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Artificial bee colony metaheuristic for energy-efficient clustering and routing in wireless sensor networks

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Abstract

Swarm intelligence (SI)-based metaheuristics are well applied to solve real-time optimization problems of efficient node clustering and energy-aware data routing in wireless sensor networks. This paper presents another superior approach for these optimization problems based on an artificial bee colony metaheuristic. The proposed clustering algorithm presents an efficient cluster formation mechanism with improved cluster head selection criteria based on a multi-objective fitness function, whereas the routing algorithm is devised to consume minimum energy with least hop-count for data transmission. Extensive evaluation and comparison of the proposed approach with existing well-known SI-based algorithms demonstrate its superiority over others in terms of packet delivery ratio, average energy consumed, average throughput and network life.

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References

  • Abbasi AA (2007) A survey on clustering algorithms for wireless sensor networks. Comput Commun 30(14):2826–2841

    Article  Google Scholar 

  • Abdul-Salaam G, Abdullah AH (2016) A comparative analysis of energy conservation approaches in hybrid wireless sensor networks data collection protocols. Telecommun Syst 61:159–179

    Article  Google Scholar 

  • Aioffi WM, Valle CA (2011) Balancing message delivery latency and network lifetime through an integrated model for clustering and routing in wireless sensor networks. Comput Netw 55(13):2803–2820

    Article  Google Scholar 

  • Akkaya K, Younis M (2005) A survey on routing protocols for wireless sensor networks. Ad Hoc Netw 3(3):325–349

    Article  Google Scholar 

  • Al-Karaki JN, Kamal AE (2004) Routing techniques in wireless sensor networks: a survey. IEEE Wirel Commun 11(6):6–28

    Article  Google Scholar 

  • Anisi MH, Abdul-Salaam G (2015) Energy harvesting and battery power based routing in wireless sensor networks. Wirel Netw 1–18. DOI:10.1007/s11276-015-1150-6

  • Ari AAA, Yenke BO (2016) A power efficient cluster-based routing algorithm for wireless sensor networks: honeybees swarm intelligence based approach. J Netw Comput Appl 69:77–97

    Article  Google Scholar 

  • Arora VK, Sachdeva M, Sharma V (2016) A survey on leach and others routing protocols in wireless sensor network. Optik Int J Light Electron Opt 127:6590–6600

    Article  Google Scholar 

  • Attea BA, Khalil EA (2012) A new evolutionary based routing protocol for clustered heterogeneous wireless sensor networks. Appl Soft Comput 12(7):1950–1957

    Article  Google Scholar 

  • Bari A, Jaekel A, Wazed S (2009) A genetic algorithm based approach for energy efficient routing in two-tiered sensor networks. Ad Hoc Netw 7(4):665–676

    Article  Google Scholar 

  • Chamam A, Pierre S (2010) A distributed energy-efficient clustering protocol for wireless sensor networks. Comput Electr Eng 36(2):303–312

    Article  MATH  Google Scholar 

  • Chang JH, Tassiulas L (2004) Maximum lifetime routing in wireless sensor networks. IEEE/ACM Trans Netw (TON) 12(4):609–619

    Article  Google Scholar 

  • Chen DR (2016) An energy-efficient QoS routing for wireless sensor networks using self-stabilizing algorithm. Ad Hoc Netw 37:240–255

    Article  Google Scholar 

  • Cobo L, Quintero A (2010) Ant-based routing for wireless multimedia sensor networks using multiple QoS metrics. Comput Netw 54(17):2991–3010

    Article  Google Scholar 

  • Deng S, Shen L, Li J (2011) Mobility-based clustering protocol for wireless sensor networks with mobile nodes. Wirel Sens Syst IET 1(1):39–47

    Article  Google Scholar 

  • Dimokas N, Mohamed Y, Katsaros D (2010) Energy-efficient distributed clustering in wireless sensor networks. J Parallel Distrib Comput 70(4):371–383

    Article  MATH  Google Scholar 

  • Ding Y, Chen R, Hao K (2016) A multi-path routing algorithm with dynamic immune clustering for event-driven wireless sensor networks. Neurocomputing 203:139–149

  • El-Basioni BMM, El-Kader A (2011) An optimized energy-aware routing protocol for wireless sensor network. Egypt Inform J 12(2):61–72

    Article  Google Scholar 

  • Fatemeh Najafi MAD (2011) Formatting a novel clustering protocol based on artificial immune system algorithm for wirelesssensor networks. Int J Adv Eng Sci Technol 6(2):256–260

    Google Scholar 

  • Gajjar S, Dasgupta K, Sarkar M (2016) Famacrow: fuzzy and ant colony optimization based combined mac, routing, and unequal clustering cross-layer protocol for wireless sensor networks. Appl Soft Comput 43:235–247

    Article  Google Scholar 

  • Guo W, Zhang W (2013) A survey on intelligent routing protocols in wireless sensor networks. J Netw Comput Appl 38:185–201

    Article  Google Scholar 

  • Heinzelman WB, Chandrakasan AP (2002) An application-specific protocol architecture for wireless microsensor networks. IEEE Trans Wirel Commun 1(4):660–670

    Article  Google Scholar 

  • Hoang D, Kumar R, Yadav P (2014) Real-time implementation of a harmony search algorithm-based clustering protocol for energy efficient wireless sensor networks. IEEE Trans Ind Inform 10:774–783

    Article  Google Scholar 

  • Hu Y-F, Ren LH, Dinga Y-S (2015) An endocrine cooperative particle swarm optimization algorithm for routing recovery problem of wireless sensor networks with multiple mobile sinks. Inf Sci 300:100–113

    Article  Google Scholar 

  • Huang H, Yu F, Hu G (2011) Energy-aware interference-sensitive geographic routing in wireless sensor networks. Commun IET 5(18):2692–2702

    Article  MathSciNet  Google Scholar 

  • Huang P, Xiao L, Wang C (2012) Improving end-to-end routing performance of greedy forwarding in sensor networks. IEEE Trans Parallel Distrib Syst 23(3):556–563

    Article  Google Scholar 

  • Jadhav P, Satao R (2016) A survey on opportunistic routing protocols for wireless sensor networks. Proc Comput Sci 79:603–609

    Article  Google Scholar 

  • Jin Y, Kim Y, Wang L (2008) Eemc: an energy-efficient multi-level clustering algorithm for large-scale wireless sensor networks. Comput Netw 52(3):542–562

    Article  MATH  Google Scholar 

  • Karaboga D, Akay B (2009) A comparative study of artificial bee colony algorithm. Appl Math Comput 214(1):108–132

    MathSciNet  MATH  Google Scholar 

  • Kong L, Pan JS (2015) A balanced power consumption algorithm based on enhanced parallel cat swarm optimization for wireless sensor network. Int J Distrib Sens Netw 2015:20

    Google Scholar 

  • Krishnan R, Starobinski D (2006) Efficient clustering algorithms for self-organizing wireless sensor networks. Ad Hoc Netw 4(1):36–59

  • Kuila P, Jana PK (2014) Energy efficient clustering and routing algorithms for wireless sensor networks: particle swarm optimization approach. Eng Appl Artif Intell 33:127–140

    Article  Google Scholar 

  • Kulkarni RV, Venayagamoorthy GK, Förster A (2011) Computational intelligence in wireless sensor networks: a survey. IEEE Commun Surv Tutor 13(1):68–96

    Article  Google Scholar 

  • Kumar D, Patel R, Aseri TC (2009) Eehc: energy efficient heterogeneous clustered scheme for wireless sensor networks. Comput Commun 32(4):662–667

    Article  Google Scholar 

  • Liu M, Sun S, Xu S (2012) An agent-assisted QoS-based routing algorithm for wireless sensor networks. J Netw Comput Appl 35(1):29–36

    Article  Google Scholar 

  • Liu Z, Xue L, Zheng Q (2012) A distributed energy-efficient clustering algorithm with improved coverage in wireless sensor networks. Future Gener Comput Syst 28(5):780–790

    Article  Google Scholar 

  • Lung CH, Zhou C (2010) Using hierarchical agglomerative clustering in wireless sensor networks: an energy-efficient and flexible approach. Ad Hoc Netw 8(3):328–344

    Article  Google Scholar 

  • Mao X, Xu X, Tang S (2011) Energy-efficient opportunistic routing in wireless sensor networks. IEEE Trans Parallel Distrib Syst 22(11):1934–1942

    Article  Google Scholar 

  • Mao S, Hou YT (2007) Beamstar: an edge-based approach to routing in wireless sensor networks. IEEE Trans Mobile Comput 6(11):1284–1296

    Article  Google Scholar 

  • Mhatre V, Rosenberg C (2004) Design guidelines for wireless sensor networks: communication, clustering and aggregation. Ad Hoc Netw 2(1):45–63

    Article  Google Scholar 

  • Mottola L, Picco GP (2011) Muster: adaptive energy-aware multisink routing in wireless sensor networks. IEEE Trans Mobile Comput 10(12):1694–1709

    Article  Google Scholar 

  • Ozturk C, Hancer E (2015) Dynamic clustering with improved binary artificial bee colony algorithm. Appl Soft Comput 28:69–80

    Article  Google Scholar 

  • Qi H, Chakrabarty K, Iyengar SS (2001) Distributed sensor networksa review of recent research. J Franklin Inst 338(6):655–668

    Article  MATH  Google Scholar 

  • Saleem M, Di Caro GA, Farooq M (2011) Swarm intelligence based routing protocol for wireless sensor networks: survey and future directions. Inform Sci 181(20):4597–4624

    Article  Google Scholar 

  • Saleem M, Farooq M (2012) Beesensor: a bee-inspired power aware routing protocol for wireless sensor networks. In: Applications of evolutionary computing. Springer, pp 81–90

  • Selvakennedy SSY, Sinnappan S (2007) A biologically-inspired clustering protocol for wireless sensor networks. Comput Commun 30(14):2786–2801

    Article  Google Scholar 

  • Song MAO, Zhao CL (2011) Unequal clustering algorithm for WSN based on fuzzy logic and improved ACO. J China Univ Posts Telecommun 18(6):89–97

  • Swades D, Wu H, Qiao C (2003) Meshed multipath routing with selective forwarding: an efficient strategy in wireless sensor networks. Comput Netw 43(4):481–497

    Article  MATH  Google Scholar 

  • Thulasiraman P, White KA (2016) Topology control of tactical wireless sensor networks using energy efficient zone routing. Digit Commun Netw 2:1–14

    Article  Google Scholar 

  • Tyagi S, Kumar N (2012) A systematic review on clustering and routing techniques based upon leach protocol for wireless sensor networks. J Netw Comput Appl 36(2):623–645

    Article  Google Scholar 

  • Wang L, Geng S, Zhang R (2009) An energy-balanced ant-based routing protocol for wireless sensor networks. In: 5th international conference on wireless communications, networking and mobile computing, 2009, IEEE, pp 1–4

  • Wang B, Ma D, Lim HB (2012) A coverage-aware clustering protocol for wireless sensor networks. Comput Netw 56(5):1599–1611

    Article  Google Scholar 

  • Yang J, Zhao W, Xu B, Xu M (2009) A multipath routing protocol based on clustering and ant colony optimization for wireless sensor networks. Sensors 10(5):4521–4540

    Article  Google Scholar 

  • Yau K-LA, Teal PD, Komisarczuk P (2012) Reinforcement learning for context awareness and intelligence in wireless networks: review, new features and open issues. J Netw Comput Appl 35(1):253–267

    Article  Google Scholar 

  • Yi S, Cho Y, Heo J (2007) Peach: power-efficient and adaptive clustering hierarchy protocol for wireless sensor networks. Comput Commun 30(14):2842–2852

    Article  Google Scholar 

  • Yick J, Ghosal D, Mukherjee B (2008) Wireless sensor network survey. Comput Netw 52(12):2292–2330

    Article  Google Scholar 

  • Younis O, Fahmy S (2004) Heed: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans Mob Comput 3(4):366–379

    Article  Google Scholar 

  • Zahedi ZM, Shokouhifar M, Akbari R (2016) Swarm intelligence based fuzzy routing protocol for clustered wireless sensor networks. Expert Syst Appl 55:313–328

    Article  Google Scholar 

  • Zeng B, Dong Y (2016) An improved harmony search based energy-efficient routing algorithm for wireless sensor networks. Appl Soft Comput 41:135–147

    Article  Google Scholar 

  • Zhang H, Shen H (2010) Energy-efficient beaconless geographic routing in wireless sensor networks. IEEE Trans Parallel Distrib Syst 21(6):881–896

    Article  Google Scholar 

Download references

Acknowledgments

The authors of the study acknowledge the contribution of I. K. Gujral Punjab Technical University, Kapurthala, Punjab, India.

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Authors and Affiliations

  1. I. K. G Punjab Technical University, Kapurthala, Punjab, 144001, India

    Palvinder Singh Mann

  2. S B S State Technical Campus, Punjab Technical University, Ferozepur, 152004, Punjab, India

    Satvir Singh

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  1. Palvinder Singh Mann
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  2. Satvir Singh
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Correspondence to Palvinder Singh Mann.

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Communicated by V. Loia.

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Mann, P.S., Singh, S. Artificial bee colony metaheuristic for energy-efficient clustering and routing in wireless sensor networks. Soft Comput 21, 6699–6712 (2017). https://doi.org/10.1007/s00500-016-2220-0

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  • DOI: https://doi.org/10.1007/s00500-016-2220-0

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