Saud Araba. Hs BSc (Honours) and MSc n Electrcal Engneerng were earned at Kuwat Unversty n 1999 and 2002, hs PhD n Electrcal and Computer Engneerng was earned from Queen s Unversty, Canada, n Dr Taha s general research nterest s n the area of computer networks and communcatons. Hs partcular focus, however, has been on rado resource management n wreless networks. Recent themes n ths drecton nclude the desgn of resource schedulers wth reduced complexty and enablng machne-to-machne communcatons. Other currently actve areas of nterest nclude smplfed localzaton n massve wreless sensng networks, moble securty n the Internet of Thngs, and modellng n networked cyber-physcal systems. He has wrtten and lectured extensvely on broadband wreless networks, focusng on rado resource management technques. He s also the co-author of the book LTE, LTE-Advanced and WMAX: Toward IMT-Advanced Networks by Wley & Sons and a presenter for several tutorals at key IEEE Communcatons Socety events. Hs servce record ncludes organzng and servng on the edtoral and techncal programme commttees of many esteemed publcaton events and venues, as well as advsng and revewng actvtes for fundng agences, techncal book publshers and research journals and conferences. Dr Taha s currently a Senor Member of the IEEE and the IEEE. Tarek Bejaou receved hs Industral Engneerng Dploma from the Natonal Engneerng School of Monastr (ENIM) n 1992 and worked as Engneer and Char n several companes untl the begnnng of Dr Bejaou receved hs PhD degree n Informaton and Communcaton Technologes from the Unversty of Pars-Sud, Orsay, France, n 2005, and has conducted researches at the Unversty of Pars-Sud and the Unversty of Pars Dauphne between 2005 and Dr Bejaou s currently an Assocate Professor at the Faculty of Scences of Bzerta, Unversty of Carthage, Tunsa and was the Charman of the Computer Engneerng Department of the Hgher Insttute of Appled Scences and Technologes of Mateur, between 2008 and Dr Bejaou has authored some book chapters and several publcatons n reputable journals, conferences and workshops n the areas of wreless and moble system and networks. In 2008, he receved the Best Paper Award at the IEEE/ACS AICCSA conference. He has been a member of the techncal programme and organzng commttees of several nternatonal IEEE conferences and workshops. Dr Tarek Bejaou s the founder and the Char of the Tunsan Wreless Communcatons Socety Wrel. Commun. Mob. Comput. 2015; 15: John Wley & Sons, Ltd.