{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T19:18:09Z","timestamp":1775848689933,"version":"3.50.1"},"reference-count":34,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2022,12,13]],"date-time":"2022-12-13T00:00:00Z","timestamp":1670889600000},"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>With the advances in sensing technologies, sensor networks became the core of several different networks, including the Internet of Things (IoT) and drone networks. This led to the use of sensor networks in many critical applications including military, health care, and commercial applications. In addition, sensors might be mobile or stationary. Stationary sensors, once deployed, will not move; however, mobile nodes can move from one place to another. In most current applications, mobile sensors are used to collect data from stationary sensors. This raises many energy consumption challenges, including sensor networks\u2019 energy consumption, urgent messages transfer for real-time analysis, and path planning. Moreover, sensors in sensor networks are usually exposed to environmental parameters and left unattended. These issues, up to our knowledge, are not deeply covered in the current research. This paper develops a complete framework to solve these challenges. It introduces novel path planning techniques considering areas\u2019 priority, environmental parameters, and urgent messages. Consequently, a novel energy-efficient and reliable clustering algorithm is proposed considering the residual energy of the sensor nodes, the quality of wireless links, and the distance parameter representing the average intra-cluster distance. Moreover, it proposes a real-time, energy-efficient, reliable and environment-aware routing, taking into account the environmental data, link quality, delay, hop count, nodes\u2019 residual energy, and load balancing. Furthermore, for the benefit of the sensor networks research community, all proposed algorithms are formed in integer linear programming (ILP) for optimal solutions. All proposed techniques are evaluated and compared to six recent algorithms. The results showed that the proposed framework outperforms the recent algorithms.<\/jats:p>","DOI":"10.3390\/s22249789","type":"journal-article","created":{"date-parts":[[2022,12,14]],"date-time":"2022-12-14T03:21:52Z","timestamp":1670988112000},"page":"9789","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Energy and Environment-Aware Path Planning in Wireless Sensor Networks with Mobile Sink"],"prefix":"10.3390","volume":"22","author":[{"given":"Fatma H.","family":"El-Fouly","sequence":"first","affiliation":[{"name":"Department of Communication and Computer Engineering, Higher Institute of Engineering, El-Shorouk Academy, El-Shorouk City 11837, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ahmed B.","family":"Altamimi","sequence":"additional","affiliation":[{"name":"Computer Engineering Department, College of Computer Science and Engineering, University of Ha\u2019il, Ha\u2019il 8650, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0281-9381","authenticated-orcid":false,"given":"Rabie A.","family":"Ramadan","sequence":"additional","affiliation":[{"name":"Computer Engineering Department, College of Computer Science and Engineering, University of Ha\u2019il, Ha\u2019il 8650, Saudi Arabia"},{"name":"Department of Computer Engineering, Faculty of Engineering, Cairo University, Giza 12613, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ilyas, M., and Mahgoub, I. 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