A Coveage Ga Fllng Algothm n Hybd Senso Netwok Tan L, Yang Mnghua, Yu Chongchong, L Xuanya, Cheng Bn A Coveage Ga Fllng Algothm n Hybd Senso Netwok 1 Tan L, 2 Yang Mnghua, 3 Yu Chongchong, 4 L Xuanya, 5 Cheng Bn 1, Fst Autho Beng Technology and Busness Unvesty, tanl@th.btbu.edu.cn 2, Coesondng Autho Beng Insttute of Infomaton Technology, Unt 96627 of PLA, yang_mh@foxmal.com 3, Beng Technology and Busness Unvesty,chongzhy@v.sna.com 4, Beng Insttute of Technology, xuanya0214@sna.com 5, Beng Insttute of Technology, cbae@163.com Abstact Deloyment of senso netwoks s usually mlemented by andom thowng n a non-nvasve way. The deloyment ocess nevtably lead to netwok coveage holes, netwok slt, ovelaed coveage and othe ssues. In ode to move netwok coveage and maxmze netwok efomance, ths ae esents a netwok coveage ga fllng algothm (CGFA) based on chaactestcs of hybd netwok comosed of statc nodes and moble nodes. The algothm constucts a vtual foce feld between nodes and some ules ae defned to conduct the movng of moble nodes. Smulaton shows the nodes ae deloyed to cove the ga as much as ossble. The efomance of CGFA s comaed wth that of othe smla algothms and futhe vefes the effectveness of the algothm. Keywods: Weless Senso Netwok Hybd Deloyment Vtual Foce Coveage 1. Intoducton Weless senso netwok (WSN) s a mult-ho senso netwok comosed of gous of nodes wth weless tansmttes and eceves. Because of no need of netwok nfastuctue suot, WSN s easy to deloy and mlement, so WSN s wdely used n the cvl, mltay, ndustal and othe felds [1,2]. In the elevant eseach feld, an motant eseach focus s the oblem of deloyment of nodes, namely, how to deloy nodes to the taget aea n a easonable manne n ode to acheve the maxmzaton of netwok coveage. In hybd senso netwok, senso nodes consst of statc nodes and moble nodes. In addton to the sensng, comutng and communcaton caabltes, moble nodes also have some moblty and can be deloyed ndeendently accodng to self-deloyment algothm [3]. The eseach on coveage of hybd senso netwok can be dvded nto two asects: one s edeloyment of moble nodes to effectvely move netwok coveage, as n [4] the othe eles on the use of netwok moblty. To monto non-coveage aea ntemttently, the movement of moble nodes s constant. Ths ae focuses on the fst. In the comlex envonmental condtons, the node deloyment s usually aled by a andom thowng n non-nvasve way [5], whch easly leads to the uneven dstbuton of nodes n the netwok and esults n some oblems such as netwok dvson, coveage holes and ovelang coveage. So a lage numbe of nodes become useless. To ths end, afte deloyment of statc node, some moble nodes wth self-oganzng featue ae adoted to move netwok coveage efomance. In the followng Fgue 1, a statc netwok toology s shown. Clealy a lage numbe of gas exst. Unde deal condtons moble nodes automatcally deloy nto the gas. Fgue1. Coveage gas and holes Intenatonal Jounal of Advancements n Comutng Technology(IJACT) Volume4, Numbe4, Mach 2012 do: 10.4156/act.vol4.ssue4.24 192
A Coveage Ga Fllng Algothm n Hybd Senso Netwok Tan L, Yang Mnghua, Yu Chongchong, L Xuanya, Cheng Bn Recently the oblem on deloyment of hybd nodes has made some eseach achevements. Nguyen et al [6] oosed an enegy effcent dsatch algothm n whch node event locaton s mlemented by the statc, moble nodes ae n chage of the analyss of the ncdent. Mahbub et al [7] constucted a thee-te heteogeneous netwok stuctue, the cost functon s dven by the moble node movement to mnmze netwok load. Du X. et al [8] oosed a gd-based deloyment algothm accodng to moble node densty.by calculatng the gd densty moble nodes ae dven fom hghdensty aeas to low-densty aea to ncease the netwok coveage. Zhou Tong et al [9] also oosed to enhance hybd netwok coveage by HSDA algothm. In ae [10], a egonal coveage algothm s oosed. The taget netwok aea s dvded nto n2 vtual small squae, each vtual squae s numbeed and can be comletely coveed by one senso node. Afte ntal deloyment, each statc node belongs to a vtual squae and then moble nodes move to collect nfomaton on the dstbuton of the statc node. If some squaes ae found to not be occued by statc nodes, the moble nodes deend on collected nfomaton to detemne whethe to sto and be esonsble fo ths squae montong. In ae [11], the taget aea s also dvded nto seveal vtual gds, and the moble node can only move between adacent vtual gd. Each moble node s aanged though the exchange of nfomaton between nodes. The algothm tends to each a system balance. So the deloyment of senso nodes ae usually andom and ae one to fom coveage holes, whch esults n low netwok coveage. Geneally solutons to move netwok coveage ae to e-deloy some moble nodes to comensate fo coveage holes n the netwok. Ths ae esents a hybd netwok coveage ga fllng algothm based on vtual foces and some mechanze to futhe enhance netwok coveage. The emande of ths ae s oganzed as follows. The establshment of node model, fomulaton of foces, movement equaton and algothm descton ae descbed n Secton 2.Smulaton exement s addessed n Secton 3. Analyss and evaluatons s dscussed n Secton 4.Concluson s the fnal secton. 2. CGFA self-deloyment algothm Afte thowng to the deloyment aea, moble nodes wll move unde neghbo s attactve foces, eulsve foces and eulsve foces fom obstacles.moble nodes follow the esultant foce of attacton and eulson fom hgh otental felds to low otental felds.because otental felds n coveage gas and looholes s lowe o none, the moble nodes automatcally move along the gadent descent decton of otental feld and eventually deloy to local mnmum otental oston. Afte the ntal thowng, some moble nodes may have no neghbos. In ths condton, the moble node wll ente a andom seachng status untl t encountes a neghbo.because of attactve foces, all nodes ae one to move togethe to become clustes. 2.1 Node Model of CGFA Accodng to CGFA, the node model s as follows: Node model of CGFA as shown n Fgue 2 can be exessed by a 6-tule as ", s,, c,,, whee ( x, y ) s senso node coodnate. Each senso node can measue a cetan ange. The adus of eceton s senso adus s n the model. Each senso node can send and eceve by weless connecton, the communcaton dstance s communcaton adus of nodes c. s eulsve foce ange. If the dstance among nodes s between c and, the nodes ae fa neghbos s set of node s fa neghbos. If the dstance between nodes s and attactve foces ae fomed. less than,the nodes ae nea neghbos and eulsve foces ae aeaed. s set of node s nea neghbos. The elaton of s, and c s gven n Fgue 2, whee s c. The elaton of attactve foce and eulsve foce s shown n Fgue 3. A collecton of obstacles s O and moble nodes eceve eulsve foces fom them to kee away fom collson. 193
A Coveage Ga Fllng Algothm n Hybd Senso Netwok Tan L, Yang Mnghua, Yu Chongchong, L Xuanya, Cheng Bn Fgue2. Node model Fgue 3. Vtual foce egulaton Montong aea s a R R ectangle, some statc senso nodes and moble senso nodes ae andom deloyed n t, a hybd self-oganzng senso netwok aea. The assumtons of the oosed algothm ae as follows: 1. Snce most of the sensng devces ae sotoc, such as temeatue, humdty, lght and heat senstve senso, we may assume that the sensng ange of senso nodes s dsc-shaed, the sensng adus of statc nodes and moble nodes s the same adus. 2. The senso node communcaton model s also dsc-shaed and communcaton adus s seveal tmes than sensng adus. In the scoe of the communcaton adus, nodes can communcate wth each othe. 3. All the statc senso nodes n the netwok ae homogeneous and all moble nodes ae also homogeneous. Dffeent fom statc node, moble node can move feely. Othe chaactestcs of statc nodes and moble nodes ae the same. 4. Statc nodes and moble nodes can be self-ostonng, though GPS o some ostonng algothm [12,13]. 2.3 Fomulaton In hybd netwok, evey node eceves foce fom othe nodes o fom obstacles and begns to walk. Seveal vtual foce fomulatons ae oosed as follows: 1. The eulsve foce whch moble node eceves fom moble node s eesented n Equaton (1). n kmm FR 0 d(, ), (1) l d (, ) 1 whee d (, ) s dstance between node k s a constant, l s dstance coeffcent. and m s mass of node, the value usually s 1 2 The attactve foce whch moble node eceves fom moble node Equaton (2). (3). kmm F d whee ka s a constant, l a s dstance coeffcent, usuallyl A s eesented n n a " (, ) c, (2) la 1 d (, ) l. 3. The eulsve foce whch moble node eceves fom obstacle 1 whee ko s a constant, l o s dstance coeffcent. a s eesented n Equaton n kmm o FO 0 d (, ) L, O l (3) o d (, ) 194
A Coveage Ga Fllng Algothm n Hybd Senso Netwok Tan L, Yang Mnghua, Yu Chongchong, L Xuanya, Cheng Bn All nodes move unde the esultant foce and f the value of esultant foce s zeo, node stos at once. When the esultant foce s not zeo, node movement ule s descbed as Equaton (4). ( t t) F / F t v ( t) (4) Whee t stands fo tme nteval. Whee v stands fo aveage seed of node. 2.4 CGFA Algothm Descton CGFA algothm s a dstbuted algothm. Evey node executes ths algothm and moves smultaneously. Accodng to Equaton (4), the seudo code of CGFA algothm s descbed as below: 1 Intal ( xy, ), t, c,, s, 2 whle ( Any nodes s stll movng) 3 foeach ( node Collecton of nodes) 4 Calculate s and, M1 =,M2=, M3= 5 f (M1+ M2 + M3 ==0) 6 Move to andom oston ( xy, ) 7 else 8 Calculate s eulsve foce F R fom, accodng to Equaton(1), 9 Calculate s attactve foce F A fom, accodng to Equaton(2), " 10 Calculate s obstacle foce F A fom, accodng to Equaton(3), O 11 F FA FR FO 12 If ( F = = 0 ) then 13 Wat( t ) 14 else 15 Calculate movng decton F / F 16 Calculate new oston ( xy, ), by Equaton (4) 17 Move to new oston 18 endwhle 3. Smulaton The efomance of the CGFA algothm n ths ae s evaluated by smulato ONE. CGFA algothm has seveal motant aametes and the default values ae summazed n Table 1. Table1. Paamete of node Paamete Values Remaks s 20m Senso adus c 45m Communcaton adus 20m Reulsve adus v 1.5m/s Velocty t 0.1s Tme nteval 195
A Coveage Ga Fllng Algothm n Hybd Senso Netwok Tan L, Yang Mnghua, Yu Chongchong, L Xuanya, Cheng Bn In the exement, 400 statc nodes(black) and 200 moble nodes(blue) ae scatteed n a egon of sze 400 400 m2 at the begnnng. Moble nodes move unde CGFA and the deloyment ocess of ths hybd netwok s shown n Fgue 4-6. In Fgue 4, the 400 statc nodes ae scatteed n the egon andomly and seve gas and holes aea. In Fgue 5, 200 moble nodes ae added nto the feld and the coveage s 84.69%. Some aeas ae ovelaed and gas stll exst. In Fgue 6, moble nodes ae dven nto gas as much as ossble and ovelaed coveage between moble nodes and statc nodes s educed geatly. The coveage nceases to 91.95%. Fg 4. 400 statc nodes ntal Fg 5. 200 moble nodes added Fg 6. CGFA deloyment comlete In Fgue 7-8, movement of moble nodes such as P464 ae demonstated n detal (movng ath s shown n geen).node P464 ntally s solated, but though andom walk t fnd neghbos and ons the netwok unde the gudance of vtual attactve foces. Othe moble nodes also ty to cove the blank gas. Fgue 7. Coveage and quantty Fgue 8. Comason of dffeent algothms 4. Pefomance Analyss and Evaluaton In Fgue 9, the comason on node quantty and coveage s llustated. In CGFA, the ado of statc nodes and moble nodes s 2:1. Fom t we can conclude that CGFA needs fewe nodes at the same coveage. CGFA obvously nceases the coveage and saves moe nodes. 196
A Coveage Ga Fllng Algothm n Hybd Senso Netwok Tan L, Yang Mnghua, Yu Chongchong, L Xuanya, Cheng Bn Fgue 9. Coveage and quantty Refeence to [8], HSVA s an effcent method to deloy nodes n hybd netwok. In Fgue 10, the coveage s comaed n dffeent algothms accodng to the ado of 2:1. The esults show that CGFA acheves hghe coveage than HSDA snce CGFA bulds vtual attactve foce among nodes and solated moble nodes can on the netwok by actve seachng. Fgue 10. Comason of dffeent algothms 5. Concluson Hybd senso netwok takes the advantages of the hgh flexblty of moble nodes and low cost of statc nodes and becomes a omsng latfom fo many alcatons. In ths ae, a moved deloyment algothm s oosed to fll gas and holes of coveage and to emove ovelang. Smulaton esults have been used to vefy the oosed algothm. 6. Acknowledge Ths wok s suoted by Chnese Post-doctoal Scence Foundaton unde Gant 20100481501, Chnese Natonal Natue Scence Foundaton of Chna unde Gant 61063042 and Reseach Foundaton fo Youth Scholas of Beng Technology and Busness Unvesty. 7. Refeences [1] Hao Wang, Weless senso netwoks fo an extended cty ntellgent tansotaton system, Intenatonal Jounal of Advancements n Comutng Technology,vol.3,no.5,. 300-307, 2011. 197
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