網際網路技術學刊 Journal of Internet Technology

發行人：趙涵捷 Publisher: Han-Chieh Chao 出版者：台灣學術網路管理委員會 Published by: Academic Network Executive Committee 發行所：國立宜蘭大學 Publication Office: National Ilan 宜蘭縣宜蘭市神農路1段1號 Yilan, Taiwan, ROC Airiti Press Inc.（台北辦公室） Airiti Press Inc. 新北市永和區成功路一段80號18樓 Yonghe Dist., New Taipei City, Taiwan, ROC 協辦單位：國立東華大學電機系 Department of Electrical Engineering, National Dong Hwa University Shou-Feng, Hualien, Taiwan, ROC 指導單位：教育部 Supervisor: Ministry of Education, Taiwan, ROC 編輯委員會： Editorial Board: 主任委員：何榮桂 Board Chairman: Rong Guey He 總編輯：趙涵捷 Editor-in-Chief: Han-Chieh Chao 副總編輯：陳懷恩、朱彥明、賴槿峰 Associate Editor-in-Chief: Whai-En Chen, Yen-Ming Chu, Chin-Feng Lai 助理編輯：黃珮珊 Assistant Editor: Pei-Shan Huang 委員： Editors: 中研院計中主任：王大為 Academic Sinica: Da-Wei Wang 台大計中主任：孫雅麗 National Taiwan University: Yea-Li Sun 政大計中主任：楊亨利 National Chengchi University: Heng-Li Yang 中央計中主任：李允中 National Central University: Wan-Chung Lee 交大資訊中心主任：蔡錫鈞 National Chiao Tung University: Shi-Chun Tsai 中興計中主任：呂瑞麟 National Chung Hsing University: Jui-Lin Lu 中正計中主任：李新林 National Chung Cheng University: Sing-Ling Lee 成大計中主任：陳響亮 National Cheng Kung University: Shang-Liang Chen 中山圖資處處長：李錫智 National Sun Yat-Sen University: Shie-Jue Lee 東華資網中心主任：黃振榮 National Dong Hwa University: Chenn-Jung Huang 宜大圖資館館長：陳偉銘 National Ilan University: Wei-Ming Chen 暨南計中主任：吳坤熹 National Chi Nan University: Quincy Wu 東大計中主任：郭達源 National Taitung University: Tah-Yuan Kuo 台大電機系教授：郭斯彥 National Taiwan University: Sy-Yen Kuo 清大資工系教授：黃能富 National Tsing Hua University: Nen-Fu Huang 亞洲大學副校長：曾憲雄 : Shian-Shyong Tseng 交大電信系教授：張仲儒 National Chiao Tung University: Chung-Ju Chang 成大電機系教授：陳立祥 National Cheng Kung University: Lih-Shyang Chen 東華資工系教授：張瑞雄 National Dong Hwa University: Ruay-Shiung Chang 中央大學資工系教授：施國琛 National Central University: Timothy K. Shih 成大工科系教授：黃悅民 National Cheng Kung University: Yueh-Min Huang 成大電機系教授：楊竹星 National Cheng Kung University: Chu-Sing Yang 台北大學資工系教授：陳裕賢 National Taipei University: Yuh-Shyan Chen 台科大電機系教授：韓永祥 National Taiwan University of Science and Technology: Yung-Hsiang Sam Han Osaka University: Lei Shu Huazhong University of Science and Technology: Min Chen NEC Europe Ltd: Juergen Quittek Kuwait University: Mohsen Guizani University of Canterbury: Ray Hunt Bell Laboratories: Daniel G. Waddington Staffordshire University: Lorna Uden Tokyo University: Hiroshi Esaki Berlin Technology University: Odej Kao Technological Education Institute of Piraeus: Charalampos Z. Patrikakis Ohio State University: Hojjat Adeli University of the District of Columbia: Sherali Zeadally Strayer University: Naixue Xiong University of Western Ontraio: Abdallah Shami University of Murcia: Gregorio Martinez Seoul of Technology: Jong Hyuk Park (Liaison Wonkweng University: Young-Sik Jeong editor for Korea)

00-1-編委會(封面裡).indd 1 2012/5/29 下午 10:55:20 Information for Authors

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16-投稿須知.indd 1 2012/5/24 下午 10:22:28 (1) Journal: Han-Chieh Chao, Reen-Cheng Wang and Jiann-Liang Chen, The Novel Network Topology Based Domain Name Service with Mobile Computing Consideration, J. Microcomputer Applications, Vol.18, No.3, 1999, pp.279-296. (2) Books: Jean-Jacques Slotine and Weiping Li, Applied Nonlinear Control, Prentice Hall, Englewood Cliffs, NJ, 1991, pp.100-105. (3) Proceedings: Nen-Fu Huang, Ko-Shung Chen, Han-Chieh Chao and Jen-Yi Pen, A Distributed Multicast Tree Migration Scheme for ATM Based Personal Communication Networks, Proc. IEEE Globecom, London, November, 1996, pp.201-206. (4) Theses: Andrew Pllard, Flow in Tee Junction, Ph.D. Thesis, University of London, London, UK, 1978. (5) Reports: Rajeev Agrawal and Rajendran Rajan, Performance bounds for guaranteed and adaptive services, December, 1996. IBM Technical Report RC 20649. The sample format can be download from http://jit.ndhu.edu.tw/doc/002.doc Manuscripts should be submitted to http://aspers.airiti.com/jit/WebOnline.aspx

Correspondence Journal of Internet Technology Library and Information Center, National Ilan University No. 1, Sec. 1, Shennong Rd., , Yilan County 260, Taiwan, ROC Tel: +886-3-9317017 Fax: +886-3-9363756 E-mail: [email protected]

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Contents Invited Paper 1. A Framework for Bottleneck Analysis in High-Performance Software Design...... 369 Issa Traore, Isaac Woungang, Ahmed Awad El Sayed Ahmed, Mohammed S. Obaidat

Regular Paper 1. BCHED -- Energy Balanced Sub-Round Local Topology Management for Wireless Sensor Network...... 385 Wei Zhang, Naixue Xiong, Laurence T. Yang, Gangmin Jia, Jilin Zhang 2. An Asynchronous Duty Cycle Adjustment MAC Protocol for Wireless Sensor Networks...... 395 Yu-Chia Chang, Jehn-Ruey Jiang, Jang-Ping Sheu 3. Improvement on a Smart Card Based Password Authentication Scheme...... 405 Debiao He, Jianhua Chen, Jin Hu 4. Practical Remote Mutual Authentication with Key Agreement Scheme for Mobile Devices on Elliptic Curve Cryptosystem...... 411 Shuhua Wu, Fei Kang, Qiong Pu 5. Service Protocol Adaptability Assessment for Supporting Mediated Service Interactions...... 419 ZhangBing Zhou, Lei Shu, Jianwei Niu 6. A Simple Keystroke Dynamics-Based Authentication System Using Means and Standard Deviations...... 439 Chao-Liang Liu, Ting-Yi Chang, Mao-Lun Chiang, Cheng-Jung Tsai 7. Mobile Agent Based Resource Monitoring for Job Submission in Grid with Virtual Database...... 445 C. Valliyammai, S. Thamarai Selvi 8. Identifying P2P Applications Using Ensemble Learning and Co-Training...... 453 Jian-Min Wang, Cheng-Lu Qian, Chun-Hui Che, Hai-Tao He, Fang You 9. A Secure Dynamic Identity Based Remote User Authentication Scheme Using Secret Sharing...... 463 Yun Liu, Zi-Yao Cheng, Chin-Chen Chang, Zhen-Jiang Zhang 10. Tone Placement Methods for PAPR Reduction under the SSPA-Type Nonlinear HPA Model...... 471 Soobum Cho, Sang Kyu Park

Special Issue on Computer Image, Graphics and Application in Ubiquitous Environment 1. Requirement Analysis and System Synthesis Technique for FIC Applications...... 479 Eunyoung Lee 2. Quality of VoIP in WiMAX and UMTS...... 491 Sheetal Jadhav, Haibo Zhang, Zhiyi Huang 3. CSP Based Web Service Composition Model with Buffer at the Business Logic Process Level...... 501 Hwa-Young Jeong, Yang Sun Lee 4. A Context Awareness and Prediction Support System for Efficient Management of U-City...... 509 Jae-Hyuk Cho 5. A Quantitative Comparison of Memory Allocators for Multicore and Multithread Applications...... 521 Taís Borges Ferreira, Rivalino Matias, Jr., Autran Macêdo, Lucio Borges de Araújo

00-3Contents.indd 1 2012/5/29 下午 10:48:12 BCHED -- Energy Balanced Sub-Round Local Topology Management for Wireless Sensor Network 385

BCHED -- Energy Balanced Sub-Round Local Topology Management for Wireless Sensor Network

Wei Zhang1, Naixue Xiong2, Laurence T. Yang3, Gangmin Jia1, Jilin Zhang1 1School of Computer Science and Technology, Hangzhou Dianzi University, China 2School of Information Technology, Jiangxi University of Finance and Economics, China 3Department of Computer Science, St. Francis Xavier University, Canada {magherozhw, xiongnaixue}@gmail.com, [email protected], [email protected], [email protected]

Abstract Topology controlling is one of the key technologies to achieve this goal. The hierarchical topology control Topology controlling based on cluster structure is algorithm introduces the concept of network cluster which an important method to improve the energy efficiency divides the monitoring nodes in the object area into a of wireless sensor network (WSN) systems. Frequent number of subsets [5]. Each cluster consists of a cluster clustering process of classical controlling methods, such as head and some ordinary nodes. The algorithm makes LEACH, is apt to cause serious energy consuming. Some qualified nodes to be cluster head nodes, which integrates improved methods reduced re-clustering frequency, but data from ordinary nodes and forwards it. these methods sometimes lead to energy imbalance in the In this paper, we shall discuss and study the key issues stable communication period. In this paper, a hierarchical of hierarchical topology controlling, and a hierarchical topology controlling method BCHED is proposed. With topology control algorithm called BCHED will be proposed double round clustering mechanism, BCHED activates to help balancing the energy consumption of nodes in a local re-clustering process between two rounds of data wireless sensor networks, so that the network lifetime can transmission, and with optional cluster head exchanging be extended. The remainder of this paper is organized as mechanism, BCHED reorganize the node clusters according follows. Section 2 briefly surveys the related works. Section to their residual energy distribution. Experimental results 3 describes the network model and the problem we try to show that, with BCHED, the energy balance performance handle. Section 4 presents the BCHED protocol. Section of WSN system is significantly improved, and the system 5 evaluates the performance of BCHED by analyzing the lifetime can be effectively extended. result of some experiments compared with some typical topology controlling protocols and Section 6 concludes the Keywords: Wireless sensor network, Topology controlling, paper. Network clustering. 2 Related Works 1 Introduction In order to improve the energy efficiency of wireless Wireless sensor networks are usually composed of sensor network, and to enhance its robustness and stability, a large number of cheap nodes randomly distributed in a a series of in-depth research on topology controlling method specific area. Through mutual cooperation, these nodes can has been made. At present, there are two main directions in collect the data packets with useful information (such as this research field: node power controlling and hierarchical temperature, humidity, etc.). Then, the information in the topology controlling [6]. (1) Node power controlling. network data packets is processed and sent to an observer Without considering the antenna device, the node coverage node (or sink node) [1]. Wireless sensor network is a bridge was round. With the increasing of transmission power, the between natural environment and information world, which coverage area of each nodes shall increase accordingly. has broad application prospects, such as military defense, If the each node always employ its maximum power to environmental monitoring and so on. Nevertheless, wireless communicate with all other nodes, there should be a waste sensor networks have obvious limitations. The energy of energy to some extent. The node power controlling resource limitation of wireless sensor networks is quite method can improve the energy efficiency by adjusting serious since the actual sensor nodes are usually battery- the transition power of each node. (2) Hierarchical powered tiny embedded systems [2-4]. Accordingly, topology controlling. This method introduces the concept considering the lifetime of wireless sensor networks, of network cluster which divides the monitoring nodes in improving the energy efficiency is one of the primary the object area into a number of subsets [1-2]. Each cluster design goals for wireless sensor networks. consists of a cluster head and some ordinary nodes. The algorithm makes qualified nodes to be cluster head nodes,

*Corresponding author: Naixue Xiong; E-mail: [email protected]

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which integrates data from ordinary nodes and forwards EEDRCP algorithm improves LEACH algorithm in it. Ordinary nodes in the cluster periodically switch the stable period by exchanging cluster head every two between sleep and work status, so that the network energy rounds of data communication. However, if the residual consumption shall decrease and the network lifetime can be energy of the current cluster head is much greater than prolonged. any other node in the cluster, the cluster head exchanging AS a typical node power controlling method, Kawadia mechanism of EEDRCP shall employ an ordinary node proposed the CAMPOW [7] algorithm. COMPOW forces to replace it. Finally, it will help to relief the problem of all nodes to use the same level of power which is simple energy imbalance. Muti-level cluster is also promising and can decrease the communication cost. But, when mechanism to save energy of WSN, with PEHC protocol the wireless network nodes are unevenly distributed, the [13], higher-level clusters are only used for inter-cluster minimum power to ensure the connectivity among the communication between cluster heads and the base station node in the area with some sparse regions can be much so that transmission energy is minimized. higher. According to the rule of CAMPOW, the energy consumption in other nodes will also increase sharply 3 Problem Statement even if they are in the dense regions and then the energy efficiency of the whole system shall decrease sharply as a The wireless sensor network we studied is composed result. CLUSTERPOW [8] improved CAMPOW algorithm of n nodes and a sink node. Each node has a unique ID by dividing a network into clusters according to the route number, and it is randomly distributed in a region of M × relationship and energy constraint among nodes, and each M. The network can be considered as a graph G = (V, E), node adjust its own power lever according to its cluster where V denotes the set of nodes and E represents the set level relationship. By these means, CLUSTERPOW can of links [14]. For any two nodes, if their distance is less avoid the problem that too many nodes tend to use high- than the node’s communication radius, they are defined as power when they didn’t have to. neighbors. This model has following properties [11]: (1) LEACH (Low Energy Adaptive Clustering Hierarchy) sensor nodes do not be moved after being deployed; (2) all [9] is one of the most typical hierarchical topology control sensor nodes have similar energy and equal status; (3) the algorithm. LEACH protocol divides the network lifetime energy of each node is limited; (4) after deployment, the by “round.” After deploying nodes, LEACH protocol network does not require human maintenance; (5) location firstly classifies all nodes, each node decides whether to information of each node is known after deployment; (6) be a cluster head or an ordinary node by itself through a nodes have the capability of data integration; (7) nodes certain algorithm, and then ordinary nodes should decide have data transmission periodically; (8) the energy of which cluster to join. During operation of the network, each nodes and energy consumption balance in the network cluster head integrates and forwards the data from ordinary is mainly considered to improve the network lifetime. nodes in its cluster. With LEACH protocol, each node has The transmission failure, fault tolerance and security in the same probability to be a cluster head. To some extent, communication are not considered in this paper. LEACH balances energy consumption of nodes and extends Our main purpose is to extend the lifetime of wireless the network lifetime. Compared with the network protocols sensor networks. It has been introduced in Section 2 that without topology controlling method, LEACH can extend HEED protocol [11] improves LEACH algorithm in the the network lifetime by about 30%. However, it can not clustering process, but, HEED has no improvement in guarantee the uniform distribution of clusters because it cluster stable period. Literature [12] proposed EEDRCP does not consider the residual energy and nodes’ locations. algorithm, which has improved the stable period of the Location information depend GAF algorithm [10] is also LEACH algorithm. It makes the cluster head exchange typical topology controlling solutions. character with ordinary node every two rounds of inner- HEED algorithm (Hybrid Energy Efficient Distributed cluster communication. However, if the energy of the Clustering) [11] and EEDRCP algorithm [12] are typical current cluster head is the largest in the cluster, then examples of improved clustering algorithms based on EEDRCP will abandon the current cluster head through LEACH. HEED improves LEACH in the clustering process the exchange mechanism, and one of ordinary nodes in by taking the residual energy of nodes into account, and the cluster will be the cluster head during the next inner- selecting with iteration method to make the nodes with cluster communication round. This sometimes leads to higher residual energy as cluster heads. HEED uses primary energy imbalance, which is not favorable for improving the parameter and secondary parameter to select cluster heads network lifetime. instead of selecting them randomly, but HEED algorithm did not make any improvement during the stable period.

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4 BCHED Algorithm wireless sensor networks. EEDRCP selects cluster heads according to the residual energy of nodes. And it forms the As the analysis in Section 2, HEED makes the hybrid topology with advantages of the plain topology, the network starts a new clustering process after one round hierarchical topology and location-based topology. The of data transmission. Although the energy consumption timeline model of EEDRCP algorithm is shown in Figure of a clustering process is much less than that of stable 1. Although EEDRCP algorithm improves the LEACH period, frequent clustering will cause serious energy algorithm in the stability phase of the cluster, there are still waste [15]. EEDRCP improved the stable period of the some problems. If the current cluster head possesses most LEACH algorithm. It makes the cluster head exchange competent energy in its cluster, EEDRCP will abandon the character with ordinary node every two rounds of inner- current cluster head through the exchange mechanism, and cluster communication. However, if the current cluster head one of ordinary nodes in the cluster will be the cluster head possesses most competent energy in its cluster, EEDRCP during the next round of inner-cluster communication. This will abandon the current cluster head through the exchange will accelerate the death of an ordinary node, which is not mechanism, and one of ordinary nodes in the cluster will conductive to the network lifetime. be the cluster head during the next round of inner-cluster communication. This will lead to energy imbalance, and it stability stability process process is not conducive to the network lifetime. Based on the above analysis, in order to relief the clustering even clustering even odd round odd round imbalance of energy consumption in the wireless sensor process round process round networks nodes caused by frequent clustering, we propose an algorithm called BCHED, which employs double round Figure 1 Timeline Model clustering mechanism and optional cluster head exchanging mechanism to extend the network lifetime. In this section 4.2 BCHED Design and Analysis we firstly review the HEED algorithm and EEDRCP Based on the above analysis, in order to solve the algorithm briefly, and then the design detail of BCHED problem of energy waste caused by frequent clustering, we shall be presented. propose BCHED algorithm. BCHED uses double round clustering mechanism and optional cluster head exchanging 4.1 HEED and EEDRCP mechanism to extend the network lifetime. HEED algorithm can extend network lifetime by Firstly, the energy consumption model in our research distributing the energy consumption throughout the is described in this section, which is designed based on network. HEED’s primary parameter is set according to the the First Order Radio Model (FORDM). Figure 2 shows residual energy distribution, which can be used to randomly the scheme of First Order Radio Model. FORDM uses select the set of the initial cluster heads. Secondary a transmission circuit and a power amplifier to transport parameter depends on the inner-cluster communication information, and a receiving circuit is employed to receive cost, which is used to “break ties.” A tie in this context means that a node falls within the “range” of more than d one cluster head, and this includes the situation when two tentative cluster heads fall within the same range. HEED can be divided into the following three steps: initialize, repeat and finalize. Although HEED algorithm is superior packet to LEACH algorithm in the distribution of cluster heads, /bits ETx(k,d) there are still some problems. HEED algorithm only Transmiss Power improves the LEACH in the clustering process, but there ion circuit amplifier is no improvement in the stable period. Throughout the ETx-elec(k) ETx-amp(k,d) stable period of HEED, cluster heads have to remain the same. However, cluster heads play an important role in the process of data transmission because they are responsible packet for data fusion and forwarding data. Finally, energy of ETx(l) /bits cluster heads will be consumed quickly in stable period of Receiving cluster. circuit EEDRCP algorithm introduces the double-rounds ETx-elec(l) clustering mechanism which improves energy efficiency of Figure 2 First Order Radio Model

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information. ETx-elec refers to the energy consumption by Initialize

the transmission circuit, and ERx-elec refers to the energy establish a neighbor table consumption by the receiving circuit. The model satisfies compute and broadcast the the following assumptions: (1) all of sensor nodes should communication cost use the same structure, and their energy should be limited; compute the probability to (2) the location of sink node should be fixed; (3) the be a cluster head node can use the same energy consumption to transmit

information in different directions. repeat The energy consumption to transmit k bits of

information can be calculated with Equation (1). Eelec refers to the energy consumption to transmit 1 bit of information, finalize Determine the status of no so k × Eelec denotes the energy consumption of the circuit to the node

transmit or receive k bits of information. εfs and εamp are two parameters of amplifier according to the distance of data steady process transmission, because signal attenuation refers to different the first round of transmission 2 models under different conditions of distance. k × εfs × d 4 optional cluster head exchange and k × εamp × d denotes the energy consumption of the power amplifier in different conditions. d is the distance of the second round of transmission data transmission, and d0 is the threshold distance. When

d < d0, signal attenuation refers to the free space channel 2 model and the consumption of amplifier is k × εfs × d . When d > d , the consumption of amplifier isk × ε × d4. Whether 0 amp or not the network dies

(1) yes

end

The energy consumption to receive k bits of Figure 3 Flow Diagram of BCHED information can be calculated with Equation (2). We can see that the energy consumption of the transmission circuit network, and each round is divided into odd round and even is roughly equal to that of the receiving circuit. round according to their time order. The optional cluster head exchanging mechanism works between and odd round ERx(k) = ERx−elec(k) = k × Eelec (2) and an even one. The residual energy of current cluster head and ordinary nodes shall be compared to determine which The wireless sensor network topology control algorithm node should be selected as the next cluster head. BCHED BCHED proposed in this paper is based on the back-up algorithm is divided into two stages: clustering process and node in detail to improve the stable period of HEED. In stable period. BCHED, optional cluster head exchanging mechanism is designed to balance the energy consumption and extend CHprob = max(Cprob × Eresidual / Emax, pmin) (3) network lifetime. Figure 1 shows the timeline model when the target yyClustering Process network protocol works. When the network starts to work, it The clustering process shall achieve the following should firstly start the clustering process. Then the network goals: (1) the election of cluster heads; (2) solving the starts the stable period. The stable period is composed of ownership of common nodes. The clustering process is two rounds of data transmission. BCHED inserts a special divided into three stages: initialize, repeat and finalize node filtering stage at the end of the first round, to help the stage. current cluster head to determine which node should be (1) In the Initialize stage, each node broadcasts with the selected as the next cluster head by comparing the residual given cluster size, and starts to establish a neighbor energy among the ordinary nodes in the cluster. Figure 3 table. Then, each node calculates the communication shows the flow diagram of BCHED. cost and broadcasts the relative information. Finally, Here is the basic strategy of cluster head exchange: each node calculates the probability of being a CH with

“round” is defined to indicate the operational phase of the the Equation (3). In Equation (3), Eresidual refers to the

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residual energy, Cprob refers to the initial proportion of finalize:

CH (cluster head) in the network, and pmin is designed If (Is_fianl_CH ← FALSE) to limit the frequency of iteration so that the whole If ((SCH ← {v: v is a final cluster process can complete in a limited period of time which head}) ≠ φ ) is acceptable for the real-time requirement of the wireless sensor network. Figure 4 shows the pseudo- my_cluster_head ← least_cost(SCH) code of initialize stage. join_cluster(cluster_head_ID, (2) In the repeat stage, there are several round of iterations. NodeID) For example, in iteration round i, i ≤ Niter (Niter refers Else to the total number of iterations), each “uncovered (as Cluster_head_msg(NodeID, defined below)” node try to be elected as a cluster head final_CH, cost)

with probability CHprob. After step i, the set of tentative Else Cluster_head_msg(NodeID, final_CH, cost) cluster heads, SCH, is defined as {cluster heads after step

i-1È new heads selected in step i}. A node vi selects Figure 6 pseudo-code of finalize stage its cluster head (my_cluster_head) to be the node with the lowest cost in S (S may include v itself if it is CH CH i After this process, Monitoring area is divided into a selected as a tentative cluster head ). All nodes then number of clusters. Each cluster consists of a cluster head double their CH and go to the next step. If S of v is prob CH i and some ordinary nodes. Cluster head assigns time slot null, then v is “uncovered” (Figure 5). i to the ordinary nodes, within specified time slots ordinary (3) In finalize stage, each node determines the last status. nodes send data to the cluster head. After the cluster head After this stage, v become a cluster head or an ordinary receives data from ordinary nodes, it finishes data fusion node within a cluster. Figure 6 shows the pseudo-code and then forwards the data. of finalize stage. yyStable Period The main task in this period is the inner-cluster Initialize: communication and inter-cluster communication. For Snbr ← {v: v lies within my cluster range} inner-cluster communication the ordinary nodes send data Compute and broadcast cost to ∈ Snbr to the cluster head according to time slots, inter-cluster CH ← max(C × E / E , p ) prob prob residual max min communication refers to the communication between Is_final_CH ← FALSE the cluster head. LEACH algorithm uses a single round Figure 4 Initialize Stage clustering which refers that after electing cluster head, the network starts a new clustering process just after one repeat: round of data transmission, and this leads to instability of If ((SCH ← {v: v is a cluster the network. However, if the stable period lasts too long, head}) ≠ φ ) energy consumption right in the cluster heads shall be

my_cluster_head ← least_cost(SCH) accelerated. If my_cluster_head = NodeID BCHED employs a double-rounds clustering strategy If(CHprob=1) in the stable period. Double-rounds clustering refers that Cluster_head_msg(NodeID, the network starts a new clustering process after two rounds final_CH, cost) of data transmission. Figure 7 shows the stable period. Each Is_fianl_CH ← TRUE Else round is composed of TNO TDMA frames. In each TDMA Cluster_head_msg(NodeID, frame, each ordinary node transmits data to its cluster head, final_CH, cost) and cluster head fuse and forward the data. Stable period in ElseIf (CHprob = 1) BCHED is composed of following steps: Cluster_head_msg(NodeID, (1) During the odd round of data transmission. every final_CH, cost) ordinary node transmits data to its cluster head, and Is_fianl_CH ← TRUE cluster head fuse and forward the data ElseIf Random(0, 1) ≤ CHprob Cluster_head_msg(NodeID, (2) If the current CH still has the most residual energy, it tentative_CH, cost) still acts as a CH in the even round. Otherwise, another CHprevious ← CHprob node with most energy shall take its place in even CHprevious ← min(CHprob × 2, 1) round. Until CHprevious = 1 (3) After two rounds of data transmission, a new clustering Figure 5 Repeat Stage process shall begin.

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First Round (TNO TDMA frames) d a d Ordinary nodes a transmit information CH CH c Cluster head fuse and c b b forward data (2) If E > E (1) If Ea > E d b a

Whether d d CH has the No a exchange a most cluster head CH residual CH c c energy b b (4 ) If Ec > E CH (3 ) If Ec > E a yes

Second Round (T TDMA d NO a frames) Ordinary nodes CH transmit information c b (5) exchange Cluster head fuse and forward data Figure 8 Optional Cluster Head Exchanging Mechanism

Figure 7 Stable Period energy Ea. In this example, Ea is greater than Ed, so node a returns an ack frame to node d. Then node d goes to sleep. The main difference of BCHED with EEDRCP is that In Figure 8(2), node a sends a packet with its own the cluster head determines to convert the cluster head role residual energy Ea to node b. Node b returns an ack to node according to actual demand after the first round of data a because Eb is greater than Ea. In Figure 8(3), thing is the transmission. This will cause two different results: same as (1) and (2). (1) If the residual energy of the current cluster head is In Figure 8(4), after the above three steps, node c is greater than any node within the cluster, the cluster chosen as the node with most residual energy. head will not be changed. In Figure 8(5), after a period of time, node c doesn’t (2) If the residual energy of the current cluster head is receive an ack frame from CH, and it becomes the new less than the ordinary node with the highest residual cluster head in the even round. energy, the current cluster head will exchange role with Figure 9 shows the pseudo-code of stable period. the ordinary node, finally, the new cluster head will Compared with HEED algorithm, BCHED algorithm be responsible for data fusion and forwarding in even introduces double-rounds clustering mechanism and an round of data transmission. To implement this mechanism, after odd round of data transmission, an ordinary node sends a data package stable period: If Is_fianl_CH = TRUE with information of its own residual energy, and then the assign TDMA slot node which receives the package will extract the energy receive data from Sord ← {v: v joins information and compares it with its own residual energy. the cluster} Once any node finds that it possesses more residual energy, fuse and forward data it will return an ack frame to the source node, and then it Else will communicate with other nodes in cluster. Finally, the transmite the data to node with highest residual energy is picked out. Figure 8 my_cluster_head If the end of first round ← T shows the optional cluster head exchanging mechanism. NO TDMA frames {a, b, c, d, CH} refers to an normal cluster in the network. energy_msg (NodeID, Eresidual) Node a, b, c and d refers to ordinary nodes. And CH refers optional CH (cluster head) to the current cluster head. exchange In Figure 8(1), the odd round just ended, and the local If the end of second round ← TNO re-clustering just begins. Node d sends a packet with its TDMA frames start clustering process again own residual energy Ed to node a. And then node a extract

the information of Ed and compares it with its own residual Figure 9 Pseudo-Code of Stable Period

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optional cluster head exchanging mechanism to avoid Figure 10 shows that the proportion of cluster heads is unnecessary global cluster head replacement. Compared very high (85%) for very small cluster ranges, and the this with EEDRCP, BCHED algorithm avoids sorting in proportion becomes smaller as the range increases. the cluster head, and selects the ordinary node with the maximum residual energy in the cluster with a linear BCH-HEED 80 complex algorithm, which effectively control the costs of communication as well as energy. 70 s 60

5 Experimental Results 50

40 In this section, we will compare and discuss the performance of BCHED algorithm in the following aspects: 30 Percentage of cluster head cluster of Percentage (1) The proportion of cluster heads; (2) Standard deviation 20

of residual energy and network lifetime. 10 50 100 150 200 250 300 350 400 The relative simulation parameters are listed in Table Cluster radious(meters) 1. d0 is the threshold distance. Eelec refers to the energy Figure 10 Proportion of Cluster Heads consumption to transmitting 1 bit of information. εfs and εamp are two parameters of amplifier according to the distance of 5.2 Energy and Network Lifetime data transmission. Efusion refers to the energy consumption In the wireless sensor network system, when the of data fusion for 1 bit in 1 node. Round (Tno) means that first node dies, it can be considered that the system can’t in Tno TDMA frames, each ordinary node periodically transmits data to its cluster head, and cluster head fuse and properly work anymore. So, at this time, the standard deviation of residual energy of all nodes in the system can forward data. Cprob refers to the initial proportion of cluster be employed to measure the performance of BCHED in head in the network. pmin is designed to limit the frequency of iteration. We can see the detail of these parameters in energy balance. Figure 11 compares the energy balance Section 4.2. performance of HEED and BCHED, and Figure 12 shows the network lifetime with these two protocols. In these Table 1 Simulation Parameters experiments, it is assumed that the power of each node can not be changed. The number of nodes varies from 300 to Parameter value 700, and the maximum energy of a node is 2 energy units. d0 75 m All nodes are randomly distributed in a field with dimension Eelec 50 nJ/bit 100*100, and the location of sink node is (75, 150). Figure 2 εfs 10 pJ/bit/m 11 shows that at the end of network lifetime, the standard 4 deviation of residual energy of nodes with BCHED is εamp 0.0013 pJ/bit/m smaller than that with HEED, which denotes that BCHED E 5 nJ/bit/signal fusion have better energy balance performance. Figure 12 shows Data packet size 100 bytes that, compared with HEED, BCHED extends network Broadcast packet size 25 bytes lifetime by nearly 10%. Packet header size 25 bytes

Round (T ) 5 TDMA frames 0.4 HEED mindegree no BCH-HEED mindegree

Cprob 5%

pmin 0.0005 0.3 n

5.1 The Proportion of Cluster Head 0.2 Firstly, we observe the proportion of cluster heads

in the wireless sensor network after performing BCHED standard deviatio 0.1 algorithm. In this experiment, it is assumed that 1000 nodes are randomly distributed in a 2,000 × 2,000 field, and after being deployed, they will not be moved. Cluster radius 0.0 300 350 400 450 500 550 600 650 700 varies from 25 to 400. Each sample needs to form global number of nodes clusters for 100 times under certain cluster radius, and we Figure 11 Standard Deviation of Residual Energy when One take the average proportion of cluster heads as the result. Node Dies

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900 HEED--Min degree BCH-HEED--Min degree 6 Conclusion

750 Improving the energy efficiency is one of the primary 600 design goals for wireless sensor networks. Hierarchical

450 topology controlling method introduces the concept of network cluster to achieve this goal. In this paper, we 300 studied the key issues of hierarchical topology controlling.

ounds until the first node dies node first the until ounds Typical controlling methods usually launch a global 150 #r clustering process after each data transmission round, 0 and frequent clustering is apt to cause serious energy 300 350 400 450 500 550 600 650 700 Number of nodes consuming. Some improved methods can extend the network lifetime with better cluster distribution mechanism, Figure 12 Network Lifetime and the frequency of re-clustering process is also reduced. But, without local cluster head tuning mechanism, these Another experiment is designed to observe the methods sometimes lead to energy imbalance in the stable performance of BCHED with network nodes of variable period, which is not favorable for improving the network power. In this experiment, it is assumed that each node can lifetime. tune the power of its radio unit to use minimum energy to In order to balance the energy consumption in wireless communicate with its neighbors. AMRP is defined as cost sensor networks, a new hierarchical topology controlling of the clusters, which is calculated according to Equation method BCHED is proposed in this paper. With double (4): round clustering mechanism of BCHED, two rounds of data transmission constitute a stable period, and the global (4) clustering process between these two rounds is abolished. At the end of an odd round, the optional cluster head Let MinPwr denote the minimum power level required i exchanging mechanism of BCHED shall work and the next by node v (1 ≤ i ≤ M) to communicate with a cluster head i cluster head is to be selected by comparing the residual u, where M is the number of nodes within the cluster range. energy among the ordinary nodes in the cluster. In this experiment, the number of nodes varies from 300 to The results of the experiments in Section 5 shows that, 700, the nodes are deployed in a 100 × 100 field, and the with BCHED, at the end of network lifetime, the standard location of sink node is (75, 150). Figure 13 shows that, deviation of residual energy of nodes with BCHED can be compared with HEED, BCHED extends the lifetime of smaller than that with classical method, and this extends the system with variable power nodes by 10%-20%. From network lifetime by nearly 10%. Further experiments Figure 11, Figure 12, and Figure 13, it can be concluded shows, in the WSN systems with energy variable nodes, the that in terms of energy consumption balance performance, energy balance performance is much better. BCHED is superior to HEED. In the future, we will implement BCHED and investigate its performance in typical WSN platforms. In 900 HEED--ARMP BCH-HEED--ARMP order to solve the network coverage problem when such

750 WSN system is composed of power adjustable sensor nodes, the optimization mechanism of back-up cluster head 600 selection shall be researched. rst node dies fi 450 e th l ti Acknowledgements 300

150 This work is supported by the Zhejiang Provincial #rounds un Natural Science Foundation of China (No. Y1090940, 0 300 350 400 450 500 550 600 650 700 Y1101104), the National Natural Science Foundation of Number of nodes China (No. 61100193), and the Important National Science Figure 13 Network Lifetime with Variable Power Nodes & Technology Specific Projects of Zhejiang Province of China (No. 2009C03015-1).

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References Conference on Mobile Computing and Networking, Rome, Italy, July, 2001, pp.70-84. [1] Naixue Xiong, Athanasios V. Vasilakos, Laurence T. [11] O. Younis and S. Fahmy, Distributed Clustering in Yang and Ekram Hossain, An Adaptive and Predictive Ad-Hoc Sensor Networks: A Hybrid, Energy-Efficient Approach for Autonomic Multirate Multicast Approach, Proc. 23th Annual Joint Conference of Networks, ACM Transactions on Autonomous and IEEE Computer and Communications Societies, Adaptive Systems, Vol.6, No.3, 2011, pp.11-24. Hong Kong, China, March, 2004, pp.629-640. [2] Naixue Xiong, Xiaohua Jia, Laurence T. Yang, [12] Qing-Zhang Chen, Xiao-Min Zhao and Xiao-Ying Athanasios V. Vasilakos, Yingshu Li and Yi Pan, Chen, Design of Double Rounds Clustering Protocol A Distributed Efficient Flow Control Scheme for for Improving Energy Efficient in Wireless Sensor Multirate Multicast Networks, IEEE Transactions on Networks, Journal of Software, Vol.21, No.11, 2010, Parallel and Distributed Systems, Vol.21, No.9, 2010, pp.2933-2943. pp.1254-1266. [13] Shi-Jin Dai, Le-Min Li, Tin-Yu Wu and Gwo-Ruey [3] Xiaofei Wang, Min Chen, Taekyoung Kwon and Yu, A Hierarchical Power-Efficient Routing Protocol Han-Chieh Chao, Multiple Mobile Agents Itinerary for Wireless Sensor Networks, Journal of Internet Planning in Wireless Sensor Networks: Survey and Technology, Vol.10, No.5, 2009, pp.473-481. Evaluation, IET Communications, Vol.5, No.12, [14] Salah A. Aly, Zhenning Kong and Emina Soljanin, 2011, pp.1769-1776. Fountain Codes Based Distributed Storage [4] Chin-Feng Lai, Yueh-Min Huang, Jong Hyuk Park Algorithms for Large-Scale Wireless Sensor and Han-Chieh Chao, Adaptive Body Posture Analysis Networks, Proc. of IPSN 2008, St. Louis, MO, April, for Elderly-Falling Detection with Multisensors, 2008, pp.171-182. IEEE Intelligent Systems, Vol.25, No.2, 2010, pp.20- [15] Z. C. Ma, Y. N. Sun and T. Mei, Survey on Wireless 30. Sensors Network, Journal of China Institute of [5] Jianzhong Li and Hong Gao, Survey on Sensor Communications, Vol.25, No.4, 2004, pp.14-124. Network Research, Journal of Computer Research and Development, Vol.45, No.1, 2008, pp.1-15. Biographies [6] Naixue Xiong, Athanasios V. Vasilakos, Laurence T. Yang, Lingyang Song, Yi Pan, Rajgopal Kannan Wei Zhang received the BE degree and Yingshu Li, Comparative Analysis of Quality in School of Information Science and of Service and Memory Usage for Adaptive Failure Engineering of Wuhan University of Detectors in Healthcare Systems, IEEE Journal on Science and Technology in China in 2000, Selected Areas in Communications, Vol.27 No.4, and he received the MEc and PhD degree 2009, pp.495-509. in Computer School of Wuhan University [7] Swetha Narayanaswamy, Vikas Kawadia, R. S. in China in 2004 and 2008, respectively. Sreenivas and P. R. Kumar, Power Control in Ad- He is currently a lecturer with School of Computer Science Hoc Networks: Theory, Architecture, Algorithm and and Technology, Hangzhou Dianzi University, China. His Implementation of The COMPOW Protocol, Proc. research interests include wireless sensor network and European Wireless Conference, Florence, Italy, Intelligent Computing. He is a member of Association February, 2002, pp.156-162. for Computing Machinery (ACM) and China Computer [8] Vikas Kawadia and P. R. Kumar, Power Control Federation (CCF). and Clustering in Ad Hoc Networks, Proc. 22nd Annual Joint Conference of the IEEE Computer Naixue Xiong received his both PhD and Communications Societies, San Francisco, CA, degrees in Wuhan University (about March, 2003, pp.459-469. software engineering), and Japan [9] W. B. Heinzelman, A. P. Chandrakasan and H. Advanced Institute of Science and Balakrishnan, An Application-Specific Protocol Technology (about dependable networks), Architecture for Wireless Micro Sensor Networks, respectively. Before he attends WIT, he IEEE Transactions of Wireless Communications, worked in Georgia State University as Vol.1, No.4, 2002, pp.660-670. an adjust assistant professor, visiting assistant professor, [10] Ya Xu, John Heidemann and Deorah Estrin, and postdoc over 4 years. His research interests include Geography-Informed Energy Conservation for Security and Dependability, Cloud Computing, Networks, Ad Hoc Routing, Proc. 7th Annual International and Optimization Theory. Dr. Xiong published about 130

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international journal papers. Some of his works were has been invited to give around 20 keynote talks at various published in IEEE JSAC, IEEE or ACM Transactions, international conferences and symposia. ACM Sigcomm Workshop, IEEE INFOCOM, ICDCS, and IPDPS. He has been a General Chair, Program Chair, Gangmin Jia received the BE degree in Publicity Chair, PC member and OC member of over 100 Communication Engineering School of international conferences, and as a reviewer of about 100 Hangzhou Dianzi University in China international journals, including IEEE JSAC, IEEE SMC in 2009. He is currently a postgraduate (Part: A/B/C), IEEE Transactions on Communications, student with School of Computer Science IEEE Transactions on Mobile Computing, IEEE Trans. and Technology, Hangzhou Dianzi on Parallel and Distributed Systems. He is serving as an University, China. His research interests associate editor or editor member for over 10 international include wireless sensor network and journals (including Information Science), and a guest editor intelligent computing. for over 10 international journals, including Sensor Journal, WINET and MONET. He has received the Best Paper Jilin Zhang received the BE degree Award in the 10th IEEE International Conference on High in Information Engineering School of Performance Computing and Communications (HPCC- Jinan University in China in 2002, and 08) and the Best student Paper Award in the 28th North he received the MEc degree in Computer American Fuzzy Information Processing Society Annual School of Shandong University in China Conference (NAFIPS2009). He is a member of IEEE, IEEE in 2005. He received the PhD degree in ISATC, IEEE TCPP, and IEEE TCSC, and also a Chair Computer School of the University of of “Trusted Cloud Computing” in IEEE Computational Science and Technology Beijing in China. He is currently a Intelligence Society (CIS). lecturer with School of Computer Science and Technology, Hangzhou Dianzi University, China. His research interests Laurence T. Yang is a professor in include low-level and architecture-specific optimization, computer science at St. Francis Xavier performance modeling, and parallel computing. He is a University, Canada. His research member of Association for Computing Machinery (ACM) includes high performance, embedded and China Computer Federation (CCF). and ubiquitous/pervasive comp. He has published around 300 papers (including around 100 international journal papers such as IEEE and ACM Transactions, SCI/EI indexed around 292 papers) in refereed journals, conference proceedings and book chapters in these areas. He has been involved in more than 100 conferences and workshops as a program/general/steering conference chair and more than 300 conference and workshops as a program committee member. He served as the vice-chair of IEEE Technical Committee of Supercomputing Applications (TCSA) until 2004, currently is the chair of IEEE Technical Committee of Scalable Computing (TCSC), the chair of IEEE Task force on Ubiquitous Computing and Intelligence. He is also in the steering committee of IEEE/ACM Supercomputing conference series and National Computing Allocation Committee of Canada. In addition, he is the editors-in- chief of several international journals. He is serving as an editor for around 20 international journals. He has been acting as an author/co-author or an editor/co-editor of 25 books. He has won 5 Best Paper Awards; 4 IEEE Best Paper Awards; 2 IEEE Outstanding Paper Awards; one Best Paper Nomination; Distinguished Achievement Award, 2005; IEEE Distinguished Achievement Award, 2009; Canada Foundation for Innovation Award, 2003. He

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