Research Article A Priority-Based CSMA/CA Mechanism to Support Deadline-Aware Scheduling in Home Automation Applications Using IEEE

Hindawi Publishing Corporaion Inernaional Journal of Disribued Sensor Neworks Volume 213, Aricle ID 13984, 12 pages hp://dx.doi.org/1.1155/213/13984 Research Aricle A Prioriy-Based CSMA/CA Mechanism o Suppor Deadline-Aware Scheduling in Home Auomaion Applicaions Using IEEE 82.15.4 Mario Colloa, Gianfranco Scaà, and Giovanni Pau Facolà di Ingegneria,Archieurae delle Scienze Moorie,Universià degli Sudi di Enna Kore Ciadella Universiaria, 941 Enna, Ialy Correspondence should be addressed o Gianfranco Scaà; gianfranco.scaa@unikore.i Received 11 January 213; Acceped 22 April 213 Academic Edior: Danny Hughes Copyrigh 213 Mario Colloa e al. This is an open access aricle disribued under he Creaive Commons Aribuion License, which permis unresriced use, disribuion, and reproducion in any medium, provided he original work is properly cied. The wireless sensor neworks (WSNs) are characerized by several small nodes able o perform measuremens on one or more parameers and o communicae wih each oher hrough several proocols. Mos of home auomaion neworks (depending on he specific applicaion) are mainly characerized by periodic raffic flows. In sof real-ime conexs, he main problem is represened by he efficien allocaion of guaraneed ime slos (GTSs) for periodic raffic flows ransmission in IEEE 82.15.4 neworks. Moreover, i is imporan o ensure adequae performance for hose embedded devices compeing for he access o he medium hrough he carrier sense muliple access/collision avoidance algorihm (CSMA/CA). The main aim of his paper is o show a new approach for nework flows scheduling in home auomaion applicaions based on IEEE 82.15.4 wireless sensor neworks. This work addresses several advanages due o he inroducion of rae monoonic (RM) for guaraneed ime slos (GTSs) allocaion combined wih prioriy-based CSMA/CA for laencies reducion on ransmission aemps as clearly demonsraed by obained resuls. 1. Inroducion In order o provide a deailed inroducion o he issue, his secion will be divided ino hree subsecions. Secion 1.1 specifically deals wih wireless sensor neworks for home auomaion sysems, explaining he reasons which led o he choice of he IEEE 82.15.4 proocol. In Secion 1.2, a general overview of he IEEE 82.15.4 proocol will be shown, placing emphasis on how i suppors real-ime communicaion using he guaraneed ime slos mechanism. Finally, Secion 1.3 will discuss he main moivaions and aims of his research work. 1.1. Wireless Sensor Neworks in Home Auomaion Sysems. Wireless sensor neworks are widely used in several applicaion areas including daa processing [1], indusry [2 5] home auomaion [6 8], and road monioring [9, 1] hanks o several characerisics like flexibiliy, adapabiliy, and scalabiliy [11]. An auomaed house is he inegraion of embedded devices wih oher nonauomaed sysems such as lighing, heaing, and air condiioning in order o realize smar applicaions for home conrol. The main aim of his inegraion is o provide greaer comfor, safey, opimizing and he energy consumpion. Wireless sensor neworks are fundamenal in home auomaion applicaions whose main requiremens are qualiy of service (QoS) and realime consrains saisfacion [12]. Mos of he domoic sysems, currenly available on he marke, use wired neworks hrough differen communicaion proocols like Eherne [13], X-1 [14], Modbus [15], or Powerline [16]. Alhough heir funcionaliy and reliabiliy have been proven over he years, some imporan disadvanages mus be considered. For example, Powerline and X-1 use he exising power line bu suffer of high error raes on poor qualiy lines affeced by noise. Modbus and Eherne require cables for boh power and daa ransmission. This can be expensive in erms of implemenaion and mainenance coss as well as being aesheically no very funcional. WSNs represen he obvious soluion o hese problems because hey consis of several low cos and low power devices. There are several proocols available for sensor neworks like Blueooh and

2 Inernaional Journal of Disribued Sensor Neworks Guaraneed ime slos GTSs Beacon 1 2 3 4 5 6 7 8 9 1 11 12 13 14 15 Inacive period Beacon CAP Conenion access period CFP Conenion free period Figure 1: IEEE 82.15.4 MAC superframe srucure. IEEE 82.15.4 [17]. Through Blueooh i is possible o connec up o seven acive devices for each picone and i uses frequency hopping (FH) and ime division muliplexing (TDM) in order o regulae ransmissions. Moreover, i is characerizedbyhighpowerconsumpion.asaconsequence, he IEEE 82.15.4 sandard proocol is more appropriae for home auomaion applicaions. 1.2. The IEEE 82.15.4 Proocol. The IEEE 82.15.4 sandard provides he physical (PHY) layer and medium access conrol (MAC) sublayer specificaions for low daa rae (up o 25 kbps in ISM frequencies, 2.4 GHz) wireless conneciviy. According o he IEEE 82.15.4 sandard proocol, a wireless sensor nework can opionally operae in beacon-enabled mode (he more suiable for real-ime raffic flows managemen). In his case, he ime axis is divided ino a sequence of superframes, each one delimied by special signaling packes (beacons). The beacons are ransmied by he PAN coordinaorandareresponsibleforhesynchronizaionofallnework devices. In his operaing mode, he superframe is divided ino ime slos and conains a conenion access period (CAP)inwhichhemulipleaccessesohechannelare managed hrough he CSMA/CA algorihm. The superframe also provides a conenion free period (CFP), in which cerain saions can obain access o he medium wihou collisions (in FIFO order) in special guaraneed ime slos (GTSs), andaninaciveperiodinwhichheradioinerfacecanbe pu in a low energy consumpion saus in order o improve energy savings. Figure 1 shows he IEEE 82.15.4 superframe srucure. 1.3. Moivaions and Main Aim. The use of wireless echnologies in home auomaion neworks needs he sudy and he implemenaion of new scheduling and QoS [18, 19] managemen mechanisms in order o mee real-ime consrains. In fac, considering he IEEE 82.15.4 proocol, in conenion access period he access o he medium is variable and unpredicable due o he backoff mechanism. In his work, we propose an approach based on he combined useofraemonoonic(rm)[2], for GTSs allocaion in he conenion free period, and a variaion of he CSMA/CA algorihm for channel accesses managemen in he CAP based on raffic flows classificaion. The proposed approach canhelpinhedevelopmenofhomeauomaionapplicaions characerized, as known, by sof real-ime consrains. The main aim of his work is o reduce he waiing ime during access aemps o he radio channel of embedded devices improving, a he same ime, nework performance of home auomaed environmens. Resuls, obained hrough several measuremen campaigns, show how differeniaing raffic flows makes i possible o effecively improve performance in erms of hroughpu/workload (Th/Wl) on each embedded device and, in general, on he whole nework. The paper is organized as follows. Secion 2 repors he main lieraure works abou approaches o improve IEEE 82.15.4 neworks performance. Secion 3 shows he considered nework archiecure, he proposed approach, and a probabilisic analysis abou relaionship beween nework hroughpu and he probabiliyofeachnodeofindheradiochannelfree. Secion 4 proposes a es-bed scenario showing obained resuls, while Secion 5 summarizes he paper reporing conclusions. 2. Relaed Works The IEEE 82.15.4 wireless sensor neworks have been sudied by researchers which evaluaed several aspecs. In order o cover he main issues, he relaed works secion has been organized by opic areas. Our main aim is o ake sock of he curren siuaion abou he various aspecs of he issue objec ofhisworkandhenoproposeourimprovemens. 2.1. Home Auomaion Neworks Applicaions Based on he IEEE 82.15.4 Sandard Proocol. In he lieraure, here are several works focused on home and building auomaion, and many of hem use he IEEE 82.15.4 sandard proocol for wireless conneciviyof sensornodes. In [21], he deploymen of wireless sensor neworks and wireless sysems applied o home and building auomaion sysems is analyzed. Auhors propose an in-house deerminisic code based on 3D ray launching in order o analyze he effec of he indoor opology and morphology in he operaion of wireless links wihin differen realisic scenarios. Several simulaions were performed in order o obain performance parameers, such as RSSI (received signal srengh indicaion) and PER (packe error rae). Simulaion resuls show ha he analysis of he opology of he wireless sensor nework has a srong impac on complex indoor scenarios. The use of adequae radioplanning sraegies, hrough he applicaion of deerminisic echniques in he planning phase, leads o opimal wireless nework deploymens in erms of capaciy, qualiy of service, and energy consumpion. The purpose of [22] is o

Inernaional Journal of Disribued Sensor Neworks 3 demonsrae he use of IEEE 82.15.4 o provide real-ime environmenal informaion o a smar home simulaor. In his work, he simulaor iself and a brief echnical inroducion of he IEEE 82.15.4 sandard are presened. Moreover, he auhors analyze he reliabiliy of IEEE 82.15.4 in a real home auomaion applicaion. In fac, auhors came o he conclusion ha he IEEE 82.15.4 sandard is very reliable and easy o implemen in home wireless nework scenarios hanks o he versailiy and scalabiliy of he proocol. In addiion, an analysis on exposure levels o elecromagneic fields is provided. Using he IEEE 82.15.4 proocol, he exposure levels of elecromagneic radiaion are very low, abou 6 imes lower han an ordinary cell phone. The auhors of [23] describe he IEEE 82.15.4/ZigBee communicaion proocol, and hey presen is poenial deploymen in smar home environmens. Some examples of prooype applicaions, in home securiy and auomaion using a ZigBee-based wireless sensor nework, are presened. The auhors made a comparison beween he designed ZigBee-based wireless smar home sysem and oher exising sysems in marke. A careful analysis on wireless archiecure shows ha sensors and communicaion devices, used for he deploymen in smar home, are no required o have a high speed in communicaion capaciies. The auhors show how using he ZigBee nework echnology, as wireless communicaion sandard, makes i possible o saisfy home auomaion neworks requiremens, because IEEE 82.15.4 allows o obain robus mesh neworks and complee ineroperabiliy. Insead, more sudies are needed o limi he energy consumpions of devices, o improve he nework scheduling mechanism, and o validae he coexisence of muliple proocols. 2.2. Energy Saving IEEE 82.15.4 Applicaions in Home Auomaion Neworks. The need of smar energy managemen in home environmens, for susainable energy efficiency and moneary savings, is analyzed in several works. The auhors of [24] provide a comprehensive summary of he sae of he ar in home area communicaions and neworking echnologies for energy managemen. The analysis shows ha here are several wireless sandards for home area neworks, including IEEE 82.15.4, and, accordingly, he sysem designers choose he wireless echnology ha bes fis heir applicaion. Moreover, he auhors poin ou on he challenges dealing wih he design of energy managemen sysems, in erms of accuracy, compaibiliy, low power cos, and inegraion, in order o provide he guidelines for sandardized and more user-friendly smar energy home auomaion sysems. Energy managemen is also examined in [25]. This work inroduces a novel home-energy conrol sysem design, based on ZigBee devices, ha provides inelligen services for users. The auhors implemen he proposed sysem and demonsrae is poenialiy using a real es bed. Afer an accurae analysis, he paper clearly shows ha smar home conrol sysems can provide significan cos savings in home environmen applicaions. In his work, a specific disseraion abou lighing energy reducion is done. In fac, by using an auomaed conrol sysem i could be possible o urn lighs off based on several facors such as available dayligh or ime of day. Therefore, he use of wireless connecions raher han wired neworks involves several benefis in erms of flexibiliy and money savings. In order o mee home auomaion neworks requiremens, several aspecs of he IEEE 82.15.4 medium access conrol (MAC) in conenion access period (CAP), conenion free period (CFP), and he overall cross period, respecively, are analyzed in [26]. An exensive discussion focuses on a variey of adapive real-ime proocols based on IEEE 82.15.4 and on many problems of wireless neworks like high laency, sysem complexiy, implemenaion overhead, and, mainly, grea energy consumpion. The auhors come o he conclusion ha he requiremens of all aspecs usually canno be saisfied simulaneously. However, he nework efficiency can be significanly improved opimizing he original specificaions and dynamically adjusing he IEEE 82.15.4 proocol parameers. A home auomaion nework archiecure for energy managemen inside smar grid environmens is presened in [27]. In order o achieve smargridpoenial,heauhorsaimoresolveheproblemof ineroperabiliy among differen communicaions echnologies deployed in he grid. The auhors propose a framework for end-o-end ineroperabiliy in home and building area neworks. This framework includes he 6LoWPAN proocol in order o simplify he use of IPv6 and ZigBee applicaion profiles. The auhors also focus on oher issues, including inerference miigaion and load scheduling, and hey propose a soluion o hem. They propose a prioriy conenion algorihm for high prioriy messages managemen, while, a he same ime, he proposed approach uses a compression and scheduling mechanism in order o increase he efficiency of ransferred daa. Moreover, a frequency-agiliy-based inerference miigaion algorihm is proposed in order o guaranee he performance of nework proocols coexisence. 2.3. GTS Mechanism in Home Auomaion Neworks. Wireless echnologies in home auomaion applicaions need he developmen of new scheduling mechanisms in order o mee real-ime consrains. A scheduling scheme, whose main aim is o obain opimal parameers regarding he IEEE 82.15.4 frame and subframes in home auomaion neworks, is presened in [28]. The proposed approach uses guaraneed ime slos (GTSs) for ransmission of real-ime periodic raffic flows, since hey can guaranee ime consrains using he periodic delivery of beacon frames as provided by he IEEE 82.15.4 proocol. The auhors consider a se of nodes requiremens in an IEEE 82.15.4 nework in order o define he beacon inerval considering he required periods and he duycycles.moreover,heacivesubframeduraionischosen according o required bandwidhs and o ensure energy saving.theauhorsshowresulsinermsofhroughpu for differen frame and subframes lenghs. Numerical resuls show ha frame and subframe duraion and GTS s schedule can be deermined in order o ensure an efficien use of he nework resources. Several works on he GTS aim a increasing uilizaion and reducing he wase of bandwidh. Anyhow, using IEEE 82.15.4 sandard proocol, he GTS does no guaranee he reliable ransmission in mulihop neworks. For his reason, GTS mechanism is also analyzed in

4 Inernaional Journal of Disribued Sensor Neworks [29] where auhors propose and implemen a mulihop GTS mechanism for reliable ransmission in mulihop neworks. Aferadiscussiononhereliableransmissioninmulihop neworks, he auhors presen simulaions resuls. In fac, several simulaions have been carried ou hrough NS-2 simulaor, and resuls show ha low end-o-end delay and high delivery raio can be checked. Therefore, hanks o hese feaures, he proposed mechanism is especially suiable for delivering ime-sensiive daa. In [3], a preliminary soluion for he ransmission of real-ime ime-riggered raffic over he IEEE 82.15.4 sandard in a home auomaion environmen wih real-ime requiremens is shown. Auhors define he design soluions focusing on GTSs ransmission and recepion for ime-riggered raffic wih real-ime requiremens. The proposed approach can be useful for infrasrucure-o-vehicle and vehicle-o-vehicle communicaions and home auomaion applicaions supporing life monioring. The auhors focus heir fuure works in peer-opeer opology because, in his case, a device can communicae wih any oher device and, furhermore, several coordinaors may exis. The peer-o-peer opology has he advanage of increased coverage area bu i involves increased message laency and nodes synchronizaion. 2.4. Coexisence of IEEE 82.15.4 wih Oher Communicaion Proocols in Home Auomaion Neworks. Several works in he lieraure analyze he coexisence of IEEE 82.15.4 wih oher neworks proocols in home auomaion applicaions. In [31], a unneling soluion ha allows running KNX/EIB over IEEE 82.15.4 links is presened. The auhors analyze wireless sensor and acuaor neworks as an alernaive o wiredsoluionsinhehomeandbuildingauomaiondomain because several echnologies ha fulfill he specific requiremens of his class of wireless neworks have reached commercial saus. The approach proposed by auhors emulaes he properies of he KNX/EIB wired medium via wireless communicaion, over an IEEE 82.15.4 nework, allowing a seamless exension. Moreover, his novel archiecure provides a basic level of communicaions securiy using a shared key hrough sandard IEEE 82.15.4 securiy mechanism. As fuure works, he auhors aim o a beer evaluaion of proposed approach performance, in erms of he effecs of conenion occurring on he unneling medium. The use of 6LoWPAN and IEEE 82.15.4 proocols has been presened in [27], while 6LoWPAN, IPv6, and IEEE 82.15.4 proocols are also used in[32]. The auhors propose a prooypical implemenaion of a home auomaion nework ha uses IPv6 over 6LoWPAN o conrol home applicaions. The proposed implemenaion is based on an embedded web server which, conneced over a low-power IEEE 82.15.4 nework, provides he abiliy o remoely open and close an elecric door lock. Through his archiecure, i is also possible o conrol oher elecronic consumer devices such as heaing, air condiioning, lighing sysems, and many ohers. The use of he proposed approach can offer many benefis for energy conservaion, and, a he same ime, i can involve new usage paerns in home auomaion applicaions, such as assised living or smar grids. In [33] he developmen process of a smar home nework is presened based on IEEE 82.15.4/ZigBee echnology wih he combinaion of SAANe, a smar home appliance communicaion proocol. The SAANe proocol aims a solving he daa recogniion beween differen ypes of devices because mos of ZigBee devices profiles were no buil compleely. Therefore, he combinaion of ZigBee and SAANe proocols can be a soluion o solve several problems. The inegraion beween he wo proocols has been successfully applied in order o achieve a supervisory home conrol sysem. The approach proposed by auhors implemens he funcions of enrance conrol, emperaure and humid sensing, and appliance conrol. A mehodology o measure and avoid WiFi inerference while deploying and insalling ZigBee-based producs in a home auomaion archiecure is inroduced in [34]. A deailed analysis shows ha ZigBee producs can successfully wihsand inerference from microwave ovens and Blueooh devices bu hey are sill vulnerable o high load WiFi raffic. Anyhow, he auhors come o he conclusion ha ZigBee can coexis wih WiFi in a ypical home environmen if several prevenaive measures are aken ino accoun. The recommendaions o avoid WiFi inerference, ha auhors derived experimenally, are o place WiFi rouer no closer han 5 meers of window shuers, and, moreover, i would be appropriae o use a frequency offse of a leas 2 MHz beween ZigBee and WiFi. However, oher facors, such as raffic ype, migh also affec he performance of a sysem under WiFi inerference. In fuure works, he auhors focus on a more horough sudy, aking ino accoun hese facors and using real user raffic insead of synheically generaed raffic. 3. The Proposed Approach In his work, a wo-iered archiecure in home auomaion environmen (Figure 2) is shown.the firs ier is characerized by a WSN in which devices are organized in home cells (HCs). Each HC is managed by a PAN coordinaor ha provides several modules. (i) Eherne module: i is he inerface hrough which i is possible o esablish a wired connecion beween each home cell and he real-ime Eherne backbone. (ii) The IEEE 82.15.4 module hrough which he PAN coordinaor receives and processes daa deeced by is home devices (s). (iii) Scheduling module: his module is a qualiy of service (QoS) manager for real-ime (RT) communicaions and dynamically decides ransmission prioriies of s using an approach based on rae monoonic (RM) and prioriy-based CSMA/CA (PB). As already said, main sysem devices are home devices (s) and PAN coordinaors. Each sends daa acquired o is PAN coordinaor and can be eiher an IEEE 82.15.4 reduced funcion device (RFD) or a full funcion device (FFD) in a clusered nework. This paper addresses several advanages in he use of a novel inracell scheduling approach combined wih he use of. The PAN coordinaors are

Inernaional Journal of Disribued Sensor Neworks 5 Home cell HC Home cell HC PAN coordinaor 82.15.4 Scheduler EDF + CSMA/CA + PC Home cell HC PAN coordinaor 82.15.4 Scheduler EDF + CSMA/CA + PC Eherne inerface PAN coordinaor 82.15.4 Scheduler EDF + CSMA/CA + PC Eherne inerface Eherne inerface Real-ime Eherne backbone Figure 2: Nework scenario. responsible for daa ransmission of heir associaed nodes and for scheduling raffic decisions wihin heir respecive home cells. The inracell scheduling in his archiecure is realized hrough he preallocaion of guaraneed ime slos o devices involved in ransmissions of periodic messages hrough he RM scheduling algorihm [2]. The GTS lis conains he addresses of all devices ineresed o ransmi. Each device will wai is urn according o is address posiion in he GTS Lis and hen i will ransmi using is allocaed GTS. In case ofhighworkloadsorhighnumberofnodes,iispossibleo use he. The use of GTSs, allocaed wih RM, guaranees a deerminisic allocaion of slos. Consider (i) a se of messages M i, each one wih relaive deadline (d i )equaloheperiod(t i ); (ii) online scheduling; (iii) nonpreempion. Rae monoonic and earlies deadline firs (EDF) [2] produce he same schedule. Under hese assumpions, we could also use he EDF algorihm. Figure 3 demonsraes how 7 messages, each wih d i =T i and a cerain compuaional ime (C i ), as described by Table 1, can indifferenly be scheduled using RM or EDF. I is imporan o remind ha in case of RM algorihm, he schedulabiliy is guaraneed if n C i ( ),68. (1) i=1 T i Oherwise, in case of EDF algorihm, he schedulabiliy is guaraneed if n C i ( ) 1. (2) T i i=1 M 1 M 2 M 3 M 4 M 5 M 6 M 7 2 4 6 8 1 12 14 16 18 2 22 24 26 28 3 Figure 3: Se of messages scheduled a he same way wih EDF and RM. Table 1: Scheduling parameers. d i =T i C i U i M 1 5 1.2 M 2 1 2.2 M 3 15 1.6 M 4 15 1.6 M 5 3 1.3 M 6 3 2.6 M 7 3 1.3 I is also possible o have a guaranee abou messages schedulabiliy, in accordance wih deadlines, hrough he known Jeffay s heorem [2]. A se of periodic requess (messages) is scheduled using a nonpreempive algorihm if wo condiions are me. The firs equaion (1) relaes o sysem uilizaion (in erms of bandwidh, as we are dealing wih

6 Inernaional Journal of Disribued Sensor Neworks he ransmission of packes), whereas he second equaion (2) refers o he sysem demand. Theorem 1. Asysemcanscheduleaseofperiodicrequess using nonpreempive EDF algorihm if Jeffay s condiions ((2) and (3))areme: n C i U o =U P +U S =( +U T S ) 1, (3) i i=1 1<i n; L,T 1 <L<T n :L C i + i 1 j=1 L 1 T j C j. The periodic raffic flows are represened by a se of periodic variables τp = {p1,p2,...,pn},wherep i =(C i,t i ),soredin a nondecreasing order by period (i.e., for any pair of variables p i and p j,ifi>jhen T i T j ), and C i is he ransmission ime for a periodic raffic flow generaed by ih wireless node. Equaion (3) relaes o he sysem uilizaion (in erms of bandwidh, as we are dealing wih he ransmission of packes), whereas (4) refers o he sysem demand. Equaion (3) defines ha oal bandwidh uilizaion mus no exceed 1; U P is he uilizaion facor for periodic raffic while US is he uilizaion facor for sporadic and aperiodic raffic flows (i.e., server uilizaion). The inequaliy in (3) refers o a leas upper bound on bandwidh demand ha can be achieved in an inerval of lengh L. This inerval sars when he periodic variable is invoked and ends before he relaive deadline. Then, a se of variables is schedulable if hedemandinheinervall is less han or equal o he lengh of he inerval. In his paper, we choose o work according o sloed CSMA/CA as provided by he sandard. Scheduling managemen hrough preallocaed GTS can be considered efficien. The RM + approach, proposed in his paper, guaranees he access o he medium for periodic ransmissions providing a division ino hree prioriy classes for all ransmission regulaed by CSMA/CA in conenion access period: high prioriy, medium prioriy, and low prioriy. The hree prioriy classes have been creaed modifying wo sandard parameers. (i) CW (conenion window): i is he conenion window lengh, in oher words, he number of backoff periods during which i is necessary o lisen o he channel before he ransmission. (ii) BE (backoff exponen): i is he variable ha deermines he number of backoff periods he device shall wai before channel access aemps. The number of waiing periods (CW) is a random number inside he range [, 2 BE 1] where macminbe < BE < macmaxbe. In home auomaion environmens, he coexisence of differen raffic ypes mus be aken ino accoun. In order o define he prioriy class, BE and CW variables of he CSMA/CA have been used. BE has been considered as a variable in he range 1 BE 3. Considering ha in each beacon inerval, wih n preallocaed slos for GTS ( n 7), (4) Table 2: Prioriies classificaion. CW macminbe macmaxbe High prioriy 1-1 Medium prioriy 1-2 1-2 Low prioriy 2 2-3 Sandard 2 3 5 i is possible o use up o 15-n slos for he CSMA/CA. As a consequence, i has been possible o define hree prioriy classes as shown in Table 2. These values mus be se on each HC s node in order o define he prioriy of each device. The choice of conenion window and backoff exponenial deermines nodes ransmission frequency. High-prioriy nodes will lisen o hechannelmorefrequenlyandwihhigherprobabiliyof ransmission success. Clearly, his approach does no resolve he nondeerminism of he wireless channel bu significanly reduces laencies of nodes involved in he conenion access o he channel. 3.1. Probabilisic Analysis of IEEE 82.15.4 Transmissions hrough. Anoher aspec considered and proposed hrough his paper concerns he relaionship beween he probabiliy ha a saion finds he channel free and he nework hroughpu varying CW and BE parameers. As already proposed by several works in he lieraure [35 37], he CSMA/CA algorihm can be modeled hrough an M/G/1 queue. Consider (i) n: he number of nodes associaed o a PAN coordinaor; (ii) N: he oal number of nework nodes (associaed and no); (iii) λ: packes generaion rae (according o a poisson process); (iv) T TX : he fixed packe ransmission ime; (v) Wl: nework workload; (vi) T urn : urnaround ime; (vii) T ACK : ransmission ime for ACK packe; (viii) σ: backoff slo duraion. The probabiliy (α) of channel busy during he conenion window CW, he packe loss probabiliy P loss,andheaverage delay E [D HOL ] are given by he nonlinear equaions sysem: α= (n 1)(1 P loss) Wl (CW +T TX +2T urn +T ACK ), (1/λ) + Wl +E[D HoL ] P loss =α N+1,

Inernaional Journal of Disribued Sensor Neworks 7 E[D HoL ]= N V= α V (1 α) { +α N+1 N { i= V i= W i 1 σ+(v +1) CW} 2 W i 1 σ+(n+1) CW}. 2 The equaions previously expressed in he variables α, P loss, and E [D HOL ] can be numerically solved in order o obain he value α of busy channel probabiliy, from which aferwards i is possible o obain he hroughpu value according o (5) Transmission probabiliy 1.8.6.4.2 Transmission probabiliy versus nodes number 2 4 6 8 1 12 14 16 18 2 22 24 26 28 3 32 34 36 38 4 Nodes number High prioriy Medium prioriy Low prioriy Sandard TH = n(1 P loss ) Wl T TX (1/λ) + Wl (E[D HoL ]+T TX +2T urn +T ACK ). (6) Figure 4: Transmission probabiliy esimaion. The erm (E[D HoL ]+T TX +2T urn +T ACK ) represens he waiing period in an M/G/1 queuing sysem. Figure 4 analyzes sysem s performance in erms of ransmission probabiliy behavior varying he number of nodes in he nework. I is easily observable ha he ransmission probabiliy of low prioriy nodes is slighly beer han he sandard, while medium and high prioriy nodes have a higher ransmission probabiliy. Table 3: Nodes prioriies classificaion cases. Nodes Case 1 Case 2 Case 3 Case 4 Prioriy number CW BE CW BE CW BE CW BE 2 High 1 1 1 2 1 1 1 2 3 Medium 1 2 1 2 2 2 2 2 4 Low 2 3 2 3 2 3 2 3 4. Performance Evaluaion Performance of our approach has been esed hrough a real experimenal scenario implemened using IRIS MTS3 [38] and MTS3 boards from Crossbow/Memsic and aking ino accoun requiremens of an IEEE 82.15.4 nework described in [39]. Tess have been conduced on a sar opology nework wih9rfddevices()andagaeway(pancoordinaor). In paricular, 3 high prioriy nodes, 2 medium prioriy nodes, and 4 low prioriy nodes have been considered as shown in Figure 5. Varying CW and BE parameers, 4 case analyses have been idenified, as beer explained hrough Table 3. Case 1. Consider he following: (i) high prioriy nodes CW =1,BE=1; (ii) medium prioriy nodes CW =1,BE=2; (iii) low prioriy nodes CW =2,BE=3. Figures 6 and 7 show performance obained in Case 1. Figure 6 shows how higher prioriy nodes are characerized by hroughpu/workload (Th/Wl) values higher han nodes wih lower prioriy. On average, high prioriy nodes obain beer performance wih he use of han he sandard. This is due o he fac ha hey have higher probabiliy o ransmi. In oher words, hey have a high reducion of waiing imes during radio channel accesses aemps. On he conrary, lower and medium prioriy nodes measure values lower han he sandard because for hem CW = 2 and BE = 3.Figure 7 shows improvemens in erms of Th/Wl obained by each prioriy class. In general, oal nework Th/Wl is beer han he sandard bu Th/Wl measured by all low prioriy nodes is lower. Case 2. Consider he following: (i) high prioriy nodes CW =1,BE=2; (ii) medium prioriy nodes CW =1,BE=2; (iii) low prioriy nodes CW =2,BE=3. Figures 8 and 9 show performance obained in Case 2. Figure 8 showsth/wlvaluesmeasuredoneachnode.evenin his case, higher prioriy nodes reach hroughpu/workload (Th/Wl) values higher han nodes wih lower prioriy. Bu, i is possible also o see ha even medium prioriy nodes obain beer performance hrough our approach. A he same ime, differences in resuls, beween and he sandard, decrease also for low prioriy nodes. Figure 9 shows improvemens in erms of Th/Wl classified for prioriy classes. Using a prioriy classificaion of raffic flows, he obained Th/Wl of he whole nework is higher han he sandard and, in his case, even he Th/Wl measured by all low prioriy nodes is beer han he sandard.

8 Inernaional Journal of Disribued Sensor Neworks Personal compuer USB cable PAN coordinaor + PAN coordinaor Processor radio board Home device nodes USB gaeway MIB52 + Processor radio board Sensor node IRIS MTS3 High prioriy node Low prioriy node Medium prioriy node 82.15.4 wireless communicaions Figure 5: Tes-bed scenario. 9 Case 3. Consider he following: Nodes 8 7 6 5 4 3 2 1 Sloed CSMA/CA 5 Figure 6: Case 1:Th/Wlmeasuredoneachnode. 1 (i) high prioriy nodes CW =1,BE=1; (ii) medium prioriy nodes CW =2,BE=2; (iii) low prioriy nodes CW =2,BE=3. Figures 1 and 11 show performance obained in Case 3. Figure 1 shows Th/Wl values measured on each node. Even in his case, higher prioriy nodes reach hroughpu/workload (Th/Wl) values higher han nodes wih lower prioriy. Jus nodes 1 and 3 measure he wors performance han he sandard. This is due o he fac ha he raffic flows classificaion, based on prioriies, suppors a more frequen ransmission of messages wih higher prioriy, resuling in a sligh increase of waiing imes for some nodes having medium or low prioriy. Figure 11 shows improvemens in erms of Th/Wl classified for prioriy classes. Resuls clearly

Inernaional Journal of Disribued Sensor Neworks 9 Toal Toal Prioriy classes High Medium Prioriy classes High Medium Low Low Sloed CSMA/CA 5 1 Sloed CSMA/CA 5 1 Figure 7: Case 1: Th/Wl resuls for prioriy classes. Figure 9: Case 2: Th/Wl resuls for prioriy classes. Nodes 9 8 7 6 5 4 3 2 1 Sloed CSMA/CA 5 1 Nodes 9 8 7 6 5 4 3 2 1 Sloed CSMA/CA 5 1 Figure 8: Case 2:Th/Wlmeasuredoneachnode. Figure 1: Case 3:Th/Wlmeasuredoneachnode. show how, using he proposed algorihm, he Th/Wl raio of hewholeneworkishigherhanth/wlobainedusinghe sandard algorihm. As already explained in Figure 1, he Th/Wl obained by all low prioriy nodes is lower han he sandard because hey can ransmi wih lower frequency. Case 4. Consider he following: (i) high prioriy nodes CW =1,BE=2; (ii) medium prioriy nodes CW =2,BE=2; (iii) low prioriy nodes CW =2,BE=3. Finally, Figures 12 and 13 show performance obained in Case 4. In paricular, Figure 12 shows Th/Wl values measured on each node. Even in his case, higher prioriy nodes reach hroughpu/workload (Th/Wl) values higher han nodes wih lower prioriy. This case sudy produced bes performance resuls. In fac, jus node 3 obained he wors performance, and generally, even low prioriy nodes obained beer performance han he sandard algorihm, as i is possible o see hrough Figure 13. 5. Conclusions In his paper, a novel scheduling mechanism for periodic raffic flows managemen has been proposed in order o suppor he developmen of home-auomaed neworks. The main aim is o reduce laencies of channel access aemps of nework embedded devices in home auomaion applicaions. This new approach, called rae monoonic +,

1 Inernaional Journal of Disribued Sensor Neworks Toal Toal Prioriy classes High Medium Prioriy classes High Medium Low Low Sloed CSMA/CA 5 1 Sloed CSMA/CA 5 1 Figure 11:Case 3: Th/Wl resuls for prioriy classes. Figure 13: Case 4: Th/Wl resuls for prioriy classes. Nodes 9 8 7 6 5 4 3 2 1 Sloed CSMA/CA 5 Figure 12: Case 4:Th/Wlmeasuredoneachnode. provides he preallocaion of guaraneed ime slos (GTSs) hrough he rae monoonic algorihm for hose devices which wan o ransmi periodic messages. As known, he sandard algorihm provides a FIFO allocaion of GTSs. Moreover, his approach reduces waiing imes of nodes compeing for he medium access using he CSMA/CA in conenion access period hrough a prioriy classificaion of nework raffic flows. An experimenal real scenario, based on he IEEE 82.15.4 sandard proocol, has been deployed in order o demonsrae benefis inroduced by his approach. Varying he conenion window (CW) and he backoff Exponenial (BE) parameers, i has been possible oproducearafficflowsclassificaionbasedonprioriies. Obainedresulsshowhowhighprioriynodeswillreach beer performance han hose wih lower prioriy. Measured 1 performances are generally beer han he IEEE 82.15.4 sandard ha does no differeniae nework raffic flows. References [1] Z. Ruyan, L. Huifang, H. Shijun, and W. Dongyun, Daa processing and node managemen in wireless sensor nework, in Proceedings of he 1s Inernaional Symposium on Compuer Nework and Mulimedia Technology (CNMT 9), pp. 1 4, December 29. [2] M. Colloa, G. Pau, V. M. Salerno, and G. Scaà, A fuzzy based algorihm o manage power consumpion in indusrial wireless sensor neworks, in Proceedings of he 9h IEEE Inernaional Conference on Indusrial Informaics (INDIN 11), pp. 151 156, 211. [3] M. Colloa, L. Genile, G. Pau, andg. Scaà, A dynamic algorihm o improve indusrial wireless sensor neworks managemen, in Proceedings of he 38h Annual Conference of IEEE Indusrial Elecronics (IECON 12),pp.282 287,212. [4] V. C. Gungor and G. P. Hancke, Indusrial wireless sensor neworks: challenges, design principles, and echnical approaches, IEEE Transacions on Indusrial Elecronics, vol.56,no.1,pp. 4258 4265, 29. [5] M. Colloa, L. Lo Bello, and O. Mirabella, An innovaive frequency hopping managemen mechanism for Blueooh-based indusrial neworks, in Proceedings of he 5h Inernaional SymposiumonIndusrialEmbeddedSysems(SIES 1),pp.45 5, July 21. [6] M. Colloa, V. Coni, G. Pau, G. Scaà, and S. Viabile, Fuzzy echniques for access and daa managemen in home auomaion environmens, Journal of Mobile Mulimedia, vol. 8, no. 3, pp. 181 23, 212. [7] Y. Li, J. Maorong, G. Zhenru, Z. Weiping, and G. Tao, Design of home auomaion sysem based on ZigBee wireless sensor nework, in Proceedings of he 1s Inernaional Conference on Informaion Science and Engineering (ICISE 9), pp. 261 2613, December 29.

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