{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T09:23:20Z","timestamp":1763457800684,"version":"build-2065373602"},"reference-count":22,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2019,1,7]],"date-time":"2019-01-07T00:00:00Z","timestamp":1546819200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The geographic routing protocol only requires the location information of local nodes for routing decisions, and is considered very efficient in multi-hop wireless sensor networks. However, in dynamic wireless sensor networks, it increases the routing overhead while obtaining the location information of destination nodes by using a location server algorithm. In addition, the routing void problem and location inaccuracy problem also occur in geographic routing. To solve these problems, a novel fuzzy logic-based geographic routing protocol (FLGR) is proposed. The selection criteria and parameters for the assessment of the next forwarding node are also proposed. In FLGR protocol, the next forward node can be selected based on the fuzzy location region of the destination node. Finally, the feasibility of the FLGR forwarding mode is verified and the performance of FLGR protocol is analyzed via simulation. Simulation results show that the proposed FLGR forwarding mode can effectively avoid the routing void problem. Compared with existing protocols, the FLGR protocol has lower routing overhead, and a higher packet delivery rate in a sparse network.<\/jats:p>","DOI":"10.3390\/s19010196","type":"journal-article","created":{"date-parts":[[2019,1,9]],"date-time":"2019-01-09T03:06:06Z","timestamp":1547003166000},"page":"196","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Fuzzy Logic-Based Geographic Routing Protocol for Dynamic Wireless Sensor Networks"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0956-8164","authenticated-orcid":false,"given":"Xing","family":"Hu","sequence":"first","affiliation":[{"name":"School of Aeronautics Engineering, Air Force Engineering University, Xi\u2019an 710038, China"}]},{"given":"Linhua","family":"Ma","sequence":"additional","affiliation":[{"name":"Institute of Unmanned Systems Technology, Northwestern Polytechnical University, Xi\u2019an 710072, China"}]},{"given":"Yongqiang","family":"Ding","sequence":"additional","affiliation":[{"name":"Aviation Petty Officer School, Air Force Engineering University, Xinyang 464000, China"}]},{"given":"Jin","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Aeronautics Engineering, Air Force Engineering University, Xi\u2019an 710038, China"},{"name":"Xi\u2019an Institute of Space Radio Technology, Xi\u2019an 710000, China"}]},{"given":"Yan","family":"Li","sequence":"additional","affiliation":[{"name":"School of Aeronautics Engineering, Air Force Engineering University, Xi\u2019an 710038, China"},{"name":"Xi\u2019an Institute of Space Radio Technology, Xi\u2019an 710000, China"}]},{"given":"Shiping","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Aeronautics Engineering, Air Force Engineering University, Xi\u2019an 710038, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,1,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1016\/S1389-1286(01)00302-4","article-title":"Wireless sensor networks: A survey","volume":"38","author":"Akyildiz","year":"2002","journal-title":"Comput. Netw."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11227-013-1021-9","article-title":"Wireless sensor networks: A survey on recent developments and potential synergies","volume":"68","author":"Rawat","year":"2014","journal-title":"J. Supercomput."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Bhatti, G. (2018). Machine Learning Based Localization in Large-Scale Wireless Sensor Networks. Sensors, 18.","DOI":"10.3390\/s18124179"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Wang, K., Chen, P., and Teunissen, P. (2018). Fast Phase-Only Positioning with Triple-Frequency GPS. Sensors, 18.","DOI":"10.3390\/s18113922"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Li, J., Jannotti, J., and De Couto, D.S.J. (2000, January 6\u201311). A scalable location service for geographic ad hoc routing. Proceedings of the 6th Annual International Conference on Mobile Computing and Networking, Boston, MA, USA.","DOI":"10.1145\/345910.345931"},{"key":"ref_6","first-page":"28","article-title":"Survey on geographic routing in wireless sensor networks","volume":"35","author":"Luo","year":"2008","journal-title":"Comput. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Karp, B., and Kung, H.T. (2000, January 6\u201311). GPSR: Greedy perimeter stateless routing for wireless networks. Proceedings of the 6th Annual International Conference on Mobile Computing and Networking, Boston, MA, USA.","DOI":"10.1145\/345910.345953"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Zadeh, L.A. (1996). Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems, World Scientific.","DOI":"10.1142\/9789814261302_0001"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Pedrycz, W., and Gomide, F. (2007). Fuzzy Systems Engineering: Toward Human-Centric Computing, Wiley.","DOI":"10.1002\/9780470168967"},{"key":"ref_10","first-page":"3215","article-title":"New routing algorithm based on geographical location: GPSR-AD","volume":"29","author":"Li","year":"2009","journal-title":"J. Comput. Appl."},{"key":"ref_11","first-page":"282","article-title":"Improvement of greedy forwarding schemes based on fuzzy logic control","volume":"28","author":"Guan","year":"2011","journal-title":"Appl. Res. Comput."},{"key":"ref_12","unstructured":"Park, J., Kim, Y.N., and Byun, J.Y. (2013, January 2\u20135). A forwarder selection method for greedy mode operation of a geographic routing protocol in a WSN. Proceedings of the 2013 Fifth International Conference on Ubiquitous and Future Networks (ICUFN), Da Nang, Vietnam."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Yu, H., and Ahn, S. (2015, January 28\u201330). A geographic routing scheme with dead-end avoidance for large-scale MANETs. Proceedings of the 2015 International Conference on Information and Communication Technology Convergence (ICTC), Jeju Island, Korea.","DOI":"10.1109\/ICTC.2015.7354629"},{"key":"ref_14","first-page":"493","article-title":"Routing algorithm for Ad Hoc networks based on location prediction","volume":"36","author":"Sa","year":"2015","journal-title":"J. Chin. Comput. Syst."},{"key":"ref_15","first-page":"1242","article-title":"High performance routing algorithm based on geographic location prediction","volume":"36","author":"Sa","year":"2015","journal-title":"J. Northeast. Univ. (Nat. Sci.)"},{"key":"ref_16","first-page":"59","article-title":"Geographic routing algorithm based on location prediction in WSN","volume":"45","author":"Wang","year":"2018","journal-title":"Comput. Sci."},{"key":"ref_17","unstructured":"Lin, J.L., and Kuo, G.S. (2006, January 7\u201310). A novel location-fault-tolerant geographic routing scheme for wireless ad hoc networks. Proceedings of the IEEE 63rd Vehicular Technology Conference, VTC 2006-Spring, Melbourne, Australia."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Xiao, H., Zhang, H., and Wang, Z. (2017, January 21\u201323). An RSSI based DV-hop algorithm for wireless sensor networks. Proceedings of the 2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM), Victoria, BC, Canada.","DOI":"10.1109\/PACRIM.2017.8121929"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1049\/el.2017.2673","article-title":"Exponential utility function based criteria for network selection in heterogeneous wireless networks","volume":"54","author":"Khan","year":"2018","journal-title":"Electron. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"558","DOI":"10.1109\/TFUZZ.2015.2460750","article-title":"Extensions of Atanassov\u2019s Intuitionistic Fuzzy Interaction Bonferroni Means and Their Application to Multiple-Attribute Decision Making","volume":"24","author":"He","year":"2016","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"875","DOI":"10.1109\/TR.2017.2717186","article-title":"A game theoretic approach to network reliability assessment","volume":"66","author":"Zhang","year":"2017","journal-title":"IEEE Trans. Reliab."},{"key":"ref_22","first-page":"123","article-title":"Representation, ranking, and distance of fuzzy number with exponential membership function using graded mean integration method","volume":"16","author":"Li","year":"2000","journal-title":"Tamsui Oxf. J. Math. Sci."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/1\/196\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:24:06Z","timestamp":1760185446000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/1\/196"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1,7]]},"references-count":22,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2019,1]]}},"alternative-id":["s19010196"],"URL":"https:\/\/doi.org\/10.3390\/s19010196","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2019,1,7]]}}}