Routing Time-Constrained Traffic in Wireless Sensor Networks

Transcription

1 Routng Te-Constraned Traffc n Wreless Sensor Networks Keal Akkaya and Mohaed Youns Departent of Coputer Scence and Electrcal Engneerng Unversty of Maryland, Baltore County Baltore, MD 2250 keal youns@cs.ubc.edu Abstract Several routng protocols have been proposed for wreless sensor networks n recent years. Alost all of these routng protocols consdered energy effcency as the ultate objectve snce energy s a very scarce resource for sensor nodes. However, any new challenges have been posed wth the ncreasng nterest n applcatons that deand certan end-to-end perforance guarantees. Such applcatons necesstated both energy and QoS aware routng protocols for wreless sensor networks. In ths paper, we propose an energy-aware routng algorth for sensor networks, whch can provde soft real-te guarantees for data delvery. The proposed algorth fnds a least-cost and delay-constraned path for each real-te data source n ters of a lnk cost that captures nodes energy reserve, transsson energy and error rate. The delay guarantees are acheved through the use of Weghted Far Queung (WFQ) packet schedulng dscplne along wth leaky bucket constraned data sources. Such eployent of WFQ at each node provdes a servce dfferentaton between two dfferent classes of traffc, naely real-te and non-real-te traffc and dvdes the outgong lnk capacty aong such classes accordngly. Sulaton results have deonstrated the effectveness of our approach for popular perforance etrcs.. Introducton Recent advances n cro-electro-echancal systes (MEMS) and low power and hghly ntegrated dgtal electroncs have led to the developent of cro sensors [][2][3][4][5]. Such sensors are generally equpped wth data processng and councaton capabltes. The sensng crcutry easures abent condtons related to the envronent surroundng the sensor and transfors the nto an electrc sgnal. Processng such a sgnal reveals soe propertes about objects located and/or events happenng n the vcnty of the sensor. The sensor sends such sensed data, usually va rado transtter, to a coand center (snk) ether drectly or through a data concentraton center (gateway). The gateway can perfor fuson of the sensed data n order to flter out erroneous data and anoales and to draw conclusons fro the reported data over a perod of te.

2 The contnuous decrease n the sze and cost of sensors has otvated ntensve research n the past few years addressng the potental of collaboraton aong sensors n data gatherng and processng, va an ad hoc wreless network. Networkng unattended sensor nodes s expected to have sgnfcant pact on the effcency of any ltary and cvl applcatons, such as cobat feld survellance, securty and dsaster anageent. A network of sensors can be used to gather eteorologcal varables such as teperature and pressure. These easureents can be used n preparng forecasts or detectng harsh natural phenoena. In dsaster anageent stuatons such as earthquakes, sensor networks can be used to selectvely ap the affected regons drectng eergency response unts to survvors. In ltary stuatons, sensor networks can be used n survellance ssons and can be used to detect ovng targets, checal gases, or presence of cro-agents. Sensor nodes are constraned n energy supply and bandwdth. Such constrants cobned wth a typcal deployent of large nuber of sensor nodes have necesstated energy-awareness at ost layers of networkng protocol stack ncludng the network layer. Routng of sensor data has been one of the challengng areas n wreless sensor network research. Current research on routng n wreless sensor networks ostly a at axzng the lfete of the network, allowng scalablty for large nuber of sensor nodes and supportng tolerance for sensor daage and battery exhauston [6][7][8][9][0]. However, current routng approaches cannot provde end-to-end perforance guarantees for applcatons that requre real-te routng of sensor data. For nstance, routng of agng data n a battle envronent requres careful handlng n order to ensure that the end-to-end delay s wthn acceptable range and the ages are receved properly wthout any dstorton. Therefore, new routng protocols that can handle Qualty of Servce (QoS) requreents along wth energy-awareness are needed. Energy-aware QoS routng n sensor networks wll ensure suffcent bandwdth or bounded delay through the duraton of connecton as well as provdng the use of ost energy effcent path. Such routng protocols n sensor networks have several applcatons ncludng real te target trackng n battle envronents, eergent event trggerng n ontorng applcatons etc. In ths paper, we present a novel echans for effcent routng of real-te traffc n wreless sensor networks. Our proposed approach extends the routng protocol n [0] and consders end-to-end delay as a constraned. The new routng approach looks for a delay-constraned path wth the least possble cost. Lnk costs are a functon of reanng sensor energy, requred transsson power and error 2

3 rate. End-to-end delay bound s acheved through the use of a Weghted Far Queung (WFQ) based packet schedulng n each sensor node [][2]. WFQ consders a dfferent queue for each ncong flow and has been shown to provde an upper bound on path delay for a leaky bucket constraned flow [3]. We regulate the ncong traffc fro the sources by usng the leaky bucket echans and separate the real-te traffc fro non-real-te traffc wth the usage of two dfferent queues n each node. Once such separaton s acheved, the servce rate for the real-te data queue, requred for eetng ost deadlnes, s estated. In the balance of ths secton we descrbe the sensor network archtecture that we consder and suarze the related work on QoS routng. Then we gve a bref background on WFQ and descrbe our approach n secton 2. Secton 3 dscusses perforance evaluaton and sulaton results. Fnally we conclude the paper n secton 4 and outlne our future research plan.. Sensor Network Archtecture A set of sensors s spread throughout an area of nterest to detect and possbly track events/targets n ths area. The sensors are battery-operated wth dverse capabltes and types and are epowered wth lted data processng engnes. The avalablty of agng sensors s of partcular nterest due to the qualty of servce constrants assocated wth data generated by such sensors. The sson for these sensors s dynacally changng to serve the Sensor nodes Gateway Node Coand Node Coand Node Coand Node Coand Node Fg. : Three-ter sensor network archtecture need of one or ultple coand nodes. Coand nodes can be statonary or oble. In a dsaster anageent envronent, coordnaton centers are typcal statonary coand nodes, whle paraedcs, fre trucks, rescue vehcles and evacuaton helcopters are exaples of oble coand nodes. A gateway node s a less energy-constraned node deployed n the physcal proxty of sensors. The gateway s responsble for organzng the actvtes at sensor nodes to acheve a sson, fusng data collected by sensor nodes, coordnatng councaton aong sensor nodes and nteractng wth coand nodes. In ths paper we only consder statonary gateway and sensor 3

4 nodes. All the sensors are assued to be wthn the councaton range of the gateway node. The archtecture s depcted n fgure. The sensor s assued to be capable of operatng n an actve ode or a low-power stand-by ode. The sensng and processng crcuts can be powered on and off. In addton both the rado transtter and recever can be ndependently turned on and off and the transsson power can be prograed for a requred range. It s also assued that the sensor can act as a relay to forward data fro another sensor. It s worth notng that ost of these capabltes are avalable on soe of the advanced sensors, e.g. the Acoustc Ballstc Module fro SenTech Inc. [4]. The gateway node s assued to know ts locaton, e.g. va the use of GPS. Whle the gateway wll take charge of sensor organzaton based on the sson and avalable energy n each sensor, we assue knowledge of whch sensors need to be actve n sgnal processng, e.g. usng the approaches presented n [][5]..2 Related Work Whle conteporary best-effort routng approaches address-unconstraned traffc, QoS routng s usually perfored through resource reservaton n a connecton-orented councaton n order to eet the QoS requreents for each ndvdual connecton. Whle any echanss have been proposed for routng QoS constraned real-te data n wre-based and wreless networks [6][7][8][9], they cannot be drectly appled to wreless sensor networks due to several characterstcs that dstngush the fro conteporary councaton and wreless ad-hoc networks. For nstance, t s not possble to buld a global addressng schee for the deployent of sheer nuber of sensor nodes. Therefore, classcal IP-based QoS protocols cannot be appled to sensor networks. Moreover, sensor nodes are tghtly constraned n ters of transsson power, onboard energy, processng capacty and storage and thus requre careful resource anageent. Due to such ssues, new QoS routng protocols are needed for wreless sensor networks. Very lttle research has been done on QoS routng n wreless sensor networks. The frst protocol for wreless networks that ncludes the noton of QoS n ts routng decsons s the Sequental Assgnent Routng (SAR) [3]. The SAR protocol creates trees routed fro one-hop neghbor of the snk by takng the QoS etrc, the energy resource on each path and the prorty level of each packet nto consderaton. By usng created trees, ultple paths fro snk to sensors are fored. One of these paths s selected accordng to the energy resources and achevable QoS on each path. SAR antans ultple paths fro nodes to snk. Although, ths ensures fault-tolerance, the protocol suffers fro the overhead of antanng the tables and states at each sensor node especally when 4

5 the nuber of nodes s very large. Our approach does not requre sensor s nvolveent n route setup therefore does not ntroduce an extra overhead to the sensor nodes. Another QoS routng protocol for sensor networks that provdes soft real-te end-to-end guarantees s SPEED [20]. The protocol requres each node to antan nforaton about ts neghbors and uses geographc forwardng to fnd the paths. SPEED strve to ensure a certan speed for each packet n the network so that each applcaton can estate the end-to-end delay for the packets by dvdng the dstance to the snk by the speed of the packet before akng the adsson decson. Moreover, t can provde congeston avodance when the network s heavly loaded. However, SPEED tres to save energy only through reducng the nuber of control packets. It does not consder any specal energy etrc n ts routng protocol. Our approach on the other hand, ntally fnds a lst of energy-aware paths by consderng the transsson and resdual energy of the nodes. The delay-constraned path s then searched aong those alternatves. 2. Energy-aware QoS routng va WFQ In order to descrbe the routng proble, we consder the followng scenaro: In a battle envronent t s crucal to locate, detect and dentfy a target. In order to dentfy a target, we should eploy agng sensors. After locatng and detectng the target wthout the need of agng sensors, we can turn on those sensors to get for nstance an age of the target perodcally and send to the gateway. Snce, t s a battle envronent; ths requres a real-te data exchange between sensors and controller n order to take the proper actons. In that case, we should deal wth real-te agng data, whch requres certan bandwdth wth nu possble delay. Therefore, a servce dfferentaton echans s needed n order to guarantee the relable delvery of such data. The goal n such an applcaton wll be to fnd an optal path to the gateway n ters of energy consupton and error rate whle eetng the end-to-end delay requreent. End-to-end delay requreent s assocated only wth the real-te data. The descrbed QoS routng proble s very slar to typ cal path constraned path optzaton (PCPO) probles, whch are proved to be NPcoplete [2]. We are tryng to fnd least-cost path, whch eets the end-to-end delay path constrant. Our approach s based on assocatng a cost functon for each lnk and usng a K least cost path algorth to fnd a set of canddate routes. Such routes are checked aganst the end-to-end constrants and the one that eets the requreents s pcked. In the balance of ths secton, we wll brefly descrbe the underlyng network operaton odel, gve soe background on WFQ and explan the detals of proposed algorth. 5

6 2. Network Operaton In the syste archtecture, gateway nodes assue responsblty for sensor organzaton based on ssons that are assgned to the network. Msson-orented organzaton of the sensor network enables the approprate selecton of only a subset of the sensors to be turned on and thus avods wastng the energy of sensors that do not have to be nvolved. Thus the gateway wll control the confguraton of the data processng crcutry of each sensor. Assgnng the responsblty of network anageent to the gateway can ncrease the effcency of the usage of the sensor resources. The gateway node can apply energy-aware etrcs to the network anageent guded by the sensor partcpaton n current ssons and ts avalable energy. Snce the gateway sends confguraton nstructons to sensors, the gateway has the responsblty of anagng transsson te and establshng routes for the outgong essages. The sensor nodes can be n one of four an states: sensng only, relayng only, sensng-relayng, and nactve. In the sensng state, the node sensng crcutry s on and t sends data to the gateway n a constant rate. In the relayng state, the node does not probe the envronent but ts councatons crcutry s on to relay the data fro other actve nodes. When a node s both sensng the target and relayng essages fro other nodes, t s consdered n the sensng-relayng state. Otherwse, the node s consdered nactve and can turn off ts sensng and councaton crcutry. The decson for deternng the node's state s done at the gateway based on the current sensor organzaton, node battery levels, and desred network perforance easures. It should be noted that our routng approach s transparent to the ethod of selectng the nodes that should sense the envronent. The gateway wll use odel-based energy consupton for the data processor, rado transtter and recever n order to track the lfe of the sensor battery. Ths odel s used n the routng algorth as explaned later. The gateway updates the sensor energy odel wth each packet receved by changng the reanng battery capacty for the nodes along the path fro the source sensor node to the gateway. The typcal operaton of the network conssts of two alternatng cycles: data cycle and routng cycle. Durng the data cycle, the nodes, whch are sensng the envronent sends ther data to the gateway. In the routng cycle, the state of each node n the network s deterned by the gateway and the nodes are then nfored about ther newly assgned states and how to route the data. Reroutng s trggered by an applcaton-related event requrng dfferent set of 6

7 sensors to probe the envronent ncludng the actvaton of agng sensors or the depleton of the battery of an actve node. 2.2 Background on WFQ In our syste odel, each node eploys a packet schedulng dscplne that approxates Generalzed Processor Sharng (GPS). GPS acheves exact weghted ax-n farness by dedcatng a separate FIFO queue for each sesson (flow) and servng an nfntely sall aount of data fro each queue n a weghted round robn fashon. Before explanng how GPS works n detals, we ntroduce the followng notaton: σ ρ : Maxu burst sze for leaky bucket on flow (packets) : Average data rate of the flow D () : End-to-end delay for flow (sec) C : Lnk bandwdth P ( ) : Maxu packet sze for flow ax P ax : Maxu packet sze allowed n the network g : Servce rate on node for flow (bt/sec) g () : Mnu of all servce rates for flow (bt/sec) M : The nuber of nodes on path of flow A GPS server serves n sessons on a lnk by gvng each sesson a share of the lnk based on n postve real nubers, Φ,...,, Φ 2 Φn. These nubers denote the relatve aount of servce to each flow on the server. Note that ths sharng s only for backlogged connectons snce nonbacklogged connectons already receve what they ask for. The GPS server ensures that backlogged connectons share the reanng bandwdth n proporton to the assgned weghts. As analyzed n [], each backlogged connecton receves a servce rate of: g = n Φ j= Φ j C However, GPS s not pleentable n practce due to ts deal flud odel. Therefore, packet approxaton algorths of GPS were proposed. Weghted Far Queung (WFQ) [2] and Packetzed Generalzed Processor Sharng (PGPS) [3] are two dentcal dscplnes developed ndependently and do not requre GPS s nfntely sall servce assupton. They serve the [] 7

8 ncong packets accordng to ther servce tes under GPS. Therefore, for each flow the packet wth the earler servce te s served frst. Throughout ths paper, we use the ter WFQ for the packet-based verson of GPS. WFQ has two portant features: Frst, t can provde far allocaton of bandwdth aong all backlogged sessons as long as the total servce rate of all sessons s less than the lnk bandwdth. Second, when cobned wth traffc regulaton, t has been shown to provde an upper bound for the end-to-end delay [3]. Such regulaton s done through the use of leaky bucket echans at the sources n order to ensure a constant data rate and to restrct the burst sze for the traffc reachng the next relay nodes. As shown n [], f a sesson s leaky bucket constraned, the aount of sesson traffc enterng the network durng nterval (τ, t] wll be: A ( τ, t) σ + ρ ( t τ ), t τ 0 Assung flow s constraned by a leaky bucket wth paraeters (σ, ρ ), the axu end-to-end delay (transsson + queung delay) for a packet of flow under WFQ, gven n [3], s: σ D( ) + g( ) 2.3 Proposed Queung Model M M Pax ( ) + = g = The queung odel s specfcally desgned for the case of coexstence of real-te and P C ax RT = non-real-te traffc n each sensor node. The odel we eploy s nspred fro class-based queung [22]. We use dfferent queues for the two dfferent types of traffc. Bascally, we have realte traffc and non-real-te (noral) traffc whose packets are labeled accordngly. On each node there s a classfer, whch checks the type of the ncong packet and sends t to the approprate queue. There s also a scheduler, whch deternes the order of packets to be transtted fro the queues accordng to the bandwdth rato r of each type of traffc on that lnk. The odel s depcted n fgure 2. The bandwdth rato r, s actually a value set by the gateway and s used n allocatng the aount of bandwdth to be dedcated to the real-te and non-real-te traffc on a partcular outgong lnk. As ndcated n fgure 2, ths r-value s also used to calculate the servce rate for each type of traffc on that partcular node, wth r µ and ( r ) µ beng respectvely the servce rate for real-te and non-real-te data on sensor node. [2] µ servce_ rate r NRTservce _ rate = ( r) µ Fg. 2: Lnk sharng rates for a sensor node 8

9 Snce n WFQ each flow has ts own queue, we consder each agng sensor node as a source of dfferent real-te flow, however only one real-te queue s used n the node to serve the data cong fro these ultple flows. Ths echans s an approxaton to flow-based WFQ approach and s used due to two reasons: Frst, havng a dfferent queue for each real-te flow wll be neffcent n ters of the storage capacty of a sensor node. Second, the realte flows are generated dynacally dependng on the nuber of actve agng sensors. Snce the nuber of such flows can change durng the sensng actvty, havng one queue wll reduce the antenance overhead. In our odel, we dedcate another separate queue to serve non-real-te data cong fro dfferent sources. The odel s depcted n fgure 3. In ths odel, the servce rato r for the real-te queue on a node wll be suaton of lnk shares of all real-te flows passng through that node. 2.4 Calculaton of lnk costs We consder the factors for the cost functon on each partcular lnk separately except the end-to-end delay requreent, whch should be for the whole path,.e. all the lnks on that path. We defne the followng cost functon for a lnk between nodes and j: where, 2 cost j = CF k = c 0 (dst j ) l + c f(energy j ) + c 2 f(e j ) k= 0 dst j s the dstance between the nodes and j, f(energy j ) s the functon for fndng current resdual energy of node j, f(e j ) s the functon for fndng the error rate on the lnk between and j. Cost factors are defned as follows: NRT flows RTflow RTflow 2 RTflow n NRTQueue RTQueue Scheduler CF 0 (Councaton Cost) = c 0 (dst j ) l, where c 0 s a weghtng constant and the paraeter l depends on the envronent, and typcally equals to 2. Ths factor reflects the cost of the wreless transsson power, whch s drectly proportonal to the dstance rased Φ Φ 2 Φ N Fg. 3: Queung odel on a sensor node r r Sensor node = N j= Φ 9

10 to soe power l. The closer a node to the destnaton, the less ts cost factor CF 0 and the ore attractve t s for routng. CF (Energy Stock) = c f(energy j ). Ths factor reflects the reanng battery lfete (energy usage rate) favorng nodes wth ore energy. The ore energy the node antans, the better the stablty of the fored routes. CF 2 (Error rate)= c 2 f(e j ) where f s a functon of dstance between nodes and j and buffer sze on node j (.e. dst j / buffer_sze j ). Lnks wth hgh error rate wll ncrease the cost functon, thus wll be avoded. 2.5 Estaton of r-values In order to fnd a QoS path for sendng real-te data to the gateway, frst we obtan a set of energyeffcent paths. Then, we further check the to dentfy the one that can eet the end-to-end delay requreent by tryng to fnd an r-value for each node on that path. Therefore, for each flow the necessary servce rate at each node should be estated. Let T requred be the requred end-to-end delay for the applcaton. Thus, we should fnd r-values so that D() T requred. Usng (2), σ g( ) M M Pax ( ) + = g = + P C ax T requred In order to fnd g fro the above equaton, we assue that the servce rate s sae for all the nodes on the path of a partcular flow,.e. g () = g calculated drectly fro (),. Once g s calculated, then the lnk share can be Φ = g * N j= C Φ j As entoned n secton 2.2, the servce rato for real-te data on a sensor node wll be the suaton of the lnk shares of all flows passng through that node,.e. r = N j= Φ j, where N s the nuber of real-te data flows passng through node and Φ j s the lnk share for a real-te flow j on node. Ths r-value s calculated for each node at the gateway and then sent to the correspondng node by the gateway. 0

11 By consderng the above calculatons, we propose the algorth shown n fgure 4, to fnd a least-cost path that eets the constrants for real-te data. The algorth calculates the cost for each lnk, lne 0 of fgure 4, based on the cost functon defned n secton 2.3. Then, for each flow fro agng sensors, the least cost path to the gateway s found by runnng a K-shortest path algorth n lne 3. Here, the least cost path s taken aong K alternatves by settng k to n lne. Between lnes 4-5, approprate r-values are calculated for each real-te data flow. In lnes 6 and 7, each node on the path of a flow calculates ts fnal r-value. If that value s not between 0 and, alternatve paths wth bgger costs are tred by ncreasng the k value (lne 2 and 3). As soon as a proper r-value s found, the loop exts (lne ). If there s no such r-value, the connecton request of that node to the gateway s rejected (lne 2-3). In order to fnd the K shortest paths,.e. K least-cost paths, we odfed an extended verson of Djkstra s algorth gven n [23]. Snce the algorth fnds a set of paths wth slar nodes and lnks, we odfed the algorth n such a way that each te a new path s searched for a partcular node; only node-dsjont paths are consdered durng the process. Ths ensures splcty and helps n fndng a proper r-value ore easly snce that node-dsjont path wll not nhert the congeston of paths whose costs are less and for whch the end-to-end delay requreents could not be et. 3. Experental Results The effectveness of the energy-aware QoS routng approach s valdated through sulaton. Ths secton descrbes the perforance etrcs, sulaton envronent, and experental results. 3. Perforance Metrcs 0 Calculate cos,, j V Fg. 4. Pseudo code for the proposed algorth We used the followng etrcs to capture the perforance of our QoS routng approach: t j k 2 Repeat 3 Fnd k th least cost path for each node 4 for each flow fro agng sensor do begn 5 Copute Φ for all the nodes fro D( ) 6 for each node (on the path of flow ) do r 7 r + Φ 8 f ( r s not n range [0,)) then 9 break; end 0 k k + untl k > K or a proper r for each node s found 2 f no proper r s found then 3 Reject the connecton T requred

12 Average delay per packet: Defned as the average te a packet takes fro a sensor node to the gateway. The applcatons that deal wth real-te data s delay senstve, so ths etrc s portant n our case. Deadlne Mss Rato: Ths s one of the ost portant etrcs n real-te applcatons, whch ndcates the nuber of packets that could not eet the specfed end-to-end deadlne. Average lfete of a node: Ths gves a good easure of the network lfete. A routng algorth, whch axzes the lfete of the network, s desrable. Average energy consued per packet: Ths ndcates the total energy consupton for each packet. Ths etrc along wth average lfete of a node shows how effcent the algorth s wth respect to energy consupton. 3.2 Envronent Setup In the experents we have consdered a network of 00 randoly placed nodes n a eter square area. The gateway poston s deterned randoly wthn the boundares of deployent area. A free space propagaton channel odel s assued [24] wth the capacty set to 2Mbps. The data packet length s 0 Kbt. Each node s assued to have an ntal energy of 5 joules. A node s consdered non-functonal f ts energy level reaches 0. For the ter CF n the cost functon, we used the lnear dscharge curve of the alkalne battery [24]. For a node n the sensng state, packets are generated at a constant rate of packet/sec. Ths value s consstent wth the specfcatons of the Acoustc Ballstc Module fro SenTech Inc. [4]. The sources generatng real-te data are assued to be leaky bucket constraned wth the axu burst paraeter σ of 0 packets. Each data packet s te-staped when t s generated to allow the calculaton of average delay per packet. In addton, each packet has an energy feld that s updated durng the packet transsson to calculate the average energy per packet snce our cost functon defned for each lnk s usng reanng energy as part of the cost. We assue that the network s tasked wth a target-trackng sson n the experent. The ntal set of sensng nodes s chosen to be the nodes on the convex hull of sensors n the deployent area. The set of sensng nodes changes as the target oves. Snce targets are assued to coe fro outsde the area, the sensng crcutry of all boundary nodes s always turned on. The sensng crcutry of the other nodes s usually turned off but can be turned on accordng to the target oveent. We also assue that each sensor node s capable of takng the age of target to dentfy 2

13 t clearly and can turn on ts agng capablty on deand. Durng sulaton, a sall subset of current actve nodes, whch are the closest nodes to the target, are selected to turn on ther agng capabltes. Therefore, the agng sensor set ay change wth the oveent of the target. The packet generaton rate for agng sensors s bgger than the noral sensors. Packets, generated by agng sensors, are labeled as of real-te type and treated dfferently at the relayng nodes. The r-value s ntally assued to be 0 but t s recalculated as agng sensors get actvated. The default end-to-end delay requreent for real-te data s taken to be 0.08 sec [26]. Targets are assued to start at a rando poston outsde the convex hull. Targets are characterzed by havng a constant speed chosen unforly fro the range 4 eters/s to 6 eters/s and a constant drecton chosen unforly dependng on the ntal target poston n order for the target to cross the convex hull regon. It s assued that only one target s actve at a te. Ths target reans actve untl t leaves the deployent regon area trggerng the generaton of a new target. 3.3 Perforance Results In ths secton, we present soe perforance results obtaned through sulaton. Dfferent real-te data generaton rates are consdered n order to capture the effects on the perforance etrcs defned earler n ths secton. Delay and Telness Metrcs: In order to copare our routng algorth wth a baselne approach, we have used the sae cost functon wth sae routng algorth wthout dong any servce dfferentaton. That s, we have not dfferentated between packets and have only one queue n each sensor node for all knds of packets. Therefore, no bandwdth allocaton s done through adjustng of r-values. We have copared ths approach wth our WFQ based approach by lookng at the average delay per packet and ss rato for the real-te packets, whch cannot eet the deadlne. When coparng the average delay per real-te packet acheved through our WFQ-odel wth the average delay per packet obtaned n the sngle queue odel, we have observed that the WFQ based approach acheves substantally better average delay (See fgure 5). Ths s due to the prorty gven to real-te packets when transttng to the gateway. For both approaches, there s an ncrease n the average delay per real-te packet when the real-te data rate s boosted. Ths s due to ncreasng the average queung delay that the real-te packets ncur. However, such ncreent n the average delay per packet s very sall n the case of WFQ-based approach. Whle, the average delay per real-te packet fro dstant nodes ncreases, nodes close to the gateway, whch have less 3

14 average delay, also generate ore real-te packets, causng the overall average delay for real-te packets to stablze. In fgure 6, we have depcted the results for the nuber of real-te packets that ssed the deadlne for both approaches. Whle our approach acheves alost 90% of ht when there s no congeston n the network, baselne approach causes ost of the packets to ss ther deadlnes. Te(sec) Baselne WFQ Mss Rato(%) Baselne WFQ RT data rate Fg. 5 : Average delay per real-te packet for dfferent real-te data rates RT data rate Fg. 6: Percentage of packets ssng the deadlne for dfferent real-te data rates Energy consupton and average node lfete When we looked at the energy usage, we have observed that routes set usng our algorth lead to the consupton of alost the sae aount of energy copared to the baselne approach, as confred fro fgures 7 and 8. There s a slght ncrease n the average energy per packet when the real-te data rate s ncreasng. Ths s due to not beng able to use the least cost path at all tes snce the least cost path ght not always provde on te delvery of constraned traffc (Fgure 7). On the other hand, our approach perfors slghtly better n ters of average lfete of nodes (Fgure 8). Ths can be explaned by the spread of traffc to dfferent nodes n our approach snce Energy Baselne WFQ RT data rate Fg. 7: Average energy consued per packet for dfferent real-te data rates Te(sec) RT data rate Fg. 8: Average lfete of a node for dfferent real-te data rates Baselne WFQ 4

15 alternatve paths are tred when end-to-end requreents cannot be et on a partcular path. Furtherore, n both cases, ore energy s consued whle the real-te data rate s ncreasng and causng sensors to generate/relay ore packets. Hence, average lfete of a node decreases because of the ncreased energy usage. 4. Concluson In ths paper, we have presented a new energy-aware real-te routng approach for sensor networks. The proposed approach fnds energy-effcent paths for real-te data wth certan end-to-end delay requreents. WFQ, whch allows servce sharng for real-te and non-real-te flows, s eployed n order to support both best effort and delay-constraned traffc at the sae te. A servce rato r s derved for calculatng the aount of bandwdth to be dedcated to the real-te and non-real-te traffc on a partcular outgong lnk. Snce WFQ provdes per flow upper bounds on end-to-end delay, each sensor generatng real-te data s consdered as a dfferent flow. However, rather than eployng a dfferent queue and lnk share for each real-te flow, a sngle queue s used to accoodate all real-te data fro dfferent flows. The real-te servce rato r for that queue s calculated as the suaton of the lnk shares of real-te flows passng through that node. Such servce rate estaton echans s used along wth leaky bucket constraned packet generaton so that end-to-end delay bounds are et. The effectveness of the proposed routng algorth s valdated through sulaton. Sulaton results show that our approach consstently perfors well n ters of ss rato and average delay, copared to a baselne echans n whch sae lnk cost functon and routng algorth are used wthout perforng any servce dfferentaton. Our approach provdes at least 80% on-te delvery of real-te data even when the network s congested through adjustng the real-te data servce rate. Moreover, the approach enhances telness wthout negatvely pactng consued energy. Whle our proposed routng approach fts a fxed gateway odel, our future research plan ncludes addressng ssues related to the relocaton and oblty of the gateway. In such cases, the frequent update of the poston of the gateway and the propagaton of that nforaton through the network ay excessvely dran the energy of nodes, especally n the presence of real-te traffc. We plan to extend to odel n order to handle the overhead of oblty and topology adjustent. 5

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