On Designing Thermal-Aware Localized QoS Routing Protocol for in-vivo Sensor Nodes in Wireless Body Area Networks

Transcription

1 Sensors 2015, 15, ; do: /s OPEN ACCESS sensors ISSN Artcle On Desgnng Thermal-Aware Localzed QoS Routng Protocol for n-vvo Sensor Nodes n Wreless Body Area Networks Muhammad Mostafa Monowar * and Fuad Bajaber Department of Informaton Technology, Faculty of Computng and Informaton Technology, Kng AbdulAzz Unversty, Jeddah-21589, Saud Araba; E-Mal: fbajaber@kau.edu.sa * Author to whom correspondence should be addressed; E-Mal: hemal.cu@gmal.com; Tel.: Academc Edtor: Leonhard M. Rendl Receved: 21 Aprl 2015 / Accepted: 5 June 2015 / Publshed: 15 June 2015 Abstract: In ths paper, we address the thermal rse and Qualty-of-Servce (QoS) provsonng ssue for an ntra-body Wreless Body Area Network (WBAN) havng n-vvo sensor nodes. We propose a thermal-aware QoS routng protocol, called TLQoS, that facltates the system n achevng desred QoS n terms of delay and relablty for dverse traffc types, as well as avods the formaton of hghly heated nodes known as hotspot(s), and keeps the temperature rse along the network to an acceptable level. TLQoS explots modular archtecture wheren dfferent modules perform ntegrated operatons n provdng multple QoS servce wth lower temperature rse. To address the challenges of hghly dynamc wreless envronment nsde the human body. TLQoS mplements potental-based localzed routng that requres only local neghborhood nformaton. TLQoS avods routng loop formaton as well as reduces the number of hop traversal explotng hybrd potental, and tunng a confgurable parameter. We perform extensve smulatons of TLQoS, and the results show that TLQoS has sgnfcant performance mprovements over state-of-the-art approaches. Keywords: localzed routng; wreless body area networks; thermal-aware; n-vvo sensors 1. Introducton Thanks to Moore s law, the contnuous decrease n sze whle growng capacty ncrease of electronc devces has made t nevtable for the development of tny and portable devces that can communcate

2 Sensors 2015, wth each other around the human body. Ths substantal development creates growng nterest amongst researchers, system desgners and applcaton developers on a new type of network archtecture generally known as a Wreless Body Area Network (WBAN). A WBAN s thus a specal type of network that ntegrates mnaturzed, ntellgent, low-power sensor nodes n, on or around a human body that contnuously montor the body functons and surroundng envronment [1]. WBAN s equpped wth nodes that are wearable and/or mplanted, and capable of wreless communcaton to transmt data to a nearby coordnator known as the Body Coordnator (BC). An mplanted sensor node, also known as an n-vvo node s a specal type of sensor whch detects and collects the desred bometrc data of a certan physologcal change nsde the body, and transmts the data to the BC. One of the major problems caused by contnuous sensng of n-vvo sensor node s the heat produced due to wreless communcaton and the power dsspaton by the sensor crcutry [2,3]. The ncreased heat causes thermal damage to the human tssue nsde the body f the communcaton s prolonged for a long tme whch mght be a threat to the human lfe [4]. Hence, temperature rse n one the sgnfcant ssues to be consdered n desgnng communcaton protocols for WBAN havng n-vvo nodes. Because of the hgh potental n e-healthcare, WBAN has been facltated nowadays wth wder range of applcatons [5] havng dstnct Qualty of Servce (QoS) demands n terms of delay, relablty, throughput etc. Moreover, a patent can be equpped wth dverse n-vvo sensors wth varous QoS requrements. For nstance, electroencephalogram (EEG), electrocardogram (ECG) and Electromyography (EMG) etc. requre hgher relablty wth real tme delvery. However, the traffc from respraton montorng, ph-level montorng sensors demand hgher relablty but can tolerate delay to some extent. Thus, addressng traffc heterogenety satsfyng respectve QoS requrements s another consderable challengng ssue for the desgn of WBAN communcaton protocols. Although a number of mplementatons generally use a sngle-hop communcaton archtecture for a WBAN to connect all sensors to a central snk node, recent researchers [6 10] ponted out that the multhop communcaton paradgm s more energy-effcent and even necessary when appled nsde the human body wth nnate severe propagaton loss. Consderng the temperature rse as a strkng metrc, a number of studes presented thermal-aware communcaton protocols explotng the mult-hop communcaton paradgm for WBAN havng n-vvo nodes. These protocols manly am to mnmze the temperature rse n route selecton procedure and gnore the QoS ssues. There are also few researches found n the lterature consderng QoS provsonng n WBAN but these studes neglect the thermal effect [11 13]. Consderng the thermal-awareness as well as QoS provsonng wth the support of traffc heterogenety of mplanted WBAN, recently TMQoS [14] has been proposed. TMQoS employs a cross-layer proactve routng framework that mantans an ongong routng table contanng end-to-end routes for all traffc types. Thus, ths protocol requres not only local knowledge, but also the knowledge of end-to-end network nformaton for the route selecton towards the BC. Although TMQoS selects the best end-to-end route satsfyng certan QoS parameters, but t has some drawbacks n the context of WBAN. Frst, ths overhead to too hgh to scale the network to a good number of nodes. Secondly, the wreless envronment nsde the human body s hghly dynamc due to ts varablty n path loss [15]. The stuaton becomes more sgnfcant n the presence of mplant sensors wth dfferent QoS demands

3 Sensors 2015, and data rates. Ths hghly dynamc nature prolongs the network convergence tme that could cause stale network nformaton to the source nodes whle selectng the route. Besdes these drawbacks, TMQoS only consders the avalable shortest path routes for traffc dssemnaton. However, the shortest-path mght not always be the best end-to-end path consderng the desred QoS metrcs and temperature rse. In ths paper, we present TLQoS, a Thermal-aware Localzed QoS routng protocol for n-vvo sensor nodes n WBAN, whch explots a localzed approach n route selecton wth the am of satsfyng the requred QoS demands of dverse n-vvo nodes as well as preventng the formaton of hghly heated nodes, known as hotspot(s) along the network. TLQoS employs potental-based greedy routng approach that reflects ts localzed behavor requrng only local neghborhood nformaton. TLQoS defnes a number of routng potentals based on the QoS metrcs and node temperature. To avod the formaton of routng loops whch mght be common n typcal greedy approaches, and to route the packet towards the snk reducng unnecessary hop traversal, hybrd potentals are ntroduced, and a routng loop avodance mechansm s presented n TLQoS. TLQoS explots a completely modular approach to address the traffc accordng to ther respectve QoS demands. TLQoS effectvely measures the parameters for route selecton explotng a cross-layer framework. Furthermore, the performance of TLQoS s evaluated compared to the state-of-the-art protocols usng smulatons. The rest of the paper s organzed as follows: Secton 2 summarzes the related works. Secton 3 presents the system model and states the prelmnares behnd the protocol. Secton 4 descrbes the proposed protocol. Secton 5 demonstrates the protocol performance usng smulaton. Fnally, Secton 6 presents the concludng remarks. 2. Related Works In recent tmes, consderng thermal-effect on human body as one of the strkng crtera, a seres of communcaton protocols have been developed [4,16 18]. The proposed protocols consder node temperature as a prmary metrc for routng decsons. The man objectve of the protocols s to mantan the temperature below some threshold and lower the temperature rse rate to avod sgnfcant damage on human body tssue. TARA [4] s one of the prmtve protocols n ths seres. TARA forwards data packets based on localzed temperature nformaton and hop-count to the destnaton. It measures temperature consderng heat generaton due to radaton from antenna as well as power dsspaton due to sensor crcutry. TARA mantans a neghbor table by exchangng neghborhood nformaton, and forwarder node s selected based on the mnmal temperature crtera. TARA estmates the temperature rse of ts neghbors by lstenng to the neghbor actvtes and countng the number of packet transmsson and recepton. A hotspot s dentfed f the estmated temperature exceeds a certan threshold. TARA avods the hotspot(s) by establshng an alternatve route toward the destnaton usng a wthdrawal strategy where a packet s sent back to ts prevous sender f all the neghbors are dentfed as hotspots. The sender then attempts to select alternate route to detour the hotspot(s). After coolng the temperature beneath some threshold, those hotspots can be consdered for later routng. Due to the wthdrawal strategy, TARA suffers from hgh end-to-end delay, lower relablty, as well as hgh energy consumpton snce the packet needs to traverse many hops when t encounters a hotspot and wll be detoured arbtrarly.

4 Sensors 2015, In order to address the problems of TARA, Bag and Bassoun [16] proposed LTR. LTR also explots greedy localzed routng approach, where coolest neghbor s always chosen for data forwardng. To prevent a packet traversng unnecessarly wth a large number of hops, a threshold parameter MAX_HOP S s defned, and f the hop-count of a packet exceeds the MAX_HOP S, then the packet s dscarded. To avod the routng loop, each packet mantans a small lst of nodes whch t has most recently vsted and f the coolest neghbor s already n the lst t s gnored to be as a forwarder and the second coolest neghbor s chosen. Because of the greedy approach, a packet n LTR s not always drected to the destnaton whch sgnfcantly ncreases the hop count, thus resultng hgher delay and lower relablty. In the same study, the authors presents ALTR, a varant of LTR, wth an ntent to mnmze the packet delvery delay. In ALTR, a packet s forwarded smlar to LTR untl the hop-count of the packet reaches a threshold, MAX_HOP S_ADAP T IV E. However, a shortest path routng algorthm s used f the hop-count value exceeds the threshold. Although, compared to LTR, ALTR optmzes the end-to-end delay to some extent, but t wastes network bandwdth through unnecessary transmssons untl the hop count reaches the threshold value. ALTR also allows a packet to traverse through hotspot(s) whle utlzng the shortest hop routng. HPR [18], as proposed by the same researchers of LTR and ALTR, follows an opposte mechansm as explaned n ALTR. In HPR, a node usually forwards the packets usng shortest hop routng. However, t chooses the coolest neghbor f t encounters a hotspot n the shortest hop-count path. Because of followng the same routng strategy upon hop-count detecton, HPR also behaves the same as LTR n terms of energy consumpton, packet delvery delay and relablty. LTRT [17] has been proposed to address the problems of LTR and ALTR. LTRT requres the knowledge of global network topology where a least temperature route s chosen from all possble routes from a sender node to a destnaton explotng the Djkstra s algorthm. LTRT, however, ncurs much protocol overhead due to ts dependency on end-to-end nformaton. Furthermore, t only chooses the least temperature route whch may not be the least delay path or relable path. QoS-aware routng protocols n the context of WBAN have not ganed much attenton so far. A QoS-aware routng framework for bomedcal sensor network has been proposed by Lang et al. [11] that provdes prortzed routng servce and user specfc QoS support explotng cross-layer functonaltes. Ths work consders user specfc QoS requrements, wreless channel status, packet prorty level, and sensor node s wllngness to be a router n route selecton. ZEQoS [12] presents an ntegrated energy and QoS-aware routng protocol followng modular approach. It provdes servce dfferentaton through classfyng traffc nto three categores, and determnes an end-to-end route that ensures the satsfyng of QoS parameters based on respectve traffc type. Explotng the geographc locaton, DMQoS [13] has been proposed for bomedcal wreless sensor networks. Ths protocol also provdes dfferentated servce for four classes of traffc, and focuses on ntegratng energy-effcency wth QoS provsonng. All the exstng QoS-aware protocols are manly desgned for nter-ban communcaton, and gnore the thermal effects that could cause n the context of ntra-ban routng. Lately, Monowar et al. [14] proposed a thermal-aware mult-constraned ntra-body QoS-routng for WBAN that ntegrates the QoS provsonng ssue wth thermal-awareness n route selecton for n-vvo sensor nodes. However, TMQoS s not well-suted for hghly dynamc envronment due to ts dependency on global network nformaton as we dscussed n the prevous secton.

5 Sensors 2015, The lack of an effcent routng protocol ntegratng thermal-awareness wth QoS provsonng for dverse traffc types thus motvates us to develop a localzed routng soluton for WBAN wth n-vvo nodes that n one hand wll address the hghly dynamc nature of ntra-ban envronment, and n other hand, wll provde QoS-provsonng for heterogeneous traffc, mnmzng the temperature rse along the network, also avodng hotspot(s). 3. System Model and Prelmnares 3.1. System Model We consder a deployment scenaro, n whch dverse types of n-vvo nodes are placed n a human body formng a WBAN. A Body Coordnator(BC) s attached to the body surface, that serves as a central data snk for the WBAN as shown n Fgure 1a. In-vvo nodes n a WBAN are usually energy constraned and responsble for sensng and transmsson functons, whle the BC could be equpped wth external power supply havng some advanced functonaltes (.e., data aggregaton, exchangng control and management packets etc.). The BC aggregates the data receved data from the nodes, processes t, and then sends t to a Base Staton (BS) or server through other networks (.e., cellular, WLAN or wred) as depcted n Fgure 1a, and ths communcaton paradgm s out of the scope of ths paper. EEG Blood Pressure ECG CO2 Moton ECG ECG Moton WBAN ph 1 9 Communcaton Lnk BC 0 SPO2 Temp WBAN node BS EMG Coordnator Moton (b) (a) Fgure 1. Network Model. (a) A Body Coordnator(BC); (b) Communcaton network topology. The above deployment scenaro can be modeled as a connectvty graph, G = (N, E), where N s the set of vertces representng the nodes n the network ncludng BC, and E s the set of edges that

6 Sensors 2015, represents the communcaton network topology as llustrated n Fgure 1b. An edge, (n, n j ) E, ff n, n j are wthn the communcaton range of each other. We assume every node n uses fxed transmsson power for the communcaton wth neghborng nodes. We defne the neghbor set of n, denoted as NB(n ), are the nodes wth whch n has drect edges. We consder all the communcaton lnks are symmetrc, that s, f n NB(n j ), then n j NB(n ). To save energy and attan hgher network connectvty, n-vvo nodes are assumed to have lmted transmsson range, thus data wll be delvered to the BC through multple hops. We assume that all the n-vvo nodes have forwardng capabltes (.e., forward other node s data) along wth ther sensng and transmsson functons. In ths paper, we focus on desgnng a new localzed and thermal-aware QoS routng protocol for a WBAN havng n-vvo nodes. The term localzed routng can be formally defned as Defnton 1. A routng protocol A s sad to be a localzed protocol, f gven the nformaton of a current node n and ts neghbor set NB(n ), the current node n can decde whch neghborng node n j, n j NB(n ) s sutable to forward the data. To know the nformaton of the neghborng nodes every node runs a HELLO protocol. For a localzed routng to be effectve, we assume that nodes are ether statonary or havng very low moblty, otherwse, nodes need to exchange HELLO packets more frequently whch could be resource consumng. Ths assumpton also agrees wth the WBAN archtecture wth n-vvo nodes, snce nodes are mplanted nsde the bologcal tssue of the human body. We also assume that n the network, node densty s suffcent enough to prevent any vod stuaton, where the vod stuaton s termed as the stuaton between two neghborng nodes when there s no node n the network closer to one of them than the other Traffc Classfcaton One of the objectves of TLQoS s the QoS provsonng for dverse traffc types havng dfferent QoS requrements. Consderng delay and relablty as the QoS metrc, we classfy the traffc as follows: Crtcal(Cr) traffc: Ths type of traffc has both the delay and relablty constrants. Examples nclude electroencephalogram (EEG), electrocardogram (ECG) and Electromyography (EMG) etc. that generate real tme contnuous data whch need to be delvered wth a lower delay and hgher relablty. Delay constraned (Dc) traffc: Ths type of traffc needs to be delvered wth lower delay, however, t can tolerate some packet losses. Tele-medcne vdeo streamng applcaton traffc possesses such requrement. Relablty constraned (Rc) traffc: The traffc belong to ths type requres hgher relablty, wthout havng any delay constrants. Example of ths type ncludes respraton montorng, ph-level montorng etc. whch can be processed offlne, but packet losses for ths type may cause severe consequences. Regular (Rg) traffc: Traffc of ths type has no delay or relablty constrants. Traffc generated from a patent s regular vtal sgn montorng applcatons such as temperature, pressure etc. corresponds to ths class of traffc.

7 Sensors 2015, Desgn of TLQoS 4.1. Overvew of TLQoS TLQoS s a thermal-aware localzed routng protocol amng to provson QoS for dverse traffc types based on ther requrements. To meet the objectve, the protocol s desgned followng a modular approach. Fgure 2 llustrates the basc archtecture of TLQoS. TLQoS explots the cross layer nteractons between layer-2 and layer-3. From Upper Layers Data Packet Layer 3 QoS-aware Packet Classfer Rg Rc Cr,Dc Delay Module Cr Relablty Module Temperature Module Data Packet Neghbor Manager Queung Manager Hello Packet Hello Packet [Rc, Rg] RQ [Cr, Dc] DCQ Hgher Prorty MAC Recever Delay Estmator Relablty Estmator Temperature Estmator MAC Transmtter Data or Hello Packets Layer 2 Data or Hello Packets From other WBAN Nodes To other WBAN Nodes Fgure 2. Protocol Archtecture. Consderng delay and relablty as the prmary QoS constrants, a module s devoted to each of these constrants as depcted n Fgure 2. The temperature module deals wth the regular packet, (no delay and relablty constrants) and ensures that the packet reaches to the BC wth a lower temperature route. The QoS-aware packet classfer classfes the packet accordng to ther QoS demands and passes t to the respectve module for further processng. The neghbor manager module runs the HELLO protocol that enables exchangng nformaton among neghborng nodes, and mantans a neghbor table. Ths module nteracts wth delay estmator, relablty estmator and temperature estmator modules n layer-2 for acqurng the respectve parameter values of a node. Upon explotng the parameter values,

8 Sensors 2015, the neghbor manager bulds the HELLO packet. It also passes the neghbor table nformaton to the delay module, relablty module and temperature module respectvely to locally select the most approprate neghborng node among the avalable canddates. The queung manager module mantans two queues namely, Delay Constraned Queue (DCQ) and Regular Queue (RQ), and mplements prorty mult-queung strategy that provdes dfferentated prorty for dverse traffc types. To mplement the localzed routng, TLoQoS adopts the potental based routng polcy. The potental based routng s frst proposed by Basu et al. [19] n the context of tradtonal network. However, ths work defnes an exclusve vrtual potental feld for each arbtrarly dstrbuted destnaton that ncurs huge overhead. Later on, Ren et al. proposed TADR [20] that explots the potental feld for localzed routng decson n the context of Wreless Sensor Network (WSN) wth a sngle snk. TADR manly focuses on ntegratng congeston avodance mechansm wth routng functonaltes. Ths work motvates us to adopt the potental based routng polcy for QoS provsonng along wth thermal-awareness n the context of WBAN havng n-vvo nodes. In ths polcy, a node measures potentals for dfferent parameters, and the trajectory of the packet s determned by the force from the potental felds. TLQoS defnes four routng potental felds namely hop count potental, delay potental, relablty potental and temperature potental. The delay module, relablty module and temperature module respectvely compute the related potental and forces for all the neghbors and choose the most sutable canddate that has the maxmum force. Whle selectng the canddate node from the neghbors, all the modules avod the hotspot node even f t has the maxmum force. The process s repeated hop-by-hop untl the packet reaches to the BC satsfyng the requrements of desred QoS. Snce, TLQoS employs greedy approach for choosng the next-hop node, and the QoS parameters as well as temperature parameter are tme-varant, hence, routng loops mght occur. However, ntegratng the QoS potental felds wth tme-nvarant hop-count feld, and controllng a confgurable parameter can prevent the routng loops, and reduce the large number of hop traversal along the network. In the subsequent sectons, we present how the potental felds and the relatve forces are constructed, and then how the dfferent modules compute the ntegrated potental and forces to decde a sutable loop-free route satsfyng the respectve QoS, also avodng the hotspot Neghbor Manager The neghbor manager module n TLQoS performs the followng functons: () Executes the HELLO protocol; () Bulds and manages neghbor table; () Interacts wth the delay, relablty, and temperature estmator module to acqure the respectve parameter values for the node; (v) Provdes the delay, relablty and temperature module wth neghbor table nformaton. Perodcally, or upon observng sgnfcant changes n the parameter values, a node broadcasts a HELLO packet to ts neghbors. The HELLO packet ncludes node ID, hop-count to the BC, average node delay, average packet loss rato, and average temperature of a node. Ths module mantans a neghbor table that assgns an entry for each neghborng node. The neghbor table structure s shown Fgure 3. The table s updated upon each recepton of the HELLO packet from a neghbor. The update ncludes addton of new entres when a new node enters nto the node s neghborhood, deleton of a

9 Sensors 2015, node entry f the update s not receved for a partcular tme perod, and updatng nformaton of the exstng entres. Neghbor ID HC Avg. Delay Avg. Packet Loss Rato Avg. Temperature Fgure 3. Neghbor Table Structure. The frequency of HELLO packet exchange s also an mportant crtera to be consdered. Snce, most of the parameters (.e., delay, packet loss rato, temperature) are hghly dynamc, hgher frequency of HELLO packet exchange would provde up-to-date nformaton but would be resource consumng. However, lower frequency could result n stale nformaton, also cause network connectvty loss. The HELLO packet nterval selecton mechansm s dscussed later n ths secton Routng Potentals TLQoS defnes potental felds on the network over whch dverse types of packets are routed to the BC. Let us consder a node, n wth potental, P generates a packet. To reach the BC, the packet needs to be forwarded to a neghbor n j, n j NB(n ). To choose a sutable canddate from NB(n ), we defne a force actng on the packet at n, as F (n, n j ) = P (n ) P (n j ) c n,n j (1) Here, c n,n j denotes the lnk cost from n to n j. Hence, the force s the potental dfference between a node n and each one of ts neghbors. The packet s now drected to a neghbor n j NB(n ) for whch the F (n, n j ) s maxmum. In partcular, a packet follows the drecton of the steepest gradent to reach to the destnaton. To provde dfferentated servces, we assgn four potental felds to a node n. We defne a set of potental felds to a node n as P(n ) = [P h n, P d n, P r n, P t n ]. Here, P h n, P d n, P r n, P t n denote the hop-count potental, delay potental, relablty potental and temperature potental respectvely Hop-Count Potental Feld The hop-count potental feld allows a packet to traverse to the BC followng a shortest path. Ths feld determnes the node-depth from the BC. Let p be the packet at a node n, and HC(n ) denotes the shortest path length n terms of hop-count from n to the BC. Hence, the hop-count potental s defned as P h n = HC(n ) (2) Thus, the hop-count force that acts upon a neghbor n j NB(n ) from the node n s gven by F h (n, n j ) = P h n P h n j c n,n j (3)

10 Sensors 2015, Here, c n,n j denotes the lnk cost from node n to n j. Smlar to [20], we consder the dstance between two nodes as the lnk cost metrc. The dstance can be measured by several technques such as measurng sgnal attenuaton or receved sgnal strength (RSSI) [21]. Pn h s tme-nvarant, and F h (n, n j ) allows a packet to traverse toward the BC wth the least number of hops. Snce, NB(n ) ncludes the nodes whch are one-hop way from n, so the hop-count dfference wll be 0, 1 or 1. Thus, the hop-count force F h (n, n j ) wll have ether of the followng values: 0, 1 1 c n,,n j c n.,n j Delay Potental Feld We defne the delay potental of a node n as P d n = D(n ) (4) Here, the functon D(n ) refers to the normalzed node delay at n and defned by Here, D avg n D(n ) = Davg n Dp req denotes the average node delay at n, and D req p (5) s the end-to-end delay requrement of a packet, n other words, the packet deadlne. Thus, delay s normalzed to the packet delay requrement. Then, we defne the delay force, F d (n, n j ) from node n to n j NB(n ) as F d (n, n j ) = P d n P d n j c n,n j (6) F d (n, n j ) allows a packet to traverse through the nodes wth mnmum latency on ts path to the BC. The delay potental feld, however, s tme varant whch changes dynamcally, and thus s not loop free. However, t can be avoded by ntegratng the feld wth tme-nvarant hop-count potental feld whch wll be descrbed later n ths secton Relablty Potental Feld The relablty potental feld, P r n on a node n s defned as P r n = R(n ) (7) Here, R(n ) denotes the average packet loss rato at node n. Hence, the lower the rato, the hgher the relablty of the node. The relablty force, F r (n, n j ) actng on node n to n j NB(n ) s gven by F r (n, n j ) = P r n P r n j c n,n j (8) Thus, drven by ths potental, a packet moves along the nodes havng least packet loss rato,.e., relable nodes on ts path to the BC. Ths potental s also tme-varant and s not loop free. However, combnng wth hop-count potental would result a loop free path as wll be dscussed later.

11 Sensors 2015, Temperature Potental Feld The temperature potental feld s defned as P t n = T (n ) (9) Here, T (n ) denotes the normalzed temperature at node n whch s defned as T (n ) = T n avg (10) T thr Here, Tn avg refers to the average temperature at node n, and T thr denotes the temperature threshold for hotspot detecton. If the value of Tn avg exceeds T thr, then T thr wll be assgned to Tn avg. Then, we defne the temperature potental force from a node n to n j NB(n ) as F t (n, n j ) = P t n P t n j c n,n j (11) Ths force drves a packet to traverse along the nodes havng least temperature on ts path to the BC. Smlar to delay and relablty potental, t s also tme-varant that mght change dynamcally, also the routng loop ssue s addressed the smlar way to delay and relablty potental feld as to be dscussed later Hybrd Potental and Routng Loop Avodance Among the four potental felds we defned, only the hop-count potental s tme-nvarant, and the remanng potentals change dynamcally. In [19], the authors proved that, a potental based routng wth tme nvarant potental s loop-free. Thus, explotng the delay, relablty and temperature potentals ndependently n routng decsons would result n routng loops. In TLQoS, we defne the hybrd potental for each of the tme-varant potental feld to address ths stuaton. Hybrd potental feld combnes a tme-nvarant potental (.e., hop-count n TLQoS) wth a tme-varant potental feld, and together mpacts on the routng decson for partcular traffc type. Dfferent combnaton patterns are possble, however, for smplcty and tractablty, we adopt lnear combnaton of the potental felds. Let Pn Hd, Pn Hr, and Pn Ht denote the hybrd potental feld for delay, relablty and temperature potental respectvely. Thus, the hybrd potentals at node n are defned as P Hd n = (1 γ)p h n + γp d n (12) P Hr n = (1 γ)p h n + γp r n (13) P Ht n = (1 γ)p h n + γp t n (14) Here, γ s an adjustable parameter where, 0 γ 1. In TLQoS, γ has sgnfcant nfluences on routng decson snce controllng ths value decdes whch part of the hybrd potental feld wll domnate.

12 Sensors 2015, Based on the hybrd potental feld, we also defne the hybrd forces from node n to n j NB(n ): The above equatons can be rewrtten as F Hd (n, n j ) = P n Hd Pn Hd j (15) c n,n j F Hr (n, n j ) = P n Hr Pn Hr j (16) c n,n j F Ht (n, n j ) = P n Ht Pn Ht j (17) c n,n j F Hd (n, n j ) = (1 γ)f h (n, n j ) + γf d (n, n j ) (18) F Hr (n, n j ) = (1 γ)f h (n, n j ) + γf r (n, n j ) (19) F Ht (n, n j ) = (1 γ)f h (n, n j ) + γf t (n, n j ) (20) In TLQoS, a packet p wth a partcular traffc type s forwarded to a neghbor for whch the relevant force s maxmum, partcularly, the neghbor n the drecton of the steepest gradent for that related force. TLQoS purposefully controls the value of γ whch changes dynamcally dependng on the number of hops a packet already traversed. Ths value sgnfcantly nfluences n routng decson. In partcular, assgnng more weghts wth tme-varant potental feld part domnates that potental n routng decson whle more weghts wth tme-nvarant hop-count potental drves a packet to traverse over a shortest path to the BC. Whle tme-varant potental domnates, routng loop mght be created as the packet can be forwarded to a neghbor that s n the same depth (.e., same hop-count) or even t can be forwarded backward to a neghbor wth hgher hop-count. Ths stuaton prevals only when the hybrd potental of all the lower-depth neghbors s greater than the hybrd potental of the node tself. In TLQoS, for any node, the related potental can ncrease by γ at maxmum. Ths s the stuaton when the Dn avg = Dp req, or the average packet loss rato, R(n ) = 1, or Tn avg = T thr. Thus, a node wll not choose a neghbor wth lower hop-count f and only f γ > 1 γ. Hence, we get, γ > 1. TLQoS 2 ntalze the value of γ wth some value greater than 1, allowng a packet to be traversed to a neghbor on 2 whch the related tme-varant potental wll be domnatng and any neghbor can be chosen rrespectve of ts hop-count value. However, to avod the routng loops or avodng a packet roamng unnecessarly around the network we mpose two condtons: Condton 1: A node wll not choose a neghbor from whch t just receved a packet. Condton 2: Whenever the hop-count value of a packet exceeds a maxmum hop-count threshold, HC max, the parameter γ s changed as γ = γ 0.1 for every hop the packet traverses untl t reaches to the BC. Condton 1 prevents a packet to be exchanged between two nodes back and forth, thus avods routng loops. Condton 2 avods a packet movng around a large number of hops, also prevents routng loops. Wth the decreasng value of γ, the tme-nvarant potental wll be domnatng that drves the packet to be closer to the BC followng the shortest path route.

13 Sensors 2015, Delay Module The delay module ams for choosng a potental forwarder for delay-constraned and crtcal traffc type. Algorthm 1 presents route selecton procedure used by delay module. Algorthm 1 Route selecton algorthm at delay module INPUT (a packet p Cr, Dc, NT) 1. f p.hc > HC max {Condton-2} then 2. γ=p.γ 3. γ = γ p.γ=γ 5. else 6. γ =p.γ 7. end f 8. for all n j n NT do 9. f Tn avg j < T thr {Hotspot Avodance} then 10. f n j / RS {Condton-1} then 11. c n,n j = dst n,n j 12. Calculate Pn d and Pn d j accordng to Equatons (4) and (5) 13. Calculate Pn Hd j accordng to Equaton (12) 14. Calculate F h (n, n j ) accordng to Equaton (3) 15. Calculate F d (n, n j ) accordng to Equaton (6) 16. Calculate F Hd (n, n j ) accordng to Equaton (18) 17. end f 18. end f 19. end for 20. Select n j wth MAX-F Hd (n, n j ), MIN-Pn Hd j, MIN-Pn h j, Random n turn 21. f p.packettype=cr then 22. Call Relablty Module wth p Cr as parameter 23. else 24. Call Queung Manager wth p Dc as parameter 25. end f The algorthm frst checks the condton-2 for the delay senstve packets. The recent value of γ s extracted from the packet header. If the hop-count value of the packet exceeds maxmum hop-count threshold, t resets the value of γ (lne-2,3). The current value of γ s also updated n the packet (lne-4). Otherwse, the γ wll not change. The delay module avods the hotspot by gnorng the neghbors for whch the average temperature exceeds some hotspot threshold, T thr (lne-9). Condton-1 s appled n lne-10 to avod the routng loop wth recent sender, RS. For the remanng neghbors other than the hotspot(s) and recent sender, the algorthm measures the requred potentals and forces (lne 11 16). Fnally, t chooses the neghbor wth maxmum hybrd delay force as ts potental forwarder. However, f more than one neghbor possesses the same maxmum force, then the potental forwarder wll be selected

14 Sensors 2015, based on mnmum hybrd delay potental, mnmum hop-count potental successvely. If the forwarder can not be determned even after ths, the algorthm chooses t randomly. After selectng the sutable forwarder node, the algorthm checks the packet type. For a crtcal packet, relablty module s called for further forwarder selecton that ensures the packet relablty. However, f the packet type s delay constraned, the queung manager module wll be called to place the packet n a proper queue for transmsson Relablty Module The relablty module chooses a forwarder locally that ensures the hgher relablty for Rc and Cr traffc type. Algorthm 2 shows the route selecton procedure at ths module. Algorthm 2 Route selecton algorthm at relablty module INPUT (a packet p Cr, Rc, NT) 1. f p.hc > HC max {Condton-2} then 2. γ=p.γ 3. γ = γ p.γ=γ 5. else 6. γ =p.γ 7. end f 8. for all n j n NT do 9. f Tn avg j < T thr {Hotspot Avodance} then 10. f n j / RS {Condton-1} then 11. c n,n j = dst n,n j 12. Calculate Pn r and Pn r j accordng to Equaton (7) 13. Calculate Pn Hr j accordng to Equaton (13) 14. Calculate F h (n, n j ) accordng to Equaton (3) 15. Calculate F r (n, n j ) accordng to Equaton (8) 16. Calculate F Hr (n, n j ) accordng to Equaton (19) 17. end f 18. end f 19. end for 20. Select n j wth MAX-F Hr (n, n j ), MIN-Pn Hr j, Random n turn 21. Call Queung Manager wth p Cr or Rc as parameter The algorthm follows a smlar procedure to the delay module n applyng Condton-1, Condton-2 and Hotspot avodance mechansm. Snce relablty s the concerned metrc here, the algorthm measures the related relablty potental and forces as shown n lne (12 16). The algorthm chooses the potental forwarder that has the maxmum hybrd relablty force, and takes nto account a neghbor wth mnmum hybrd relablty potental f more than one neghbor has the same maxmum value of F Hr (n, n j ). Unlke the delay module, we gnore the mnmum hop-count potental value as an opton,

15 Sensors 2015, as delay s not the concerned metrc n ths case. The algorthm goes for random choce f none of the mentoned condton works. After determnng an approprate forwarder node ensurng the relablty, the algorthm calls the queung manager module to place the Cr or Rc packet n the relevant queue Temperature Module Ths module focuses on route selecton for regular packet type. Snce the Rg traffc has no QoS constrants, ths module chooses a forwarder wth lower temperature among the neghbors. The route selecton procedure used n ths module s depcted n Algorthm 3. Algorthm 3 Route selecton algorthm at temperature module INPUT (a packet p Rg, NT) 1. f p.hc > HC max {Condton-2} then 2. γ=p.γ 3. γ = γ p.γ=γ 5. else 6. γ =p.γ 7. end f 8. for all n j n NT do 9. f Tn avg j < T thr {Hotspot Avodance} then 10. f n j / RS {Condton-1} then 11. c n,n j = dst n,n j 12. Calculate Pn t and Pn t j accordng to Equatons (9) and (10) 13. Calculate Pn Ht j accordng to Equaton (14) 14. Calculate F h (n, n j ) accordng to Equaton (3) 15. Calculate F t (n, n j ) accordng to Equaton (11) 16. Calculate F Ht (n, n j ) accordng to Equaton (20) 17. end f 18. end f 19. end for 20. Select n j wth MAX-F Ht (n, n j ), MIN-Pn Ht j, Random n turn 21. Call Queung Manager wth p Rg as parameter Smlar to the other module, temperature module also executes the condton-1, condton-2 and hotspot avodance mechansm followng the same procedure. The dfference les n measurng the parameter values that consders temperature related potental and forces as depcted n lne (12 16) of the algorthm. The potental forwarder s chosen havng the maxmum hybrd temperature force. If more than one neghbor has the same maxmum value of hybrd potental force, mnmum hybrd temperature potental s used to select the potental forwarder. If the potental forwarded s stll not determned, t wll be chosen randomly. At the end, queung manager wll be called wth Rg packet as a parameter.

16 Sensors 2015, Queung Manager The queung manager n TLQoS explots a mult-queue prorty polcy where hgher prorty s gven to the delay constraned traffc (Cr and Dc) than the non-delay constraned (Rc and Rg) traffc types. To acheve ths, ths module mantans two separate queues, namely DCQ and RQ for storng delay constraned packets, and non-delay constraned packets respectvely. The DCQ has the hgher prorty over RQ. It mples that the packets from RQ wll not be sent untl the DCQ becomes empty. However, t mght cause starvaton problem where the lower prorty traffc could be ndefntely blocked by hgher prorty traffc. To avod the problem we adopt the smlar mechansm as descrbed n [13], n whch a tme-out based polcy have been employed. In ths polcy, a packet wll be moved to a hgher prorty queue (rrespectve of ts type) f t wats n a lower prorty queue untl a tme-out occurs. The mult-queue prorty polcy addresses the prorty contenton between packets n the same node. However, to address the prorty contenton between neghborng nodes, the MAC protocol could be modfed whch s beyond the scope of the paper Parameter Estmaton Hop-Count Measurement The hop-count parameter s sgnfcant n TLQoS as t s the only tme-nvarant parameter consderng the low-moblty or lower frequency n topology change. The neghbor manager sets the hop-count of a node upon recevng HELLO packet from ts neghbors. Intally, all nodes except the snk wll ntalze ther hop-count value to a very large number whle the hop-count for snk wll be 0. Upon recevng HELLO packet from a neghbor, n j NB(n ); a node, n updates ts hop-count value as follows: IF (HC(n j ) + 1 HC(n )), then HC(n ) = HC(n j ) + 1 Thus, the hop-count value s determned as the mnmum hop-count to the BC.e., the shortest path length. However, f a node n detects any topologcal changes then t recalculates the hop-count as Delay Estmaton HC(n ) = mn[hc(n j )] + 1, n j NT (21) The Delay Estmator module of a node n estmates the average node delay, D avg n as follows: D avg n = D DCQ n + D tr + D proc n + D prop (22) Here, D DCQ n delay, D proc n types, D DCQ n denotes the average queung delay of DCQ at node n, D tr s the average transmsson s the processng delay at node n, and D prop s the propagaton delay. Among these four and D tr domnates the total latency. D proc n s trval and assumed to be same for all packets and D prop s the lght speed propagaton delay, hence these delays are gnored. In node delay estmaton, TLQoS consders only delay senstve packets that nclude Cr and Dc traffc, snce the delay parameter s consdered for the route selecton of delay senstve packets only as dscussed n Secton 4.5.

17 Sensors 2015, Queung delay for DCQ, Dn DCQ s usually the nterval between the tme when a delay senstve packet enters nto the queue and the tme t s ready for transmsson. The runnng average of queung delay, Dn DCQ s estmated usng the Exponentally Weghted Movng Average (EWMA) formula [22] as follows: D DCQ n = (1 β)d DCQ n + βd DCQ n (curr) (23) Here, Dn DCQ (curr) s the current observaton of queung delay at n, β s a weghtng factor whch satsfes 0 < β 1. The value of β can be emprcally chosen. We use the value β = 0.2 n our smulaton. The transmsson delay, D tr s defned as the duraton from the tme a packet begns to be served by the MAC layer to the tme when the acknowledgment of the packet s receved. The transmsson delay s also nterpreted as servce tme of the MAC layer. Let t 0 be tme when a packet arrves at the head of the queue and ready for transmsson, t ack s the tme when the acknowledgment of packet s receved, L ack s the length of acknowledgment packet and bw s the bandwdth. Hence, D tr s estmated as D tr = t ack L ack bw t 0 (24) The runnng average of transmsson delay, D tr s estmated used EWMA formula as follows D tr = (1 β)d tr + βd tr (curr) (25) Here, D tr (curr) denotes the current observaton of transmsson delay and the β s smlar to Equaton (23) Relablty Estmaton TLQoS estmates the relablty of a node n terms of ts packet loss rate. Thus, the less s the packet loss rate, the more s the relablty. The relablty estmator module measures the average packet loss rato at a node n. Let f be the sum of packet losses over a tme wndow, δt sent by node, n, and r be the number of successfully acknowledged packets over that tme wndow. Hence, the mean µ = represents the packet loss rato of node n for that tme wndow. Ths per wndow packet loss rate s then averaged wth the prevous measurements usng Wndow Mean wth EWMA (WMEWMA) formula [23] as follows: R(n ) = R(n ) α + (1 α) µ (26) Here, α s a smoothng factor whch controls the hstory of the estmator and 0 < α < 1. The value of α s also emprcally chosen and we use the value 0.4 n our smulaton Temperature Estmaton TLQoS explots the temperature estmaton procedure as descrbed n [3,4]. In partcular, the temperature rse of the tssue surroundng the WBAN nodes s measured. The major sources that are predomnant for thermal ncrease of the mplant devces nclude radaton from the node antenna and power dsspaton of the mplanted electroncs. Specfc absorpton rate (SAR) s used to determne the level of radaton beng absorbed by body tssue. The space near the antenna s known as near feld, the f r+f

18 Sensors 2015, extent of whch s λ, where λ s the rado frequency (RF) wavelength for the wreless communcaton. 2π Accordng to [10,24], the SAR n the near feld ( λ 2π SAR NF = λ ) and far feld (> ) can be estmated as follows: 2π σµω ( Idlsnθe αr ( 1 ρ σ 2 + ɛ 2 ω 2 4π R + γ )) 2 (27) 2 R SAR F F = σ ( α 2 + β 2 Idl ) 2 sn 2 θe 2αR (28) ρ σ2 + ω 2 ɛ 2 4π R 2 where, R s the dstance from the source to the observaton pont, γ s the propagaton constant, dl s the length of short conductng wre for a short dpole antenna, σ s the medum conductvty, I s the amount of current, ɛ s the relatve permttvty, µ s the permeablty, ρ s the mass densty and snθ = 1. The power dsspaton of the sensor node crcutry, can be quantfed as power dsspaton densty, P c (the power consumed by the sensor crcutry dvded by the volume of the sensor) [3]. Consderng both the sources for temperature rse, the temperature of a node at a grd pont (x,y) at tme t, denoted as T t (x, y) can be estmated as follows [3]: T t (x, y) = ( 1 tb 4 ) tk T t 1 (x, y) + t SAR ρc p ρc p 2 C p + tb T b + P c + ( tk T t 1 (x + 1, y) ρc p ρc p ρc p 2 ) + T t 1 (x, y + 1) + T t 1 (x 1, y) + T t 1 (x, y 1) The Equaton (29) explots the Fnte-Dfference Tme-Doman (FDTD) modelng technque [25] that dscretzes the dfferental form of tme and space, and the problem space s dscretzed nto small grds. In Equaton (29), t s the dscretzed tme step, s the dscretzed space step, b s the blood pressure perfuson constant, C p s the specfc heat of the tssue, T b s the fxed blood temperature, K s the thermal conductvty of the tssue. From Equaton (29), the temperature of a node at grd pont (x, y) at tme t can be determned through a functon of the temperature at (x, y) at tme t 1, and the functon of the temperature of neghborng nodes at grd ponts ((x + 1, y), (x, y + 1), (x 1, y) and (x, y 1)). Snce the sensor nodes are surgcally mplanted, hence the poston of the nodes are fxed and can be easly known. Once the propertes of the tssue, the propertes of blood flow, and the heat absorbed by the tssue wll be obtaned, the temperature at a gven tme can be measured. Reference [3] provdes the detals of ths temperature estmaton modelng. (29) HELLO Packet Interval The HELLO packet nterval should be carefully chosen to reflect the actual network status n a dynamc wreless envronment and mantan the network connectvty. In addton, the nterval should not be too short to cause unnecessary resource consumpton of the resource-constraned WBAN. Smlar to the mechansm as dscussed n [20], TLQoS explots two HELLO packet nterval, namely mnmum HELLO nterval denoted as HI mn and maxmum HELLO nterval denoted as HI max. Instead of sendng the updates for every changes n the parameter, HI mn s used for perodc updates reflectng the tme varant parameters such as delay, relablty and temperature. On the other hand, HI max

19 Sensors 2015, s chosen as hgher value that ensures the network connectvty reflectng a tme-nvarant parameter such as hop-count. We defne three threshold for HELLO packet update consderng three tme-varant parameters, namely delay update threshold, Dup; th relablty update threshold, Rup; th and temperature update threshold, Tup. th TLQoS trggers a HELLO packet f any of the followng events occur: Event-1 The recent change n delay, relablty and temperature exceeds D th up or R th up or T th up snce the last update message sent at HI mn and current value of HI mn expres Event-2 The hop-count of a node changes due to changes n topology Event-3 The current value of HI max expres snce the last HELLO packet sent at HI max Event-1 ensures that f no sgnfcant changes occur n delay, relablty or temperature snce the last HELLO packet nterval sent at HI mn, the HELLO packet wll not be transmtted. Event-2 ensures the requrement of takng mmedate acton due to the tme-nvarant parameter hop-count changes. Event-3 s used to mantan the network connectvty no matter whether any parameter changes or not. 5. Performance Evaluaton In ths secton, we evaluate the performance of TLQoS based on smulaton Smulaton Envronment We consder a network area of 10 m 10 m, n whch 50 nodes are deployed n unform random dstrbuton, and the BC s placed n the center of the network. In the smulaton, nodes send data to the BC through mult-hop communcaton. The smulaton program has been developed n C++. Table 1 descrbes the smulaton parameters. We obtan the values for tssue propertes and delectrc characterstcs from [26,27]. Intally, the temperature of all the sensors are set to 37 C. Among the 50 mplant nodes, traffc classes are dstrbuted as follows: 5 nodes are assgned Cr traffc, 10 nodes are assgned Dc traffc, Rc traffc s assgned to 15 nodes and the remanng 20 nodes are assgned to Rg traffc. Nodes are chosen randomly durng the dstrbuton. We mplement the basc functonaltes of non-beacon enabled mode of IEEE MAC protocol wth the default values [28]. As benchmark protocols, we choose TARA, ALTR and TMQoS to compare wth TLQoS. TARA and ALTR are chosen as both the protocols employ hop-by-hop approach n makng routng decson, whle TMQoS s the only protocol that provdes QoS provsonng wth end-to-end route mantenance. Each smulaton has been performed for 1000 s and we averaged the value obtaned over 10 random runs.

20 Sensors 2015, Table 1. Smulaton Parameters. Parameter Value Parameter Value EWMA factor, β 0.2 EWMA factor,α 0.4 Intal Value of γ 0.8 T thr 37.1 C ɛ at 2 MHz 826 σ at 2 MHz [ S m ] P c C p J 3600 [ kg C ] J b 2700[ m 3 s C ] t 5 s T b 37 C I 0.1 A ρ 1040 kg J K 0.498[ m 3 m s C ] 1 m HC max 2 HI mn (T LQoS) 1 s HI max (TLQoS) 10 s HELLO Interval(other protocols) 1 s Dup th 0.1 s Rup th 0.1 Tup th 0.01 C MAC Bandwdth 100 kbps Rado Range 2 m Payload Sze 256 bts Retry Lmt 5 Smulaton Tme 1000 s 5.2. Performance Metrcs We used the followng metrcs to evaluate the performance of TLQoS. Average End-to-End Latency. End-to-End latency of a packet s measured as the tme dfference between the packet generaton tme and the tme when t s receved by the BC. Delays experenced by dstnct delay-senstve data packets (Cr and Dc) are averaged over the total number of delay-senstve packets receved by the BC. On tme Packet delvery rato. It s the rato of the total number of delay-senstve packets receved by the BC wthn the deadlne to the total number of delay senstve packets generated by the WBAN nodes. Relablty. It s the rato of the total number of unque relablty-senstve packets (Cr and Rc) receved by the BC to the total number of relablty-senstve packets generated by the WBAN nodes. Average Temperature Rse. The average temperature rse of the nodes presents the average change n temperature of the nodes from that at the ntal smulaton perod. Average Energy Consumpton. Ths parameter consders the average energy consumpton of the nodes due to transmsson and recepton of packets. In our smulaton, each packet transmsson by a node consumes 0.2 unts of energy and each recepton consumes 0.1 unts of energy Smulaton Results We frst evaluate the performance of TLQoS consderng the mpacts of traffc load and bt error rates (BER). We further nvestgate the mpact of delay deadlne on QoS aware protocols such as TMQoS and TLQoS for the delay senstve packets. The results are dscussed n the followng subsectons.

21 Sensors 2015, Impact of Traffc Load Fgure 4 llustrates the performance of the protocols varyng traffc load. In ths study, we vary the traffc load by varyng data generaton rate n terms of packets generated per second. The bt error rate vares randomly rangng from 10 6 to Here, the mpact of traffc load s nvestgated on the performance metrcs for the related traffc classes. Although TARA and ALTR do not support traffc dfferentaton, however, the data related to the correspondng traffc class was collected explotng the node-id that generates traffc of a partcular type. We evaluate the average end-to-end delay only for delay senstve packets. As the traffc load ncreases, the average end-to-end delay ncreases for all the protocols as depcted n Fgure 4a. TARA exhbts the worst performance n hgh traffc load due to ts wthdrawal strategy whle a hotspot s encountered. Compared to TARA, ALTR shows better performance n ths regard, as t avods unnecessary hop traversal applyng the shortest path algorthm for packet routng after a hop-count threshold s reached. Consderng delay parameter n route selecton, both TMQoS and TLQoS acheve the sgnfcantly lower end-to-end delay compared to the non-qos aware protocols. Durng low traffc load, TLQoS and TMQoS show almost smlar performance n end-to-end delay, however, TLQoS excels the delay performance than TMQoS n hgh traffc load. The reason behnd s that, TMQoS adopts end-to-end approach n takng routng decson whch delays the propagaton of routng nformaton from BC to the source at hgh traffc load due to the ncreased contenton, n other words, the convergence tme s prolonged resultng stale nformaton durng hgh traffc load. In contrast, TLQoS employs local selecton for choosng the least delay node from ts neghbors. Despte the greedy approach, TLQoS avods the unnecessary packet transmsson along the network, and tends to follow less hop-count path to the BC due to hybrd potental feld and routng loop avodance mechansm. The mpact of traffc load on on-tme delvery rato s depcted n Fgure 4b. Ths metrc consders the effectve relablty for delay senstve packets, n partcular, t takes nto account the number of successful delvery of delay senstve packets wthn the specfed deadlne. Consderng 300 ms as a deadlne for delay senstve packets, TLQoS demonstrates the best performance regardng on-tme delvery rato among all the protocols because of ts localzed QoS provsonng approach. Due to the hgh latency at hgh traffc load, and hgher packet losses, TMQoS shows poor performance n on-tme delvery rato compared to TLQoS. TARA, because of ts poor delay performance even n moderate traffc load, the on-tme delvery rato drops sgnfcantly as the traffc load ncreases. The poor relablty performance also nfluences ths result as to be dscussed later. ALTR, however, acheves much hgher on-tme delvery rato than TARA n all traffc loads. Stll, ths performance does not exceed the performance of QoS-aware protocols lke TMQoS and TLQoS due to the lack of explotng QoS parameters as routng metrc.