無線傳感器網(wǎng)絡(luò)模型設(shè)計英文文獻翻譯(共18頁)

1、精選優(yōu)質(zhì)文檔-傾情為你奉上Model Design of Wireless Sensor Network based on Scale-Free Network TheoryABSTRACTThe key issue of researches on wireless sensor networks is to balance the energy costs across the whole network and to enhance the robustness in order to extend the survival time of the whole sensor networ

2、k. As a special complex network limited especially by the environment, sensor network is much different from the traditional complex networks, such as Internet network, ecological network, social network and etc. It is necessary to introduce a way of how to study wireless sensor network by complex n

3、etwork theory and analysis methods, the key of which lies in a successful modeling which is able to make complex network theory and analysis methods more suitable for the application of wireless sensor network in order to achieve the optimization of some certain network characteristics of wireless s

4、ensor network. Based on generation rules of traditional scale-free networks, this paper added several restrictions to the improved model. The simulation result shows that improvements made in this paper have made the entire network have a better robustness to the random failure and the energy costs

5、are more balanced and reasonable. This improved model which is based on the complex network theory proves more applicable to the research of wireless sensor network.Key-words: Wireless sensor network; Complex network; Scale-free networkI. INTRODUCTIONIn recent years, wireless sensor networks have at

6、tracted more and more related researchers for its advantages. Sensor nodes are usually low-power and non-rechargeable. The integrity of the original networks will be destroyed and other nodes will have more business burden for data transmission if the energy of some certain nodes deplete. The key is

7、sue of sensor network research is to balance the energy consumption of all sensor nodes and to minimize the impact of random failure of sensor nodes or random attacks to sensor nodes on the entire network 1.Complex network theory has been for some time since first proposed by Barabasi and Albert in

8、1998, but complex network theory and analysis method applied to wireless sensor networks research is seriously rare and develops in slow progress. As a special complex network limited especially by the environment, sensor network is much different from the traditional complex network, and the existi

9、ng complex network theory and analysis methods can not be directly applied to analyze sensor networks. Based on scale-free network theory (BA model 2, (1 this paper added a random damage mechanism to each sensor node when deployed in the generation rule; (2 considering the real statement of wireless

10、 sensor networks, a minimum and maxinum restriction on sensor communication radius was added to each sensor node; (3 in order to maintain a balanced energy comsuption of the entire network, this paper added a limited degree of saturation value to each sensor node. This improved scale-free model not

11、only has the mentioned improvements above, but also has lots of advantages of traditional scale-free networks, such as the good ability to resist random attacks, so that the existing theory and analysis methods of complex network will be more suitable for the researches of wireless sensor network.II

12、. PROGRESS OF RELATED RESEARCHHailin Zhu and Hong Luo have proposed two complex networks-based models for wireless sensor networks 3, the first of which named Energy-aware evolution model (EAEM can organize the networks in an energy-efficient way, and can produce scale-free networks which can improv

13、e the networks reliance against random failure of the sensor nodes. In the second model named Energy-balanced evolution model (EBEM, the maximum number of links for each node is introduced into the algorithm, which can make energy consumption more balanced than the previous model (EAEM.CHEN Lijun an

14、d MAO Yingchi have proposed a topology control of wireless sensor networks under an average degree constraint 4. In the precondition of the topology connectivity of wireless sensor networks, how to solve the sparseness of the network topology is a very important problem in a large number of sensor n

15、odes deployed randomly. They proved their proposed scheme can decrease working nodes, guarantee network topology sparseness, predigest routing complexity and prolong network survival period.LEI Ming and LI Deshi have proposed a research on self-organization reliability of wireless sensor network5, w

16、hich aiming on the two situations: deficiency of WSN nodes and under external attack, analyzes the error tolerance ability of different topologies of WSN, and eventually obtains optimized selforganized topological models of WSN and proposes a refined routing algorithm based on WSN.III. IMPROVED SCAL

17、E-FREE MODEL FOR WSNBecause of the limited energy and the evil application environment, wireless sensor networks may easily collapse when some certain sensor nodes are of energy depletion or destruction by the nature, and even some sensor nodes have been damaged when deployed. There is also a restri

18、ction on maxinum and mininum communication radius of sensor nodes rather than the other known scale-free networks such as Internet network, which has no restriction on communication radius. To have a balanced energy consumption, it is necessary to set up a saturation value limited degree of each sen

19、sor node 6.In response to these points, based on the traditional scale-free model, this paper has made the following improvements in the process of model establishment:(1 A large number of researches have shown that many complex networks in nature are not only the result from internal forces, but al

20、so the result from external forces which should not be ignored to form an entire complex network. Node failure may not only occour by node energy depletion or random attacks to them when sensor networks are in the working progress, but also occour by external forces, such as by the nature, when depl

21、oyed. In this paper, a mechanism of small probability of random damage has been added to the formation of sensor networks.(2 Unlike Internet network where two nodes are able to connect directly to each other and their connection are never limited by their real location, sensor network, two nodes in

22、which connect to each other by the way of multi-hop, so that each node has a maximum of length restriction on their communication radius. To ensure the sparse of the whole network, there must also be a minimum of length restriction on their communication radius. In this paper, a length restriction o

23、n communication radius of sensor nodes has been proposed in the improved model.(3 In sensor network, if there exists a sensor node with a seriously high degree, whose energy consumption is very quickly, it will be seriously bad. The whole sensor network would surely collapse if enough energy were no

24、t supported to the certain node. To avoid this situation, this paper has set up a saturation value limited degree of each sensor node. By adding the mentioned restrictions above to the formation of the scale-free model, the new improved model will be more in line with the real statement of sensor ne

25、twork. Complex network theory and analysis methods will be more appropriate when used to research and analyze the sensor network.IV . DESCRIPTION OF THE IMPROVED ALGORITHMThe specific algorithm of the improved model formation are described as follows :(1 A given region (assumed to be square is divid

26、ed into HS*HSbig squares (named as BS;(2 Each BS (assumed to be square is divided into LS*LS small squares (named as SS, and each SS can have only one node in its coverage region;(3 m0 backbone nodes are initially generated as a random graph, and then a new node will be added to the network to conne

27、ct the existing m nodes with m edges at each time interval. (m< m0, mis a quantity parameter;(4 The newly generated node v, has a certain probability of Peto be damaged directly so that it will never be connected with any existing nodes;(5 The newly generated node vconnects with the existing node

28、 i, which obeyes dependent-preference rule and is surely limited by the degree of the certain saturation value .(6 The distance div between the newly generated node v connects and the existing node i shall be shorter than the maximum dmax of the communication radius of sensor nodes.Above all, the pr

29、obability that the existing node i will be connected with the newly generated node v can be shown as follows:In order to compute it conveniently, here assumed that few nodes had reached the degree of saturation value kimax . That is, N is very minimal in Eqs.(1 so that it can be ignored here. And in

30、 Eqs.iN j 1ak Kj=0N=m 1t +- (2With The varying rate with time of ki, we get:0m 112i i i i t jj k amk amk m t mt m k +-=- (3When t,condition: k i (t i =m, we get the solution: i 2,i t k t a=(t =m (4 The probability that the degree of node I is smaller than k is:11k (tkPt i i m t P k <=> (5The t

31、ime interval when each newly generated node connected into the network is equal, so that probability density of t i is a constant parameter:01(t i P m t=+1/ we replace it into Eqs. (5, then we get:11111k (tkPt 1(t i m t k i i i t m t P P k =<=>=- (61101(t m m t k -+ So we get: 110(k (tk21(k.i

32、P m t P k m t k <=+ (7 When t , we get:2(k2m r P k -= (8 In which 12=1+=1+a , and the degree distribution we get and the degree distribution of traditional scale-free network are similar. Approximately, it has nothing to do with the time parameter t and the quantity of edges m generated at each t

33、ime interval.max Pd d iv could be calculated by the max in um restriction dmax on communicationradius of each sensor node and the area of the entire coverage region S, thatis max Pd d iv =2Sd Then we replace max Pd d iv =2S d and a=max Pd d iv (1-P e into Eqs. and eventually we get:2S 21122(k2m 2e a

34、 P km k -= (1-P d .V. SIMULATIONThis paper used Java GUI mode of BRITE topology generator to generate the topology, and parameter settings were as follows:1 N=5000N means the quantity of the sensor nodes at the end of thetopology generation.2 m=m0 =1M means the quantity of the new generated edges by

35、 the new generated node at each time interval.3 HS=500HS means the given region was divided into HS*HS big squares.4 .LS=50 LS means each big square was divided into LS*LS small squares.d=105 mind is the mininum restriction on communication radius of each sensor node.mind=1286 maxd is the maxinum re

36、striction on communication radius of each sensor node.max7 PC=1PC means wether preferential connectivity or not.8 .IG=1IG means wether incremental grouth or not.9 e P=0.01, m=1This means that any newly generated node has 1% chance to be node failure and the newly generated node if normal only connec

37、t with one existing node .Then we got each degree of the sensor network nodes from BRITE topology generator.To analyze the degree distribution, we use Matlab to calculate datas and draw graph. As can easily be seen from Fig. 1, the distribution of degree k subjected approximately to Power-Law distri

38、bution. However, the value of is no longer between 2 and 3, but a very large value, which is caused by the random damage probability P e to new generated nodes when deployed and the max in um of communication radius d max of each sensor node. It can be easily seen that the slope of P(k is very steep

39、 and P(k rears up because sensor node has a limited degree of saturation value by 180. The existence of 0 degree nodes is result from the random damage to new generated nodes when deployed. Fig. 1 Degree distribution of Improved ModelCompared with the degree distribution produced by traditional scal

40、e-free network as is shown in Fig. 2, the generation rule proposed in this paper has produced a degree distribution in a relatively low value as is shown in Fig. 1; there are some nodes of 0 degree as is shown in Fig. 1 on the left for the random damage rule; as is shown on the right in Fig. 1, ther

41、e are no nodes with higher degree than the quantity of 180 while there are some nodes whose degree are of higher degree than the quantity of 180. Fig. 2 Degree distribution of traditional Scale-free ModelVI. CONCLUSIONThis paper has added a random damage to new generated nodes when deployed; conside

42、ring multi-hop transmission of sensor network, this paper has proposed a maximum restriction on the communication radius of each sensor node; in order to improve the efficiency of energy comsumption and maintain the sparsity of the entire network, this paper has also added a minimum restriction on t

43、he communication radius of each sensor node to the improved model; to balance the energy comsuption of the entire network, this paper has proposed a limited degree of saturation value on each sensor node.In this paper, an improved scale-free network model was proposed to introduce the theory of trad

44、itional scale-free network and analysis methods into the researches of wireless sensor networks more appropriately, which would be more approximate to the real statement of wireless sensor networks.REFERENCES1 R. Albert, H. Jeong and A.-L. Barabasi. Error and attack tolerance of complex networks. Na

45、ture, 2000; 406: 378-382.2 Albert R, Barabasi A. Statistical mechanics of complex networks. Rev Mod Phys 2002; 74: 4797.3 Zhu HL, Luo H. Complex networks-based energy-efficient evolution model for wireless sensor networks. Chaos, Solitons and Fractals; 2008: 1-4.4 Chen LJ, Mao YC. Topology Control o

46、f Wireless Sensor Networks Under an Average Degree Constraint. Chinese Journal of computers 2007; 30: 1-4.5 Lei M, Li DS. Research on Self-Organization Reliability of Wireless Sensor Network . Complex system and complexity science ; 2005, 2: 1-4.6 Chen LJ, Chen DX. Evolution of wireless sensor netwo

47、rk . WCNC 2007; 556: 30037.7 Peng J, Li Z. An Improved Evolution Model of Scale-Free Network . Computer application. 2008 , 2; 1: 1-4.基于無范圍網(wǎng)絡(luò)理論的無線傳感器網(wǎng)絡(luò)模型設(shè)計張戌源通信工程部通信與信息工程學(xué)院上海,中國摘要無線傳感器網(wǎng)絡(luò)的研究的關(guān)鍵問題是是平衡整個網(wǎng)絡(luò)中的能源成本并且為了延長整個傳感器網(wǎng)絡(luò)的生存時間要增強魯棒性。作為一個特殊的復(fù)雜網(wǎng)絡(luò)特別是由于環(huán)境的限制,傳感器網(wǎng)絡(luò)很不同于傳統(tǒng)的復(fù)雜的網(wǎng)絡(luò),例如Internet網(wǎng)絡(luò),生態(tài)網(wǎng)絡(luò),社交網(wǎng)絡(luò)等。這就有

48、必要來介紹一種通過復(fù)雜網(wǎng)絡(luò)理論和分析方法如何研究無線傳感器網(wǎng)絡(luò)的方式,其中的關(guān)鍵在于能夠作出一個成功的建模,它能夠使復(fù)雜網(wǎng)絡(luò)理論和分析方法更適合無線傳感器網(wǎng)絡(luò)的應(yīng)用,以達到根據(jù)某些特定無線傳感器網(wǎng)絡(luò)的特點進行優(yōu)化?；趥鹘y(tǒng)的無尺度的網(wǎng)絡(luò)生成規(guī)則,本文對改進后的模型增加了一些限制。仿真結(jié)果表明,在本文中進行的改進,使整個網(wǎng)絡(luò)對隨機故障有一個更好的魯棒性并且能源成本更平衡和合理。這種基于復(fù)雜網(wǎng)絡(luò)理論的改進模型證明更適用于無線傳感器網(wǎng)絡(luò)的研究。關(guān)鍵詞:無線傳感器網(wǎng)絡(luò),復(fù)雜網(wǎng)絡(luò),無尺度網(wǎng)絡(luò)引言近年來,由于無線傳感器網(wǎng)絡(luò)的優(yōu)點,吸引了越來越多的相關(guān)研究人員。傳感器節(jié)點通常是低功率和非可再充電的。如果某些

49、節(jié)點的能量消耗完,原來網(wǎng)絡(luò)的完整性將被破壞并且其他進行數(shù)據(jù)傳輸?shù)墓?jié)點,會有更多的業(yè)務(wù)負擔(dān)。傳感器網(wǎng)絡(luò)的研究的關(guān)鍵問題是是平衡所有的傳感器節(jié)點能源消耗和把傳感器節(jié)點隨機錯誤影響或者是對整個網(wǎng)絡(luò)的傳感器節(jié)點隨機攻擊降到最低。復(fù)雜網(wǎng)絡(luò)理論,自從Barabasi和Albert在1998年提出已經(jīng)有一段時間了,但應(yīng)用于無線傳感器網(wǎng)絡(luò)的復(fù)雜網(wǎng)絡(luò)理論和分析方法研究嚴(yán)重稀缺并且開發(fā)進展緩慢。作為一個尤其是環(huán)境的限制特殊的復(fù)雜的網(wǎng)絡(luò),傳感器網(wǎng)絡(luò)是遠遠不同于傳統(tǒng)的復(fù)雜網(wǎng)絡(luò)并且現(xiàn)有的復(fù)雜網(wǎng)絡(luò)理論和分析法不能直接應(yīng)用到分析傳感器網(wǎng)絡(luò)上?；跓o標(biāo)度網(wǎng)絡(luò)理論(BA模型2,(1本文中當(dāng)部署在生成規(guī)則時添加到每個傳感器節(jié)點隨

50、機損傷機制(2考慮到無線傳感器網(wǎng)絡(luò)的實際聲明,傳感器通信半徑參數(shù)最大和最小限制添加到每個傳感器節(jié)點; (3為了維持整個網(wǎng)絡(luò)平衡的的能源消耗率,本文每個傳感器節(jié)點加入了和度值的限度。這對無尺度模型改善不僅提到是以上的改善,而且還具有傳統(tǒng)的無標(biāo)度網(wǎng)絡(luò)大量的優(yōu)點,如很好的抵抗隨機的攻擊的能力,從而使現(xiàn)有的復(fù)雜網(wǎng)絡(luò)的理論和分析方法,將是更適合于無線傳感器網(wǎng)絡(luò)的研究。相關(guān)的研究進展海林朱和香羅提出了兩種復(fù)雜的基于網(wǎng)絡(luò)的無線傳感器網(wǎng)絡(luò)模型3,第一個名叫能量感知的演化模型(EAEM可以以高效節(jié)能的方式組織網(wǎng)絡(luò),并能產(chǎn)生無尺度網(wǎng)絡(luò),它可以提高網(wǎng)絡(luò)抵御傳感器節(jié)點隨機失誤的可靠性。第二個模型命名為能量均衡演化模型

51、(EBEM,為每個節(jié)點的最大鏈接數(shù)被引入算法,它可以使能源消費比以前的型號更均衡(EAEM。陳立軍和毛馳提出了拓撲無線傳感器網(wǎng)絡(luò)控制下平均程度約束條件4。在無線傳感器網(wǎng)絡(luò)拓撲連通性的前提下,在大量的隨機部署的傳感器節(jié)點中,如何解決稀疏性網(wǎng)絡(luò)的拓撲結(jié)構(gòu)是一個非常重要的問題。他們證明了自己的方案可以減少工作節(jié)點,保證網(wǎng)絡(luò)拓撲稀疏,簡化路由的復(fù)雜性和延長網(wǎng)絡(luò)的生存期。雷鳴和李德氏提出了自組織無線傳感器網(wǎng)絡(luò)的可靠性的研究5,這針對兩種情況:缺乏WSN節(jié)點和外部的攻擊下,分析了不同拓撲結(jié)構(gòu)的無線傳感器網(wǎng)絡(luò)錯誤的耐受能力,并最終獲得優(yōu)化自組織的無線傳感器網(wǎng)絡(luò)的拓撲模型,并提出了基于無線傳感器網(wǎng)絡(luò)的精制路由

52、算法。改進的無標(biāo)度模型的WSN由于能量有限和惡劣的應(yīng)用環(huán)境,某些傳感器節(jié)點的能量耗盡或被自然力損壞,無線傳感器網(wǎng)絡(luò)會很容易遭到破壞,甚至還有一些傳感器節(jié)點被部署時已經(jīng)損壞。還設(shè)有一個限制最大限度和最低限度的傳感器節(jié)點的通信半徑,而不是其它已知的無標(biāo)度網(wǎng)絡(luò),如互聯(lián)網(wǎng)絡(luò),它沒有限制通信半徑。為了有一個平衡的能源消耗,有必要設(shè)置一個傳感器的有限度的飽和度值6。為了回答這些要點,根據(jù)傳統(tǒng)的無標(biāo)度模型,模型建立的過程中本文已做出以下改進:(1大量的研究表明,許多在本質(zhì)上是復(fù)雜的網(wǎng)絡(luò)不僅是內(nèi)力,也是外部勢力的結(jié)果。形成一個完整的復(fù)雜網(wǎng)絡(luò)時,這不應(yīng)被忽略。在傳感器網(wǎng)絡(luò)工作的進展中,節(jié)點故障不僅可能出現(xiàn)在節(jié)點

53、的能量消耗或他們遭受隨機攻擊時,也出現(xiàn)在外力情況下,如當(dāng)部署時的自然力。本文一種小概率的隨機損傷機制已被添加到傳感器網(wǎng)絡(luò)的形成中。(2不同于互聯(lián)網(wǎng)網(wǎng)絡(luò),其中能夠直接連接到彼此兩個節(jié)點,它們的連接永遠不會受到真實位置的限制,無線傳感器網(wǎng)絡(luò),兩個相連的節(jié)點由多跳(multi-hop的方式彼此連接,使每個節(jié)點在通信半徑上都有一個最大長度的限制。為了確保全網(wǎng)絡(luò)的稀疏性,還必須是有一個最小長度的通信半徑限制。在本文中,改進后的模型中。傳感器節(jié)點的通信半徑長度的限制,已經(jīng)提出來了。(3在無線傳感器網(wǎng)絡(luò),如果存在一個傳感器很高的節(jié)點,其能源消耗是非?？?它會嚴(yán)重不利。如果沒有足夠的能量支持某個節(jié)點,整個傳感

54、器網(wǎng)絡(luò)一定會崩潰,。為了避免這種情況,本文在每個傳感器節(jié)點建立了一個飽和值限度。通過加入上述提到的限制形成無尺度的模式,改進后的新模型將更加符合傳感器網(wǎng)絡(luò)的真實陳述。復(fù)雜網(wǎng)絡(luò)理論和分析方法將更加適合用來研究和分析傳感器網(wǎng)絡(luò)。改進算法說明具體算法改進模型形成描述如下:給定的區(qū)域(假設(shè)是正方形(1分為HS* HS 正方形(命名為BS ;(2每個BS (假設(shè)是正方形分為LS* LS 小正方形(命名為SS ,并且每個SS 中在其覆蓋區(qū)域只能有一個節(jié)點;(3M0骨干節(jié)點最初作為一個隨機產(chǎn)生的圖形,然后一個新的節(jié)點將被添加到網(wǎng)絡(luò)以每次有m 條邊連接現(xiàn)有的m 個節(jié)點的時間間隔。 (M0 M ,m 是一個量參

55、數(shù);(4對新生成的節(jié)點v ,具有一定的直接被損壞概率P ,這樣它會永遠不與任何現(xiàn)有的節(jié)點連接;(5新生成的節(jié)點v 與現(xiàn)有的連接節(jié)點i 連接,服從依賴優(yōu)先規(guī)則,肯定是被確定的目標(biāo)飽和度值k 限制;(6d 和新生成的節(jié)點V 連接并且與現(xiàn)存的節(jié)點I 之間的距離將比傳感器通信半徑最大距離max d 更短?？傊?現(xiàn)有節(jié)點的概率,我將連接與新生成的節(jié)點v 可以表示為如下:為了計算方便,這里假設(shè)幾個節(jié)點已經(jīng)達到了飽和值達到。所以上式可以被寫為: iN j 1ak Kj=0N=m 1t +-隨著i k 隨時間的變化率,我們得到:0m 112i i i i t jj k amk amk m t mt m k +-=- 當(dāng)t 趨近無窮大時,根據(jù)初始條件,i k (t =m ,我們的到結(jié)論:i 2,i t k t a=(t =m ( 節(jié)點i 的度比k 小的概率是:11k (tkPt i i