Formal Probabilistic Analysis of a Wireless Sensor Network for Forest Fire Detection

Wireless Sensor Networks (WSNs) have been widely explored for forest fire detection, which is considered a fatal threat throughout the world. Energy conservation of sensor nodes is one of the biggest challenges in this context and random scheduling is frequently applied to overcome that. The performance analysis of these random scheduling approaches is traditionally done by paper-and-pencil proof methods or simulation. These traditional techniques cannot ascertain 100% accuracy, and thus are not suitable for analyzing a safety-critical application like forest fire detection using WSNs. In this paper, we propose to overcome this limitation by applying formal probabilistic analysis using theorem proving to verify scheduling performance of a real-world WSN for forest fire detection using a k-set randomized algorithm as an energy saving mechanism. In particular, we formally verify the expected values of coverage intensity, the upper bound on the total number of disjoint subsets, for a given coverage intensity, and the lower bound on the total number of nodes.Comment: In Proceedings SCSS 2012, arXiv:1307.802

Extremal Properties of Three Dimensional Sensor Networks with Applications

In this paper, we analyze various critical transmitting/sensing ranges for connectivity and coverage in three-dimensional sensor networks. As in other large-scale complex systems, many global parameters of sensor networks undergo phase transitions: For a given property of the network, there is a critical threshold, corresponding to the minimum amount of the communication effort or power expenditure by individual nodes, above (resp. below) which the property exists with high (resp. a low) probability. For sensor networks, properties of interest include simple and multiple degrees of connectivity/coverage. First, we investigate the network topology according to the region of deployment, the number of deployed sensors and their transmitting/sensing ranges. More specifically, we consider the following problems: Assume that $n$ nodes, each capable of sensing events within a radius of $r$, are randomly and uniformly distributed in a 3-dimensional region $\mathcal{R}$ of volume $V$, how large must the sensing range be to ensure a given degree of coverage of the region to monitor? For a given transmission range, what is the minimum (resp. maximum) degree of the network? What is then the typical hop-diameter of the underlying network? Next, we show how these results affect algorithmic aspects of the network by designing specific distributed protocols for sensor networks

Energy-efficient coverage with wireless sensors

Many sensor networks are deployed for the purpose of covering and monitoring a particular region, and detecting the object of interest in the region. In these applications, coverage is one of the centric problems in sensor networks. Such problem is centered around a basic question: ``How well can the sensors observe the physical world?\u27\u27 The concept of coverage can be interpreted as a measure of quality of service provided by the sensing function in various ways depending on sensor devices and applications. On the other hand, sensor nodes are usually battery-powered and subject to limitations based on the available battery energy. It is, therefore, critical to design, deploy and operate a wireless sensor network in an energy-efficient manner, while satisfying the coverage requirement. In order to prolong the lifetime of a sensor network, we explore the notion of connected-k-coverage in sensor networks. It requires the monitored region to be k-covered by a connected component of active sensors, which is less demanding than requiring k-coverage and connectivity among all active sensors simultaneously. We investigate the theoretical foundations about connected-k-coverage and, by using the percolation theorem, we derive the critical conditions for connected-k-coverage for various relations between sensors\u27 sensing radius and communication range. In addition, we derive an effective lower bound on the probability of connected-k-coverage, and propose a simple randomized scheduling algorithm and select proper operational parameters to prolong the lifetime of a large-scale sensor network. It has been shown that sensors\u27 collaboration (information fusion) can improve object detection performance and area coverage in sensor networks. The sensor coverage problem in this situation is regarded as information coverage. Based on a probabilistic sensing model, we study the object detection problem and develop a novel on-demand framework (decision fusion-based) for collaborative object detection in wireless sensor networks, where inactive sensors can be triggered by nearby active sensors to collaboratively sense and detect the object. By using this framework, we can significantly improve the coverage performance of the sensor networks, while the network power consumption can be reduced. Then, we proceed to study the barrier information coverage problem under the similar assumption that neighboring sensors may collaborate with each other to form a virtual sensor which makes the detection decision based on combined sensed readings. We propose both centralized and distributed schemes to operate a sensor network to information-cover a barrier efficiently. At last, we propose and study a multi-round sensor deployment strategy based on line-based sensor deployment model, which can use the fewest sensors to cover a barrier. We have an interesting discovery that the optimal two-round sensor deployment strategy yields the same barrier coverage performance as other optimal strategies with more than two rounds. This result is particularly encouraging as it implies that the best barrier coverage performance can be achieved with low extra deployment cost by deploying sensors in two rounds. In addition, two practical solutions are presented to deal with realistic situations when the distribution of a sensor\u27s residence point is not fully known

Randomized Initialization of a Wireless Multihop Network

Address autoconfiguration is an important mechanism required to set the IP address of a node automatically in a wireless network. The address autoconfiguration, also known as initialization or naming, consists to give a unique identifier ranging from 1 to $n$ for a set of $n$ indistinguishable nodes. We consider a wireless network where $n$ nodes (processors) are randomly thrown in a square $X$, uniformly and independently. We assume that the network is synchronous and two nodes are able to communicate if they are within distance at most of $r$ of each other ($r$ is the transmitting/receiving range). The model of this paper concerns nodes without the collision detection ability: if two or more neighbors of a processor $u$ transmit concurrently at the same time, then $u$ would not receive either messages. We suppose also that nodes know neither the topology of the network nor the number of nodes in the network. Moreover, they start indistinguishable, anonymous and unnamed. Under this extremal scenario, we design and analyze a fully distributed protocol to achieve the initialization task for a wireless multihop network of $n$ nodes uniformly scattered in a square $X$. We show how the transmitting range of the deployed stations can affect the typical characteristics such as the degrees and the diameter of the network. By allowing the nodes to transmit at a range r= \sqrt{\frac{(1+\ell) \ln{n} \SIZE}{\pi n}} (slightly greater than the one required to have a connected network), we show how to design a randomized protocol running in expected time $O(n^{3/2} \log^2{n})$ in order to assign a unique number ranging from 1 to $n$ to each of the $n$ participating nodes

Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks

Optimal Initialization and Gossiping Algorithms for Random Radio Networks

The initialization problem, also known as naming, consists to give a unique identifier ranging from $1$ to $n$ to a set of $n$ indistinguishable nodes in a given network. We consider a network where $n$ nodes (processors) are randomly deployed in a square (resp. cube) $X$. We assume that the time is slotted and the network is synchronous, two nodes are able to communicate if they are within distance at most of $r$ of each other ($r$ is the transmitting/receiving range). Moreover, if two or more neighbors of a processor $u$ transmit concurrently at the same time slot, then $u$ would not receive either messages. We suppose also that the anonymous nodes know neither the topology of the network nor the number of nodes in the network. Under this extremal scenario, we first show how the transmitting range of the deployed processors affects the typical characteristics of the network. Then, by allowing the nodes to transmit at various ranges we design sub-linear randomized initialization protocols~: In the two, resp. three, dimensional case, our randomized initialization algorithms run in $O(n^{1/2} \log{n}^{1/2})$, resp. $O(n^{1/3} \log{n}^{2/3})$, time slots. These latter protocols are based upon an optimal gossiping algorithm which is of independent interest

Resilient Wireless Sensor Networks Using Topology Control: A Review

Wireless sensor networks (WSNs) may be deployed in failure-prone environments, and WSNs nodes easily fail due to unreliable wireless connections, malicious attacks and resource-constrained features. Nevertheless, if WSNs can tolerate at most losing k − 1 nodes while the rest of nodes remain connected, the network is called k − connected. k is one of the most important indicators for WSNs’ self-healing capability. Following a WSN design flow, this paper surveys resilience issues from the topology control and multi-path routing point of view. This paper provides a discussion on transmission and failure models, which have an important impact on research results. Afterwards, this paper reviews theoretical results and representative topology control approaches to guarantee WSNs to be k − connected at three different network deployment stages: pre-deployment, post-deployment and re-deployment. Multi-path routing protocols are discussed, and many NP-complete or NP-hard problems regarding topology control are identified. The challenging open issues are discussed at the end. This paper can serve as a guideline to design resilient WSNs

Unified Power Management in Wireless Sensor Networks, Doctoral Dissertation, August 2006

Radio power management is of paramount concern in wireless sensor networks (WSNs) that must achieve long lifetimes on scarce amount of energy. Previous work has treated communication and sensing separately, which is insufficient for a common class of sensor networks that must satisfy both sensing and communication requirements. Furthermore, previous approaches focused on reducing energy consumption in individual radio states resulting in suboptimal solutions. Finally, existing power management protocols often assume simplistic models that cannot accurately reflect the sensing and communication properties of real-world WSNs. We develop a unified power management approach to address these issues. We first analyze the relationship between sensing and communication performance of WSNs. We show that sensing coverage often leads to good network connectivity and geographic routing performance, which provides insights into unified power management under both sensing and communication performance requirements. We then develop a novel approach called Minimum Power Configuration that ingegrates the power consumption in different radio states into a unified optimization framework. Finally, we develop two power management protocols that account for realistic communication and sensing properties of WSNs. Configurable Topology Control can configure a network topology to achieve desired path quality in presence of asymmetric and lossy links. Co-Grid is a coverage maintenance protocol that adopts a probabilistic sensing model. Co-Grid can satisfy desirable sensing QoS requirements (i.e., detection probability and false alarm rate) based on a distributed data fusion model

MIMO communication systems: receiver design and diversity-multiplexing tradeoff analysis

After a few decades\u27 evolution of wireless communication systems, to ensure reliable high-speed communication over unreliable wireless channels is still one of the major challenges facing researchers and engineers. The use of multiple antennas at transmitter and receiver, known as multiple-input multiple-output (MIMO) communications, is one promising technology delivering desired wireless services. The main goal of this thesis is to study two important issues in wireless MIMO communication systems: receiver design for coded MIMO systems, and diversity-multiplexing tradeoff analysis in general fading channels;In the first part of this thesis, we decompose the receiver design problem into two sub-problems: MIMO channel estimation and MIMO detection. For the MIMO channel estimation, we develop an expectation-maximization (EM) based semi-blind channel and noise covariance matrix estimation algorithm for space-time coding systems under spatially correlated noise. By incorporating the proposed channel estimator into the iterative receiver structure, both the channel estimation and the error-control decoding are improved significantly. We also derive the modified Cramer-Rao bounds (MCRB) for the unknown parameters as the channel estimation performance metric, and demonstrate that the proposed channel estimation algorithm can achieve the MCRB after several iterations. For the MIMO detection, we propose a novel low-complexity MIMO detection algorithm, which has only cubic order computational complexity, but with near-optimal performance. For a 4x4 turbo-coded system, we show that the proposed detector had the same performance as the maximum a posteriori (MAP) detector for BPSK modulation, and 0.1 dB advantage over the approximated MAP detector (list sphere decoding algorithm) for 16-QAM modulation at BER = 10-4;In the second part of this thesis, we derive the optimal diversity-multiplexing tradeoff for general MIMO fading channels, which include different fading types as special cases. We show that for a MIMO system with long coherence time, the optimal diversity-multiplexing tradeoff is also a piecewise linear function, and only the first segment is affected by different fading types. We proved that under certain full-rank assumptions spatial correlation has no effect on the optimal tradeoff. We also argued that non-zero channel means in general are not beneficial for multiplexing-diversity tradeoff

Wireless Sensor Networks for Fire Detection and Control

Due to current technological progress, the manufacturing of tiny and low price sensors became technically and economically feasible. Sensors can measure physical surroundings related to the environment and convert them into an electric signal. A huge quantity of these disposable sensors is networked to detect and monitor fire. This paper provides an analysis of utilisation of wireless sensor networks for fire detection and control