1,644 research outputs found
Message and time efficient multi-broadcast schemes
We consider message and time efficient broadcasting and multi-broadcasting in
wireless ad-hoc networks, where a subset of nodes, each with a unique rumor,
wish to broadcast their rumors to all destinations while minimizing the total
number of transmissions and total time until all rumors arrive to their
destination. Under centralized settings, we introduce a novel approximation
algorithm that provides almost optimal results with respect to the number of
transmissions and total time, separately. Later on, we show how to efficiently
implement this algorithm under distributed settings, where the nodes have only
local information about their surroundings. In addition, we show multiple
approximation techniques based on the network collision detection capabilities
and explain how to calibrate the algorithms' parameters to produce optimal
results for time and messages.Comment: In Proceedings FOMC 2013, arXiv:1310.459
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
Real-Time and Energy-Efficient Routing for Industrial Wireless Sensor-Actuator Networks
With the emergence of industrial standards such as WirelessHART, process industries are adopting Wireless Sensor-Actuator Networks (WSANs) that enable sensors and actuators to communicate through low-power wireless mesh networks. Industrial monitoring and control applications require real-time communication among sensors, controllers and actuators within end-to-end deadlines. Deadline misses may lead to production inefficiency, equipment destruction to irreparable financial and environmental impacts. Moreover, due to the large geographic area and harsh conditions of many industrial plants, it is labor-intensive or dan- gerous to change batteries of field devices. It is therefore important to achieve long network lifetime with battery-powered devices.
This dissertation tackles these challenges and make a series of contributions. (1) We present a new end-to-end delay analysis for feedback control loops whose transmissions are scheduled based on the Earliest Deadline First policy. (2) We propose a new real-time routing algorithm that increases the real-time capacity of WSANs by exploiting the insights of the delay analysis. (3) We develop an energy-efficient routing algorithm to improve the network lifetime while maintaining path diversity for reliable communication. (4) Finally, we design a distributed game-theoretic algorithm to allocate sensing applications with near-optimal quality of sensing
Joint Routing and STDMA-based Scheduling to Minimize Delays in Grid Wireless Sensor Networks
In this report, we study the issue of delay optimization and energy
efficiency in grid wireless sensor networks (WSNs). We focus on STDMA (Spatial
Reuse TDMA)) scheduling, where a predefined cycle is repeated, and where each
node has fixed transmission opportunities during specific slots (defined by
colors). We assume a STDMA algorithm that takes advantage of the regularity of
grid topology to also provide a spatially periodic coloring ("tiling" of the
same color pattern). In this setting, the key challenges are: 1) minimizing the
average routing delay by ordering the slots in the cycle 2) being energy
efficient. Our work follows two directions: first, the baseline performance is
evaluated when nothing specific is done and the colors are randomly ordered in
the STDMA cycle. Then, we propose a solution, ORCHID that deliberately
constructs an efficient STDMA schedule. It proceeds in two steps. In the first
step, ORCHID starts form a colored grid and builds a hierarchical routing based
on these colors. In the second step, ORCHID builds a color ordering, by
considering jointly both routing and scheduling so as to ensure that any node
will reach a sink in a single STDMA cycle. We study the performance of these
solutions by means of simulations and modeling. Results show the excellent
performance of ORCHID in terms of delays and energy compared to a shortest path
routing that uses the delay as a heuristic. We also present the adaptation of
ORCHID to general networks under the SINR interference model
Aggregation Scheduling Algorithms in Wireless Sensor Networks
In Wireless Sensor Networks which consist of tiny
wireless sensor nodes with limited battery power, one of the most
fundamental applications is data aggregation which collects nearby
environmental conditions and aggregates the data to a designated
destination, called a sink node. Important issues concerning the
data aggregation are time efficiency and energy consumption due
to its limited energy, and therefore, the related problem, named
Minimum Latency Aggregation Scheduling (MLAS), has been the
focus of many researchers. Its objective is to compute the minimum
latency schedule, that is, to compute a schedule with the minimum
number of timeslots, such that the sink node can receive the
aggregated data from all the other nodes without any collision or
interference. For the problem, the two interference models, the graph
model and the more realistic physical interference model known as
Signal-to-Interference-Noise-Ratio (SINR), have been adopted with
different power models, uniform-power and non-uniform power (with
power control or without power control), and different antenna
models, omni-directional antenna and directional antenna models.
In this survey article, as the problem has proven to be NP-hard,
we present and compare several state-of-the-art approximation
algorithms in various models on the basis of latency as its
performance measure
Data Aggregation Scheduling in Wireless Networks
Data aggregation is one of the most essential data gathering operations in wireless networks. It is an efficient strategy to alleviate energy consumption and reduce medium access contention. In this dissertation, the data aggregation scheduling problem in different wireless networks is investigated. Since Wireless Sensor Networks (WSNs) are one of the most important types of wireless networks and data aggregation plays a vital role in WSNs, the minimum latency data aggregation scheduling problem for multi-regional queries in WSNs is first studied. A scheduling algorithm is proposed with comprehensive theoretical and simulation analysis regarding time efficiency. Second, with the increasing popularity of Cognitive Radio Networks (CRNs), data aggregation scheduling in CRNs is studied. Considering the precious spectrum opportunity in CRNs, a routing hierarchy, which allows a secondary user to seek a transmission opportunity among a group of receivers, is introduced. Several scheduling algorithms are proposed for both the Unit Disk Graph (UDG) interference model and the Physical Interference Model (PhIM), followed by performance evaluation through simulations. Third, the data aggregation scheduling problem in wireless networks with cognitive radio capability is investigated. Under the defined network model, besides a default working spectrum, users can access extra available spectrum through a cognitive radio. The problem is formalized as an Integer Linear Programming (ILP) problem and solved through an optimization method in the beginning. The simulation results show that the ILP based method has a good performance. However, it is difficult to evaluate the solution theoretically. A heuristic scheduling algorithm with guaranteed latency bound is presented in our further investigation. Finally, we investigate how to make use of cognitive radio capability to accelerate data aggregation in probabilistic wireless networks with lossy links. A two-phase scheduling algorithm is proposed, and the effectiveness of the algorithm is verified through both theoretical analysis and numerical simulations
Performance assessment of real-time data management on wireless sensor networks
Technological advances in recent years have allowed the maturity of Wireless Sensor Networks
(WSNs), which aim at performing environmental monitoring and data collection. This sort of
network is composed of hundreds, thousands or probably even millions of tiny smart computers
known as wireless sensor nodes, which may be battery powered, equipped with sensors, a radio
transceiver, a Central Processing Unit (CPU) and some memory. However due to the small size and
the requirements of low-cost nodes, these sensor node resources such as processing power, storage
and especially energy are very limited.
Once the sensors perform their measurements from the environment, the problem of data
storing and querying arises. In fact, the sensors have restricted storage capacity and the on-going
interaction between sensors and environment results huge amounts of data. Techniques for data
storage and query in WSN can be based on either external storage or local storage. The external
storage, called warehousing approach, is a centralized system on which the data gathered by the
sensors are periodically sent to a central database server where user queries are processed. The
local storage, in the other hand called distributed approach, exploits the capabilities of sensors
calculation and the sensors act as local databases. The data is stored in a central database server
and in the devices themselves, enabling one to query both.
The WSNs are used in a wide variety of applications, which may perform certain operations on
collected sensor data. However, for certain applications, such as real-time applications, the sensor
data must closely reflect the current state of the targeted environment. However, the environment
changes constantly and the data is collected in discreet moments of time. As such, the collected
data has a temporal validity, and as time advances, it becomes less accurate, until it does not
reflect the state of the environment any longer. Thus, these applications must query and analyze
the data in a bounded time in order to make decisions and to react efficiently, such as industrial
automation, aviation, sensors network, and so on. In this context, the design of efficient real-time
data management solutions is necessary to deal with both time constraints and energy consumption.
This thesis studies the real-time data management techniques for WSNs. It particularly it focuses
on the study of the challenges in handling real-time data storage and query for WSNs and on the
efficient real-time data management solutions for WSNs.
First, the main specifications of real-time data management are identified and the available
real-time data management solutions for WSNs in the literature are presented. Secondly, in order to
provide an energy-efficient real-time data management solution, the techniques used to manage
data and queries in WSNs based on the distributed paradigm are deeply studied. In fact, many
research works argue that the distributed approach is the most energy-efficient way of managing
data and queries in WSNs, instead of performing the warehousing. In addition, this approach can provide quasi real-time query processing because the most current data will be retrieved from the
network.
Thirdly, based on these two studies and considering the complexity of developing, testing, and
debugging this kind of complex system, a model for a simulation framework of the real-time
databases management on WSN that uses a distributed approach and its implementation are
proposed. This will help to explore various solutions of real-time database techniques on WSNs
before deployment for economizing money and time. Moreover, one may improve the proposed
model by adding the simulation of protocols or place part of this simulator on another available
simulator. For validating the model, a case study considering real-time constraints as well as energy
constraints is discussed.
Fourth, a new architecture that combines statistical modeling techniques with the distributed
approach and a query processing algorithm to optimize the real-time user query processing are
proposed. This combination allows performing a query processing algorithm based on admission
control that uses the error tolerance and the probabilistic confidence interval as admission
parameters. The experiments based on real world data sets as well as synthetic data sets
demonstrate that the proposed solution optimizes the real-time query processing to save more
energy while meeting low latency.Fundação para a Ciência e Tecnologi
The Hybrid Algorithm for Data Collection over a Tree Topology in WSN
Wireless sensor networks have wide range of application such as analysis of traffic, monitoring of environmental, industrial process monitoring, technical systems, civilian and military application. Data collection is a basic function of wireless sensor networks (WSN) where sensor nodes determine attributes about a phenomenon of concern and transmits their readings to a common base station(sink node). In this paper, we use contention-free Time Division Multiple Access (TDMA) support scheduling protocols for such data collection applications over tree-based routing topology. We represent a data gathering techniques to get the growing capacity, routing protocol all along with algorithms planned for remote wireless sensor networks. This paper describes about the model of sensor networks which has been made workable by the junction of micro-electro-mechanical systems technologies, digital electronics and wireless communications. Firstly the sensing tasks and the potential sensor network applications are explored, and assessment of factors influencing the design of sensor networks is provided. In our propose work using data compression and packet merging techniques; or taking advantage of the correlation in the sensor readings. Consider continuous monitoring applications where perfect aggregation is achievable, i.e., every node is capable of aggregate the entire packets expected from its children as well as that generate by itself into a particular packet before transmit in the direction of its sink node or base station or parent node. Keyword: Aggregation, Data Converge-cast, Data fusion, Energy Efficiency, Routing and TDMA
A Green TDMA Scheduling Algorithm for Prolonging Lifetime in Wireless Sensor Networks
Fast data collection is one of the most important research issues for Wireless Sensor Networks (WSNs). In this paper, a TMDA based energy consumption balancing algorithm is proposed for the general k-hop WSNs, where one data packet is collected in one cycle. The optimal k that achieves the longest network life is obtained through our theoretical analysis. Required time slots, maximum energy consumption and residual network energy are all thoroughly analyzed in this paper. Theoretical analysis and simulation results demonstrate the effectiveness of the proposed algorithm in terms of energy efficiency and time slot scheduling
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