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Geographic and Opportunistic Clustering for Underwater WSNs
Abstract
In this paper, we propose Geographic and Oppor-tunistic Clustering (GOC) protocol for Underwater Wireless Sensor Networks. GOC is an improved version of Geographic and Opportunistic Routing for UWSNs (GEDAR). GOC uses a hybrid system in which the recovery algorithm of GEDAR is implemented alongside the clustering approach depending on the neighbor list of the void node. Similar to the architecture of GEDAR, GOC comprises of a swarm architecture in which multiple sonobuoys reside on surface of water. Nodes are capable of moving with a velocity of v = 2.4 /min at an energy cost of E = 1500 mJ/m. Improving the packet delivery ratio is GOC's achieved parameter. However, energy consumption and delay are compromised due to formation of clusters and association of nodes with the cluster head.
... Since the OR protocols use the OR metrics, to avoid unnecessary literature searching, Table V lists the OR metrics with several OR protocol deployments alongside their paper references. Routing Metric Protocol EXOR [39], Economy [59], SOAR [41], MORE [27], CodeOR [66], XCOR [67] ETX O3 [206], SlideOR [207], CCACK [65], OMNC [208], Consort [58], MaxOPP [209], ORPL [210], CAOR [211], TORP [212], ORPSN [213], CAR [214], CORMAN [48] ExOR compact [215], NCOR [216], WBFL [217], E-MORE [218], ViMOR [219] EAX LCAR [47], OAPF [111] , ORDF [220], ABF,SAF [119] [118] EATT MABF, SMAF [119] [118], CoRoute [221], CRAHN [222], PLASMA [113], ROMP [114], DSMA [223], COMO [224] EDC ORW [124] [125], ORPL [225], ORPL-DT [32] DOF [226], Staffetta [227], COF [96] M-MPP MPP [169], MaxPoS [172] PoS MaxASA, MinTT [172] [173], MPOS [228] FS * ORR [167], MORR [229] EPA EGOR [149], GEDAR [230] [231], HydroCast [232], GOC [233], EQGOR [162], U-OR [164] Fig. 12: Chronological introduction of OR metrics. ...
High-speed, low latency, and heterogeneity features of 5G, as the common denominator of many emerging and classic wireless applications, have put wireless technology back in the spotlight. Continuous connectivity requirement in low-power and wide-reach networks underlines the need for more efficient routing over scarce wireless resources, in multi-hp scenarios. In this regard, Opportunistic Routing (OR), which utilizes the broadcast nature of wireless media to provide transmission cooperation amongst a selected number of overhearing nodes, has become more promising than ever. Crucial to the overall network performance, which nodes to participate and where they stand on the transmission-priority hierarchy, are decided by user-defined OR metrics embedded in OR protocols. Therefore, the task of choosing or designing an appropriate OR metric is a critical one. The numerousness, proprietary notations, and the objective variousness of OR metrics can cause the interested researcher to lose insight and become overwhelmed, making the metric selection or design effort-intensive. While there are not any comprehensive OR metrics surveys in the literature, those who partially address the subject are non-exhaustive and lacking in detail. Furthermore, they offer limited insight regarding related taxonomy and future research recommendations. In this paper, starting with a custom tutorial with a new look to OR and OR metrics, we devise a new framework for OR metric design. Introducing a new taxonomy enables us to take a structured, investigative, and comparative approach to OR metrics, supported by extensive simulations. Exhaustive coverage of OR metrics, formulated in a unified notation, is presented with sufficient details. Self-explanatory, easy-to-grasp, and visual-friendly quick references are provided, which can be used independently from the rest of the paper.
High-speed, low latency, and heterogeneity features of 5G, as the common denominator of many emerging and classic wireless applications, have put wireless technology back in the spotlight. Continuous connectivity requirement in low-power and wide-reach networks underlines the need for more efficient routing over scarce wireless resources, in multi-hp scenarios. In this regard, Opportunistic Routing (OR), which utilizes the broadcast nature of wireless media to provide transmission cooperation amongst a selected number of overhearing nodes, has become more promising than ever. Crucial to the overall network performance, which nodes to participate and where they stand on the transmission-priority hierarchy, are decided by user-defined OR metrics embedded in OR protocols. Therefore, the task of choosing or designing an appropriate OR metric is a critical one. The numerousness, proprietary notations, and the objective variousness of OR metrics can cause the interested researcher to lose insight and become overwhelmed, making the metric selection or design effort-intensive. While there are not any comprehensive OR metrics surveys in the literature, those who partially address the subject are non-exhaustive and lacking in detail. Furthermore, they offer limited insight regarding related taxonomy and future research recommendations. In this paper, starting with a custom tutorial with a new look to OR and OR metrics, we devise a new framework for OR metric design. Introducing a new taxonomy enables us to take a structured, investigative, and comparative approach to OR metrics, supported by extensive simulations. Exhaustive coverage of OR metrics, formulated in a unified notation, is presented with sufficient details. Self-explanatory, easy-to-grasp, and visual-friendly quick references are provided, which can be used independently from the rest of the paper. Finally, a new insightful framework for future research directions is developed. This tutorial-survey has been organized to benefit both generalists and OR specialists equally, and to be used not only in its entirety but selectively as well.
Existing move-restricted node self-deployment algorithms are based on a fixed node communication radius, evaluate the performance based on network coverage or the connectivity rate and do not consider the number of nodes near the sink node and the energy consumption distribution of the network topology, thereby degrading network reliability and the energy consumption balance. Therefore, we propose a distributed underwater node self-deployment algorithm. First, each node begins the uneven clustering based on the distance on the water surface. Each cluster head node selects its next-hop node to synchronously construct a connected path to the sink node. Second, the cluster head node adjusts its depth while maintaining the layout formed by the uneven clustering and then adjusts the positions of in-cluster nodes. The algorithm originally considers the network reliability and energy consumption balance during node deployment and considers the coverage redundancy rate of all positions that a node may reach during the node position adjustment. Simulation results show, compared to the connected dominating set (CDS) based depth computation algorithm, that the proposed algorithm can increase the number of the nodes near the sink node and improve network reliability while guaranteeing the network connectivity rate. Moreover, it can balance energy consumption during network operation, further improve network coverage rate and reduce energy consumption.
In this paper, we propose a distributed data-gathering scheme using an autonomous underwater vehicle (AUV) working as a mobile sink to gather data from a randomly distributed underwater sensor network where sensor nodes are clustered around several cluster headers. Unlike conventional data-gathering schemes where the AUV visits either every node or every cluster header, the proposed scheme allows the AUV to visit some selected nodes named path-nodes in a way that reduces the overall transmission power of the sensor nodes. Monte Carlo simulations are performed to investigate the performance of the proposed scheme compared with several preexisting techniques employing the AUV in terms of total amount of energy consumption, standard deviation of each node's energy consumption, latency to gather data at a sink, and controlling overhead. Simulation results show that the proposed scheme not only reduces the total energy consumption but also distributes the energy consumption more uniformly over the network, thereby increasing the lifetime of the network.
Underwater wireless sensor networks (UWSNs) have been showed as a promising technology to monitor and explore the oceans in lieu of traditional undersea wireline instruments. Nevertheless, the data gathering of UWSNs is still severely limited because of the acoustic channel communication characteristics. One way to improve the data collection in UWSNs is through the design of routing protocols considering the unique characteristics of the underwater acoustic communication and the highly dynamic network topology. In this paper, we propose the GEDAR routing protocol for UWSNs. GEDAR is an anycast, geographic and opportunistic routing protocol that routes data packets from sensor nodes to multiple sonobuoys (sinks) at the sea's surface. When the node is in a communication void region, GEDAR switches to the recovery mode procedure which is based on topology control through the depth adjustment of the void nodes, instead of the traditional approaches using control messages to discover and maintain routing paths along void regions. Simulation results show that GEDAR significantly improves the network performance when compared with the baseline solutions, even in hard and difficult mobile scenarios of very sparse and very dense networks and for high network traffic loads.
During the last couple of decades Underwater Wireless Sensor etworks (UWS) attracting more and more attention for ocean monitoring systems. Due to adverse environment, UWS face many problems like bandwidth limitations, high error probability, node movements and 3-dimensional space, and with such challenges, we need a robust and scalable architecture for providing a self configuring network of distributed nodes. In order to handle the problem of large propagation delays and unreliable link quality, many authors proposed multi-hop data delivery routing schemes. But, such multi-hop routing protocols drain more energy of the nodes near the sink. In this paper, we proposed a "Temporary Cluster Based Routing" protocol, which not only make use of equal energy consumption for all the nodes throughout the network but also it helps to save energy, as it prefer to send the sensed data over short distances. Moreover, it does not require any location information of sensor nodes and only a small number of nodes are involved during the end to end routing process. This makes it suitable not only for stationary and mobile networks but for the hybrid networks as well.
In Underwater Wireless Sensor Networks (UWSNs), localization is one of most important technologies since it plays a critical role in many applications. Motivated by widespread adoption of localization, in this paper, we present a comprehensive survey of localization algorithms. First, we classify localization algorithms into three categories based on sensor nodes' mobility: stationary localization algorithms, mobile localization algorithms and hybrid localization algorithms. Moreover, we compare the localization algorithms in detail and analyze future research directions of localization algorithms in UWSNs.
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.
We propose a localization scheme for underwater acoustic sensor networks (UWSN) that does not require a priori infra-structure or synchronization between nodes. An autonomous underwater vehicle (AUV) aids in localizing the sensor nodes while roaming across the underwater sensor field. The objectives of this paper are to describe how to localize nodes using AUV and to describe the tradeoffs involved, i.e. ratio of localized nodes and localization accuracy. We show that localization success improves as the duration of the AUV localization process increases. In addition, we investigated localization using two methods, bounding-box and triangulation. The former achieves a higher localization ratio but with a higher error. In certain scenarios, we achieved 100% nodes localized with 3% error.
In this paper, we study the geographic collaborative forwarding (GCF) scheme, a variant of opportunistic routing, which exploits the broadcast nature and spatial diversity of the wireless medium to improve the packet delivery efficiency. Our goal is to fully understand the principles, the gains, and the tradeoffs of the node collaboration and its associated cost, thus provide insightful analysis and guidance to the design of more efficient routing/forwarding protocols. We first identify the upper bound of the expected packet advancement (EPA) that GCF can achieve and prove the concavity of the maximum EPA. With energy efficiency as a major concern, we propose a new metric, EPA per unit energy consumption, which balances the packet advancement, reliability and energy consumption. By leveraging the proved properties, we then propose an efficient algorithm which selects a feasible candidate set that maximizes this local metric. We validate our analysis results by simulations, and justify the effectiveness of the new metric by comparing the performance of GCF with those of the existing geographic and opportunistic routing schemes.
Since sensor networks can be composed of a very large number of nodes, the developed protocols for these networks must be scalable. Moreover, these protocols must be designed to prolong the battery lifetime of the nodes. Typical existing routing techniques for ad hoc networks are known not to scale well. On the other hand, the so-called geographical routing algorithms are known to be scalable but their energy efficiency has never been extensively and comparatively studied. For this reason, a novel analytical framework is introduced. In a geographical routing algorithm, the packets are forwarded by a node to its neighbor based on their respective positions. The proposed framework allows to analyze the relationship between the energy efficiency of the routing tasks and the extension of the range of the topology knowledge for each node. The leading forwarding rules for geographical routing are compared in this framework, and the energy efficiency of each of them is studied. Moreover partial topology knowledge forwarding, a new forwarding scheme, is introduced. A wider topology knowledge can improve the energy efficiency of the routing tasks but can increase the cost of topology information due to signaling packets that each node must transmit and receive to acquire this information, especially in networks with high mobility. The problem of determining the optimal knowledge range for each node to make energy efficient geographical routing decisions is tackled by integer linear programming. It is demonstrated that the problem is intrinsically localized, i.e., a limited knowledge of the topology is sufficient to take energy efficient forwarding decisions, and that the proposed forwarding scheme outperforms the others in typical application scenarios. For online solution of the problem, a probe-based distributed protocol which allows each node to efficiently select its topology knowledge, is introduced and shown to converge to a near-optimal solution very fast
The great advances made in the wireless technology have enabled the deployment of wireless communication networks in some of the harshest environments such as volcanoes, hurricane-affected regions, and underground mines. In such challenging environments suffering from the lack of infrastructure, traditional routing is not efficient and sometimes not even feasible. Moreover, the exponential growth of the number of wireless connected devices has created the need for a new routing paradigm that could benefit from the potentials offered by these heterogeneous wireless devices. Hence, in order to overcome the traditional routing limitations, and to increase the capacity of current dynamic heterogeneous wireless networks, the opportunistic routing paradigm has been proposed and developed in recent research works. Motivated by the great interest that has been attributed to this new paradigm within the last decade, we provide a comprehensive survey of the existing literature related to opportunistic routing. We first study the main design building blocks of opportunistic routing. Then, we provide a taxonomy for opportunistic routing proposals, based on their routing objectives as well as the optimization tools and approaches used in the routing design. Hence, five opportunistic routing classes are defined and studied in this paper, namely, geographic opportunistic routing, link-state-aware opportunistic routing, probabilistic opportunistic routing, optimization-based opportunistic routing, and cross-layer opportunistic routing. We also review the main protocols proposed in the literature for each class. Finally, we identify and discuss the main future research directions related to the opportunistic routing design, optimization, and deployment.
Underwater sensor networks are necessary to detect and track unknown targets in the maritime environment. Localization of sensors becomes a crucial problem. This paper presents a new method based on multi-objectivization to localize the sensors using triaxial magnetometers. In this localization system, a DC current-carrying solenoid coil serves as a magnetic source and the inertial magnetometer measure the three-component of magnetic flux intensity. Then, the localization problem is translated into a multi-objective optimization problem by minimizing each error function. Without using depth sensor, it is difficult to find the global optimum of the functions due to the homogeneous magnetic field. Accordingly, we propose a hybrid algorithm using improved non-dominated sorting genetic algorithm and linear multi-metering method to determine the sensor position. To reduce time consumption during the optimization process, a simplified discrete model of the magnetic field is derived. Experiment results show that the proposed localization method has a high accuracy and strong robustness.
Compared with conventional oceanic monitoring applications, Underwater Sensor Networks (UWSN) can allow real-time monitoring of the underwater environment. In this paper, we propose a tiered architecture for the deployment of UWSN, where an acoustic mesh network is located between the underwater senor networks and central monitoring system such that it can act as the ldquobackbone networkrdquo for sensor nodes. A novel routing protocol is designed specifically for such an underwater mesh network. This protocol is a best effort protocol where packets are forwarded along redundant and interleaved paths in a specified belt. In order to increase packet delivery rate, we adopts ldquomulti-sink routingrdquo, where the packet from a source node can be sent simultaneously over spatially diverse routing to multiple sinks located in different locations. Our simulation result demonstrated that our scheme could achieve high delivery rate without very high energy cost.
Due to adverse 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 its predicted mobility pattern. Anchor nodes with known locations in the network will control the whole localization process in order to balance the tradeoff 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.
The widespread adoption of the Wireless Sensor Networks (WSNs) in various applications in the terrestrial environment and the rapid advancement of the WSN technology have motivated the development of Underwater Acoustic Sensor Networks (UASNs). UASNs and terrestrial WSNs have several common properties while there are several challenges particular to UASNs that are mostly due to acoustic communications, and inherent mobility. These challenges call for novel architectures and protocols to ensure successful operation of the UASN. Localization is one of the fundamental tasks for UASNs which is required for data tagging, node tracking, target detection, and it can be used for improving the performance of medium access and network protocols. Recently, various UASN architectures and a large number of localization techniques have been proposed. In this paper, we present a comprehensive survey of these architectures and localization methods. To familiarize the reader with the UASNs and localization concepts, we start our paper by providing background information on localization, state-of-the-art oceanographic systems, and the challenges of underwater communications. We then present our detailed survey, followed by a discussion on the performance of the localization techniques and open research issues.
A SEA Swarm (Sensor Equipped Aquatic Swarm) is a sensor "cloud" that drifts with water currents and enables 4D (space and time) monitoring of local underwater events such as contaminants, marine life and intruders. The swarm is escorted at the surface by drifting sonobuoys that collect the data from underwater sensors via acoustic modems and report it in real-time via radio to a monitoring center. The goal of this study is to design an efficient anycast routing algorithm for reliable underwater sensor event reporting to any one of the surface sonobuoys. Major challenges are the ocean current and the limited resources (bandwidth and energy). In this paper, we address these challenges and propose HydroCast, a hydraulic pressure based anycast routing protocol that exploits the measured pressure levels to route data to surface buoys. The paper makes the following contributions: a novel opportunistic routing mechanism to select the subset of forwarders that maximizes greedy progress yet limiting co-channel interference; and an efficient underwater "dead end" recovery method that outperforms recently proposed approaches. The proposed routing protocols are validated via extensive simulations.
Underwater mobile sensor networks have recently been proposed as a way to explore and observe the ocean, providing 4D (space and time) monitoring of underwater environments. We consider a specialized geographic routing problem called pressure routing that directs a packet to any sonobuoy on the surface based on depth information available from on-board pressure gauges. The main challenge of pressure routing in sparse underwater networks has been the efficient handling of 3D voids. In this respect, it was recently proven that the greedy stateless perimeter routing method, very popular in 2D networks, cannot be extended to void recovery in 3D networks. Available heuristics for 3D void recovery require expensive flooding. In this paper, we propose a Void-Aware Pressure Routing (VAPR) protocol that uses sequence number, hop count and depth information embedded in periodic beacons to set up next-hop direction and to build a directional trail to the closest sonobuoy. Using this trail, opportunistic directional forwarding can be efficiently performed even in the presence of voids. The contribution of this paper is twofold: 1) a robust soft-state routing protocol that supports opportunistic directional forwarding; and 2) a new framework to attain loop freedom in static and mobile underwater networks to guarantee packet delivery. Extensive simulation results show that VAPR outperforms existing solutions.
We propose a new link metric called normalized advance (NADV) for geographic routing in multihop wireless networks. NADV selects neighbors with the optimal trade-off between proximity and link cost. Coupled with the local next hop decision in geographic routing, NADV enables an adaptive and efficient cost-aware routing strategy. Depending on the objective or message priority, applications can use the NADV framework to minimize various types of link cost.We present efficient methods for link cost estimation and perform detailed simulations in diverse scenarios. Our results show that NADV outperforms current schemes in many aspects: for example, in high noise environments with frequent packet losses, the use of NADV leads to 81% higher delivery ratio. When compared to centralized routing under certain settings, geographic routing using NADV finds paths whose cost is close to the optimum.
AUV-aided localization for underwater sensor networks Wireless Algorithms, Systems and Applications
- Melike Erol
- Fm Luiz
- Mario Vieira
- Gerla
Erol, Melike, Luiz FM Vieira, and Mario Gerla. " AUV-aided localization
for underwater sensor networks. " Wireless Algorithms, Systems and
Applications, 2007. WASA 2007. International Conference on. IEEE,
2007.