Traffic Priority Based Adaptive and Responsive Congestion and Rate Control for Wireless Mesh Networks

Transcription

1 Computer and Informaton Scence; Vol. 7, No. 2; 2014 ISSN E-ISSN Publshed by Canadan Center of Scence and Educaton Traffc Prorty Based Adaptve and Responsve Congeston and Rate Control for Wreless Mesh Networks Maheen Islam 1, M. Lutfar Rahman 1,2 & Mamun-Or-Rashd 1,3 1 Department of Computer Scence and Engneerng, East West Unversty, Dhaka, Bangladesh 2 Department of Computer Scence and Engneerng, Unversty of Dhaka, Dhaka, Bangladesh 3 Daffodl Internatonal Unversty, Dhaka, Bangladesh Correspondence: Maheen Islam, Department of Computer Scence and Engneerng, East West Unversty, Dhaka, Bangladesh. E-mal: maheen@ewubd.edu Receved: March 30, 2014 Accepted: Aprl 25, 2014 Onlne Publshed: Aprl 28, 2014 do: /cs.v7n2p99 URL: Abstract Congeston Control n Wreless Mesh Networks (WMNs) has been a wdely studed context orented utlzaton maxmzaton problem. The traffc n WMNs has a wde range of varatons (.e. bandwdth, jtter, delay jtter senstve applcatons) due to ts use as the backbone network for accessng Internet. Eventually, traffc varaton contrbutes to channel saturaton and may brng up congeston due to contenton caused by concurrent transmsson, buffer overflows and tme varyng wreless channel condton. In ths paper, we propose a dstrbuted congeston control scheme for wreless mesh networks to ensure hgher network throughput whle avodng congeston and mantanng nter-flow farness where real tme and non-real tme traffc coexsts. Our proposed technque handles congeston by restrctng the avalable transmsson rate of downstream nodes among the upstream nodes accordng to ther flow demands based on three basc parameters: packet arrval rate, servce rate and buffer occupancy. We also ntroduce prortzed queues n each node to treat real tme and non-real tme traffc dfferently. Therefore, congeston degree calculaton, rate allocaton and prortzng traffc ensures hgher network throughput and guaranteed delvery of real tme traffc. Experments conducted on ns-2 smulatons demonstrate that our proposed algorthm can acheve sgnfcant mprovements n both overall network throughput and nter-flow farness for both non real tme and delay bound traffc. Keywords: wreless mesh network, congeston control, traffc prortzaton 1. Introducton Wreless mesh networkng has become one of the most transprng technologes for large scale network solutons. It covers most of the uncovered networkng ssues such as flexble, adaptve and reconfgurable archtecture and at the same tme, offers a cost-effectve solutons to servce provders. In WMNs, nodes are comprsed of mesh routers and mesh clents, where mesh routers have mnmal moblty and form the backbone of WMNs. They provde network access for both mesh and conventonal clents. The ntegraton of WMNs wth other networks such as the Internet, cellular, IEEE , IEEE , IEEE , sensor networks, etc., can be accomplshed through the gateway and brdgng functons n the mesh routers. Mesh clents can be ether statonary or moble, and can form a clent mesh network among themselves and wth mesh routers. WMN s a promsng wreless technology for numerous applcatons, e.g., broadband nternet access, communty and neghborhood networks, enterprse networkng, buldng automaton, etc (Akyldz & Wang, 2005). The traffc n WMNs has a wde range of varatons (.e. bandwdth, jtter, delay jtter senstve applcatons) due to ts use as the backbone network for accessng Internet. Eventually, traffc varaton contrbutes to channel saturaton and may brng up congeston due to contenton caused by concurrent transmsson, buffer overflows and tme varyng wreless channel condton. As WMN s a multhop network, congeston takng place at a sngle node may dffuse to the whole network and degrade ts performance drastcally. Therefore, congeston control s a crucal ssue for WMNs. Congeston control mechansm s responsble for preventng the occurrence of congeston, as well as for allevatng the mpact of congeston on network f t occurs. Also, congeston control scheme should ensure a far dstrbuton of resources among nodes. 99

2 In the Internet, congeston has been resolved by applyng end-to-end congeston control algorthm,.e. Transmsson Control Protocol (TCP). However, t has been reported that TCP does not perform well n a mult hop wreless envronment (Holland & Vadya, 2002), whch usually results n neffcent and unfar bandwdth allocaton among dfferent flows. One of the well known reasons for TCP performance degradaton s that tradtonal TCP assumes that the packet loss happens only due to the congeston n the network. However ths assumpton may not be true n wreless networks, snce the packet loss also happens due to erroneous wreless characterstcs, MAC contenton, unstable network condtons and moblty of nodes. As TCP assumes all losses ndcate congeston, when non congeston packet losses occur n wreless networks, besdes retransmttng the lost packet, TCP also reduces ts transmsson rate as a result the network throughput drops quckly. Moreover once wreless channels are back to the normal operaton, the classcal TCP cannot be recovered quckly. Also an end-to-end congeston and rate control s napproprate for wreless mesh networks, because t suffers from the adverse effects of mult-hop wreless envronments, such as varable round-trp-tmes (RTT), hgh BER and rado nterferences. Hop-by-hop schemes result n better performance than a correspondng end-to-end scheme by reactng to network congeston faster than end-to-end mechansms. Besdes TCP, many applcatons n nternet such as audo and vdeo streamng use User Datagram Protocol (UDP) as a transport protocol, snce they requre tmely delvery of data rather than relable transmsson. As UDP protocol njects traffc nto the network wthout seekng any feedback regardng the capacty of the network, more packets get collded and congeston stuaton gets worse. Coexstence of real tme and non-real tme traffc may drect the stuaton even worse. Rate control algorthms are ncompatble for real tme traffc as t has certan sgnfcant prorty on tme bound rather than relablty. Therefore, to avod congeston WMN requres an effectve congeston control protocol whch s capable of avodng/controllng congeston at the same tme ensures a guaranteed servce for the prortzed traffc, whle assgnng rates to flows, real tme traffc should get hgher opportunty to be transmtted as compared to non real tme traffc. In ths paper, we propose a dstrbuted congeston control scheme for wreless mesh networks to ensure hgher network throughput whle avodng congeston and mantanng nter-flow farness where real tme and non-real tme traffc coexsts. Our proposed technque deals wth three followng basc parameters: packet arrval rate, servce rate and buffer occupancy. Based on these basc parameters, we have calculated the congeston degree of a node whch determnes three dfferent states: no congeston, antcpated congeston and congeston. In antcpated congeston state the downstream node restrcts the avalable transmsson rate among the upstream nodes accordng to ther flow demands. In congeston state, the downstream node scales down the avalable rate among the upstream nodes proportonately to ncrease free buffer and thus allevate congeston from the network. Our proposed technque also ntroduces two dfferent queues n each node for handlng real tme and non-real tme traffc. In each state, as we defned earler, real tme traffc gets more share of the allocated rate than the non-real tme traffc. Therefore, congeston degree calculaton, rate allocaton and prortzng traffc ensures hgher network throughput and guaranteed delvery of real tme traffc. The rest of the paper s organzed as follows. Secton 2 dscusses the related work n the lterature. Secton 3 descrbes network and node archtecture, Secton 4 descrbes the problem of congeston control n WMN and Secton 5 presents the proposed protocol. Performance evaluaton s carred out n Secton 6 and the paper concludes n Secton Related Works In recent publcatons several approaches for congeston control n wreless multhop networks have been proposed. So far, there are two dfferent types of approaches for congeston control n the exstng lterature: end-to-end congeston and hop-by-hop congeston control. However, a consderable research has been performed on mprovng the throughput of TCP for wreless envronment. These works attempt to mprove wreless TCP throughput by dstngushng the packet loss due to congeston and lnk falure. We have artculated the pros and cons of the above mentoned technque n the followng: A lot of work has been done focusng the area of TCP enhancement where TCP responds to specal wreless characterstcs. To dscern between congeston and non congeston losses n multhop wreless networks several varants of TCP such as TCP ELFN (Holland & Vadya, 2002), TCP Feedback (Chandran & Prakash, 2001) and TCP-Bus (Km & Cho, 2001) were proposed. Upon detecton of a route falure event by the network layer, these protocols ceases further packet transmsson untl the route recovery. In (Lu & Sun, 2007), a TCP enhancement called Congeston Coherence for WMN has been proposed whch dstngushes congeston losses from transmsson errors and multpath reorderng based on ECN (Explct congeston notfcaton) markng by ntermedate routers and thus reduces false retransmsson, tmeouts, unnecessary congeston wndow reductons, and thus provdes mprovements than exstng wreless TCP enhancements. In ECRFN (Zmmermann & Gunes, 2007), the TCP sources are alerted by the network 100

3 nodes regardng wreless errors and route falure, to prevent useless wndow sze reducton and halt packet transmsson tll route s re-establshed. ATCP (Lu & Sngh, 2001), ntroduces a layer known as Adhoc TCP between the TCP and IP layers whch receves dstnct feedback from network layer and nternet layer regardng route falure, network congeston and packet corrupton. A good number of end-to-end rate based congeston control protocols has been dscussed n lterature, where the rate of the source node s regulated by ts destnaton. Here each ntermedate node n the network estmates the avalable bandwdth at the node and attaches the nformaton wth all forwardng packets. Upon recevng these packets, the recever calculates the allowable bandwdth on the path and notfes the source through acknowledgement. In ATP (Sundaresan & Svakumar, 2003), ntermedate nodes n a connecton stamps the sum of the average queung and transmsson delay experenced by packets traversng through them and the recever sends rate feedback to the sender usng the weghted average the delay. ATP sender uses the nverse of ths delay as the sendng rate. In EXACT (Chen & Vadya, 2004), routers calculate sustanable rates for each flow as the nverse of MAC contenton and transmsson tme of a packet and then the rates are pggybacked. As both ATP and EXACT controls the rate only at the source node based on feedback from the network, the tme untl the feedback eventually reaches the source node, the rapdly varyng medum condtons may change whch leads to msleadng rate adaptaton by the source. In LRTP (Ranwala & Chueh, 2007), each ntermedate node measures the effectve bandwdth of each of ts wreless lnk, farly allocates t among the flows gong through t and the sender adjusts ther sendng rates based on the mnmum allocaton across all hops. Snce WMN nodes n the proposed archtecture run the LRTP protocol and the end user moble nodes and the nodes n the wred network runs TCP, n LRTP each ngress/egress WMN node has to employ a TCP-LRTP proxy. LRTP protocol also suffers from unfar channel sharng problem as when an ntermedate node allocates channel bandwdth among the nput flows, t does not consder the nterference relatonshp among the neghborng nodes and the number of flows gong over them. In AR-TCP (Venkata & Sva, 2006), lnk qualty s measured consderng the sgnal strength receved from each of ts neghborng node and avalable bandwdth s estmated. RBCC (Zha & Fang, 2005), measures the sendng rate of each flow by the channel utlzaton status at the bottleneck node whch s the rato of the total length of the busy perod to the total tme durng a tme nterval. WCP (Rangwala & Govndan, 2008) s an AIMD-based rate-control protocol whch explctly reacts to congeston wthn a wreless neghborhood. On congeston at a lnk, WCP sgnals all flows traversng the neghborhood of that lnk, to multplcatvely reduce ts rate by half. The man dfference wth TCP s that congeston s sgnaled to all flows traversng the neghborhood of a congested lnk. In EWCCP (Rangwala & Govndan, 2008), the ntermedate routers calculate the congeston feedback based on the sze of the neghborhood queue on each wreless lnk and adds feedback n the congeston header of the packet. When the packet arrves at the recever, the feedback feld n the congeston header holds the sum of all feedbacks gven by all wreless lnks along the path. The aggregated congeston feedback s echoed back to the sender wth an acknowledgement from the recever. The man objectve of TCP-AP (ElRakabawy & Lndemann, 2005), s to adaptvely set a TCP senders transmsson rate usng an estmate of the current 4-hop propagaton delay and the coeffcent of varaton of recently measured round-trp tmes. It s well known that the packets n multhop wreless networks do not collde wth the transmsson of the packets four hops away. Hence, the problem of packet bursts s solved by spreadng the transmsson of successve data packets accordng to the calculated 4-hop propagaton delay from the round trp tme (RTT) estmated at the source. As TCP-AP schedules packets n TCP layer, for multple flows between source and destnaton t suffers from mproper schedulng of packets at MAC layer that leads to self contenton of packets n the network. Ths protocol also shows severe unfarness towards the sources that are located longer dstance away from ther destnatons, snce t depends on RTT to schedule packets. ElRakabawy and Lndemann (2009) ntroduces MAP, whch operates at the wreless TCP source as well as at the mesh gateway, and transmts TCP packets by adaptng the transmsson rate accordng to the current network state. MAP dentfes the current load n the neghborhood by measurng the current level of contenton by means of the coeffcent of varaton of recently measured round trp tmes and also accounts for the spatal reuse constrant of IEEE mesh networks by measurng Out-of-Interference Delay (OID) as the tme elapsed between transmttng a TCP packet by the TCP source node and recevng the packet at a hdden termnal. In (Lu & Sun, 2007), when a routers queue length exceeds a threshold, the router stamps every ncomng packet wth a ECN (Early Congeston Notfcaton) bt set. Wth ECN, when a packet s dropped by a congested router, the ECN congeston sgnal carred by that packet s lost, but packets before and after the lost packet mantan coherent congeston nformaton. A packet loss s consdered as a congeston loss f any packet n ts coherence context s marked. In ths case, the recever responds wth duplcate ACKs to trgger an end-to-end retransmsson and wndow reducton at the source. Al Islam and Raghunathan (2011) devse a neural network based congeston control technque named TCP, where competng flows are treated ndependently and farness s not addressed. 101

4 Hop-by-hop congeston control studed n lterature has been dscussed n followng, where local feedback on the sustanable rate for each node s transmtted to the respectve upstream node, n order to establsh some knd of backpressure towards the source. SECC (Sadegh & Yang, 2006), uses local nformaton avalable at nodes to detect congeston, computes target rate for the congested flows, notfes upstream nodes the target rates and fnally upstream nodes modfes e channel access parameters to adjust the MAC transmsson rate to remove. SECC outperforms TCP n wreless networks due to beng able to reactng to dynamc wreless condton and neghborhood congeston promptly. But SECC congeston control n one part of the network may cause congeston n other part of the network. Addtonally, ths approach uses explct feedback to the upstream nodes that mposes feedback traffc on the network. In AR-TP (Pace & Gungor, 2007) protocol the router calculates the rates for the flows passng through t based on two dfferent threshold levels of router buffer; employs a back pressure mechansm to request the prevous neghbor n the data flow for a rate adaptaton and also asks the next hop neghbor to allow the congested node to ncrease the sendng rate for that knd of traffc that caused congeston through a forward threshold adaptaton technque. In order to mtgate congeston n one part of the network, AR-TP (Pace & Gungor, 2007) may ntroduce congeston on the other parts of the network. By usng the forward threshold adaptaton mechansm, a node may release ts own congeston, but ntroduce congeston n ts downstream nodes. Lnk Layer Adaptve Pacng (LLAP) (Frankln & Murthy, 2008) scheme tres to reduce the MAC contenton n the network by properly schedulng the packets at the source node. In LLAP, the four hop transmsson delay n a path s estmated by measurng the queung and transmsson delay ncurred at the bottleneck node n a dstrbuted manner and accordngly packets are paced for transmssons to reduce self contenton. In CXCC (Scheuermann & Mauve, 2008), a fast and effcent mplct backpressure mechansm s establshed towards the packet source by preventng the transfer of a second packet belongng to a partcular flow to a node untl ths node has forwarded the prevous one. Thus a CXCC requres keepng per flow state n the ntermedate nodes whch requres certan computatonal overhead. As CXCC s a cross-layer protocol, ts mplementaton wll also requre sgnfcant changes over the network partcpants protocol stack. In CFRC (Alam & Lee, 2011), the rates of the lnks are mantaned for a certan weght, and the njecton rates of the flows are set accordngly based on the weght of the flows and the weght for whch the lnks rate are mantaned. If the average queue sze of any lnk exceeds a predefned threshold, CFRC assumes that the lnk s congested. Lnks that route ther traffc va the same bottleneck lnk synchronze ther rate decrement, enforced through a rate-bounded backpressure sent by the bottleneck node to all lnks that use the bottleneck lnk to forward ther packets. However, f the lnks obtan the rates based on ther respectve downstream bottleneck lnks, flows usng dfferent bottleneck regons mght acheve dfferent throughput. To avod congeston, Masr and Gat (2012) antcpate the future buffer usage by combnng the queue lengths durng prevous control ntervals. NICC provdes mplct mult-bt congeston feedback usng underexploted felds n the frames header to ensure accurate rate control wthout nducng addtonal overhead. Jamshad and Levs (2014) dscusses the role of buffer szes n reducng queueng delays n wreless mesh networks. The proposed work ams to dstrbute the neghborhood buffer among the bottleneck contenton neghborhood to maxmze bottleneck utlzaton. In (Jamshad & Shhada, 2013), authors propose a gateway controlled centralzed schedulng mechansm for managng flow rates to avod congeston and mprove farness between network flows. 3. System Models 3.1 Network Model We consder a Wreless Mesh Network modeled by a network graph G N = (V N, E N ), where V N = {1,...,n} s the set of nodes (mesh clents, mesh routers and gateways) and E N = {(,j) :, j E N } s the set of b-drectonal lnks between the nodes. Some of the router nodes n the backbone network, called gateway nodes, connect to the Internet through wred lnk. The clent nodes utlze the mesh backbone network by gettng connected to the edge routers of the WMNs. In turns, the core router nodes form a multhop adhoc network among themselves to relay the traffc to and from mesh clent nodes. 102

5 Table 1. NS-2 smulaton parameters Parameter Value Total Area 1000 m 1000 m Number of nodes 100 CPThresold value e-11 CSThreshold value e-10 Routng Protocol AODV Packet sze 64 Bytes Buffer length 50 Data Sources 5~25 Offered load 5~100 pkts per sec (pps) Smulaton tme 50 s 3.2 Node Model and Traffc Classfer Coexstence of dfferent prorty based network traffc led us towards traffc classfer wth a vew to offer prorty based treatment. In our proposed technque, we consder two dfferent traffc classes namely: real tme traffc class (RT class) and non real-tme traffc class (NRT class). The RT class s assgned to hgh prorty real tme traffc such as real tme audo/vdeo. For NRT traffc, havng a low delay s not too mportant. Hgher prorty traffc classes need to have hgher throughput and low delay bound. We mplement separate queues for each traffc class. To dscrmnate traffc classes from each other, the mesh node adds a traffc class dentfer to ts local packets and places them n the proper queue. Ths dentfer represents the traffc class of each packet. An ntermedate node receves packet n nput queue, whch are then sent to dfferent traffc class queues accordng to ther traffc class. To provde qualty of servce for hgh prorty RT traffc flows n a wreless mesh network, a scheduler moves the packets from the Traffc class Queue to Transmsson Queue usng weghted round robn (WRR) schedulng to be dscussed n Secton Congeston n WMN To understand the effect of congeston n WMN we perform the followng experments usng the popular tool ns-2 (ns-2, 2008) wth 100 nodes under varous traffc loads. The parameters used n our study are lsted n Table 1. We estmate the acheved throughput n Fgure 1 for dfferent number of source nodes by varyng the offered load n the network. The characterstcs observed n throughput vs offered load graph sgnfes the fact that under lower offered load, the acheved end-to-end throughput ncreases lnearly but reaches a maxmum and starts decreasng wth ncreasng offered load. The same observaton s depcted n Fgure 2, where end-to-end delay has smlar lnear and exponental relaton wth offered load. Ths confrms the urgent need of a congeston control protocol n WMN. Fgure 1. Acheved throughput for varyng offered load for dfferent number of sources 103

6 Fgure 2. End-to-end delay for varyng offered load for dfferent number of sources We now take a closer look at the load vs throughput and load vs delay characterstc and dentfy four dfferent operatng regons from the experment and observed behavor. In Fgures 3 and 4 we have replcated representatvegraphs for 15 sources from Fgure 1 and Fgure 2 respectvely. Hence, our dscussons and results n ths paper apply to a general load vs. throughput and delay n WMN wth any set of parameter values, wth the specfc case (Number of sources = 15) used only for llustraton purposes. From Fgures 3 and 4, t s evdent that wth ncreased traffc load the system progress through the followng four operatng regons: No Congeston, Low Throughput, Low Delay (NC, LT, LD): Intally when the traffc volume s low, network s congeston free, delvers packets quckly but throughput s low Antcpated Congeston, Hgh Throughput, Low Delay (AC, HT, LD): More ncrease n traffc ncreases network throughput to a maxmum level but headng towards congeston. Congeston, Hgh Throughput, Hgh Delay (C, HT, HD): Fnally when network can not handle excessve flow of packets, congeston occurs resultng n packet loss and hgher end-to-end delay. Congeston, Low Throughput, Hgh Delay (C, LT, HD): As congeston state gets worse wth further traffc load, more packets are dropped at congested nodes. Snce the network capacty s wasted n partally movng packets from the source to the destnaton, network throughput drops off. Fgure 3. Four dfferent operatng regons and the acceptable operatng regon n throughput vs offered load graph 104

7 Fgure 4. Three dfferent operatng regons n end-to-end delay vs offered load graph Our am s to mantan hgher network throughput and lower delay whle avodng congeston, whch can be acheved f traffc flow resdes n acceptable operatng regon as mentoned n Fgure 3. Another sgnfcant observaton regardng MAC level congeston s dentfed n the followng. In WMN, snce neghborng nodes usng CSMA lke protocol share the same wreless channel, collsons could occur when multple nodes try to grab the channel at the same tme. Ths neghborhood congeston ncreases packet servce tme at nodes. Here the packet servce tme, s defned as the average processng tme of the data packets whch covers packet watng, collson resoluton and packet transmsson tmes at MAC layer. When packet servce tme at a node s greater than the packet nter-arrval tme, then there should be backlogged packets nsde the node and the nodes queue bulds up, whch lead to sgnfcant delay n delverng packets, may cause packet drop and thus decrease overall system throughput. We defne the rato of packet servce tme and packet nter-arrval tme at a node as congeston degree. We have measured the packet delvery rato and congeston degree for varous offered load n the network whch s shown n Fgure 5. We make the followng observatons from Fgure 5. Fgure 5. Delvery rato and congeston degree for dfferent offered load The delvery rato of packets s hgh untl a certan level of offered load, beyond whch the delvery rato drops. Such decrease n delvery rato s observed regardless of the number of source nodes. Moreover t s also apparent that wth greater number of source nodes the delvery rato falls more quckly than smaller number of source nodes. Ths stuaton occurs snce the network s unable to handle the ncreased njecton of data packets and packets are dropped due to congeston whch leads to poorer network throughput. 105

8 For any number of source nodes, the value of congeston degree ncreases for ncreased offered load. It has also been observed that when the value of congeston degree s greater than 1, the delvery rato of packets decreases. Ths s because when the nodes n a network serve the packets at a rate smaller than the rate at whch the packets arrve, the value of congeston degree goes beyond 1. As a result arrvng packets at nodes buld up queues and at some pont packets get dropped and thus lower the packet delvery rato. Based on these observatons, Congeston Degree seems to be a sgnfcant parameter that can be used for antcpatng upcomng congeston. 5. Proposed Protocol In ths secton we propose a congeston control mechansm whch reles on nformaton locally avalable at nodes. The developed protocol uses hop by hop sgnalng to notfy the upstream nodes of the congeston and the rates the downstream nodes can support. The upstream nodes then adjust ther transmsson rates. In the proposed archtecture, Congeston Detecton module checks for congeston at a node consderng local nodes nput traffc rate, output traffc rate and buffer occupancy. Dependng on the nodes congeston state, the Rate Adjustment module calculates the modfed rates for the upstream nodes consderng ndvdual upstream nodes average nput traffc rate. Congeston Sgnalng Module dssemnates the modfed rates to upstream nodes to releve downstream nodes congeston state. 5.1 Congeston Detecton In order to precsely measure local congeston level at node V, we defne two parameters for node V : average queue sze, Q_avg_V and congeston degree CD_V. Suppose the current queue sze at node V s Q_curr_V, then the average queue sze s computed usng EWMA (exponental weghted movng average) algorthm as follows n Equaton (1). Q _ avg _ V (1 ) Q _ Avg _ V Q _ cur _ V (1) where β s a weght factor. A value of β closer to 0, calculates the average queue sze gvng more emphass on the hstorcal behavor of the queue. To fnd the effectve value of the parameter β, n our smulaton we vared the value of β to measure the number of packet drops at downstream nodes for varable number (2 to 5) of upstream nodes. The result lsted n Table 2 reveals that the best possble result can be acheved by selectng a smaller value for β. In our smulaton we used a value of β = Table 2. Effect of the value of parameter β on buffer drop rate β No. of Buffer Drops Buffer Drop Rate (%) Congeston degree of node V, denoted as CD_V, s defned as the rato of the mean packet servce tme (T_serv_V ) over the mean packet nter-arrval tme (T_arr_V ) over a predefned tme nterval n node V as n Equaton (2): T _ serv _ V CD _ V (2) T _ arr _ V Here the mean packer nter-arrval tme T_arr_V, s defned as the nterval between the arrval of two adjacent data packets from upstream traffc, and the mean packet servce tme T_serv_V, s defned as the average processng tme of the data packets at node V. T_serv_V of a packet s the tme elapse between the nstant that a packet enters the queue to the nstant that a lnk layer acknowledgement s receved from the correspondng downstream or the packet s dropped after a predefned maxmum number of retransmssons. Thus T_serv_V, covers backoff delay, channel busy tme and physcal transmsson delay. To measure T_arr_V and T_serv_V at each node V, EWMA (exponental weghted movng average) algorthm s used. The congeston degree CD_V s proposed to reflect the current congeston ntensty at each mesh node. When the nter-arrval tme s smaller than the packet servce tme, the congeston degree s larger than 1 and the node 106

9 experences congeston. Otherwse when the congeston degree s smaller than 1, t ndcates that the volume of load offerd to the node doesn t exceed the node s forwardng capablty. Our proposed congeston detecton algorthm categorzes a nodes congeston state nto one of the followng by () montorng node s congeston degree CD_V and () comparng the node s average queue sze Q_avg_V wth a maxmum queue threshold Q_max_V. (No Congeston state): Q_avg_V < Q_max_V and CD_V < 1. In ths state no congeston s experenced as the average queue occupancy level s lower than the queue threshold. (Antcpated Congeston state): Q_avg_V < Q_max_V and CD_V > 1. When the packet arrval rate s greater than the departure rate, t ndcates that congeston may occur at near future. (Congeston state): Q_avg_V > Q_max_V and CD_V > 1. When the average queue sze exceeds the predefned maxmum threshold, congeston s experences by that node. 5.2 Rate Adjustment In the proposed network model, each node V receves data packets from each of ts upstream node V j (Up_V ) at a rate Rate_n_V j (Up_V ) and calculates the average nput rate, Rate_avg_V j (Up_V ) of upstream node V j (Up_V ), as Equaton (3): Rate _ avg _ V ( Up _ V ) (1 w ) Rate _ avg _ V ( Up _ V ) w Rate _ n _ V ( Up _ V ) (3) j q where 0 < w q < 1 s a constant. The total traffc nput rate, denoted as Total_n_V, at node V s the sum of average nput rates of all the upstream nodes V j (Up_V ). Average queue sze Q_avg_V and congeston degree CD_V, enables node V to detect congeston and average nput rate of upstream nodes Rate_avg_V j (Up_V ) and output rate of node V Rate_out_V, provdes nformaton to calculate a target rate Rate_tr_V j (Up_V ) for each of ts upstream node V j (Up_V ) to avod or mtgate congeston. The algorthm lsted n Table 3, summarzes the procedure of congeston detecton and rate readjustment. Table 3. Congeston detecton and Rate adjustment Algorthm Algorthm: Congeston detecton and Rate adjustment Input: Q_ max_v, T _ arr _ V, T _ serv_ V, Rate_ n_ Vj( Up_ V ) for each upstream node V j Result: Congeston state and Rate _ tr_ Vj( Up_ V ) 1: Intalze node nformaton 2: Compute Q _ avg_ V, CD _ V, Rate _ avg _ V j ( Up _ V ), total _ rn 3: f Q _ avg_ V Q _ max_ V and CD _ V 1 then 4: no congeston 5: end f 6: f Q_ avg_ V Q_ max_ V and CD _ V 1 then 7: 1 Rate _ out _ V T _ serv _ V Rate _ avg _ V j ( Up _ V ) 8: Rate _ tr _ V j( Up _ V ) Rate _ out _ V Rate _ total _ V 9: end f 10: f Q _ avg_ V Q _ max_ V then 1 11: Rate _ out _ V ; T _ serv _ V 12: Rate _ avg _ V j ( Up _ V ) Rate _ tr _ V j( Up _ V ) Rate _ out _ V Rate _ total _ V Rate_ tr _ V j ( Up_ V ) 13: Rate_ tr _ V j ( Up_ V ) CD_ V 14: end f 107 j q j

10 The mechansm of congeston detecton and rate adjustment s performed perodcally at a fxed tme nterval. Node V obtans ts average queue sze Q_avg_V, mean packet nter-arrval tme T_arr_V,mean packet servce tme T_serv_V to check for the congeston state. Our proposed algorthm reacts n dfferent ways for dfferent congeston state as followng: As long as a node s buffer occupancy s underutlzed, whch has been recognzed as (NC, LT, LD) regon n Secton 4, t does not send any rate adjustment notfcaton to the upstream flows. When new nodes become actve n neghborhood of node V or some of the upstream nodes produce more traffc, packet nter-arrval tme decreases and as an mpact congeston degree of V wll ncrease and the V enters (AC, HT, LD) regon. In such case node V experences an early congeston. In order to avod congeston, node V dstrbutes ts maxmum allowable output rate among the upstream nodes based on ther average nput rate whch ensures the network to operate n the expected operaton regon as mentoned n Fgure 3. Fnally when the average queue sze exceeds the maxmum queue threshold, node V experences permanent congeston, hghlghted as (C, LT, HD) regon n Fgure 3. In such a stuaton, upstream node s transmsson rate s decreased more aggressvely n order to reduce packet loss and allevate congeston quckly. The target rates of the upstream nodes are scaled down based on node V s output rate and degree of congeston Traffc Prortzng In our proposed method, a downstream node prortzes to schedule packets for transmsson consderng ther traffc type. To accomplsh ths, the downstream node mantans separate vrtual queues for each traffc type (VQ NRT for NRT class and V QRT for RT class) and a queue (VQ) to manage empty buffer spaces. Upon recepton of a packet, the downstream node reserves the head bucket from the empty vrtual queue for the packet and adds the bucket to the tal of the approprate queue dependng on the traffc class of the packet. When a packet s transmtted successfully, buffer space s made free and placed at the tal of empty vrtual queue. On recepton of the frst packet from an upstream node, downstream node assgns t to the approprate vrtual queue and the ntal queue weght s 1 for the RT class traffc and 2 for NRT class traffc. When a packet s scheduled to be transmtted, the node selects packet from the vrtual queue whch has lowest weght. On transmsson of each packet from the queue VQ, where,, ts weght s updated as Equaton (4). 108 _ _ Where, Pckt_sze s the sze of a packet n bytes and the value of Pckt_prorty s 1 for NRT traffc and 2 for RT traffc. Thus the scheduler serves RT traffc wth hgher prorty whle avods the chance of starvaton by usng Round Robn (RR) schedulng. 6. Performance Evaluaton To assess the performance of our proposed scheme, we have performed extensve smulaton usng ns-2 smulator (ns-2, 2008). 6.1 Smulaton Metrc and Parameters The smulaton parameters are set as follows. 100 nodes are randomly dstrbuted n a square regon of 1000 m 1000 m. For the smulaton setup, the transmsson range and carrer sense range are set to 250 m and 550 m, respectvely. The routng protocol used s AODV (Adhoc on Demand Dstance Vector Routng). The channel capacty s set to 11 Mbps and we assume that the queue sze of all nodes to be 50. The range of channel contenton wndow sze s [1, 63]. The sze of every packet s 64 Bytes. Number of sources transmttng packets, vares from 5 to 30 and the offered load vares from 5pps (packets/second) to 100 pps. The followng metrcs has been realzed to valdate the effcency of our proposed scheme. Throughput: The system throughput or aggregate throughput s the sum of the data rates that are delvered to all destnatons n a network. We measured the throughput usng the formula (total number of bytes receved by all destnatons / duraton of the flow). Number of collsons: The number of dropped packets due to collson. Number of buffer drops: The number of dropped packets due to buffer overflows. Delvery rato: Packet delvery rato s defned as the rato of data packet receved by the destnatons to those generated by the sources. End-to-end delay: End-to-end delay refers to the tme taken for a packet to be transmtted across a network (4)

11 from source to destnaton consstng of transmsson and propagaton delays plus varable queung and processng delay. Congeston degree: Congeston degree of a node s the rato of the mean packet servce tme over the mean packet nter-arrval tme over a predefned tme nterval n the node. Effcency: It s measured as the rato of number of hops traveled by each successful recepton of a packet at destnaton to the total number of transmssons requred for the packet n the entre path. The performance comparsons of the followng four mechansms are carred out. No Congeston Control (NoCC): Under ths scheme packets are transmtted wthout controllng transmsson rates at the sources and forwarders. Lnk Layer Adaptve Pacng (LLAP): LLAP (Frankln & Murthy, 2008) tres to reduce the contenton n the network by schedulng packets from a source wth an nterval of FHD (Four Hop Delay) so that they do not collde to each other n the path. In ths scheme, the downstream congested nodes packet forwardng delay s propagated to the source node by ntroducng addtonal delay to the transmsson of packets at all the ntermedate core nodes. Adaptve and Responsve Transport Protocol (AR-TP): It s a hop by hop congeston control mechansm explaned n Pace and Gungor (2007). In AR-TP, every ntermedate router s equpped wth one buffer for each neghbor and two dfferent thresholds are used n each buffer to montor the magntude of traffc load at the router. The rate control scheme of AR-TP protocol contans a back pressure mechansm to request the upstream node for a rate adaptaton and a forward threshold adaptaton mechansm whch asks the downstream to allow the congested node to ncrease the sendng rate to release congeston. Proposed Protocol: Our proposed technque employs congeston degree along wth the buffer occupancy level at a node to determne dfferent congeston states: no congeston, antcpated congeston and congeston. In antcpated congeston state the downstream node restrcts the avalable transmsson rate among the upstream nodes accordng to ther flow demands. In congeston state, the downstream node scales down the avalable rate among the upstream nodes accordng to congeston degree to mtgate congeston mmedately whle mantanng hgh network throughput. In each node two dfferent queues has been ntroduced for handlng real tme and non-real tme traffc. For any congeston state of a node, real tme traffc gets more share of the allocated rate than the non-real tme traffc. 6.2 Smulaton Metrc and Parameters Fgure 6 shows the throughput of the dfferent protocols for varyng network loads. For NoCC, as the source nodes ncrease the amount of the traffc they transmt, network throughput ncreases. After the network reaches saturaton, however, wthout use of congeston control the throughput s reduced due to collsons and contenton overhead. But, wth LLAP the reducton n throughput s less, as the sources adaptvely controls the offered load nto the network based on FHD of packets n the network, t guarantees that packets orgnatng from the same source are not drooped due to self contenton. AR-TP also acheves hgher throughput than NoCC, as the upstream nodes pump packets nto the network at a rate regulated by ther downstream nodes takng nto account the buffer state, whch reflects the congeston status of the network. Fgure 6. Throughput of dfferent protocols for varyng offered load 109

12 As seen n Fgure 6, the proposed protocol outperforms other protocols under comparson, snce t dynamcally adjusts data rate of the flows n a responsve manner due ts hop-by-hop nature and avods network congeston, whle maxmzng the network utlzaton effcency. Fgure 7. No. of collsons for varyng offered load Fgure 7 and Fgure 8 shows collson drop rate for varous protocols In case of NoCC, drop rate ncreases sharply wth the ncreased number of njected packets and data sources. Snce all nodes try to acqure the meda for transmsson, huge number of collson occurs. In LLAP, as all ntermedate nodes synchronze ther packet departure wth the delay accounted by ther mmedate downstream nodes; they are able to reduce useless packet transmsson retres that eventually reduce MAC collson. All ntermedate nodes n AR-TP protocol use a Backpressure mechansm to notfy ts mmedate downstream nodes the supported rate of the network whch prohbt the downstream nodes to capture the congested shared meda that eventually reduces number of collsons. But when a node tres to releve ts congested state, t uses a forward threshold polcy where t Fgure 8. No. of collsons for dfferent number of sources requests the mmedate upstream node to adjust the upstream nodes buffer threshold to gve a chance to ncrease the downstream nodes rate wthout consderng the neghborhood congeston phenomena. As a result when the neghborhood s already congested the rate ncrease also ncreases the collson rate. In the proposed method a node montors ts local congeston through ts own buffer occupancy level and the neghbors congeston status by the congeston degree parameter. So when a node notfes a reduced rate to ts mmedate upstream, t reflects the overall neghborhood congeston condton of the networks. Thus n a busy envronment, all nodes at the vcnty of a congested neghborhood, refran tself from attempts to capture the meda to avod collson. 110

13 Buffer drop rates of dfferent protocols are plotted n Fgure 9 and 10. Uncontrolled rate of transmsson mechansm n NoCC s the man reason of hgher packet drops. LLAP and AR-TP scheme experence lower packet drops than NoCC, snce they use rate control mechansm to control congeston. In proposed method, to mnmze buffer drop, buffer occupancy level s montored and compared wth a threshold level. Whenever a rate feedback s sent to an upstream, buffer use and the tme taken to serve a packet s taken nto consderaton; whch works as an ndcator of future hgh buffer occupancy level. Fgure 9. No. of packet drops due to buffer overflow for varyng offered load Fgure 10. No. of packet drops due to buffer overflow for dfferent number of sources Fgure 11. Packet delvery rato for varyng offered load 111

14 Fgure 12. Packet delvery rato for dfferent number of sources Accordng to Fgures 11 and 12, snce NoCC, experences huge amount of collson and buffer drops, the ultmate delvery rato s very poor. AR-TP also exhbts poor delvery rato as t sends explct rate feedback notfcaton as well as through forward threshold algorthm t nduces large number of collsons. Our proposed protocol can acheve around 90% delvery rato. Fgure 13 compares end-to-end delay for dfferent protocols under dverse offered loads. In NoCC, the ncrease n end-to-end delay s due to the fact that, packet queung delay and the contenton delay n the path ncreases wth ncreased data rates of the sources. In the case of LLAP, the ngress node pushes packets nto the path wth nterval of FHD between consecutve packets. So, the ncrease n end-to-end delay s due to the packet queung delay at the ngress node. The end-to-end delay saturates when the queue s full. AR-TP can reduce end-to-end delay sgnfcantly over NoCC and LLAP as t controls nodes transmsson rate accordng to network load. In the proposed method sources mantans the traffc njecton rate at a level so that the network works around the maxmum throughput zone. Here the ntermedate packet queung and processng delay s mnmzed whch ensures lower end-to-end delay. Fgure 13. End-to-end delay for varyng offered load Fgure 14 shows the delvery rato and effcency for dfferent retransmsson lmts. From the graphs n the fgure, t can easly be perceved that the hgher number of retransmssons ncreases the delvery rato but lowers the effcency. Our proposed protocol can acheve more than 90% delvery rato and 98% effcency wth retransmsson lmt

15 Fgure 14. Delvery rato and Effcency for dfferent retransmsson lmt Fgure 15 shows the delvery rato and congeston degree for dfferent packet loads. From the graph n the fgure, t s apparent that wth NoCC, under the hgher traffc load, ncreased packet servce tme ncreases congeston degree and also lowers delvery rato. When a node gets congested, the value of congeston degree promptly exceeds 1, at that pont nodes start droppng off packets and more load ncrease n node decreases the delvery rate drastcally. Our proposed method tres to lmt the packet arrval rate below the packet servce rate at a node, whch eventually allows a node to push the entre receved packet nto the network wthout droppng them and hence mantan the delvery rato. Fgure 15 shows that for the proposed method, the delvery rato s hgh as long the value of congeston degree s less than 1. Fgure 15. Delvery rato and CD for varous offered load Our proposed protocol uses a traffc classfer whch prortzes real tme traffc over non real tme traffc. To evaluate the performance of the proposed traffc classfer, we assumed that each node has dfferent traffc classes: RT and NRT. We evaluate the performance under WRR scheduler whch has been dscussed n Secton Snce WRR scheduler ensures that packets wth lower weghts receve more network bandwdth than those wth more weght n Fgure 16, we can observe that the proposed model, can assgn network bandwdth to each traffc class based on ts weght. The RT class has hgher throughput than NRT class. Snce NoCC protocol cannot dstngush between traffc classes, ts total throughput s plotted n Fgure

16 Fgure 16. Throughput of NRT and RT traffc class Fgure 17, shows the end-to-end packet delay for both NoCC and proposed protocol. The RT class has the hghest prorty, so the end-to-end delay for ths class s always lower than that of NRT class. The NoCC protocol uses a common buffer for all traffc classes, and hence cannot ensure low delay necessary for hgh prorty RT traffc class. Thus, NoCC has the hghest end-to-end delay. Fgure 17. End-to-end delay of NRT and RT traffc class 7. Conclusons and Future Work In ths paper, we proposed a novel load adaptve and traffc prorty senstve congeston control technque for WMN. Our target was to mantan hgher network throughput whle avodng congeston and grantng prortzed treatment for real tme traffc. The sgnfcant contrbutons to ths paper are: ) the use of three elementary n-node parameters: packet nput rate, packet servce rate and buffer occupancy, to reflect the current congeston state of a node and ts neghborhood, ) restrct the rate of upstreams proportonately accordng ther requrement and ) puttng emphass on schedulng delay bound traffc. Through ns-2 smulatons, we found that the employment of our proposed protocol greatly reduces the collson drops and avods buffer drops, whch n turn ncreases delvery rato and network throughput for both real tme and non real tme class traffc. Recent studes reveal that the use of multple rados at each node can mprove the bandwdth utlzaton and reduce neghborhood contenton on WMN. Assgnment of avalable channels to rado nterfaces at the vcnty of contendng neghborhood to mtgate congeston s a challengng ssue. We plan to extend our work n mult rado mult channel (MRMC) envronment where complex ner-flow and ntra-flow nterference among contendng lnks lmt the utlzaton of avalable network bandwdth. Based on the congeston and rate control 114

17 mechansm proposed n ths paper, our future work focuses on developng an ntellgent and dynamc channel assgnment strategy to mnmze congeston and maxmze trafc flow rate. References Akyldz, I. F., Wang, X., & Wang, W. (2005). Wreless mesh networks: a survey. Computer Networks, 47(4), Al Islam, A. A., & Raghunathan, V. (2011, March). End-to-end congeston control n wreless mesh networks usng a neural network. In Wreless Communcatons and Networkng Conference (WCNC), 2011 IEEE (pp ). IEEE. Alam, M. M., Islam, M. S., Hamd, M. A., Hong, C. S., & Lee, S. (2011). Congeston-aware far rate control n wreless mesh networks. Annals of Telecommuncatons-Annales des Telecommuncatons, 66(5-6), Chandran, K., Raghunathan, S., Venkatesan, S., & Prakash, R. (2001). A feedback-based scheme for mprovng tcp performance n ad hoc wreless networks. Personal Communcatons, IEEE 8(1), Chen, K., Nahrstedt, K., & Vadya, N. (2004). The utlty of explct rate-based flow control n moble ad hoc networks. In Wreless Communcatons and Networkng Conference, 2004, WCNC (vol. 3, pp ) IEEE. ElRakabawy, S. M., Klemm, A., & Lndemann, C. (2005). Tcp wth adaptve pacng for multhop wreless networks. In Proceedngs of the 6th ACM nternatonal symposum on Moble ad hoc networkng and computng (pp ). ElRakabawy, S. M., & Lndemann, C. (2009). Practcal rate-based congeston control for wreless mesh networks. In Kommunkaton n Vertelten Systemen (KVS) (pp. 3-15). Frankln, A. A., & Murthy, C. (2008). A lnk layer adaptve pacng scheme for mprovng throughput of transport protocols n wreless mesh networks. Computer Networks, 52(8), Holland, G., & Vadya, N. (2002). Analyss of tcp performance over moble ad hoc networks. Wreless Networks 8(2-3), Informaton Scences Insttute. (2008). ns-2 network smulator. Software package. Retreved from Jamshad, K., Shhada, B., Showal, A., & Levs, P. (2014). Deflatng Lnk Buffers n a Wreless Mesh Network. Ad Hoc Networks. Jamshad, K., Ward, P., Karsten, M., & Shhada, B. (2013). The effcacy of centralzed flow rate control n based wreless mesh networks. EURASIP Journal on Wreless Communcatons and Networkng, 2013(1), Km, D., Toh, C., & Cho, Y. (2001). Tcp-bus: Improvng tcp performance n wreless ad hoc networks. Journal of Communcatons and Networks, 3(2), Lu, C., Shen, F., & Sun, M. T. (2007). A unfed tcp enhancement for wreless mesh networks. In Parallel Processng Workshops, 2007 (pp ). ICPPW 2007 Lu, J., & Sngh, S. (2001). Atcp: Tcp for moble ad hoc networks. Selected Areas n Communcatons, IEEE Journal on, 19(7), Masr, A. E., Sardouk, A., Khoukh, L., & Gat, D. (2012). An effcent and far congeston control protocol for IEEE based Wreless Mesh Networks. In Personal Indoor and Moble Rado Communcatons (PIMRC), 2012 IEEE 23rd Internatonal Symposum on (pp ). IEEE. Pace, P., Natalzo, E., & Gungor, V. C. (2007). An adaptve and responsve transport protocol for wreless mesh networks. In Proceedngs of IEEE ICC. Rangwala, S., Jndal, A., Jang, K.Y., Psouns, K., & Govndan, R. (2008). Understandng congeston control n mult-hop wreless mesh networks. In Proceedngs of the 14th ACM nternatonal conference on Moble computng and networkng (pp ). Ranwala, A., Sharma, S., De, P., Krshnan, R., & Chueh, T. C. (2007). Evaluaton of a stateful transport 115