Jun-Hong Cui

The challenges of building mobile underwater wireless networks for aquatic applications

The large-scale mobile underwater wireless sensor network (UWSN) is a novel networking paradigm to explore aqueous environments. However, the characteristics of mobile UWSNs, such as low communication bandwidth, large propagation delay, floating node mobility, and high error probability, are significantly different from ground-based wireless sensor networks. The novel networking paradigm poses interdisciplinary challenges that will require new technological solutions. In particular, in this article we adopt a top-down approach to explore the research challenges in mobile UWSN design. Along the layered protocol stack, we proceed roughly from the top application layer to the bottom physical layer. At each layer, a set of new design intricacies is studied. The conclusion is that building scalable mobile UWSNs is a challenge that must be answered by interdisciplinary efforts of acoustic communications, signal processing, and mobile acoustic network protocol design.

VBF: vector-based forwarding protocol for underwater sensor networks

In this paper, we tackle one fundamental problem in Underwater Sensor Networks (UWSNs): robust, scalable and energy efficient routing. UWSNs are significantly different from terrestrial sensor networks in the following aspects: low bandwidth, high latency, node float mobility (resulting in high network dynamics), high error probability, and 3-dimensional space. These new features bring many challenges to the network protocol design of UWSNs. In this paper, we propose a novel routing protocol, called vector-based forwarding (VBF), to provide robust, scalable and energy efficient routing. VBF is essentially a position-based routing approach: nodes close to the “vector” from the source to the destination will forward the message. In this way, only a small fraction of the nodes are involved in routing. VBF also adopts a localized and distributed self-adaptation algorithm which allows nodes to weigh the benefit of forwarding packets and thus reduce energy consumption by discarding the low benefit packets. Through simulation experiments, we show the promising performance of VBF.

DBR: depth-based routing for underwater sensor networks

Providing scalable and efficient routing services in underwater sensor networks (UWSNs) is very challenging due to the unique characteristics of UWSNs. Firstly, UWSNs often employ acoustic channels for communications because radio signals do not work well in water. Compared with radio-frequency channels, acoustic channels feature much lower bandwidths and several orders of magnitudes longer propagation delays. Secondly, UWSNs usually have very dynamic topology as sensors move passively with water currents. Some routing protocols have been proposed to address the challenging problem in UWSNs. However, most of them assume that the full-dimensional location information of all sensor nodes in a network is known in prior through a localization process, which is yet another challenging issue to be solved in UWSNs. In this paper, we propose a depth-based routing (DBR) protocol. DBR does not require full-dimensional location information of sensor nodes. Instead, it needs only local depth information, which can be easily obtained with an inexpensive depth sensor that can be equipped in every underwater sensor node. A key advantage of our protocol is that it can handle network dynamics efficiently without the assistance of a localization service. Moreover, our routing protocol can take advantage of a multiple-sink underwater sensor network architecture without introducing extra cost. We conduct extensive simulations. The results show that DBR can achieve very high packet delivery ratios (at least 95%) for dense networks with only small communication cost.

Energy-Efficient Cooperative Communication in a Clustered Wireless Sensor Network

In this paper, we consider a clustered wireless sensor network where sensors within each cluster relay data packets to nearby clusters using cooperative communications. We propose a cooperative transmission scheme based on distributed space-time block coding and conduct a systematic analysis on the resulting energy consumption. Compared with existing work, our distinctions are twofold: (1) Only sensors that can correctly decode received packets participate in the cooperative transmission, where the number of cooperating nodes depends on both channel and noise realizations; and (2) we use packet-error-rate-based analysis rather than symbol-error-rate-based analysis. This is more realistic since error detection is usually done at the packet level via, e.g., cyclic-redundancy-check codes. Based on the analysis, we further minimize the overall energy consumption by power allocation between the intracluster and intercluster transmissions. With numerical methods, we investigate how energy consumption is affected by the transmit power allocation, the total number of sensors in a cluster, the end-to-end packet error rate requirement, and the relative magnitudes between the intracluster and intercluster distances. Comparisons with direct (noncooperative) transmission schemes demonstrate the significant energy-saving advantage of the proposed cooperative scheme.

Scalable Localization with Mobility Prediction for Underwater Sensor Networks

Due to harsh aqueous environments, non-negligible node mobility and large network scale, localization for large-scale mobile underwater sensor networks is very challenging. In this paper, by utilizing the predictable mobility patterns of underwater objects, we propose a scheme, called Scalable Localization scheme with Mobility Prediction (SLMP), for underwater sensor networks. In SLMP, localization is performed in a hierarchical way, and the whole localization process is divided into two parts: anchor node localization and ordinary node localization. During the localization process, every node predicts its future mobility pattern according to its past known location information, and it can estimate its future location based on the predicted mobility pattern. Anchor nodes with known locations in the network will control the localization process in order to balance the trade-off between localization accuracy, localization coverage, and communication cost. We conduct extensive simulations, and our results show that SLMP can greatly reduce localization communication cost while maintaining relatively high localization coverage and localization accuracy.

Localization for large-scale underwater sensor networks

In this paper, we study the localization problem in large-scale under-water sensor networks. The adverse aqueous environments, the node mobility, and the large network scale all pose new challenges, and most current localization schemes are not applicable. We propose a hierarchical approach which divides the whole localization process into two sub-processes: anchor node localization and ordinary node localization. Many existing techniques can be used in the former. For the ordinary node localization process, we propose a distributed localization scheme which novelly integrates a 3-dimensional Euclidean distance estimation method with a recursive location estimation method. Simulation results show that our proposed solution can achieve high localization coverage with relatively small localization error and low communication overhead in large-scale 3-dimensional underwater sensor networks.

Building underwater ad-hoc networks and sensor networks for large scale real-time aquatic applications

Large-scale underwater ad-hoc networks (UANET) and underwater sensor networks (UWSN) are novel networking paradigms to explore the uninhabited oceans. However, the characteristics of these new networks, such as huge propagation delay, floating node mobility, and limited acoustic link capacity, are significantly different from ground-based mobile ad-hoc networks (MANET) and wireless sensor networks (WSN). In this paper we adopt a top-down approach to explore the new research subject. We at first show a new practical application scenario that cannot be addressed by existing technology and hence demands the advent of the UANET and UWSN. Then along the layered protocol stack, we go down from the top application layer to the bottom physical layer. At each layer we show a set of new design challenges. We conclude that UANET and UWSN are challenges that must be answered by inter-disciplinary efforts of acoustic communication, signal processing and mobile acoustic network protocol design

Aggregated multicast: an approach to reduce multicast state

IP multicast suffers from a scalability problem with the number of concurrently active multicast groups because it requires a router to keep the forwarding state for every multicast tree passing through it and the number of forwarding entries grows with the number of groups. In this paper, we propose an approach to reduce the multicast forwarding state. In our approach, multiple groups are forced to share a single delivery tree. We discuss the advantages and some implementation issues of our approach, and conclude that it is feasible and promising. We then propose metrics to quantify state reduction and analyze the bounds on state reduction of our approach. Finally, we use simulations to verify our analytical bounds and quantify the state reduction. These initial simulation results suggest that our method can reduce multicast state significantly.

R-MAC: An Energy-Efficient MAC Protocol for Underwater Sensor Networks

Underwater sensor networks are significantly different from terrestrial sensor networks in that sound is mainly used as the communication medium. The long propagation delay and limited bandwidth of acoustic channels make the existing MAC protocols designed for radio networks either unpractical or not energy efficient for underwater sensor networks. In this paper, we propose a reservation-based MAC protocol, called R-MAC. The major design goals of R-MAC are energy efficiency and fairness. R-MAC schedules the transmissions of control packets and data packets to avoid data packet collision completely. The scheduling algorithms not only save energy but also solve the exposed terminal problem inherited in RTS/CTS-based protocols. Furthermore, the scheduling algorithms allow nodes in the network to select their own schedules, thus loosening the synchronization requirement the protocol. Additionally, R-MAC supports fairness. By simulations, we show that R-MAC is an energy efficient and fair MAC solution for underwater sensor networks.

Efficient localization for large-scale underwater sensor networks

In this paper, we study the localization problem in large-scale underwater sensor networks. The adverse aqueous environments, the node mobility, and the large network scale all pose new challenges, and most current localization schemes are not applicable. We propose a hierarchical approach which divides the whole localization process into two sub-processes: anchor node localization and ordinary node localization. Many existing techniques can be used in the former. For the ordinary node localization process, we propose a distributed localization scheme which novelly integrates a 3-dimensional Euclidean distance estimation method with a recursive location estimation method. Simulation results show that our proposed solution can achieve high localization coverage with relatively small localization error and low communication overhead in large-scale 3-dimensional underwater sensor networks.