Maximizing the Robustness of Wireless Sensor Networks with Optimal Sink Designation

Wireless communication between sensors allows the formation of flexible sensor networks, which can be deployed rapidly over wide or inaccessible areas. However, the need to gather data from all sensors in the network imposes constraints on the distances between sensors. This survey describes the state of the art in techniques for determining the minimum density and optimal locations of relay nodes and ordinary sensors to ensure connectivity, subject to various degrees of uncertainty in the locations of the nodes.

Base station (BS) positioning is an effective method for improving the performance of wireless sensor networks (WSNs). A metric-aware optimal BS positioning and relocation mechanism for WSNs is proposed. This technique locates the BS with respect to the available resources and the amount of traffic traveling through the sensor nodes. The BS calculates its own position over time in response to the dynamic environment in which the sensor nodes operate. In most WSN environments, communication channel experiences nonlinearity that is influenced by path loss, attenuation of signal as it propagated through space, greater than 2. In this work, we solved the problem of BS positioning in nonlinear environments. We propose a weighted linear or nonlinear least squares optimization depending on the value of the path loss exponent. We also propose a distributed algorithm that can effectively handle the required computation by exploiting node cooperation. The goal is to minimize the total energy consumption and to prolong lifetime of the WSNs. The performance of the proposed technique is evaluated for various network setups and conditions. Our simulation results demonstrate that BS positioning and relocation can significantly improve the lifetime and power efficiency in WSNs.

Overlay networks provide base infrastructures for many areas including multimedia streaming and content distributions. Since most overlay networks are highly decentralized and self-organized, cut vertices may exist in such systems due to the lack of centralized management. A cut vertex is defined as a network node whose removal increases the number of network components. Failure of these nodes can break an overlay into a large number of disconnected components and greatly downgrade the upper layer services like media streaming. We propose here a distributed mechanism, CAM, which efficiently detects the cut vertices before they fail and neutralizes them into normal overlay nodes with slight overhead so that the possibility of network decomposition is minimized after they fail. We prove the correctness of this algorithm and evaluate the performance of our design through trace driven simulations.

Abstract One of the fundamental design challenges in designing a Wireless Sensor Network (WSN) is to maximize the network lifetime, as each sensor node of the network is equipped with a limited power battery. To overcome this challenge, different methods were developed in the last few years using such techniques as network protocols, data fusion algorithms using low power, energy efficient routing, and locating optimal sink position. This paper focuses on finding the optimal sink position. Relay nodes are introduced in conjunction with the sensor nodes to mitigate network geometric deficiencies since in most other approaches the sensor nodes close to the sink become heavily involved in data forwarding and, thus, their batteries are quickly depleted. A Particle Swarm Optimization (PSO) based algorithm is used to locate the optimal sink position with respect to those relay nodes to make the network more energy efficient. The relay nodes communicate with the sink instead of the sensor nodes. Tests show that this approach can save at least 40% of the energy and prolong the network lifetime.

Congestion is a challenging problem in wireless sensor networks , which exacerbates with the high volume of data traffic imposed by video applications such as video surveillance and target tracking. Deployment of multiple sinks is a candidate solution for congestion and is also promising in terms of reliability and energy-efficiency. In order to gain the maximum benefit from multiple sinks, it is essential to distribute the load among them evenly. In this paper, we propose a cross layer geographic forwarding scheme MLBRF (Multi-Sink Load Balanced Reliable Forwarding) which aims to provide reliable and energy efficient video delivery in a multi-sinked sensor network for target tracking. In order to provide load balancing among the sinks, MLBRF proposes a sink selection mechanism based on fuzzy logic for the frame forwarding which evaluates the traffic density in the direction of each sink by combining two dynamic criteria which are the number of contenders and the buffer occupancy levels in the neighborhood with the static distance criterion. The performance of the fuzzy sink selection mechanism is compared using simulation with various sink selection mechanisms. The results show that MLBRF gains the maximum benefit from deploying multiple sinks in terms of reliability, latency and energy efficiency by using the proposed fuzzy sink selection mechanism.

In this paper, we address the problem of assigning the sink role to a subset of nodes in a wireless sensor network with a given topology such that the resulting network configuration is robust against denial-of-service type attacks such as node destruction, battery exhaustion and jamming. In order to measure robustness, we introduce new metrics based on a notion defined in [1]. We argue that our metrics are more appropriate to measure the robustness of network configurations than the widely known connectivity based metrics. We formalize the problem of selecting the sink nodes as an optimization problem aiming at minimizing the deployment budget while achieving a certain level of robustness.We propose an efficient greedy heuristic algorithm that approximates the optimal solution reasonably well.

With their distributed nature and redundant operation capability, wireless sensor networks are very suitable for border surveillance scenarios that track intruders trying to breach to a safe side. In such scenarios, keeping the operation going on for as long as possible is the most important aspect of the network. We propose that by placing sink at a carefully selected coordinate will results in a longer living network. We also place restrictions on the candidate locations so that the sensing quality of the network is above a useful predetermined value and the sink is placed in a relatively safe location to avoid destruction. In order to find the suitable coordinates we propose a modified lifetime metric which takes quality and safety measures into account. We also propose a genetic algorithm which uses a discrete event simulator-in-the-loop over a three dimensional terrain to find locations for the sink that fits the given quality and safety restrictions. Using a three dimensional underlying terrain makes the proposed approach more realistic. The results obtained for various sensor network scenarios indicate that the proposed algorithm can find locations that increase the lifetime by also considering the sensing quality and safety.

Existing work on placing additional relay nodes in wireless sensor networks to improve network connectivity typically assumes homogeneous wireless sensor nodes with an identical transmission radius. In contrast, this paper addresses the problem of deploying relay nodes to provide fault-tolerance with higher network connectivity in heterogeneous wireless sensor networks, where sensor nodes possess different transmission radii. Depending on the level of desired fault-tolerance, such problems can be categorized as: (1) full fault-tolerance relay node placement, which aims to deploy a minimum number of relay nodes to establish k (k ges 1) vertex-disjoint paths between every pair of sensor and/or relay nodes; (2) partial fault-tolerance relay node placement, which aims to deploy a minimum number of relay nodes to establish k (k ges 1) vertex-disjoint paths only between every pair of sensor nodes. Due to the different transmission radii of sensor nodes, these problems are further complicated by the existence of two different kinds of communication paths in heterogeneous wireless sensor networks, namely two-way paths, along which wireless communications exist in both directions; and one-way paths, along which wireless communications exist in only one direction. Assuming that sensor nodes have different transmission radii, while relay nodes use the same transmission radius, this paper comprehensively analyzes the range of problems introduced by the different levels of fault-tolerance (full or partial) coupled with the different types of path (one-way or two-way). Since each of these problems is NP-hard, we develop O(sigmak <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> )-approximation algorithms for both one-way and two-way partial fault-tolerance relay node placement, as well as O(sigmak <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> )-approximation algorithms for both one-way and two-way full fault-tolerance relay node placement (sigma is the best performance ratio of existing approximation algorithms for finding a minimum k-vertex connected spanning graph). To facilitate the applications in higher dimensions, we also extend these algorithms and derive their performance ratios in d-dimensional heterogeneous wireless sensor networks (d ges 3). Finally, heuristic implementations of these algorithms are evaluated via simulations.

Reliable, full network connectivity in wireless sensor networks (WSN) is difficult to maintain. Awareness of the state of network connectivity is similarly challenging. Harsh, unattended, low-security environments and resource-constrained nodes exacerbate these problems. An ability to detect connectivity disruptions, also known as cut detection, allows WSN to conserve power and memory while reducing network congestion . We propose ER-CD and LR-CD, protocols that detect cuts while providing energy-efficiency and robustness to attack. Using distributed, cluster-based algorithms, ER-CD recognizes and determines the scope of disrupted connectivity while examining available data for evidence of an attack. For more resource-constrained networks, LR-CD enhances security through the use of a robust outlier detection algorithm. Extensive simulations and a hardware implementation provide experimental validation across a range of network sizes and densities. Results indicate that energy-efficiency can be improved by an order of magnitude in denser networks while malicious nodes are detected at deviations of 1% from expected behavior.

Sensors typically use wireless transmitters to communicate with each other. However, sensors may be located in a way that they cannot even form a connected network (e.g, due to failures of some sensors, or loss of battery power). In this paper we consider the problem of adding the smallest number of additional (relay) nodes so that the induced communication graph is 2-connected. The problem is NP -hard. In this paper we develop O(1)-approximation algorithms that find close to optimal solutions in time O((kn)) for achieving k-edge connectivity of n nodes. The worst case approximation guarantee is 10, but the algorithm produces solutions that are far better than this bound suggests. We also consider extensions to higher dimensions, and the scheme that we develop for points in the plane, yields a bound of 2dMST where dMST is the maximum degree of a minimum-degree Minimum Spanning Tree in d dimensions using Euclidean metrics. In addition, our methods extend with the same approximation guarantees to a generalization when the locations of relays are required to avoid certain polygonal regions (obstacles). We also prove that if the sensors are uniformly and identically distributed in a unit square, the expected number of relay nodes required goes to zero as the number of sensors goes to infinity.

Two fundamental functions of the sensor nodes in a wireless sensor network are to sense its environment and to transmit sensed information to a basestation. One approach to prolong sensor network lifetime is to deploy some relay nodes whose main function is to communicate with the sensor nodes, other relay nodes, and the basestations. It is desirable to deploy a minimum number of relay nodes to achieve certain connectivity requirement. In this paper, we study four related fault-tolerant relay node placement problems, each of which has been previously studied only in some restricted form. For each of them, we discuss its computational complexity and present a polynomial time O(1)-approximation algorithm with a small approximation ratio. When the problem reduces to a previously studied form, our algorithm either improves the previous best algorithm or reduces to the previous best algorithm.

The major challenge in designing wireless sensor networks (WSNs) is the support of the functional, such as data latency, and the non-functional, such as data integrity, requirements while coping with the computation, energy and communication constraints. Careful node placement can be a very effective optimization means for achieving the desired design goals. In this paper, we report on the current state of the research on optimized node placement in WSNs. We highlight the issues, identify the various objectives and enumerate the different models and formulations. We categorize the placement strategies into static and dynamic depending on whether the optimization is performed at the time of deployment or while the network is operational, respectively. We further classify the published techniques based on the role that the node plays in the network and the primary performance objective considered. The paper also highlights open problems in this area of research.

The relay node placement problem for wireless sensor networks is concerned with placing a minimum number of relay nodes into a wireless sensor network to meet certain connectivity and survivability requirements. In this paper, we study constrained versions of the relay node placement problem, where relay nodes can only be placed at a subset of candidate locations. In the connected relay node placement problem, we want to place a minimum number of relay nodes to ensure the connectivity of the sensor nodes and the base stations. In the survivable relay node placement problem, we want to place a minimum number of relay nodes to ensure the biconnectivity of the sensor nodes and the base stations. For each of the two problems, we discuss its computational complexity, and present a framework of polynomial time O(1) -approximation algorithms with small approximation ratios.