5,283 research outputs found
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 nodes, each
capable of sensing events within a radius of , are randomly and uniformly
distributed in a 3-dimensional region of volume , 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
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
Coverage Protocols for Wireless Sensor Networks: Review and Future Directions
The coverage problem in wireless sensor networks (WSNs) can be generally
defined as a measure of how effectively a network field is monitored by its
sensor nodes. This problem has attracted a lot of interest over the years and
as a result, many coverage protocols were proposed. In this survey, we first
propose a taxonomy for classifying coverage protocols in WSNs. Then, we
classify the coverage protocols into three categories (i.e. coverage aware
deployment protocols, sleep scheduling protocols for flat networks, and
cluster-based sleep scheduling protocols) based on the network stage where the
coverage is optimized. For each category, relevant protocols are thoroughly
reviewed and classified based on the adopted coverage techniques. Finally, we
discuss open issues (and recommend future directions to resolve them)
associated with the design of realistic coverage protocols. Issues such as
realistic sensing models, realistic energy consumption models, realistic
connectivity models and sensor localization are covered
Connectivity, Coverage and Placement in Wireless Sensor Networks
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
Self-* distributed query region covering in sensor networks
Wireless distributed sensor networks are used to monitor a multitude of environments for both civil and military applications. Sensors may be deployed to unreachable or inhospitable areas. Thus, they cannot be replaced easily. However, due to various factors, sensors\u27 internal memory, or the sensors themselves, can become corrupted. Hence, there is a need for more robust sensor networks. Sensors are most commonly densely deployed, but keeping all sensors continually active is not energy efficient. Our aim is to select the minimum number of sensors which can entirely cover a particular monitored area, while remaining strongly connected. This concept is called a Minimum Connected Cover of a query region in a sensor network. In this research, we have designed two fully distributed, robust, self-* solutions to the minimum connected cover of query regions that can cope with both transient faults and sensor crashes. We considered the most general case in which every sensor has a different sensing and communication radius. We have also designed extended versions of the algorithms that use multi-hop information to obtain better results utilizing small atomicity (i.e., each sensor reads only one of its neighbors\u27 variables at a time, instead of reading all neighbors\u27 variables). With this, we have proven self-* (self-configuration, self-stabilization, and self-healing) properties of our solutions, both analytically and experimentally. The simulation results show that our solutions provide better performance in terms of coverage than pre-existing self-stabilizing algorithms
PERFORMANCE ANALYSIS AND OPTIMIZATION OF QUERY-BASED WIRELESS SENSOR NETWORKS
This dissertation is concerned with the modeling, analysis, and optimization of large-scale, query-based wireless sensor
networks (WSNs). It addresses issues related to the time
sensitivity of information retrieval and dissemination, network lifetime maximization, and optimal clustering of sensor nodes in mobile WSNs. First, a queueing-theoretic framework is proposed to evaluate the performance of such networks whose nodes detect and advertise significant events that are useful for only a limited time; queries generated by sensor nodes are also time-limited. The main performance parameter is the steady state proportion of generated queries that fail to be answered on time. A scalable approximation for this parameter is first derived assuming the transmission range of sensors is unlimited. Subsequently, the proportion of failed queries is approximated using a finite transmission range. The latter
approximation is remarkably accurate, even when key model
assumptions related to event and query lifetime distributions and network topology are violated.
Second, optimization models are proposed to maximize the
lifetime of a query-based WSN by selecting the transmission
range for all of the sensor nodes, the resource replication
level (or time-to-live counter) and the active/sleep schedule of nodes, subject to connectivity and quality-of-service constraints. An improved lower bound is provided for the minimum transmission range needed to ensure no network nodes are isolated with high probability. The optimization models select the optimal operating parameters in each period of a finite planning horizon, and computational results indicate that the maximum lifetime can be significantly extended by adjusting the key operating parameters as sensors fail over time due to energy depletion.
Finally, optimization models are proposed to maximize the
demand coverage and minimize the costs of locating, and
relocating, cluster heads in mobile WSNs. In these models, the locations of mobile sensor nodes evolve randomly so that each sensor must be optimally assigned to a cluster head during each period of a finite planning horizon. Additionally, these models prescribe the optimal times at which to update the sensor locations to improve coverage. Computational experiments illustrate the usefulness of dynamically updating cluster head locations and sensor location information over time
Topology Analysis of Wireless Sensor Networks for Sandstorm Monitoring
Sandstorms are serious natural disasters, which are commonly seen in the Middle East, Northern Africa, and Northern China.In these regions, sandstorms have caused massive damages to the natural environment, national economy, and human health. To avoid such damages, it is necessary to effectively monitor the origin and development of sandstorms. To this end, wireless sensor networks (WSNs) can be deployed in the regions where sandstorms generally originate so that sensor nodes can collaboratively perform sandstorm monitoring and rapidly convey the observations to remote administration center. Despite the potential advantages, the deployment of WSNs in the vicinity of sandstorms faces many unique challenges, such as the temporally buried sensors and increased path loss during sandstorms. Consequently, the WSNs may experience frequent disconnections during the sandstorms. This further leads to dynamically changing topology. In this paper, a topology analysis of the WSNs for sandstorm monitoring is performed. Four types of channels a sensor can utilize during sandstorms are analyzed, which include air-to-air channel, air-to-sand channel, sand-to-air channel, and sand-to-sand channel. Based on the channel model solutions, a percolation-based connectivity analysis is performed. It is shown that if the sensors are buried in low depth, allowing sensor to use multiple types of channels improves network connectivity. Accordingly, much smaller sensor density is required compared to the case, where only terrestrial air channels are used. Through this topology analysis a WSN architecture can be deployed for very efficient sandstorm monitoring
- …