Log in

SEES: a scalable and energy-efficient scheme for green IoT-based heterogeneous wireless nodes

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

Realizing energy-efficient communication in the IoT-based large-scale systems has become a key challenge in the past few years. The need is to minimize the global energy usage of battery-operated objects so as to reduce data transmission cost and extend the network lifetime. In this paper, we propose SEES, a scalable and energy-efficient scheme for green IoT-based heterogeneous wireless nodes. We study the impact of energy-harvesting techniques by utilizing ambient energy-harvesting relay nodes in such a way that enables a higher energy conservation and guarantees a long-lived network. SEES includes: (1) a zone-based hybrid-placement scheme, (2) a Multi-Stage Weighted Election heuristic (MSWE), and (3) a Minimum Cost Cross-layer Transmission model (MCCT). Our aim is to ensure an even-random deployment of heterogeneous nodes, a scalable pre-deterministic placement of energy-harvesting nodes, a fair energy-load balancing among all the zones, and a minimum energy-cost for data transmission from the bottom layer to the topmost layer. SEES is a general scheme that supports up to n levels of heterogeneity, as well as m different election parameters (static and dynamic, associated with m generated weights), and can be used for any type of IoT-based deployment. Experimental results of extensive simulations indicate the superiority of SEES over the other traditional protocols proposed in literature. It can save up to \(62\%\) of the total energy, and, at least, it increases the network lifetime by 58, 68, 70, \(42\%\); the stability period by 192, 108, 424, \(150\%\); and the network throughput by 107, 111, 100, \(114\%\); over LEACH, SEP, ZSEP, and hetDEEC protocols respectively, for all the cases and scenarios tested.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20

Similar content being viewed by others

References

  • Abbas Z, Yoon W (2015) A survey on energy conserving mechanisms for the internet of things: wireless networking aspects. Sensors 15(10):24,818–24,847

  • Abbasi AA, Younis M (2007) A survey on clustering algorithms for wireless sensor networks. Comput Commun 30(1415):2826–2841

    Article  Google Scholar 

  • Abdollahzadeh S, Navimipour NJ (2016) Deployment strategies in the wireless sensor network: a comprehensive review. Comput Commun 91–92:1–16

    Article  Google Scholar 

  • Abdul-Qawy ASH, Srinivasulu T (2017) EH-mulSEP: energy-harvesting enabled multi-level SEP protocol for IoT-based heterogeneous WSNs. In: 3rd International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT) (Presented)

  • Agiwal M, Roy A, Saxena N (2016) Next generation 5g wireless networks: a comprehensive survey. IEEE Commun Surveys Tutori 18(3):1617–1655

    Article  Google Scholar 

  • Akyildiz I, Su W, Sankarasubramaniam Y, Cayirci E (2002) Wireless sensor networks: a survey. Comput Netw 38(4):393–422

    Article  Google Scholar 

  • Al-Fuqaha A, Guizani M, Mohammadi M, Aledhari M, Ayyash M (2015) Internet of things: a survey on enabling technologies, protocols, and applications. IEEE Commun Surveys Tutor 17(4):2347–2376

    Article  Google Scholar 

  • Anastasi G, Conti M, Francesco MD, Passarella A (2009) Energy conservation in wireless sensor networks: a survey. Ad Hoc Netw 7(3):537–568

    Article  Google Scholar 

  • Augustin A, Yi J, Clausen T, Townsley WM (2016) A study of lora: long range and low power networks for the internet of things. Sensors 16(9)

  • Bauer M, Bui N, De Loof J, Magerkurth C, Nettsträter A, Stefa J, Walewski JW (2013) IoT Reference Model. Springer, Berlin Heidelberg, pp 113–162

    Google Scholar 

  • Begishev V, Samuylov A, Moltchanov D, Samouylov K (2017) Modeling the process of dynamic resource sharing between lte and nb-iot services. In: Vishnevskiy VM, Samouylov KE, Kozyrev DV (eds) Distributed computer and communication networks. Springer, Cham, pp 1–12

    Google Scholar 

  • Borgia E (2014) The internet of things vision: key features, applications and open issues. Comput Commun 54:1–31

    Article  Google Scholar 

  • Brar GS, Rani S, Chopra V, Malhotra R, Song H, Ahmed SH (2016) Energy efficient direction-based pdorp routing protocol for wsn. IEEE Access 4:3182–3194

    Article  Google Scholar 

  • Carbajales RJ, Zennaro M, Pietrosemoli E, Freitag F (2015) Energy-efficient internet of things monitoring with low-capacity devices. In: Internet of Things (WF-IoT), 2015 IEEE 2nd World Forum on, pp 305–310

  • de Carvalho Silva J, Rodrigues JJPC, Alberti AM, Solic P, Aquino ALL (2017) Lorawan—a low power wan protocol for internet of things: a review and opportunities. In: 2017 2nd International Multidisciplinary Conference on Computer and Energy Science (SpliTech), pp 1–6

  • Chen M, Miao Y, Hao Y, Hwang K (2017) Narrow band internet of things. IEEE Access 5:20557–20577

  • Chen RC, Hsieh CF, Chang WL (2016) Using ambient intelligence to extend network lifetime in wireless sensor networks. J Ambient Intell Humaniz Comput 7(6):777–788

    Article  Google Scholar 

  • Cui X, Liu Z (2009) Bcee: A balanced-clustering, energy-efficient hierarchical routing protocol in wireless sensor networks. In: 2009 IEEE International Conference on Network Infrastructure and Digital Content, pp 26–30

  • DGAniello G, Gaeta M, Hong TP, (2018) Effective quality-aware sensor data management. IEEE Trans Emerg Topics Comput Intell 2(1):65–77

  • De Guglielmo D, Anastasi G, Seghetti A (2014) From IEEE 802.15.4 to IEEE 802.15.4e: a step towards the internet of things. Springer, Cham, pp 135–152

  • Decuir J (2010) Bluetooth 4.0: Lowenergy. Cambridge Silicon Radio SR PLC, UK

  • Djenouri D, Bagaa M (2015) Energy harvesting aware relay node addition for power-efficient coverage in wireless sensor networks. In: IEEE International Conference on Communications (ICC), pp 86–91

  • Faisal S, Javaid N, Javaid A, Khan MA, Bouk SH, Khan ZA (2013) Z-SEP: zonal-stable election protocol for wireless sensor networks. J Basic Appl Sci Res (JBASR) 3(5):132–139

    Google Scholar 

  • Gaeta M, Loia V, Tomasiello S (2015) Multisignal 1-d compression by F-transform for wireless sensor networks applications. Appl Soft Comput 30:329–340

    Article  Google Scholar 

  • Gaeta M, Loia V, Tomasiello S (2016) Cubic bspline fuzzy transforms for an efficient and secure compression in wireless sensor networks. Inf Sci 339:19–30

    Article  MATH  Google Scholar 

  • Gandotra P, Jha RK (2017) A survey on green communication and security challenges in 5g wireless communication networks. J Netw Comput Appl 96:39–61

    Article  Google Scholar 

  • Gandotra P, Jha RK, Jain S (2017) Green communication in next generation cellular networks: A survey. IEEE Access 5:11727–11758

  • Gherbi C, Aliouat Z, Benmohammed M (2016) An adaptive clustering approach to dynamic load balancing and energy efficiency in wireless sensor networks. Energy 114:647–662

    Article  Google Scholar 

  • Gulia S, Nagendra SS, Khare M, Khanna I (2015) Urban air quality management—a review. Atmos Pollut Res 6(2):286–304

    Article  Google Scholar 

  • Gupta V, Pandey R (2016) An improved energy aware distributed unequal clustering protocol for heterogeneous wireless sensor networks. Eng Sci Technol Int J 19(2):1050–1058

    Article  Google Scholar 

  • Hari U, Ramachandran B, Johnson C (2013) An unequally clustered multihop routing protocol for wireless sensor networks. In: International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp 1007–1011

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

    Article  Google Scholar 

  • Heinzelman WR, Chandrakasan A, Balakrishnan H (2000) Energy-efficient communication protocol for wireless microsensor networks. In: 33rd Annual Hawaii International Conference on System Sciences, pp 1–10

  • Huang J, Meng Y, Gong X, Liu Y, Duan Q (2014) A novel deployment scheme for green internet of things. IEEE Internet Things J 1(2):196–205

    Article  Google Scholar 

  • Jaffri ZUA, Cai Y (2014) Zet: Zone and energy threshold based clustering routing protocol for wireless sensor networks. In: 23rd International Conference on Computer Communication and Networks (ICCCN), pp 1–6

  • Kamalinejad P, Mahapatra C, Sheng Z, Mirabbasi S, Leung VCM, Guan YL (2015) Wireless energy harvesting for the internet of things. IEEE Commun Mag 53(6):102–108

    Article  Google Scholar 

  • Kumar A, Kim H, Hancke GP (2013) Environmental monitoring systems: a review. IEEE Sens J 13(4):1329–1339

    Article  Google Scholar 

  • Kumar JS, Zaveri MA (2016) Hierarchical clustering for dynamic and heterogeneous internet of things. Proc Comput Sci 93:276 – 282, proceedings of the 6th International Conference on Advances in Computing and Communications

  • Kumaramangalam MV, Adiyapatham K, Kandasamy C (2014) Zone-based routing protocol for wireless sensor networks. Int Scholar Res Not 2014:1–9

    Article  Google Scholar 

  • Liao Y, Qi H, Li W (2013) Load-balanced clustering algorithm with distributed self-organization for wireless sensor networks. IEEE Sens J 13(5):1498–1506

    Article  Google Scholar 

  • Lin TH, Liaw DC (2015) Development of an intelligent disaster information-integrated platform for radiation monitoring. Nat Hazards 76(3):1711–1725

    Article  Google Scholar 

  • Lindsey S, Raghavendra C, Sivalingam KM (2002) Data gathering algorithms in sensor networks using energy metrics. IEEE Trans Parallel Distrib Syst 13(9):924–935

    Article  Google Scholar 

  • LoRa Alliance (2015) White paper: a technical overview of lora and lorawan. The LoRa Alliance, San Ramon

    Google Scholar 

  • Lu X, Wang P, Niyato D, Kim DI, Han Z (2015) Wireless networks with rf energy harvesting: a contemporary survey. IEEE Commun Surveys Tutor 17(2):757–789

    Article  Google Scholar 

  • Mahdavinejad MS, Rezvan M, Barekatain M, Adibi P, Barnaghi P, Sheth AP (2017) Machine learning for internet of things data analysis: a survey. Digital Communications and Networks

  • Maksimovic M (2018) Greening the future: green internet of things (G-IoT) as a key technological enabler of sustainable development. Springer, Cham, pp 283–313

    Google Scholar 

  • Mary SA, Gnanadurai JB (2016) Enhanced zone stable election protocol based on fuzzy logic for cluster head election in wireless sensor networks. Int J Fuzzy Syst, Springer pp 1–14

  • Mathna C, ODonnell T, Martinez-Catala RV, Rohan J, OFlynn B (2008) Energy scavenging for long-term deployable wireless sensor networks. Talanta 75(3):613–623

  • Mekki K, Bajic E, Chaxel F, Meyer F (2018) A comparative study of lpwan technologies for large-scale iot deployment. ICT Express

  • Meng J, Zhang X, Dong Y, Lin X (2012) Adaptive energy-harvesting aware clustering routing protocol for wireless sensor networks. In: 7th International ICST Conference on Communications and Networking (CHINACOM), pp 742–747

  • Minoli D (2011) Designing green networks and network operations: saving run-the-engine costs, 1st edn. CRC Press Inc, Boca Raton

    Book  Google Scholar 

  • Minoli D (2013) Building the Internet of Things with IPv6 and MIPv6: the evolving world of M2M communications, 1st edn. Wiley, USA

  • Minoli D, Sohraby K, Kouns J (2017a) IoT security (IoTSec) considerations, requirements, and architectures. In: 2017 14th IEEE Annual Consumer Communications Networking Conference (CCNC), pp 1006–1007

  • Minoli D, Sohraby K, Occhiogrosso B (2017b) IoT considerations, requirements, and architectures for smart buildings energy optimization and next generation building management systems. IEEE Internet Things J 4(1):269–283

    Google Scholar 

  • Mondal P, Basu M (2009) Adoption of precision agriculture technologies in india and in some develo** countries: scope, present status and strategies. Prog Nat Sci 19(6):659–666

    Article  Google Scholar 

  • Muruganathan SD, Ma DCF, Bhasin RI, Fapojuwo AO (2005) A centralized energy-efficient routing protocol for wireless sensor networks. IEEE Commun Mag 43(3):S8–13

    Article  Google Scholar 

  • Naznin M, Chowdhury AS (2015) Zdg: Energy efficient zone based data gathering in a wireless sensor network. In: International Conference on Networking Systems and Security (NSysS), pp 1–7

  • Peng S, Wang T, Low C (2015) Energy neutral clustering for energy harvesting wireless sensors networks. Ad Hoc Netw 28:1–16

    Article  Google Scholar 

  • Perera C, Liu CH, Jayawardena S (2015) The emerging internet of things marketplace from an industrial perspective: a survey. IEEE Trans Emerg Topics Comput 3(4):585–598

    Article  Google Scholar 

  • Pierpaoli E, Carli G, Pignatti E, Canavari M (2013) Drivers of precision agriculture technologies adoption: A literature review. Procedia Technology 8:61–69, 6th International Conference on Information and Communication Technologies in Agriculture, Food and Environment (HAICTA 2013)

  • Qin Y, Sheng QZ, Falkner NJ, Dustdar S, Wang H, Vasilakos AV (2016) When things matter: a survey on data-centric internet of things. J Netw Comput Appl 64:137–153

    Article  Google Scholar 

  • Rani S, Talwar R, Malhotra J, Ahmed S, Sarkar M, Song H (2015) A novel scheme for an energy efficient internet of things based on wireless sensor networks. Sensors 15(11):28603–28626

  • Rault T, Bouabdallah A, Challal Y (2014) Energy efficiency in wireless sensor networks: a top–down survey. Comput Netw 67:104–122

    Article  Google Scholar 

  • Samo D, Anka L (2009) Multi-attribute decision analysis in gis: weighted linear combination and ordered weighted averaging. Informatica 33:459474

    MATH  Google Scholar 

  • SASA M, JB G (2015) A zone-based clustering protocol for wireless sensor networks. In: 9th International Conference on Computer Engineering and Applications, pp 151–161

  • Schellberg J, Hill MJ, Gerhards R, Rothmund M, Braun M (2008) Precision agriculture on grassland: applications, perspectives and constraints. Eur J Agron 29(2):59–71

    Article  Google Scholar 

  • Shah T, Javaid N, Qureshi TN (2012) Energy efficient sleep awake aware (eesaa) intelligent sensor network routing protocol. In: 2012 15th International Multitopic Conference (INMIC), pp 317–322

  • Shahraki A, KuchakiRafsanjani M, BorumandSaeid A (2017) Hierarchical distributed management clustering protocol for wireless sensor networks. Telecommun Syst Springer 65(1):193–214

  • Shaikh FK, Zeadally S (2016) Energy harvesting in wireless sensor networks: a comprehensive review. Renew Sustain Energy Rev 55:1041–1054

    Article  Google Scholar 

  • Shaikh FK, Zeadally S, Exposito E (2017) Enabling technologies for green internet of things. IEEE Syst J 11(2):983–994

    Article  Google Scholar 

  • Shalli R, Jyoteesh M, Rajneesh T (2015) Energy efficient chain based cooperative routing protocol for {WSN}. Appl Soft Comput 35:386–397

    Article  Google Scholar 

  • Sheikh OM, Mahmoud SA (2012) Cross-layer design for smart routing in wireless sensor networks. In: Wireless Sensor Networks—Technology and Protocols., InTech, chap 09, pp 189–214

  • Singh S (2017) Energy efficient multilevel network model for heterogeneous WSNs. Eng Sci Technol Int J 20(1):105–115

    Article  Google Scholar 

  • Singh S, Malik A, Kumar R (2016) Energy efficient heterogeneous DEEC protocol for enhancing lifetime in WSNs. Eng Sci Technol Int J 20(1):345–353

    Article  Google Scholar 

  • Smaragdakis G, Matta I, Bestavros A (2004) Sep: a stable election protocol for clustered heterogeneous wireless sensor networks. In: International Workshop on SANPA, pp 251–261

  • Sohraby K, Minoli D, Znati T (2007) Wireless sensor networks: technology, protocols, and applications. Wiley

  • Soyata T, Copeland L, Heinzelman W (2016) Rf energy harvesting for embedded systems: a survey of tradeoffs and methodology. IEEE Circuits Syst Mag 16(1):22–57

    Article  Google Scholar 

  • Tocchi A, Roca V, Angrisani L, Bonavolont F, Moriello RSL (2017) First step towards an iot implementation of a wireless sensors network for environmental radiation monitoring. In: 2017 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), pp 1–6

  • Vangelista L, Zanella A, Zorzi M (2015) Long-range iot technologies: the dawn of lora™. In: Atanasovski V, Leon-Garcia A (eds) Future access enablers for ubiquitous and intelligent infrastructures. Springer, Cham, pp 51–58

    Chapter  Google Scholar 

  • Wang YPE, Lin X, Adhikary A, Grovlen A, Sui Y, Blankenship Y, Bergman J, Razaghi HS (2017) A primer on 3g pp narrowband internet of things. IEEE Commun Mag 55(3):117–123

    Article  Google Scholar 

  • Weyrich M, Ebert C (2016) Reference architectures for the internet of things. IEEE Softw 33(1):112–116

    Article  Google Scholar 

  • Wixted AJ, Kinnaird P, Larijani H, Tait A, Ahmadinia A, Strachan N (2016) Evaluation of lora and lorawan for wireless sensor networks. In: 2016 IEEE SENSORS, pp 1–3

  • Yetgin H, Cheung KTK, El-Hajjar M, Hanzo LH (2017) A survey of network lifetime maximization techniques in wireless sensor networks. IEEE Commun Surveys Tutor 19(2):828–854

    Article  Google Scholar 

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

  • Yu J, Qi Y, Wang G (2011) An energy-driven unequal clustering protocol for heterogeneous wireless sensor networks. J Control Theory Appl 9(1):133–139

    Article  MathSciNet  Google Scholar 

  • Zhang P, **ao G, Tan HP (2013) Clustering algorithms for maximizing the lifetime of wireless sensor networks with energy-harvesting sensors. Comput Netw 57(14):2689–2704

    Article  Google Scholar 

  • Zhang P, Tan HP, **ao G, Yu Y (2015) Maximizing lifetime in clustered wsns with energy harvesting relay: Profiling and modeling. In: IEEE Tenth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), pp 1–6

  • Zhu C, Leung VCM, Shu L, Ngai ECH (2015) Green internet of things for smart world. IEEE Access 3:2151–2162

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Antar Shaddad H. Abdul-Qawy.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abdul-Qawy, A.S.H., Srinivasulu, T. SEES: a scalable and energy-efficient scheme for green IoT-based heterogeneous wireless nodes. J Ambient Intell Human Comput 10, 1571–1596 (2019). https://doi.org/10.1007/s12652-018-0758-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-018-0758-7

Keywords

Navigation