Journal of Network and Computer Applications

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1 Journal of Network and Computer Applcatons 37 (2014) Contents lsts avalable at ScenceDrect Journal of Network and Computer Applcatons journal homepage: HOCA: Healthcare Aware Optmzed Congeston Avodance and control protocol for wreless sensor networks Abbas Al Rezaee a,n, Mohammad Hossen Yaghmaee b, Amr Masoud Rahman a, Amr Hossen Mohajerzadeh b a Department of Computer Engneerng, Scence and Research Branch, Islamc Azad Unversty, Tehran, Iran b Department of Computer Engneerng, Ferdows Unversty of Mashhad, Mashhad, Iran artcle nfo Artcle hstory: Receved 11 May 2012 Receved n revsed form 17 December 2012 Accepted 23 February 2013 Avalable onlne 6 March 2013 Keywords: Wreless sensor networks Congeston control Healthcare Routng protocol Optmzaton abstract Wreless sensor networks consst of a large number of small, low-power sensors that communcate through wreless lnks. Wreless sensor networks for healthcare have emerged n recent years as a result of the need to collect data about patents physcal, physologcal, and vtal sgns n the spaces rangng from personal to hosptal and avalablty of the low cost sensors that enables ths data collecton. One of the major challenges n these networks s to mtgate congeston. In healthcare applcatons, such as medcal emergences or montorng vtal sgns of patents, because of the mportance and crtcalty of transmtted data, t s essental to avod congeston as much as possble (and n cases when congeston avodance s not possble, to control the congeston). In ths paper, a data centrc congeston management protocol usng AQM (Actve Queue Managements) s proposed for healthcare applcatons wth respect to the nherent characterstcs of these applcatons. Ths study deals wth end to end delay, energy consumpton, lfetme and farness. The proposed protocol whch s called HOCA avods congeston n the frst step (routng phase) usng multpath and QoS (Qualty of Servce) aware routng. And n cases where congeston cannot be avoded, t wll be mtgated va an optmzed congeston control algorthm. The effcency of HOCA was evaluated usng the OPNET smulator. Smulaton results ndcated that HOCA was able to acheve ts goals. & 2013 Elsever Ltd. All rghts reserved. 1. Introducton Wreless Sensor Networks (WSNs) have been wdely appled n dfferent areas such as healthcare montorng (Akyldz et al., 2002; Armjo et al., 2007; Cao et al., 2005). They have nherent characterstcs unlke tradtonal wreless networks. Sensor nodes have scarce resources for computaton, storage, communcaton bandwdth, and, most mportantly, energy supply. So far, extensve studes have been done on dfferent layers of WSNs (Akkaya and Youns, 2005; Sohraby and Wang, 2006). The event-drven nature of WSNs leads to unpredctable network load, especally n healthcare applcatons. Typcally, WSNs carry low traffc load when there are no specal events. But the occurrence of mportant events may cause burst traffcs whch lead to congeston n the network. Transport protocols control congeston n end to end or cross layer manner. n Correspondng author. Tel.: þ E-mal addresses: aa.rezaee@srbau.ac.r (A.A. Rezaee), hyaghmae@ferdows.um.ac.r (M.H. Yaghmaee), Rahman@srbau.ac.r (A.M. Rahman), ah.mohajerzadeh@stu-mal.um.ac.r (A.H. Mohajerzadeh). Nowadays, Healthcare aware Wreless Sensor Networks (HWSNs) have receved a great attenton due to the propertes of WSNs such as relablty, nteroperablty, effcency, wearablty, low-power consumpton and nexpensveness. One of the applcatons of WSNs s remote montorng of patents by doctors and nurses whch elmnates the need to be physcally present n the patent stes (Cao et al., 2006). Fgure 1 shows dfferent sensors attached to patents beng capable of sensng patent nformaton whch can be senstve (vtal sgns, such as the heart rate and breathng condton) or non-senstve (motonal sgns, such as legs sensors). The receved nformaton can be transmtted to the control center wth the help of neghborng nodes. Senstve nformaton needs low delay and low packet loss whle non-senstve data can tolerate more delay and more packet loss. We restrcted ourselves to healthcare applcatons whch requre statonary sensor nodes (they do not change ther locatons for at least a few hours). In medcal emergences, t s qute lkely that the sensors placed n the dfferent patents sense and transmt vtal patent nformaton very frequently and smultaneously. Ths leads to ncreased lkelhood of network congeston n such applcatons. Congeston n WSNs leads to droppng of packets at the nodes, ncreased consumpton of the lmted energy n the nodes and /$ - see front matter & 2013 Elsever Ltd. All rghts reserved.

2 A.A. Rezaee et al. / Journal of Network and Computer Applcatons 37 (2014) Fg. 2. Causes of congeston n wreless sensor networks. Fg. 1. Dfferent sensors on patent s body. reducton of the throughput of the network. In lfe-crtcal applcatons nvolvng large numbers of patents, congeston s extremely undesrable and may lead to the death of a patent. However, tmely arrval of the packets at ther destnatons ensures the safety and survval of the patents. Obvously, complete elmnaton of congeston s unlkely. But, t s possble to sgnfcantly reduce the effects of congeston,.e., sgnfcantly decreasng the number of packets that get dropped due to congeston, the large amount of unwanted consumpton of the lmted energy at the sensors and ncreasng the number of packets that get successfully delvered wth respect to the number of packets whch are sent from the dfferent nodes. We addressed the problem of congeston by proposng a new approach to avod t. In ths approach, congeston wll be avoded by dstrbutng packets through multple routes and f congeston stll occurs, we run an optmzed congeston control algorthm. Congeston control algorthms are classfed as source based or network based. Source based algorthms are deployed at the end host where the transport protocol s responsble for detectng congeston n the network. Network based algorthms, on the other hand, are mplemented n the ntermedate network devces, especally routers. Based on the degree of congeston detected n the network, source based algorthms adapt the rate at whch the applcaton s sendng traffc. Ths mechansm, more popularly known as end to end congeston control s employed by transport protocols such as the Transmsson Control Protocol (TCP). In network based algorthms, the ntermedate network equpments are responsble for detectng oncomng as well as subsstng congeston and provde feedback to the sender for ndcatng the stuaton. Source based algorthms work well for traffc that s responsve to congeston e.g. TCP traffc. However non-senstve traffc e.g. User Datagram Protocol (UDP) traffc may stll cause congeston due to ts greedy behavor. Thus, the need arses for network based congeston avodance and control mechansms. There are dfferent factors nvolved n the desgn of transport protocols for sensor networks: congeston control and relable data delvery. Snce most data move from sensor nodes to the snk, congeston s lkely to occur around the snk. In order to ncrease the speed of the connecton process, mprove effcency and decrease transmsson delay, sensor network transport protocols should facltate the process of the ntal connecton or use protocols wthout connecton. Most applcatons n wreless networks are passve, meanng that the network s montored nactvely and wats for an event before sendng data. When an event occurs, these applcatons may have quanttatve packets to send. Transport control protocols should treat dfferent types of sensor network nodes farly. If possble, nter-layer optmzaton should be consdered n the desgn of the transport protocol. For example, f a routng algorthm nforms the transport protocol about route falure, the protocol can nfer that the packet loss s not caused by congeston, but due to route falure. In such a condton, the sender can mantan ts present rate. Bascally, two factor causes congeston n sensor networks (see Fg. 2). The frst s when the packet arrval rate s hgher than packet servce rate whch occurs mostly n nodes closer to the snk. The second s the performance at the lnk level ncludng competton, collson and bt error. Ths type of congeston occurs on the lnk. Congeston control s mportant n tradtonal TCP networks as well as wreless sensor networks. QTCP (actve Queue management support TCP) (Farzaneh et al., 2011) s one of the latest work for controllng congeston n tradtonal TCP networks wth the help of AQM (actve queue management). Because of the nherent nature and the man goal of WSN to transmt data n an energy effcent way tradtonal congeston control protocols cannot drectly used n wreless sensor network (Abbas et al., 2008). So there was a need to desgn transport protocols for wreless sensor network that could deal wth three mechansms n case of congeston: congeston detecton, congeston notfcaton, and rate adjustment. There are dfferent congeston detecton methods that are employed n wreless sensor networks. One common mechansm s the use of queue length (Wan et al., 2003; Balakrshnan et al., 2004; Adjeroh and Yaghmaee, 2008), packet servce tme (Bajcsy and Ee, 2004) or the rato between servce tme and the tme between packets n an ntermedate node (Daneshmand et al., 2007). For sensor networks usng MAC layer protocols such as CSMA, channel load can also be used as a tool for congeston detecton (Wan et al., 2003). When congeston s detected, transport protocols transfer congeston nformaton from the congested nodes to other nodes on the route to the snk or the source nodes that have had a part n detectng congeston. Congeston nformaton can be as small as a bnary CN (Congeston Notfcaton) bt (Wan et al., 2003; Balakrshnan et al., 2004; Akyldz et al., 2003) or contan more nformaton such as permtted data rate (Bajcsy and Ee, 2004) or congeston degree as n Daneshmand et al. (2007). Sensor nodes can adjust ther sendng rate after recevng congeston notfcaton. If a bt CN s

3 218 A.A. Rezaee et al. / Journal of Network and Computer Applcatons 37 (2014) receved, the AIMD (Addtve Increase and Multplcatve Decrease) method or other types of t are usually appled. However, f more comprehensve congeston nformaton s avalable, rate adjustment can be done more accurately (Bajcsy and Ee, 2004; Daneshmand et al., 2007). Today, dfferent algorthms presented n the feld of WSN, are more sutable for some applcatons wth regard to ther output parameters and dagrams. In most of congeston control methods, the rate of packet sendng s reduced mmedately after congeston occurs and the lost senstve packets are tred to be retreved. Ths needs to an extra buffer n the prevous nodes n order to keep the packets n t untl recevng acknowledgment for them makng these methods costly. Also, ths makes senstve traffc streams to reduce ther sendng rate. However, t s favorable that the sendng rate for senstve traffc streams sn t greatly reduced. So, n the proposed protocol, we have developed a congeston avodance phase n whch several paths are made prmarly and the nearest one s allocated to senstve traffc. Havng multple paths makes the traffc streams be dstrbuted among them farly based on ther senstveness. Ths leads to less probablty of packet loss especally for senstve packets and hence less probablty of senstve packet rate reducton. The mentoned problem s more crtcal for the senstve applcatons lke health care n whch the rate of senstve data packets hasn t to be decreased. Also, we try to allocate an approprate bandwdth for senstve traffc along wth usng (PQ) prorty queue approach n every node s output whle servcng. Ths means that the more senstve a packet s the sooner t s servced. Totally, all the aforementoned polces beng used n our proposed protocol, results n reducton of packet loss rate for senstve data packets and consequently reduced delay for them untl reachng destnaton. In ths protocol, through a congeston control problem, some QoS parameters lke delay, packet loss and network lfetme are compared wth respect to the other methods. In the applcatons lke healthcare, these parameters are very consderable because droppng of a senstve packet may leads n a patent death. Also, n such applcaton, delay n packet arrval wll cause later decson and hence harmng the patents. Ths s more notceable n patents bedrdden n ICU. If the battery of a sensor attached to a bedrdden patent n ICU s dscharged earler than normal just when there s a fluctuaton n hs vtal sgns lke blood pressure or hear beat, the patent s lfe can face a serous rsk. The proposed protocol s composed of two man parts, routng and congeston control. Proposed routng protocol s a data centrc protocol whch composed of 4 dfferent phase. The phases are dscussed n Secton 3 n detals. We have evaluated the requrements of the healthcare applcatons, and consder them n desgnng proposed protocol. Forth phase of proposed routng protocol s data transmsson. Smlar to other networks, congeston may occur n network nodes. We have also proposed a congeston control mechansm whch s dscussed n Secton As ts man job, congeston control mechansm adjusts nodes sendng rate (especally source nodes) n order to manage congeston n ntermedate nodes. In Secton 4, smulaton results have been presented. And fnally n Secton 5 we conclude the paper. 2. Related works Dfferent protocols have been proposed for congeston control. These protocols are dfferent n terms of congeston detecton, congeston notfcaton, and rate adjustment mechansms. In Fuson (Balakrshnan et al., 2004) congeston s detected by usng queue length and controlled n a stop-and-start non smooth manner so that when congeston s detected and notfed, neghborng nodes stop forwardng packets to the congested node mmedately. In CODA (Congeston Detecton and Avodance) (Wan et al., 2003) protocol congeston s detected also by usng queue length at the ntermedate nodes. CODA protocol uses a combnaton of the present and past channel load and the level of buffer load n order to detect congeston n each recever accurately and at low costs. It uses the selectve backpressure method for congeston notfcaton and the mult-source regulaton for rate adjustment. CODA also controls the rate of flow of packets based on the AIMD algorthm. CCF (Congeston control and farness) protocol (Bajcsy and Ee, 2004) detects congeston based on packet servce tme. The CCF method carres out upstream congeston control usng a scalable and dstrbuted algorthm that ensures the far delvery of the packets to the central staton as well as removng congeston. CCF formulates congeston control and determnes the number of downstream nodes, the average sendng rate of the packets and the producton rate n each sensor. PCCP (Prorty-based Congeston Control protocol) (Daneshmand et al., 2007) s a prorty based upstream congeston control protocol and measures a congeston degree as the rato between packet arrvals and packet servce tme. PCCP also uses rate adjustment algorthm unlke that of the AIMD technque. It supports farness n weghtng sensor nodes. PCCP uses dfferent degrees of prorty ndexes, so a sensor node wth a hgher prorty ndex uses more bandwdth and njects more traffc. PCCP allows the applcaton layer to cancel the prorty ndex n a specal area n each senor node. Ths aspect can be useful for a large number of sensor network applcatons. There are lmtatons for PCCP whch nclude the lack of packet recovery. QCCP-PS (Queue based Congeston Control Protocol wth Prorty Support) (Adjeroh and Yaghmaee, 2008) s a queue based Congeston Control Protocol wth Prorty Support whch uses the queue length as a congeston degree ndcator. It controls the congeston wth the packet prorty based on the node prorty for a WSN. QCCP-PS also mproves the PCCP by controllng the queue more fnely but t does not have any mechansm for handlng prortzed heterogeneous traffc n the network. The sendng rate of each traffc source n the QCCP-PS s ncreased or decreased based on ts congeston degree and ts prorty ndex. The rate adjustment for each traffc source s based on ts prorty ndex as well as ts current congeston degree. ECODA (Enhanced congeston detecton and avodance) (Tao and Yu, 2010) uses dual buffer thresholds and weghted buffer dfference for congeston detecton. Ths method s dfferent from tradtonal sngle buffer threshold methods (Wan et al., 2003; Bajcsy and Ee, 2004; Daneshmand et al., 2007). It can dfferentate congeston level and dealt wth them correspondngly. ECODA s composed of three mechansms: 1) Usng dual buffer thresholds and weghted buffer dfference for congeston detecton; 2) Flexble Queue Scheduler based on packet prorty; 3) A bottleneck-node-based source sendng rate control scheme n case of persstent congeston. ECODA also adopts hop-by-hop congeston control scheme for transent congeston. FACC (A Farness-Aware Congeston Control scheme) (Huang et al., 2009) s a rate-based farness aware congeston control protocol that dvdes all ntermedate sensor nodes nto near-source and nearsnk nodes. Ths protocol detects congeston accordng to packet loss rate at the snk node. Every tme a packet s lost n near-snk nodes, they send a WM (Warnng Message) to the near-source nodes. When the near-source nodes receve WM, they send a CM (Control Message) to the source nodes to notfy t of the updated sendng rate. These messages cause overhead n the network and f any one of them gets lost because of path break, t may leads to a problem n congeston notfcaton as well as rate adjustment LACAS (Msra et al., 2009) s a Learnng Automata-Based Congeston Avodance Scheme for Healthcare Wreless Sensor Networks whch s more effectve n dealng wth congeston

4 A.A. Rezaee et al. / Journal of Network and Computer Applcatons 37 (2014) problems n healthcare WSNs. The process of learnng n ths work s a learnng loop consstng of the RE (Random Envronment), and the LA (Learnng Automata). The LA tres to learn the optmal acton (send rate) offered by the RE. An mportant feature of LACAS s that t ntellgently learns from the past and mproves ts performance sgnfcantly as tme progresses. One of the lmtatons of ths work s that ts envronment offers only bnary responses for any acton selected by the automaton. Table 1 presents the characterstcs of some of popular congeston control protocols. In ESRT (Event-to-Snk Relable Transport) (Akyldz et al., 2003), the node montors the congeston notfcaton bt whch s located n the packet header and obtans a common rate for all sensors so that no packet s lost. Ths method supports farness but all sensors cannot adapt to the worst rate n the congeston stuaton. In ths method, a new congeston control pattern capable of far allocaton of bandwdth s proposed. Of course, we expect that each flow should have a far share of the bandwdth based on ts producton rate. In sensor networks, both the number of actve flows and the accessble bandwdth change wth tme. Therefore, we cannot consder a fxed rate for each flow. In order to acheve a far sharng of the bandwdth, the followng method has been proposed. used for healthcare remote montorng applcatons whose networks contan data wth dfferent levels of mportance and dfferent prortes for dfferent patents. The proposed protocol acts as a cross layer. As mentoned before, n HOCA the dutes of transport layers and the network are carred out smultaneously. Frst, the snk (the telemedcne center) sends ts requrements (requred nformaton) to network nodes (sensors connected to the patent s body). In the meantme, any network node observng the event specfed by the snk, wll nform the snk wth an event report (patent s condton) usng the phase 2 procedure. In the second phase, the ntal routng tables are formed. These tables are then used n the thrd phase where dfferent routes are chosen n the fnal routng tables. The fnal tables are produced n the thrd phase dependng on the prorty of the transferred data. The fourth phase s the data forwardng phase n whch the data recorded from the events observed by nodes are gven to the snk. A large volume of data s moved n ths phase; therefore a procedure for congeston control s needed. In HOCA, an adaptve procedure has been proposed for controllng source sendng rates. Ths procedure s also carred out n the fourth phase n case of congeston. Generally Fg. 3a c shows the proposed protocol structure. 3. The proposed protocol The proposed protocol has been desgned for congeston management n wreless sensor networks for healthcare applcatons. The man objectve of the proposed protocol s to avod, or f not possble, control congeston n wreless sensor networks. Smlar to other data centrc protocols such as REEP (Msra et al., 2008), Drected dffuson (Jang, 2007) and TPGF (Two-Phase geographc Greedy Forwardng) (Shu et al., 2010) HOCA has been developed n dfferent phases. All these protocols use dfferent phases to perform dfferent crucal tasks. TPGF (Shu et al., 2010) also uses multpath transmsson. And they are all developed for wreless sensor networks. HOCA consders two man parameters, energy and delay (besdes lfetme and farness). In all routng protocols whch are developed for WSN, energy should be consdered as a goal parameter. Delay s the man goal parameter for healthcare applcatons. HOCA consders two types of traffcs: senstve and non-senstve. Senstve traffcs are desgned to transfer hgh prorty data (they need low delay) and nonsenstve traffc s desgned to transfer normal traffc. The proposed protocol works n the followng phase: 1) request dssemnaton whch s performed by the snk, 2) event occurrence report whch s performed usng packets that are forwarded from sensors located on patents body to the snk, 3) route establshment, 4) data forwardng and rate adjustment n case of congeston occurrence. In the desgn of HOCA, congeston control as the man objectve affects other objectves. Routng has been consdered as a part of the general objectve. In ths protocol, data are sent wth dfferent prortes. Therefore t can be 3.1. Request dssemnaton phase Ths s the frst phase n carryng out the routng protocol. In ths phase, nformaton requred by the snk node (medcal center) such as patents vtal sgns should be sent to all network nodes. In other words, snk requrements are requested and dstrbuted throughout the network based on dfferent algorthms presented for dstrbutng data n wreless sensor networks. However, the type of data s very mportant. In some stuatons, parameters may nclude hghly senstve nformaton such as heartbeat or blood sugar level (for some patents such as those wth dabetes). Ths phase s started by the snk and the packets that are used for the mplementaton of ths phase are the same structure. The proposed protocol uses the MLAF (Multmeda locaton aded Floodng) (Mohajerzadeh et al., 2010) algorthm n ths phase. MLAF algorthm uses new methods to optmze energy consumpton. Also, ths algorthm supports dstrbuton of data wth dfferent prortes. In applcatons where data dstrbuton s carred out through the whole network, ths method s not very effectve. But, the opton of data dstrbuton wth dfferent prortes s very mportant for medcal montorng applcatons n whch data dstrbuton depends on the poston of the target nodes (patents). The followng consderatons should be taken nto account n the structure of the packets to be transferred. The prorty: n wreless sensor networks for medcal montorng applcatons, we may have dfferent types of traffc wth dfferent Table 1 Congeston control protocols for wreless sensor networks. Protocol Congeston detecton Congeston notfcaton Rate adjustment Fuson (Balakrshnan et al., 2004) Queue length Implct Hop by hop rate adjustment CODA (Wan et al., 2003) Queue length and channel state Explct Rate adjustment smlar to AIMD CCF (Bajcsy and Ee, 2004) Packet servce tme Implct Hop by hop rate adjustment PCCP (Daneshmand et al., 2007) Packet nterval tme and packet servce tme Implct Hop by hop rate adjustment QCCP-PS (Adjeroh and Yaghmaee, 2008) Queue length Implct Hop by hop rate adjustment ECODA (Tao and Yu, 2010) Dual buffer thresholds and weghted buffer dfference Implct Delay dependent FACC (Huang et al., 2009) Packet Drop At the Snk node Explct Hop by hop rate adjustment

5 220 A.A. Rezaee et al. / Journal of Network and Computer Applcatons 37 (2014) Fg. 3. (a) Flowchart of Phase 1 and Phase 2 n congeston avodance part. (b) Flowchart of Phase 3 and Phase 4 n congeston avodance part. (c) Flowchart of Phase 4 congeston control part. characterstcs. Therefore, whle transferrng a request, the type of patent and ts prorty should be specfed. Tme: we may have several requests for a certan patent n dfferent ponts n tme. The tme of each request should be specfed so that the nodes can determne the order of transmsson for dfferent requests. However, requests for some patents have an expry perod. After the end of the perod the request s not consdered anymore.

6 A.A. Rezaee et al. / Journal of Network and Computer Applcatons 37 (2014) Characterstcs of the request: each request should contan the dutes of the sensors connected to the patent s body. The specfcaton of how these requests are answered should also exst n the nodes. The above condtons are frst met and then the packets are dstrbuted n the network. For example, n a medcal montorng applcaton the above condtons for a request (patent status report request) are defned n the followng manner, respectvely: Usually, n medcal montorng applcatons data related to vtal sgns have hgh prorty; therefore ths type of request s assgned a hgh prorty. Also, we can consder other types of traffcs for data related to patent movements whch have a lower prorty. Request dssemnaton tme s set as the present tme. It s specfed n the request that each sensor on the patent s body should report vtal sgns out of the normal range to the snk wth hgh senstvty. The normal range s determned by the expert Event report phase After the request dssemnaton phase, f a sensor senses an event based on ts duty, t wll report the sgn to the snk accordng to the specfcatons. The report must have the requred characterstcs so that the snk can show the proper reacton. In ths phase, the nformaton related to the occurrng event s sent to the snk, however basc data related to the event are sent n the data forwardng phase. Moreover, the prelmnares of packet routng are also determned n ths phase. For ths purpose, the patent node creates a packet contanng the nformaton related to the sensed event and sends t to all ts neghbors. Snce nodes (patents) are aware of ther own postons the packets are sent to the neghbors that are closer to the snk than the sender. The routng tables requred for the routng of node data n the route from the packet to the snk wll be provded. And the fnal routng wll be carred out n the route formng phase. After creatng the packet (whch we call phase 2 packet), f the nodes are aware of ther postons ths wll lead to lower energy consumpton for the protocol. However snce we need to locate all the nodes t cannot be appled everywhere. It s worth notng that n applcatons where the request should only be sent to part of the network, nodes are aware of ther postons. After recevng the packet from phase 2, each node creates a record labeled phase 2 table n a routng table. The prorty of the packet (compared to the prorty of the traffc and the event n queston), the source node, the sender, the length of the covered route and the number of covered hops are kept n ths record. In the proposed protocol, each node has an ID that s placed n all outgong packets. The length of the covered route s obtaned from the length of the route from the source of the packet to the current node. After creatng the record, the node sends the packet back to ts neghbors. Ths procedure s repeated untl the packet reaches the snk. Note that from any source, there could be more than one record n each node s phase 2 table. The reason for ths s that phase 2 packets may arrve at a node from dfferent routes. Only packets wth dentcal felds are gnored. At the end of phase 2, each node has a routng table called phase 2, table whch s used for fnal routng n phase 3. Records n phase 2 routng table determne the possble routes between the desred node and the source node sensng the event. Appendx A presents the pseudo code related to the phase 2 mechansm Route establshment phase After the arrval of phase 2 packets at the snk, a type 3 confrmaton packet s sent to the source node by the snk whch notfes the source node to send ts data to the snk for processng. Then, sensors from one or more patent(s) may send messages. In ths stage, the snk chooses one or several nodes for the fnal transfer of data based on the nformaton sent from source nodes. In phase 2 packets, each node specfes the level of ts mportance. For example, the heart beat sensor or the knesthetc sensor connected to the patent s foot sends a message to the center and specfes the level of mportance. The snk chooses the source node for the patent s report based on the specfed level of mportance. Followng the selecton of the source, phase 3 packets are sent. As the phase 3 packet moves along the route, t creates a phase 3 routng table. Phase 3 routng table s the fnal routng table for routng the data sent from the source. The transfer confrmaton depends on the prorty of the sensed event. Two types of confrmatons are consdered, hgh prorty confrmaton (senstve traffc) and low prorty confrmaton (non-senstve traffc). The snk checks the phase 2 routng table n order to send a hgh prorty confrmaton. The frst record s chosen for sendng confrmaton. Phase 2 packets are then arranged chronologcally n the phase 2 routng. Upon recevng a type 2 packet, the nodes place t n the frst record. In fact, the number assgned to the packet record n the phase 2 routng table determnes ther tme sequence. Snce tme s very mportant nsenstve applcatons, the frst record n the phase 2 routng table whch s chronologcally the frst created record s chosen. However, n choosng records, the source node n the record s always consdered. Moreover, only records n whch the source node s the one chosen by the snk wll be consdered. Each node forms two tables n phase 3: Phase 3 routng table wth hgh prorty and phase 3 routng table wth low prorty. Durng ths phase, two tables are completed. Routng table of each node mantans the best routes to the snk through ts neghbors whch are closer to the snk. Consderng the maxmum number of neghbors for each node n WSN, the routng table wll be practcal and small. When a node receves a phase 3 packet wth hgh prorty, t creates a hgh prorty record for the packet n the phase 3 routng table. Ths table conssts of the followng components: sender (the source node of the recevng phase 3 packet wth hgh prorty), recever (the destnaton node for the phase 3 packet wth hgh prorty), source node (the node sensng the event whch s the fnal destnaton of the phase 3 packet) and type of applcaton (ths component wll be used n networks desgned for multple applcatons). Based on what has been mentoned so far, each node chooses the frst record from the phase 2 routng table as the next hop for the hgh prorty phase 3 packets. Ths procedure wll contnue untl the packet reaches the source. In fact, at the end of phase 3, a record s placed n the senstve phase 3 routng table for each source. What has so far been mentoned n Secton 3.3 s related to hgh prorty traffc. We wll go on to explan the creaton of low prorty phase 3 routng table. From among the records n the phase 2 routng table, the snk consders the records chosen n relaton to the source. For each of these records, the probablty RSP s computed usng the followng equaton: TD RSP ¼ =HC P for all j A Selected Records ðtd ð1þ =HC Þ where TD s the route length and HC s the number of hops for the th record route. RSP s the route select probablty of choosng the record as the next hop for the low prorty phase 3 packets.

7 222 A.A. Rezaee et al. / Journal of Network and Computer Applcatons 37 (2014) After determnng RSP s for all the records wth the ntended source, two records are chosen based on probablty. Then, the low prorty phase 3 packet s sent to these records. Dfferent routes are chosen so that farness s observed n energy consumpton of the network nodes. Each node receves a phase 3 packet wth low prorty and records t n ts routng table. Then, through a procedure smlar to that of the snk, the next two neghborng hop neghbors are chosen and the phase 3 packet s sent to them. All the characterstcs are recorded n non-senstve phase 3 routng records. Appendx B presents the pseudo code related to the phase 3 mechansm Data forwardng phase Towards the end of phase 3, senstve and non-senstve phase 3 routng tables are created. Each node wll contan asenstve phase 3 routng table and anon-senstve phase 3 routng table. Ths provdes multpath routng for our proposed protocol and can dstrbute packets through more than one path. Dependng on the type of the sensed event, the source node (the node sensng the event) can send ts data to the snk after recevng senstve traffc from phase 3. As mentoned before, all nodes ncludng the source node have two types of routng table. Senstve phase 3 routng table s used for sendng senstve data and non-senstve phase 3 routng table s used for sendng nonsenstve data. In the senstve phase 3 routng table, there s only one record toward the snk for each source. Each node receves senstve traffc from the node n queston and uses the traffc to send the record to the next hop. However, n each non-senstve phase 3 routng table, there wll be more than one record for each source n the table. Each record has a probablty RSP based on whch the next hop s chosen. The greater the RSP n the record, the more lkely t wll be chosen. Fnally, a record wll be chosen as the next hop and data are sent to ths record. Appendx C presents the pseudo-code related to the phase 4 mechansm Congeston control mechansm n ntermedate nodes Our goal s to provde routng and congeston management n WSN s for healthcare applcatons. Congeston management comprses two phases: Congeston avodance and congeston control. Congeston avodance s mplemented by dstrbuted routng algorthm (Secton 3). AQM schemes are one of the mportant mechansms that provde qualty of servce and prevent congeston n IP networks that perform specal operatons n our protocol to acheve better performance for end flows. Wth these mechansms, congeston s controlled and network degradaton s avoded (Borden and Frou, 2000). Fgure 4 depcts the queung model on an ntermedate node. In ths fgure a classfer has been provsoned n network layer. The purpose of a classfer s to classfy dfferent types of data and route them n ther correspondng queues. Fg. 4. The structure of an ntermedate sensor node. The type of data s located n the packet header. We defne three type of traffc; hgh prorty, low prorty and control packets. Senstve traffcs are sent to class 1, non-senstve traffc sent to class 2 and control packets are sent to class 3. In our proposed protocol the CBWFQ (Class Based Weghted Far Queue) scheduler (Fscher et al., 2008) s used wth the addton of a PQ (Prorty Queue). The use of PQ ensures low latency and more relablty for senstve traffcs. PQ allows senstve traffcs to be dequeued and sent frst. Whle there s a class 1 packet n the queue, the scheduler sends class 1 packets out of queue. In order to provde farness between class 1 and other classes, only 20 percent of network bandwdth s assgned to class 1 traffcs, so usng PQ scheduler does not cause unfarness. Indeed fewer queung delays for class 1 traffcs results from PQ scheduler whch use for senstve traffcs Proposed AQM. AQM (Actve queue management) has been proposed as a soluton of preventng packet loss due to buffer overflow. In a network, f the queue length sn t sutably managed, the senders wll contnue sendng the packets at the ntal rate leadng to packet loss. Therefore, usng AQM methods, the proposed protocol reduces sendng rate of packet senders before exceedng a determned threshold n order to prevent the packets from beng dropped. In a senstve applcaton lke health care, packet loss s a very mportant problem whch has to be reduced as much as possble. P s the packet loss probablty whch s determned by actve queue management mechansm. HOCA uses a flexble procedure for queue management. The proposed procedure shares the queue n each node for the flows passng the node. However, the boundares between queues are not fxed; meanng that f one of the actve flows has free space n ts queue, other flows facng a lack of space can use ths free space on certan condtons. In other words, queues n Fg. 3 are separated vrtually wth flexble boundares. The probablty of the drop (P ) of a packet n th queue s determned usng the followng equaton: P ¼ b 1 :dqv b 2 Uð1 ð Xn j ¼ 1 q j =QLÞÞþP pr When a packet s receved by the node, drop probablty P s computed for the packet. Packet wll be queued or dropped, based on P value. In fact, hgher probabltes of loss for a flow show that the correspondng queue s n crtcal status wth respect to the congeston. Therefore, the weght of P has been used drectly n determnng the sendng rate and the degree of congeston n each node. P pr s an ntal value for P whch s determned usng Eq. (3). q j presents the number of packets stored n jth vrtual queue. dqv shows the level of varaton n the length of the th vrtual queue. The value of dqv can be postve or negatve. dqv s multpled by coeffcent b 1 as presented n Eq. (4).Ifdqv s postve, t wll reman postve after multplyng by b 1 and wll fnally cause an ncrease n P. It means that f the varaton n theflowqueuelengthspostve (the queue sze s prolonged) the packet loss probablty and the probablty of congeston are ncreased. b 2 specfes the flexblty of the flow queues. The expresson P n j ¼ 1 q j specfes the total used space n the node queue. Dvdng the total by QL (total space n the node queue) gves us the percentage of used space n the node queue. Multplyng ths value by b 2 wll result n a number whch reduces the value of P. In other words, the greater the free space n the queue the lesser the packet loss probablty of the flows. However, the effect of ths value depends on the b 2 parameter. b 1 and b 2 are determned based on node prorty by the user: ( P pr ¼ 0 f : q!2uql=3un n 2 ð3þ :ðq =QLÞ 2 f : q Z2UQL=3Un ð2þ

8 A.A. Rezaee et al. / Journal of Network and Computer Applcatons 37 (2014) dqv ¼ qnew q old QL=n ð4þ The parameters n Eqs. (2) (4) are determned n a perodcal manner. Therefore, n Eq. (4) the value of q old s the queue length n the th flow n the precedng calculaton and the value of q new s the queue length n the th flow n the present calculaton. Generally, n all the equatons q shows the queue length n the th flow. Parameter n s the number of node s neghbors Proposed rate adjustment. Congeston control, as mentoned n Secton 1, conssts of two parts: (1) Congeston notfcaton and (2) rate adjustment. These procedures are done nterestedly n a hop by hop manner, from the congested node to the source node wth rate adjustng packets ncludng chldren rate portons. As dscussed n Secton , AQM consders arrval rate (q new q old )andqueue length (q) n order to determne P.WeuseP as congeston ndcator. Followng usng proposed Optmzaton problem (Eq. (5)) the upstream neghbor s rate adjustment s performed. Snce data are transferred n the data forwardng phase, t s lkely to have network congeston n ths phase. HOCA controls congeston by controllng the sender s data sendng rate. However, congeston wll also be prevented as far as possble, usng multple routng. The mechansm of congeston control comprses two parts: actve queue mechansm n ntermedate nodes and sender rate control mechansm. Actve queue mechansm manages queues as well as detectng the level of congeston. The followng equatons show the optmzaton problem whch s used n order to control the forwardng rate. " # Mn F ¼ a Xn 1 y UP 1þy þð1 aþy c ð5:1þ ¼ 1 y 1 þy 2 þþy n þy c ¼ 1 8,0ry r1 0ry c r1 0rar1 ð5:2þ Fg. 5. The model used n ntermedate nodes. of produced traffc) corresponds to the rate determned by the next hop node. Eq. (3) s a statement of the mentoned condton. n s the number of upstream neghbors (precedng chld nodes), q the number of packets n the queue related to th traffc and QL/n s the maxmum queue length n th traffc. Each node after recevng a set of packets runs Eq. (5.1) functon and n case of detectng congeston or an ncrease n the sendng rate of one of the senders, determnes the sendng rate of the precedng node(s) and provdes ths rate to the nodes. All y parameters are n the range (0 and 1); 1 meanng that the entre bandwdth can be used and 0 meanng that no data can be sent. Parameter a determnes the mportance of congeston n the network. The greater ths parameter, the greater the mportance of congeston control n the network. For example, f a s set as 1, the factor of y c becomes zero and the value of y c s practcally 1. In ths case, accordng to Eq. (5.2), the rate of all the senders wll be zero. X n ¼ 1 y ðq :n=qlþ!y NH c ð5:3þ In Eq. (5 1), n s the number of upstream neghbors and P s the drop probablty computed by Eq. (2). The am of optmzaton s to mnmze the functon of Eq. (5.1). Fgure 5 clarfes the varables n Eq. (5). Eqs. (5.2) and (5.3)) present the optmzaton problem condtons. The mportance of congeston control s determned by a parameter by the user. The network has been consdered dentcal n the desgn of the HOCA protocol. Therefore all lnks n the network are dentcal and have the same bandwdth. y 1, y 2,y y n are the shares of the frst, second, y and nth sender, respectvely. Each sender can determne ts sendng rate by multplyng y by lnk bandwdth (whch s the same n the entre network). y c s used as the congeston parameter. In fact, y c s part of the node s ncomng bandwdth whch cannot be used because of congeston. y NH c s the current node s share for sendng data whch s determned by the next hop node (parent). For example, y 1 s gven to the precedng chld node by the present node, and t s known as y NH c n that node. The optmzaton functon (Eq. (5.1)) determnes the congeston degree n the present node as well as the sendng rate n the precedng chld nodes. However, the maxmum sendng rate for the node (equal to the volume of arrvng traffc plus the volume 4. Performance evaluaton of the proposed protocol MATLAB and OPNET (/ are the two software used n nvestgatng the performance of the proposed protocol. Eq. (2) optmzaton functon along wth other requred functons were run n MATLAB. The smulaton phase was carred out usng OPNET. Snce both software have been programmed based on Cþþ we have the opton of creatng lnks between the two. Therefore, the proposed protocol was smulated by lnkng the two software usng Cþþ compler. In order to mplement the proposed protocol, both MATLAB and OPNET software were used concurrently. The optmzed functon (2) wth the other related functons are mplemented n MATLAB software. Then OPNET calls MATLAB functons when needed. Fgure 6 llustrates the used topology. Table 2 presents parameters used n smulatons. Our optmzaton algorthm s very smple and consequently doesn t mpose a heavy calculatng load on the protocol. Each source node generates data unts accordng to a Posson process and the servce rate s constant. In addton to backpressure methods as factors of evaluatng the proposed protocol performance, the REEP (Jang, 2007) protocol was also used. The algorthm proposed n (Yaghmaee and Adjeroh, 2009), consders shortcomngs of CCF and PCCP and tres to solve them effectvely. Ths algorthm s useful more for multmeda applcatons. It hasn t used routng phase and just

9 224 A.A. Rezaee et al. / Journal of Network and Computer Applcatons 37 (2014) Fg. 7. Lfe tme over traffc load. Fg. 6. The topology whch s used n smulaton. Table 2 Smulaton parameters. Transmsson range 40 m Intal node energy 50 J Type traffc Senstve and non-senstve Network area m 2 Packet sent energy 12 mj Packet receve energy 10 mj Congeston detecton epoch Each 50 packet reduces the rate of sendng nodes n occurrence of congeston. But, n senstve applcatons lke medcal health care, t sn t favorable to reduce the sendng rate of packets; meanng that through allocatng a proper bandwdth, t s tred to reduce the sendng rate only for non-senstve traffc not for senstve one. Therefore, among routng algorthms, we chose REEP whch s a mult-phase algorthm close to health care structure to be compared wth our work. The major problem of REEP s gnorng the prorty and forwardng all the packets from the same path. Thus n the proposed algorthm, the REEP problem was solved va a mult-path method along wth support of packet prortzng. REEP s a data-centrc, energy effcent and relable routng protocol for WSNs. Ths protocol follows dfferent phases lke other data centrc protocols for routng whch nclude: Sense event propagaton, Informaton event propagaton and Request event propagaton. REEP also uses an energy threshold value n order to make the sensor nodes energy-aware. REEP also has fve mportant elements,.e. sense event, nformaton event, request event, energy threshold value and request prorty queue (RPQ). We use REEP besdes back pressure n order to make a reasonable bass to fnd the proposed protocol effcency. The proposed protocol uses MLAF (Mohajerzadeh et al., 2010) algorthm n the frst phase. MLAF s specally desgned for data dssemnaton n wreless sensor networks. Data centrc Routng protocol REEP uses Floodng to perform the frst phase that has a lower effcency. MLAF algorthm prevents the wastng of energy by consderng new method and provdes the possblty of data transmsson wth dfferent prortes Energy performance comparson Lfe tme, remanng average energy and farness are three mportant factors that should be taken nto account n evaluatng the performance of the proposed protocol. Fgures 7 and 8 llustrate lfetme and remanng average energy of the network, respectvely. The horzontal axs represents traffc load n kb/s and the vertcal Fg. 8. Mean remaned energy over traffc load. axs represents lfetme per tme unt. Network lfetme spans from the tme the smulaton s run untl the frst node des. As you can see n Fg. 7, the performance of HOCA s obvous n comparson wth REEP from the vew of traffc load, whch are about 400 packets per tme unt. For example, at a traffc load of 200 packets per tme unt, HOCA ncreases lfetme n comparson to REEP by about 78 percentages. HOCA uses multple paths to send data. Ths method ensures far dstrbuton of traffc at the destnaton, whch ncreases network lfe tme whle the REEP uses one way traffc transmsson. We can see n Fg. 7 that HOCA has a better performance than REEP n terms of network lfe tme. In Fg. 8, the mean of remanng node energy at the tme of death for the frst node has been calculated. Accordng to the results n Fg. 8, the mean remanng energy n nodes for the HOCA protocol s less than REEP. The lower remanng energy s a result of hgher energy consumpton. If the nodes consume most of ther energy untl the end of smulatons, the protocol s consdered more successful. Of course, energy consumpton wth more attenton to ncrease percentage n lfe tme (Fg. 7) s acceptable. As we mentoned before, respectng farness on energy consumpton s one of the powerful pont of HOCA n energy performance. If we can keep better balance n the energy consumpton of nodes the lfetme of the network ncreases under the same condtons. Accordng to Fg. 9, farness parameter s more successful n HOCA rather than REEP one. Consdered parameter has calculated wth Eq. (6). Eq. (6) calculates the varance of normalzed remanng energy of network nodes to average remaned energy (Ave) of total network(in worst case half of the nodes get energy empty and half reman full, so f we normalze the equaton we can acheve normalzed farness equaton.). In Eq. (6), Energy s node remanng energy when smulatons end.

10 A.A. Rezaee et al. / Journal of Network and Computer Applcatons 37 (2014) Packet loss comparson Fg. 9. Farness over traffc load. Fgures 11 and 12 show packet loss over traffc load and tme, respectvely. Fgure 11 shows Aggregatve number of dropped packets n the networks wth respect to traffc load. As mentoned n Secton 1 there are two dfferent flows n network: senstve and non-senstve traffc. In Fg. 11 there are three flows: Senstve HOCA, non-senstve HOCA and one flow for REEP. Be careful REEP has no prorty for dfferent traffc, so regardless of packet prorty does the same reacton. As can been seen n Fg. 11 HOCA s more successful n packet delvery. Of course for traffc loads less than 60 due to lack of congeston, packet loss for both protocols are low and close. But n other ponts HOCA has been able to decrease packet loss n an approprate level. Another pont s the packet loss dfference between the senstve and non-senstve flows. One of the needs of the senstve traffc s to mnmze packet loss. It can be seen n Fg. 11 that HOCA has acheved ts goal. In Fg. 12 aggregatve packet loss rate over tme wth ntal source rate 200 packets per second has been shown. Accordng to Fg. 12 before the tme 10 due to exstng of control packets, the possblty of controllng source rate s a dffcult process. Also hop by hop rate adjustment from congested node to source node wll be accompaned wth delay. Wth regard to the mentoned above after tme 10 rate adjustment performs effcently and as a result packet loss rate decreases that can be seen n Fg. 12. In Fg. 13 HOCA protocol n addton to REEP s compared wth 25% and 50% backpressure too. Back pressure refers to the backpressure algorthms wth 25% and 50%reducton percentages, respectvely, n a sensor s data rate n response to a backpressure Fg. 10. Near-snk nodes energy over tme. As t s clear n Eq. (6) the more farness parameter, the protocol s much success that t means remanng energy of nodes are closer wth each other. If farness parameter s equal one, the network has the best and the most farness case (all nodes have the same remaned energy), however when t s equal zero we have the most unfarness case of energy consumpton. DEV ¼ Xn ðenergy AveÞ 2 ¼ 1 Farness ¼ 1 DEV=DEV Worst ð6þ In WSNs, when data converge toward the snk, congeston s more lkely to happen at sensors near snk whch are lkely to receve more data than they can forward. Every near-snk sensor node s a hotspot and so, ts resources are more valuable. By provdng farness, network lfetme wll be prolonged. As t s clear n Fg. 10 the rate and speed of nodes resdual energy for HOCA s closer wth each other rather than REEP one. There are four nodes wth number such as 13, 15, 19 and 21 on snk s neghborhood. The more ncreasng lfe tme, the more successful network we have. In order to ncrease network lfe tme, the traffc near the snk has to dstrbute among all nodes so that ts lfe tme prolongs. In REEP method, all the packets reach to snk by node 15 and other near snk nodes do not partcpate n traffc pass. So speed of ths s less than other nodes and lfe tme of network get worst. But n proposed method by far traffc dstrbuton between all nodes, the speed of node energy decreases gong to be dmnshng so that t causes network longer lfe tme and farness mprovement on energy consumpton. In Fg. 10, horzontal axs s the tme and vertcal axs shows nodes resdual energy. At the end, the total results of Fgs show that HOCA energy performance s more effcent. Fg. 11. Packet loss over traffc load (Kbps). Fg. 12. Packet loss over tme.