Saleh Ibrahim

Surface-Level Gateway Deployment for Underwater Sensor Networks

The performance of underwater sensor networks (UWSNs) is greatly limited by the low bandwidth and high propagation delay of acoustic communications. Deploying multiple surface-level radio-capable gateways can enhance UWSN performance from many aspects. In this paper, we mainly focus on the surface gateway deployment, which is modelled as an optimization problem. Integer Linear Programming (ILP) is used for solving variations of the deployment optimization problem. The tradeoff between the number of surface gateways and the expected delay and energy consumption is analyzed. We conduct simulations to evaluate the benefits of surface gateway optimization and investigate the effect of acoustic channel capacity and the underwater sensor node deployment pattern. Our results show the significant advantages of surface gateway optimization. The results also provide useful guidelines for real network deployment.

Efficient surface gateway deployment for underwater sensor networks

Deploying multiple surface-level radio-capable gateways enhances the performance of underwater acoustic sensor network. The locations of gateways have to be carefully selected to maximize the benefit in a cost-effective way. In this paper, we show how to efficiently solve the surface gateway deployment optimization problem, using heuristic approaches. The results of applying these proposed algorithms to a variety of practical deployment scenarios suggest that these heuristics are nearly optimal for practical cases.

Towards efficient dynamic surface gateway deployment for underwater network

In underwater acoustic sensor network, deploying multiple surface-level radio capable gateways is an efficient way to alleviate the burdens of high propagation delay and high error probability during transmission. However, the locations of gateways need to be carefully selected to maximize the benefit in a cost-effective way. In this paper, we present our formulation of the surface gateway deployment problem as an integer linear programming (ILP) and we solve the problem with heuristic approaches to provide a realtime solution for large scale deployment problems. By applying the proposed heuristic algorithms to a variety of deployment scenarios, we show that they are nearly optimal for practical cases, which opens the door for dynamic deployment. Therefore, we extend our solution to a dynamic case and propose a modified framework that integrates Aqua-sim, a NS2-based underwater wireless sensor network simulator. Our simulation result shows the benefits of dynamic gateway redeployment over static deployment.

Many-to-Many Game-Theoretic Approach for the Measurement of Transportation Network Vulnerability

The vulnerability of a transportation network is strongly correlated with the ability of the network to withstand shocks and disruptions. A robust network with strategic redundancy allows traffic to be redistributed or reassigned without unduly compromising system performance. High-volume edges with limited alternative paths represent system vulnerabilities—a feature of transportation networks that has been exploited to identify critical components. A mixed-strategy, stochastic game-theoretic approach is presented for the measurement of network vulnerability. This method is designed to incorporate all origins and destinations in a network in a computationally efficient manner. The presented method differs from previous efforts in that it provides a many-to-many measure of vulnerability and edge-based disruptions that may not reside on a common path. A game that considers all possible origin–destination pairs is constructed between a router, which seeks minimum cost paths for travelers, and a network tester, which maximizes travel cost by disabling edges within the network. The method of successive averages is used for routing probabilities, and a weighted entropy function is employed to compute edge-disruption probabilities. The method is demonstrated on a small example network and then applied to the Sioux Falls, South Dakota, network. Results indicate good correspondence with a previous method that used equilibrium assignment and rapid solution convergence.

General optimization framework for surface gateway deployment problem in underwater sensor networks

The performance of underwater sensor networks (UWSNs) is greatly limited by the low bandwidth and high propagation delay of acoustic communications. Deploying multiple surface-level radio-capable gateways can enhance UWSN performance metrics, reducing end-to-end delays and distributing traffic loads for energy reduction. In this paper, we study the problem of gateway placement for maximizing the cost-benefit of this UWSN architecture. We develop a mixed integer programming (MIP) gateway deployment optimization framework. We analyze the tradeoff between the number of surface gateways and the expected delay and energy consumption of the surface gateway architecture in the optimal case. We used an MIP solver to solve the developed optimization problem and integrated the optimal results to serve as an input for our simulations to evaluate the benefits of surface gateway optimization framework. We investigated the effect of acoustic channel capacity and the underwater sensor node deployment pattern on our solution. Our results show the significant advantages of surface gateway optimization and provide useful guidelines for real network deployment.

Geometry-assisted gateway deployment for underwater sensor networks

Deploying radio-capable gateways at the sea surface can mitigate the limitations of acoustic communications in underwater sensor networks (UWSN). Finding the best placement for gateways is formulated as an ILP problem. The choice of gateway candidate locations can affect both the feasibility and the quality of the solution. In this paper, we show the limitation of using a regular mesh of candidate locations, and present a novel algorithm for defining candidate locations that both reduces the complexity of the optimization problem and enhances the feasibility and quality of the solution.

An efficient heuristic for estimating transportation network vulnerability

Estimating the criticality of each link in a transportation network is a crucial step for guiding the design and deployment of vulnerability reduction measures. Using exhaustive simulations based on user-equilibrium assignment to evaluate the effect of the failure of each link (or set of links) can be prohibitively time-consuming for reasonably-sized transportation networks. In this paper, we propose an alternative heuristic approach to the estimation the vulnerability of network links employing efficient graph-theoretical algorithms. In particular, our model estimates the cost of single link failure based on the increase in shortest path travel time taking into account the effect of congestion. Results show that the proposed method can reliably be used to estimate the relative effect of each link failure on the system travel time and rank links accordingly.

Surface gateway placement strategy for maximizing underwater sensor network lifetime

Network lifetime is often a crucial measure of the cost-effectiveness of underwater wireless sensor networks and a guiding factor of their deployment. In this paper, we propose a placement strategy for surface gateway nodes in order to maximize network lifetime under a given set of functional requirements. We formulate the problem as an optimization problem and solve it for sample networks. Results show a trade-off between lifetime and other performance metrics, such as average end-to-end delay. We propose a multi-objective reformulation of the problem to strike the required balance between performance and lifetime.

Enhancing Underwater Acoustic Sensor Networks Using Surface Radios: Issues, Challenges and Solutions

In this chapter, we focus on a novel network architecture, UASN-MG, which has multiple surface gateways for underwater acoustic sensor networks. The surface gateways communicate with each other using surface radio and form a radio network on the water surface. Thus, two networks, an underwater acoustic network formed by underwater sensor nodes and a surface radio network formed by the surface gateways, are involved. Such a network architecture can bring about many benefits such as high throughput and energy efficiency. However, integrating multiple surface gateways into underwater acoustic sensor networks also incurs many new design challenges. In this chapter, we describe this new network architecture and its benefits in detail. Then we discuss the design challenges in this new architecture. Afterwards, three design examples are given, from different perspectives, to illustrate the techniques that cope with these challenges and optimize the network’s performance. Finally, we conclude the chapter with discussions on possible future research directions.

Performance analysis of efficient pipeline architectures for underwater big data analytics

Underwater sensor networks (UWSNs) have emerged as an essential technology for various undersea applications. However, the use of acoustic links in UWSNs poses critical challenges in terms of overall delay, energy consumption and low bandwidth, which make the transmission of raw data in large sizes impractical. In our previous work, we employed various nodes (processing nodes, gateway nodes, and sensing nodes) that are used to construct different candidate architectures (i.e. single, pipeline, and hybrid of parallel/pipeline). We exploit the idea of in-network data processing in order to reduce the volume of data and extract only valuable information. In this paper, we analytically calculate and compare the performance of the various types of proposed architectures. The tradeoff between the cost of processing and the expected speedup is also analyzed. The results confirm our previous research hypothesis that processing the collected data locally and applying the idea of pipeline/parallel processing leads to significant improvement in the performance of UWSNs.