Elsevier

Ad Hoc Networks

Volume 93, October 2019, 101912
Ad Hoc Networks

Energy efficient multi-objective evolutionary routing scheme for reliable data gathering in Internet of underwater acoustic sensor networks

https://doi.org/10.1016/j.adhoc.2019.101912Get rights and content

Highlights

  • We propose an energy efficient evolutionary multi-objective clustering mechanism for reliable data transmission, network load balancing and prolonging the lifetime of UASNs.

  • We propose an energy efficient evolutionary multi-objective routing mechanism to significantly reduce the probability of packet loss during reliable data transmission in UWSNs.

  • Performance evaluations show that the proposed approach is efficient in terms of packet delivery ratio, throughput, delay and residual energy compared to the existing routing schemes.

Abstract

Earth's surface is covered with two-thirds of water. The marine world covers the lakes, rivers and sea and is rich in natural resources largely unexplored by human beings. Recently, underwater wireless sensor network (UWSN) with the advancement in the Internet of underwater smart things has emerged as promising networking techniques to explore the mysteries of vastly unexplored ocean environments for several underwater applications. These applications include offshore exploration, pollution monitoring, disaster prevention, oceanographic data collection, offshore oil fields monitoring, tactical surveillance applications and several others. However, the underwater channel impairments caused by multipath effects, fading, bit errors, variable and high latency and low bandwidth severely limits the data transmission reliability for UWSNs-based applications. This results in poor quality-aware data gathering in UWSNs. Therefore, designing a quality of service (QoS)-aware data gathering protocol to monitor and explore oceans is challenging in the underwater environments. In this paper, we propose a bio-inspired multi-objective evolutionary routing protocol (called MERP) for UWSNs-based applications. The designed routing protocol exploits the features of the natural evolution of the multi-objective genetic algorithm in order to provide reliable and energy-aware information gathering in UWSNs. The extensive simulation results show that the developed protocol attains its defined goals compared to existing UWSNs-based routing protocols during monitoring and exploring underwater environments.

Introduction

In human's survivability, water plays a vital role. Therefore, the oceanic world has been fascinating humans due to means of transportation and natural resources, such as oil, natural gases, mines, etc. [1]. In the last several years, humans with the advancement in science and technology seriously started to explore the underwater world. However, only about 10% of the 71% water world has been explored and the rest 61% is yet to be scrutinized. In recent years, the use of automated sensor and communication technologies has attracted attention for unmanned exploration of the terrestrial environment [2]. The key aim of sensor technology is to perform collaborative monitoring tasks in a given area and convey observed data to the user by employing advanced wireless or wired communication technologies [3]. However, the terrestrial sensors based on radio waves due to the presence of absorption of high-frequency components and high attenuation cannot propagate well in the underwater environment. The terrestrial sensor network can only achieve high-speed transmission in short with the expense of high-power consumption and long antennas. They cannot fulfill the requirements of long-distance underwater communication and thus not suitable for UWSNs [4]. Therefore, the terrestrial network protocols behave differently and show degradation in performance when tested in the underwater environment. Consequently, the underwater application requirements hinder the use of terrestrial sensor network algorithms or protocols directly in underwater environments. This gives rise to use acoustic waves for unmanned exploration of the underwater environment [5].

On the other hand, the key aim of the Internet of underwater things is to connect all devices located in the underwater to monitor and control the events in a real-time from any remote location worldwide [6]. The Internet of underwater things in the UWSNs has several numerous applications, such as maritime rescue, tactical surveillance, disaster prevention, oil and gas reservoir discovery and study of aquatic life. However, exploration of the oceans with the UWSNs is challenging due to corrosion, fouling, low bandwidth, high bit error rate, multi-path fading, latency, high water pressure, and other uncertain events. Therefore, the routing protocols designed with self-configuring and communicating capabilities for the acoustic sensor networks perform poorly due to time-varying link quality characteristics during unmanned exploration in the underwater environment. This results in poor quality-aware data gathering in UWSNs [7]. The low energy consumption (Ec) is another fundamental requirement for the acoustic sensor nodes (ASNs) in UWSNs. They carry limited batteries that cannot be replaced easily to recharge the energy of nodes at any time due to the unpredictable and complex environment of the ocean. Therefore, consideration of the energy efficiency and quality-aware data are vital in UWSNs [8]. Recently, the clustering mechanism has been proven as a prominent networking mechanism for balancing the network energy consumption and providing quality-aware data delivery to the end user. The key aim of the clustering mechanism is to divide the entire network into subgroups of two-level hierarchy. In a higher level hierarchy, cluster heads (CHs) are grouped together while sensors are organized autonomously to each CH as member nodes in the lower level for achieving basic network performance in UWSNs [9].

In each subgroup, a cluster leader acts as an overseer and tightly holds its member nodes for data gathering in the UWSNs. The cluster leader is responsible to provide intra-cluster transmission schedules, compute links quality and periodically monitors its member nodes. Moreover, it fuses the received data and transmits the aggregated data via direct or multi-hop manner with the help of intermediate CHs toward the sink. In addition, it is also responsible to perform tasks like relaying data, route maintenance and other routine activities [10]. Therefore, it consumes available resources at higher rates compared to other sensors in the network. This heavy data traffic distribution load most of the times leading to the early death of the cluster leaders, which may result in partitioning a region or the entire network. Hence, the cluster leaders must have higher energy than other nodes in the groups. However, appointing a clustering leader without considering its residual energy (Re), Euclidean distance and network load also degrade the overall network performance in UWSNs [11]. In addition, a cluster leader must be rotated in each cluster in a round ribbon manner to equalize the network power depletion burden of the UWSNs. Moreover, unequal size clustering architecture and a cluster leader with high residual energy and average lower distance to the neighboring sensors can significantly increase the overall data gathering efficiency and balances the network lifetime in UWSNs. Moreover, the data gathering in a multi-hop manner over highly stable links between cluster leaders can also significantly increase the data gathering efficiency with reduced energy consumption in UWSNs [12]. However, designing a highly stable clustering-based routing mechanism for efficient data gathering with low energy consumption is challenging due to unique underwater characteristics.

In this paper to handle aforesaid challenges, we propose a bio-inspired, multi-objective evolutionary routing scheme for UWSNs. The designed routing scheme exploits the features of the natural evolution of the multi-objective genetic algorithm in order to provide quality-aware and energy efficient information gathering for UWSN-based events monitoring applications. In this study, we have three contributions to the literature: First, we propose a multi-objective clustering mechanism for UWSNs-based applications. The proposed dynamic clustering mechanism generates a set of different size clusters with rotating cluster leaders, which organize sensors into a connected hierarchy over highly reliable links for distributing the data traffic load evenly in UWSNs. In addition, the small size clusters formation nearer to the sink further avoids the hotspot and memory-overrun issues in the network. Second, we propose a multi-objective cluster-based routing mechanism for UWSNs-based underwater applications. The proposed multi-objective routing method by considering the genetic alteration in the mating procedure of an evolutionary algorithm finds the best shortest routing paths from the source toward the destination in UWSNs. Due to its self-learning mechanism, the proposed scheme intelligently selects highly stable links among CHs during relaying events information from the source toward the destination in UWSNs. This results in high network throughput, packet delivery ratio and energy consumption in UWSNs. Moreover, the proposed scheme minimizes the data path loops and hotspot issues due to conveying information over predefined routing paths in a greedy manner in UWSNs. In addition, the proposed scheme minimizes route failure issues and significantly repairs a broken link in a bounded time interval by employing self-learning based intelligent mechanism in UWSNs. Third, based on the realistic underwater channel model, the detailed performance evaluations have been conducted. The extensive simulation results reveal that the proposed scheme attains its defined goals in terms of data packets delivery, packet error rates, congestion, latency, throughput, and energy consumption compared to existing UWSNs-based routing schemes during monitoring and exploring aquatic environments.

The rest of this study is organized as follows. Previous work, routing protocol design challenges, and motivations are summarized in Section 2. The proposed scheme is presented in Section 3. Section 4 presents the underwater channel model and the energy consumption model in detail. In addition, Section 4 also illustrates the simulation metrics, settings and simulation results of the proposed scheme against the existing schemes. Lastly, Section 5 concludes the paper with potential research guidelines.

Section snippets

Literature review

In the last couple of years, numerous routing protocols for events driven applications have been proposed to convey quality-aware data from the source toward the sink in UWSNs. For example, the authors in [13] propose a pressure sensor-based information collection protocol for UWSNs. The designed protocol considers the residual energy and distance information to estimate the link quality between acoustic sensors in UWSNs. The designed protocol performs superior in terms of Ec, latency and data

Proposed routing protocol (MERP)

The working procedure of MERP in underwater environments is explained in the subsequent sections.

Performance analysis

The underwater path loss and energy consumption models are given as below.

Conclusion

The underwater wireless sensor network with the advancement in the Internet of underwater smart things has emerged as a promising networking technique to facilitate the discovery of vast unexplored ocean environments. However, the unique characteristics of an underwater environment pose a number of constraints on reliable data transmission in UWSNs. Thus, the performance of ASNs for QoS-aware data gathering is hampered in UWSNs-based underwater applications. Therefore, designing a quality-aware

Acknowledgments

The work of Vehbi Cagri Gungor was supported by the Turkish Scientific and Technical Research Council (TUBITAK) under grant no. 114E248. The research work of Muhammad Faheem is supported by the Universiti Teknologi Malaysia (UTM) under research grant no. IDF.2018/ 7624524649, Malaysia. The work of Md. Asri Bin Ngadi is supported by the UTM, Malaysia.

Declaration of Competing Interest

We declare that the authors have no significant competing financial, professional, or personal interests that might have influenced the performance

Muhammad Faheem received the B.Sc. Computer Engineering degree in 2010 from the Department of Computer Engineering at the University College of Engineering & Technology, Bahauddin Zakariya University Multan, Pakistan. In 2012, he received an M.S. degree in Computer Science from the Faculty of Computer Science and Information System at Universiti Teknologi Malaysia. In the past, he served as a lecturer at Comsats Institute of Information & Technology from 2011 to 2012, Pakistan. Since 2013 he is

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  • Cited by (0)

    Muhammad Faheem received the B.Sc. Computer Engineering degree in 2010 from the Department of Computer Engineering at the University College of Engineering & Technology, Bahauddin Zakariya University Multan, Pakistan. In 2012, he received an M.S. degree in Computer Science from the Faculty of Computer Science and Information System at Universiti Teknologi Malaysia. In the past, he served as a lecturer at Comsats Institute of Information & Technology from 2011 to 2012, Pakistan. Since 2013 he is working as a lecturer/researcher at Abdullah Gul University, Kayseri, Turkey. Also, he is a Ph.D. student in the Faculty of Engineering, School of Computer Science, Universiti Teknologi Malaysia (UTM), Malaysia. His research interest includes the areas of UWSNs. communications, energy harvesting, underwater acoustic communications, cognitive radio sensor networks, and information storage and retrieval architecture in the sensor networks. Mr. Faheem has authored several papers in refereed journals and has been serving as a reviewer for numerous Journals, such as Journal of Network and Computer Applications, Ad-hoc Networks, Computer Networks, Computer Standards and Interfaces, IEEE Access, IEEE Transaction on Vehicular Technology, Pervasive and Mobile Computing, IEEE Communication magazine and Future Generation Computer Systems.

    Md Asri Ngadi received his Ph.D. in Computer Science from Aston University, Birmingham, UK in 2005. He had spent more than a decade with leading technology firms and universities as a process analyst, senior systems analyst, project manager, and lecturer. He had participated in and managed several communication and security software technologies development projects. His area of research specialization includes system survivability and security, autonomic computing and self-healing and regenerating systems, and network modeling. Currently, he is a professor and Chair of Computer and Telecommunication Engineering Department at Universiti Teknologi Malaysia (UTM), Malaysia. His contributions include publishing several academic books and in the development of programs to enhance minority involvement in bridging the ICT digital gap. He has published more than 100 papers in reputable journals and conference proceeding.

    Vehbi Cagri Gungor received his B.S. and M.S. degrees in Electrical and Electronics Engineering from Middle East Technical University, Ankara, Turkey, in 2001 and 2003, respectively. He received his Ph.D. degree in electrical and computer engineering from the Broadband and Wireless Networking Laboratory, Georgia Institute of Technology, Atlanta, GA, USA, in 2007. Currently, he is a professor and Chair of Computer Engineering Department, Abdullah Gul University (AGU), Kayseri, Turkey. His current research interests are in UWSNs. communications, machine-to-machine communications, next-generation wireless networks, wireless ad hoc and sensor networks, cognitive radio networks. Dr. Gungor has authored more than 90 papers in refereed journals and international conference proceedings and has been serving as an associate editor of prestigious journals, such as for IEEE Transactions on Industrial Electronics and Ad Hoc Networks (Elsevier). He is also the recipient of the Distinguished Young Scientist Award (The Scientific and Technological Research Council of Turkey (TUBITAK)) in 2017, Distinguished Young Scientist Award (BAGEP) in 2016, Turkish Academy of Sciences Distinguished Young Scientist Award (TUBA-GEBIP) in 2014, IEEE Trans. on Industrial Informatics Best Paper Award in 2012, the European Union FP7 Marie Curie IRG Award in 2009, AVEA Research Grant Awards in 2013 and 2014, Turk Telekom Research Grant Awards in 2010 and 2012, and the San-Tez Project Awards supported by Alcatel-Lucent, and the Turkish Ministry of Science, Industry and Technology in 2010.

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