A Probabilistic and Highly Efficient Topology Control Algorithm for Underwater Cooperating AUV Networks

The aim of the Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs) project is to make autonomous underwater vehicles (AUVs), remote operated vehicles (ROVs) and unmanned surface vehicles (USVs) more accessible and useful. To achieve cooperation and communication between different AUVs, these must be able to exchange messages, so an efficient and reliable communication network is necessary for SWARMs. In order to provide an efficient and reliable communication network for mission execution, one of the important and necessary issues is the topology control of the network of AUVs that are cooperating underwater. However, due to the specific properties of an underwater AUV cooperation network, such as the high mobility of AUVs, large transmission delays, low bandwidth, etc., the traditional topology control algorithms primarily designed for terrestrial wireless sensor networks cannot be used directly in the underwater environment. Moreover, these algorithms, in which the nodes adjust their transmission power once the current transmission power does not equal an optimal one, are costly in an underwater cooperating AUV network. Considering these facts, in this paper, we propose a Probabilistic Topology Control (PTC) algorithm for an underwater cooperating AUV network. In PTC, when the transmission power of an AUV is not equal to the optimal transmission power, then whether the transmission power needs to be adjusted or not will be determined based on the AUV’s parameters. Each AUV determines their own transmission power adjustment probability based on the parameter deviations. The larger the deviation, the higher the transmission power adjustment probability is, and vice versa. For evaluating the performance of PTC, we combine the PTC algorithm with the Fuzzy logic Topology Control (FTC) algorithm and compare the performance of these two algorithms. The simulation results have demonstrated that the PTC is efficient at reducing the transmission power adjustment ratio while improving the network performance.

[1]  Nei Kato,et al.  LTRT: An efficient and reliable topology control algorithm for ad-hoc networks , 2009, IEEE Transactions on Wireless Communications.

[2]  Y. Ahmet Sekercioglu,et al.  A Survey on Distributed Topology Control Techniques for Extending the Lifetime of Battery Powered Wireless Sensor Networks , 2013, IEEE Communications Surveys & Tutorials.

[3]  Mostafa Shamsi,et al.  A convex optimization model for topology control in network-coding-based-wireless-sensor networks , 2017, Ad Hoc Networks.

[4]  Radhika Ranjan Roy.  Reference Velocity Group Mobility , 2011 .

[5]  Michele Zorzi,et al.  Protocol design issues in underwater acoustic networks , 2011, Comput. Commun..

[6]  Gerhard P. Hancke,et al.  A Distributed Topology Control Technique for Low Interference and Energy Efficiency in Wireless Sensor Networks , 2012, IEEE Transactions on Industrial Informatics.

[7]  Juana Sendra,et al.  A Novel Topology Control Approach to Maintain the Node Degree in Dynamic Wireless Sensor Networks , 2014, Sensors.

[8]  Adnan Yazici,et al.  An adaptive, energy-aware and distributed fault-tolerant topology-control algorithm for heterogeneous wireless sensor networks , 2016, Ad Hoc Networks.

[9]  Panganamala Ramana Kumar,et al.  The Number of Neighbors Needed for Connectivity of Wireless Networks , 2004, Wirel. Networks.

[10]  S. Chandrakala,et al.  Survey on state scheduling-based topology control in unattended wireless sensor networks , 2016, Comput. Electr. Eng..

[11]  Radhika Ranjan Roy,et al.  Handbook of Mobile Ad Hoc Networks for Mobility Models , 2010 .

[12]  Kyung Sup Kwak,et al.  Distributed Topology Control With Lifetime Extension Based on Non-Cooperative Game for Wireless Sensor Networks , 2016, IEEE Sensors Journal.

[13]  José-Fernán Martínez,et al.  A Survey on Underwater Acoustic Sensor Network Routing Protocols , 2016, Sensors.

[14]  Ahmed Helmy,et al.  IMPORTANT: a framework to systematically analyze the Impact of Mobility on Performance of Routing Protocols for Adhoc Networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[15]  Ye Liu,et al.  A Complex Network Approach to Topology Control Problem in Underwater Acoustic Sensor Networks , 2014, IEEE Transactions on Parallel and Distributed Systems.

[16]  Xiaoyan Hong,et al.  A group mobility model for ad hoc wireless networks , 1999, MSWiM '99.

[17]  Nadeem Javaid,et al.  Distributed Topology Control Protocols for Underwater Sensor Networks , 2016, 2016 19th International Conference on Network-Based Information Systems (NBiS).

[18]  Milica Stojanovic,et al.  Underwater sensor networks: applications, advances and challenges , 2012, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[19]  Adnan Yazici,et al.  A Distributed Fault-Tolerant Topology Control Algorithm for Heterogeneous Wireless Sensor Networks , 2015, IEEE Transactions on Parallel and Distributed Systems.

[20]  Maode Ma,et al.  A Survey on MAC Protocols for Underwater Wireless Sensor Networks , 2014, IEEE Communications Surveys & Tutorials.

[21]  Antonio Alfredo Ferreira Loureiro,et al.  A Novel Centrality Metric for Topology Control in Underwater Sensor Networks , 2016, MSWiM.

[22]  Ruchuan Wang,et al.  Topology control algorithm for underwater wireless sensor networks using GPS-free mobile sensor nodes , 2012, J. Netw. Comput. Appl..

[23]  Mauro Leoncini,et al.  The k-Neighbors Approach to Interference Bounded and Symmetric Topology Control in Ad Hoc Networks , 2006, IEEE Transactions on Mobile Computing.

[24]  Ning Li,et al.  Probability Model Based Energy Efficient and Reliable Topology Control Algorithm , 2016 .

[25]  José-Fernán Martínez,et al.  The Balanced Cross-Layer Design Routing Algorithm in Wireless Sensor Networks Using Fuzzy Logic , 2015, Sensors.

[26]  Jennifer C. Hou,et al.  Localized fault-tolerant topology control in wireless ad hoc networks , 2006, IEEE Transactions on Parallel and Distributed Systems.

[27]  Naixue Xiong,et al.  A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks , 2016, Sensors.

[28]  Milica Stojanovic,et al.  On the relationship between capacity and distance in an underwater acoustic communication channel , 2006, Underwater Networks.

[29]  Christian Bettstetter,et al.  On the minimum node degree and connectivity of a wireless multihop network , 2002, MobiHoc '02.

[30]  Mo Li,et al.  A Survey on Topology Control in Wireless Sensor Networks: Taxonomy, Comparative Study, and Open Issues , 2013, Proc. IEEE.

[31]  Ye Liu,et al.  Topology Control for Diverse Coverage in Underwater Wireless Sensor Networks , 2016, ACM Trans. Auton. Adapt. Syst..

[32]  Rudolf Bannasch,et al.  Sweep-spread carrier for underwater communication over acoustic channels with strong multipath propagation. , 2002, The Journal of the Acoustical Society of America.