Abstract
Wireless sensor networks (WSNs) are an important component of the Internet of Things (IoT). Each multicast group in a WSN consists of a set of multicast members. In a sparse network, multicast members belonging to the same group may not be very closely spaced. On the other hand, in a dense environment, more than one multicast member of a group may highly reside within downlink regions of the same router which may or may not be a multicast member. In that case, a multicast message can be delivered to more than one multicast member in a shot. This characteristic improves the status of a node from an ordinary router to a topological kingpin. If a good number of topological kingpins are included in a multicast tree, then a great amount of energy is saved increasing network throughput. The present article proposes one such energy efficient multicast scheme: Smart–Green–Mult (SGM), based on Software Defined Wireless Sensor Network (SD-WSN) framework. The network is divided into several zones. The shape of each zone is either circular or elliptical or polygonal. Each zone is under control of an Software Defined Network controller. SDN controller of each zone is aware of the topology of the zone and can compute energy efficient paths from any source to any destination inside or outside the zone. Overall this is a multicast protocol in SD-WSN.















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Anitha J, Kumar BA, Rakesh M (2017) Multicast routing protocol for energy efficiency in wireless sensor networks. INCOSE Int Symp 27(1):871–879. https://doi.org/10.1002/j.2334-5837.2017.00399.x
Baccour N, Koubâa A, Mottola L, Zúñiga MA, Youssef H, Boano CA, Alves M (2012) Radio link quality estimation in wireless sensor networks: a survey. ACM Trans Sens Netw 8(4):34:1–34:33. https://doi.org/10.1145/2240116.2240123
Barati M, Sajadi J (2011) A learning automata based and multicast routing energy efficiency algorithm using minimum spanning tree for wireless sensor networks. Aust J Basic Appl Sci 5(12):239–248
Chen Q, Cheng S, Gao H, Li J, Cai Z (2015) Energy-efficient algorithm for multicasting in duty-cycled sensor networks. Sensors (Basel) 15(12):31224–31243. https://doi.org/10.3390/s151229860
Cheng L, Niu J, Cao J, Das SK, Gu Y (2014) QoS aware geographic opportunistic routing in wireless sensor networks. IEEE Trans Parallel Distrib Syst 25(7):1864–1875. https://doi.org/10.1109/TPDS.2013.240
De Gante A, Aslan M, Matrawy A (2014) Smart wireless sensor network management based on software-defined networking, pp 71–75. https://doi.org/10.1109/QBSC.2014.6841187
Faheem M, Butt RA, Raza B, Ashraf MW, Ngadi M, Gungor V (2019) Energy efficient and reliable data gathering using internet of software-defined mobile sinks for WSNs-based smart grid applications
Faheem M, Gungor VC (2018) MQRP: Mobile sinks-based QoS-aware data gathering protocol for wireless sensor networks-based smart grid applications in the context of industry 4.0-based on internet of things. Fut Gener Comput Syst 82:358–374
Fontes RR, Afzal S, Brito SHB, Santos MAS, Rothenberg CE (2015) Mininet-WiFi: emulating software-defined wireless networks, pp 384–389. https://doi.org/10.1109/CNSM.2015.7367387
Galluccio L, Milardo S, Morabito G, Palazzo S (2015) SDN-WISE: Design, prototyping and experimentation of a stateful SDN solution for WIreless SEnsor networks, pp 513–521. https://doi.org/10.1109/INFOCOM.2015.7218418
Gnawali O, Fonseca R, Jamieson K, Kazandjieva M, Moss D, Levis P (2013) CTP: an efficient, robust, and reliable collection tree protocol for wireless sensor networks. ACM Trans Sens Netw 10(1):16:1–16:49. https://doi.org/10.1145/2529988
Guerzoni R, Vaishnavi I, Perez Caparros D, Galis A, Tusa F, Monti P, Szabo R (2017) Analysis of end-to-end multi-domain management and orchestration frameworks for software defined infrastructures: an architectural survey. Trans Emerg Telecommun Technol 28(4):e3103. https://doi.org/10.1002/ett.3103
He Q, Wang X, Huang M (2018) OpenFlow-based low-overhead and high-accuracy SDN measurement framework. Trans Emerg Telecommun Technol 29(2):e3263. https://doi.org/10.1002/ett.3263
Huang H, Guo S, Li P, Liang W, Zomaya AY (2016) Cost minimization for rule caching in software defined networking. IEEE Trans Parallel Distrib Syst 27(4):1007–1016. https://doi.org/10.1109/TPDS.2015.2431684
Akyildiz IF, Vuran MC (2010) Wireless sensor networks, vol 4. Wiley, New York
Akyildiz IF, Su W, Sankarasubramaniam Y, Cayircil E (2002) Wireless sensor networks: a survey. Comput Netw 38(04):393–422. https://doi.org/10.1016/S1389-1286(01)00302-4
Jagadeesan NA, Krishnamachari B (2014) Software-defined networking paradigms in wireless networks: a survey. ACM Comput Surv 47(2):27:1–27:11. https://doi.org/10.1145/2655690
Jararweh Y, Al-Ayyoub M, Darabseh A, Benkhelifa E, Vouk M, Rindos A (2015) SDIoT: a software defined based internet of things framework. J Ambient Intell Humaniz Comput 6(4):453–461. https://doi.org/10.1007/s12652-015-0290-y
Kim BS, Aldwairi M, Kim KI (2018) An efficient real-time data dissemination multicast protocol for big data in wireless sensor networks. J Grid Comput. https://doi.org/10.1007/s10723-018-9447-1
Kim H, Feamster N (2013) Improving network management with software defined networking. IEEE Commun Mag 51(2):114–119. https://doi.org/10.1109/MCOM.2013.6461195
Kobo HI, Abu-Mahfouz AM, Hancke GP (2017) A survey on software-defined wireless sensor networks: challenges and design requirements. IEEE Access 5:1872–1899. https://doi.org/10.1109/ACCESS.2017.2666200
Li W, Delicato FC, Pires PF, Lee YC, Zomaya AY, Miceli C, Pirmez L (2014) Efficient allocation of resources in multiple heterogeneous wireless sensor networks. J Parallel Distrib Comput 74(1):1775–1788. https://doi.org/10.1016/j.jpdc.2013.09.012
Mathews K, Modieginyane Letswamotse BB, Malekian R, Abu-Mahfouz MA (2018) Software defined wireless sensor networks application opportunities for efficient network management: a survey. Comput Electric Eng 66(04):274–287. https://doi.org/10.1016/j.compeleceng.2017.02.026
Mottola L, Picco GP (2011) MUSTER: adaptive energy-aware multisink routing in wireless sensor networks. IEEE Trans Mob Comput 10(12):1694–1709. https://doi.org/10.1109/TMC.2010.250
Pantazis NA, Nikolidakis SA, Vergados DD (2013) Energy-efficient routing protocols in wireless sensor networks: a survey. IEEE Commun Surv Tutor 15(2):551–591. https://doi.org/10.1109/SURV.2012.062612.00084
Park C, Lahiri K, Raghunathan A (2005) Battery discharge characteristics of wireless sensor nodes: an experimental analysis. In: 2005 Second Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks. IEEE SECON 2005, pp 430–440
Picco GP (2010) Software engineering and wireless sensor networks: happy marriage or consensual divorce? ACM, New York, pp 283–286. https://doi.org/10.1145/1882362.1882421
Radhika R, Hanirex D, Muthukumaravel D (2018) Tree construction of multicast distributed systems in wireless sensor networks (WSN). Int J Pure Appl Math 118(20):255–264
Sanchez JA, Ruiz PM, Stojmnenovic I (2006) GMR: geographic multicast routing for wireless sensor networks, pp 20–29. https://doi.org/10.1109/SAHCN.2006.288405
Stancu AL, Halunga S, Vulpe A, Suciu G, Fratu O, Popovici EC (2015) A comparison between several software defined networking controllers, pp. 223–226. https://doi.org/10.1109/TELSKS.2015.7357774
Subha M, Manoranjani M (2011) Modified efficient geographic multicast protocol in multicasting over mobile ad hoc networks for QOS improvements. J Comput Appl 4(2):57–62
Sufian A, Banerjee A, Dutta P (2019) Energy and velocity based tree multicast routing in mobile ad-hoc networks. Wirel Pers Commun 107(4):2191–2209. https://doi.org/10.1007/s11277-019-06378-y
Suruliandi A, Sampradeepraj T (2015) A survey on multicast routing protocols for performance evaluation in wireless sensor network. ICTACT J Commun Technol 6(1):1057–1065. https://doi.org/10.21917/ijct.2015.0153
Tomovic S, Yoshigoe K, Maljevic I, Radusinovic I (2017) Software-defined fog network architecture for IoT. Wirel Pers Commun 92(1):181–196. https://doi.org/10.1007/s11277-016-3845-0
Wang MM, Cao JN, Li J, Dasi SK (2008) Middleware for wireless sensor networks: a survey. J Comput Sci Technol 23(3):305–326. https://doi.org/10.1007/s11390-008-9135-x
Xiang W, Wang N, Zhou Y (2016) An energy-efficient routing algorithm for software-defined wireless sensor networks. IEEE Sens J 16(20):7393–7400. https://doi.org/10.1109/JSEN.2016.2585019
Yick J, Mukherjee B, Ghosal D (2008) Wireless sensor network survey. Comput Netw 52(12):2292–2330. https://doi.org/10.1016/j.comnet.2008.04.002
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Banerjee, A., Sufian, A. Smart-Green-Mult (SGM): overhear from topological kingpins in software defined wireless sensor networks. J Ambient Intell Human Comput 12, 387–404 (2021). https://doi.org/10.1007/s12652-020-01984-2
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DOI: https://doi.org/10.1007/s12652-020-01984-2