›› 2014, Vol. 29 ›› Issue (5): 887-900.doi: 10.1007/s11390-014-1476-z

Special Issue: Computer Networks and Distributed Computing

• Computer Networks and Distributed Computing • Previous Articles     Next Articles

Assessing Diagnosis Approaches for Wireless Sensor Networks: Concepts and Analysis

Rui Li1,2(李 瑞), Ke-Bin Liu3,4(刘克彬), Member, ACM, IEEE, Xiangyang Li2,5(李向阳), Senior Member, IEEE, Member, ACM, Yuan He3,4(何 源), Member, ACM, IEEE, Wei Xi2,*(惠 维), Member, CCF, ACM, IEEE, Zhi Wang2(王 志), Ji-Zhong Zhao2(赵季中), Member, CCF, ACM, IEEE, Meng Wan6(万 猛), Member, ACM, IEEE   

  1. 1. Institute of Software Engineering, Xidian University, Xi'an 710071, China;
    2. School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China;
    3. School of Software, Tsinghua University, Beijing 100084, China;
    4. Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing 100084, China;
    5. Department of Computer Science, Illinois Institute of Technology, Chicago, IL 60616, U. S. A. ;
    6. Center for Science and Technology Development, Ministry of Education, Beijing 100080, China
  • Received:2014-02-27 Revised:2014-06-27 Online:2014-09-05 Published:2014-09-05
  • About author:Rui Li received his B.S. degree in mathematics from the Department of Applied Mathematics of Xidian University in 2006, and the Ph.D. degree in computer science from the Department of Computer Science and Technology of Xi'an Jiaotong University in 2014. He is currently a lecturer in Xidian University. His main research interests include wireless ad hoc and sensor networks, and pervasive computing.
  • Supported by:

    This work is supported by the National Natural Science Foundation of China under Grant Nos. 61190110, 61325013, 61103187, 61170213, 61228202, 61170216, and 61422207, the National Basic Research 973 Program of China under Grant No. 2014CB347800, the Natural Science Foundation of USA under Grant Nos. CNS-0832120, CNS-1035894, ECCS-1247944, and ECCS-1343306, the Fundamental Research Funds for the Central Universities of China under Project No. 2012jdgz02 (Xi'an Jiaotong University), and the Research Fund for the Doctoral Program of Higher Education of China under Project No. 20130201120016.

Diagnosis is of great importance to wireless sensor networks due to the nature of error prone sensor nodes and unreliable wireless links. The state-of-the-art diagnostic tools focus on certain types of faults, and their performances are highly correlated with the networks they work with. The network administrators feel difficult on measuring the effectiveness of their diagnostic approaches and choosing appropriate tools so as to meet the reliability demand. In this work, we introduce the D-vector to characterize the property of a diagnosis approach. The D-vector has five dimensions, namely the Degree of Coupling, the Granularity, the Overhead, the Tool Reliability and the Network Reliability, quantifying and evaluating the effectiveness of current diagnostic tools in certain networks. We employ a skyline query algorithm to find out the most effective diagnosis approaches, i.e., skyline points (SPs), from five dimensions of all potential D-vectors. The selected skyline D-vector points can further guide the design of various diagnosis approaches. In our trace-driven simulations, we design and select tailored diagnostic tools for GreenOrbs, achieving high performance with relatively low overhead.

[1] Mainwaring A, Culler D, Polastre J et al. Wireless sensor networks for habitat monitoring. In Proc. the 1st ACM WSNA, Sept. 2002, pp.88-97.

[2] Tolle G, Polastre J, Szewczyk R et al. A macroscope in the redwoods. In Proc. the 3rd ACM SenSys, Nov. 2005, pp.51-63.

[3] Mao X, Miao X, He Y et al. Citysee: Urban CO2 monitoring with sensors. In Proc. the 31st IEEE INFOCOM, March 2012, pp.1611-1619.

[4] Xia M, Dong Y, Xu W et al. MC2: Multi-mode user-centric design of wireless sensor networks for long-term monitoring. ACM Transactions on Sensor Networks, 2014, 10(3): Article No.52.

[5] Dong W, Liu Y, Chen C et al. R2: Incremental reprogramming using relocatable code in networked embedded systems. IEEE Transactions on Computers, 2013, 62(9): 1837-1849.

[6] Liu Y, He Y, Li M et al. Does wireless sensor network scale? A measurement study on GreenOrbs. IEEE Transactions on Parallel and Distributed Systems, 2013, 24(10): 1983-1993.

[7] Zhang H, Ma H, Li X et al. In-network estimation with delay constraints in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 2013, 24(2): 368-380.

[8] Cao Q, Abdelzaher T, Stankovic J et al. Declarative tracepoints: A programmable and application independent debugging system for wireless sensor networks. In Proc. the 6th ACM SenSys, November 2008, pp.85-98.

[9] Yang J, Soffa M L, Selavo L et al. Clairvoyant: A comprehensive source-level debugger for wireless sensor networks. In Proc. the 5th ACM SenSys, November 2007, pp.189-203.

[10] Ramanathan N, Chang K, Kapur R et al. Sympathy for the sensor network debugger. In Proc. the 3rd ACM SenSys, November 2005, pp.255-267.

[11] Liu Y, Liu K, Li M. Passive diagnosis for wireless sensor networks. IEEE/ACM Transactions on Networking, 2010, 18(4): 1132-1144.

[12] Khan M M H, Le H K, Ahmadi H et al. Dustminer: Troubleshooting interactive complexity bugs in sensor networks. In Proc. the 6th ACM SenSys, November 2008, pp.99-112.

[13] Li P, Regehr J. T-check: Bug finding for sensor networks. In Proc. the 9th ACM/IEEE IPSN, April 2010, pp.174-185.

[14] Sookoor T, Hnat T, Hooimeijer P et al. Macrodebugging: Global views of distributed program execution. In Proc. the 7th ACM SenSys, November 2009, pp.141-154.

[15] Woo A, Tong T, Culler D. Taming the underlying challenges of reliable multihop routing in sensor networks. In Proc. the 1st ACM SenSys, November 2003, pp.14-27.

[16] Khan M M H, Luo L, Huang C, Abdelzaher T. SNTS: Sensor network troubleshooting suite. In Proc. the 3rd IEEE DCOSS, June 2007, pp.142-157.

[17] Girod L, Elson J, Cerpa A et al. EmStar: A software environment for developing and deploying wireless sensor networks. In Proc. the USENIX Annual Technical Conference, June 27-July 2, 2004, pp.283-296.

[18] Liu K, Ma Q, Zhao X, Liu Y. Self-diagnosis for large scale wireless sensor networks. In Proc. the 30th IEEE INFOCOM, April 2011, pp.1539-1547.

[19] Khan M M H, Le H K, LeMay M et al. Diagnostic powertracing for sensor node failure analysis. In Proc. the 9th ACM/IEEE IPSN, April 2010, pp.117-128.

[20] Börzsöny S, Kossmann D, Stocker K. The skyline operator. In Proc. the 17th IEEE ICDE, April 2001, pp.421-430.

[21] Tan K L, Eng P K, Ooi B C. Efficient progressive skyline computation. In Proc. the 27th VLDB, Sept. 2001, pp.301-310.

[22] Hjaltason G, Samet H. Distance browsing in spatial databases. ACM Transactions on Database Systems, 1999, 24(2): 265-318.

[23] Papadias D, Tao Y, Fu G, Seeger B. An optimal and progressive algorithm for skyline queries. In Proc. the 2003 ACM SIGMOD, June 2003, pp.467-478.

[24] Mo L, He Y, Liu Y et al. Canopy closure estimates with GreenOrbs: Sustainable sensing in the forest. In Proc. the 7th ACM SenSys, November 2009, pp.99-112.

[25] Stamatis D. Failure Mode and Effect Analysis: FMEA from Theory to Execution. WI, USA: ASQ Quality Press, 2003.

[26] Werner-Allen G, Lorincz K, Johnson J, Lees J, Welsh M. Fidelity and yield in a volcano monitoring sensor network. In Proc. the 7th USENIX OSDI, November 2006, pp.381-396.
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[1] Liu Mingye; Hong Enyu;. Some Covering Problems and Their Solutions in Automatic Logic Synthesis Systems[J]. , 1986, 1(2): 83 -92 .
[2] Chen Shihua;. On the Structure of (Weak) Inverses of an (Weakly) Invertible Finite Automaton[J]. , 1986, 1(3): 92 -100 .
[3] Gao Qingshi; Zhang Xiang; Yang Shufan; Chen Shuqing;. Vector Computer 757[J]. , 1986, 1(3): 1 -14 .
[4] Chen Zhaoxiong; Gao Qingshi;. A Substitution Based Model for the Implementation of PROLOG——The Design and Implementation of LPROLOG[J]. , 1986, 1(4): 17 -26 .
[5] Huang Heyan;. A Parallel Implementation Model of HPARLOG[J]. , 1986, 1(4): 27 -38 .
[6] Min Yinghua; Han Zhide;. A Built-in Test Pattern Generator[J]. , 1986, 1(4): 62 -74 .
[7] Tang Tonggao; Zhao Zhaokeng;. Stack Method in Program Semantics[J]. , 1987, 2(1): 51 -63 .
[8] Min Yinghua;. Easy Test Generation PLAs[J]. , 1987, 2(1): 72 -80 .
[9] Zhu Hong;. Some Mathematical Properties of the Functional Programming Language FP[J]. , 1987, 2(3): 202 -216 .
[10] Li Minghui;. CAD System of Microprogrammed Digital Systems[J]. , 1987, 2(3): 226 -235 .

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