Results 1 - 10
of
40
Information fusion for wireless sensor networks: methods, models, and classifications,”
- Article ID 1267073,
, 2007
"... ..."
Power-efficient sensor placement and transmission structure for data gathering under distortion constraints
- in IPSN ’04
, 2004
"... We consider the joint optimization of sensor placement and transmission structure for data gathering, where a given number of nodes need to be placed in a field such that the sensed data can be reconstructed at a sink within specified distortion bounds while minimizing the energy consumed for commun ..."
Abstract
-
Cited by 54 (4 self)
- Add to MetaCart
(Show Context)
We consider the joint optimization of sensor placement and transmission structure for data gathering, where a given number of nodes need to be placed in a field such that the sensed data can be reconstructed at a sink within specified distortion bounds while minimizing the energy consumed for communication. We assume that the nodes use either joint entropy coding based on explicit communication between sensor nodes, where coding is done when side information is available, or Slepian-Wolf coding where nodes have knowledge of network correlation statistics. We consider both maximum and average distortion bounds. We prove that this optimization is NP-complete since it involves an interplay between the spaces of possible transmission structures given radio reachability limitations, and feasible placements satisfying distortion bounds. We address this problem by first looking at the simplified problem of optimal placement in the one-dimensional case. An analytical solution is derived for the case when there is a simple aggregation scheme, and numerical results are provided for the cases when joint entropy encoding is used. We use the insight from our 1-D analysis to extend our results to the 2-D case and compare it to typical uniform random placement and shortest-path tree. Our algorithm for two-dimensional placement and transmission structure provides two to three fold reduction in
A Utility-based Distributed Maximum Lifetime Routing Algorithm for Wireless Networks
"... Energy efficient routing is a critical problem in multihop wireless networks due to the severe power constraint of wireless nodes. Despite its importance and many research efforts towards it, a distributed routing algorithm that maximizes network lifetime is still missing. To address this problem, ..."
Abstract
-
Cited by 18 (0 self)
- Add to MetaCart
Energy efficient routing is a critical problem in multihop wireless networks due to the severe power constraint of wireless nodes. Despite its importance and many research efforts towards it, a distributed routing algorithm that maximizes network lifetime is still missing. To address this problem, we propose a novel utility-based nonlinear optimization formulation to the maximum lifetime routing problem. Based on this formulation, we further present a fully distributed, localized routing algorithm, which is proved to converge to the optimal point, where the network lifetime is maximized. Solid theoretical analysis and simulation results are presented to validate our solution.
Balanced Data Gathering in Energy-Constrained Sensor Networks
"... We consider the problem of gathering data from a wireless multi-hop network of energy-constrained sensor nodes to a common base station. Speci cally, we aim to balance the total amount of data received from the sensor network during its lifetime against a requirement of sucient coverage for all ..."
Abstract
-
Cited by 16 (1 self)
- Add to MetaCart
We consider the problem of gathering data from a wireless multi-hop network of energy-constrained sensor nodes to a common base station. Speci cally, we aim to balance the total amount of data received from the sensor network during its lifetime against a requirement of sucient coverage for all the sensor locations surveyed. Our main contribution lies in formulating this balanced data gathering task and in studying the eects of balancing. We give an LP network ow formulation and present experimental results on optimal data routing designs also with impenetrable obstacles between the nodes. We then proceed to consider the eect of augmenting the basic sensor network with a small number of auxiliary relay nodes with less stringent energy constraints.
Energy Efficient Sensor, Relay and Base Station Placements for Coverage, Connectivity and Routing
"... Abstract — We consider a wireless sensor network made of sensor nodes capable of sensing and communication, relay nodes capable of communication, and base stations responsible for collecting data generated by sensor nodes, to be deployed in sensor field. We address the problem of placing the sensor ..."
Abstract
-
Cited by 12 (0 self)
- Add to MetaCart
(Show Context)
Abstract — We consider a wireless sensor network made of sensor nodes capable of sensing and communication, relay nodes capable of communication, and base stations responsible for collecting data generated by sensor nodes, to be deployed in sensor field. We address the problem of placing the sensor nodes, relay nodes and base stations in the sensor field such that (i) each point of interest in the sensor field is covered by a subset of sensors of desired cardinality (ii) the resulting sensor network is connected and (iii) the sensor network has sufficient bandwidth. We propose several deployment strategies to determine optimal placements of sensor nodes, relay nodes and base stations for guaranteed coverage, connectivity, bandwidth and robustness. We study several different objectives such as minimizing the number of sensor nodes deployed, minimizing the total cost, minimizing the energy consumption, maximizing the network lifetime and maximizing the network utilization. The placement problems for reliable as well as unreliable/probabilistic detection models are formulated as Integer Linear Programs (ILPs). The practicality, effectiveness and performance of the proposed strategies are illustrated through simulations. I.
Network configuration for optimal utilization efficiency of wireless sensor networks,” Elsevier Ad Hoc Networks
, 2006
"... This paper addresses the problem of configuring wireless sensor networks (WSNs). Specifically, we seek answers to the following questions: how many sensors should be deployed, what is the optimal sensor placement, and which transmission structure should be employed. The design objective is utilizati ..."
Abstract
-
Cited by 7 (0 self)
- Add to MetaCart
(Show Context)
This paper addresses the problem of configuring wireless sensor networks (WSNs). Specifically, we seek answers to the following questions: how many sensors should be deployed, what is the optimal sensor placement, and which transmission structure should be employed. The design objective is utilization efficiency defined as network lifetime per unit deployment cost. We propose an optimal approach and an approximation approach with reduced complexity to network configuration. Numerical and simulation results demonstrate the near optimal performance of the approximation approach. We also study the impact of sensing range, channel path loss exponent, sensing power consumption, and event arrival rate on the optimal network configuration. network.
Relay Placement in Sensor Networks
, 2005
"... The problem of placing relay nodes in a wireless sensor net-work is studied in the context of balanced data gathering. Previous work is extended by showing that even the simplest classes of the relay placement problem are hard to approx-imate. This work also presents a heuristic method for both lowe ..."
Abstract
-
Cited by 5 (0 self)
- Add to MetaCart
The problem of placing relay nodes in a wireless sensor net-work is studied in the context of balanced data gathering. Previous work is extended by showing that even the simplest classes of the relay placement problem are hard to approx-imate. This work also presents a heuristic method for both lower-bounding and upper-bounding the maximum perfor-mance of a sensor network over all possible relay locations.
Recovering From a Node Failure in Wireless Sensor-Actor Networks With Minimal Topology Changes, Ameer
- IEEE Transaction on Vehicular technology,
, 2013
"... Abstract-In wireless sensor-actor networks, sensors probe their surroundings and forward their data to actor nodes. Actors collaboratively respond to achieve predefined application mission. Since actors have to coordinate their operation, it is necessary to maintain a strongly connected network top ..."
Abstract
-
Cited by 4 (0 self)
- Add to MetaCart
(Show Context)
Abstract-In wireless sensor-actor networks, sensors probe their surroundings and forward their data to actor nodes. Actors collaboratively respond to achieve predefined application mission. Since actors have to coordinate their operation, it is necessary to maintain a strongly connected network topology at all times. Moreover, the length of the inter-actor communication paths may be constrained to meet latency requirements. However, a failure of an actor may cause the network to partition into disjoint blocks and would, thus, violate such a connectivity goal. One of the effective recovery methodologies is to autonomously reposition a subset of the actor nodes to restore connectivity. Contemporary recovery schemes either impose high node relocation overhead or extend some of the inter-actor data paths. This paper overcomes these shortcomings and presents a Least-Disruptive topology Repair (LeDiR) algorithm. LeDiR relies on the local view of a node about the network to devise a recovery plan that relocates the least number of nodes and ensures that no path between any pair of nodes is extended. LeDiR is a localized and distributed algorithm that leverages existing route discovery activities in the network and imposes no additional prefailure communication overhead. The performance of LeDiR is analyzed mathematically and validated via extensive simulation experiments. Index Terms-Fault tolerance, network recovery, topology management, wireless sensor-actor network (WSAN).
Energy-Efficient Connected Coverage in Wireless Sensor Networks
"... Abstract — We address the problem of maximizing network lifetime while providing for coverage and connectivity in Wireless Sensor Networks. Static sensor nodes are deployed randomly in the region in order to provide sensing coverage to a set of points of interest in the region, called target points, ..."
Abstract
-
Cited by 4 (0 self)
- Add to MetaCart
(Show Context)
Abstract — We address the problem of maximizing network lifetime while providing for coverage and connectivity in Wireless Sensor Networks. Static sensor nodes are deployed randomly in the region in order to provide sensing coverage to a set of points of interest in the region, called target points, and to provide for communication among the active sensors to propagate the data at all times in the network. Sensors have independent sensing and transmission ranges, with no specific relation between the two. Sensor nodes are energy-constrained and hence only a minimal set of sensor nodes needs to be activated at any given time. Node activation schedules, such that mutually exclusive sets of sensor nodes are activated in succession, are determined in order to achieve extended lifetime of the network. We observe that the optimal solution to the problem is NP-Complete which motivates the need to devise efficient heuristic solutions. First we consider a simpler problem of energy-efficient coverage and formulate it using Linear Programming techniques. The structure of the formulation provides some insights towards developing algorithms for the lifetime coverage and connectivity problem. An algorithm is developed which performs within a constant factor of the optimal performance for various network sizes and is easily implementable in a distributed manner. We compare the performance of the algorithm with the optimal solution and with appropriately derived bounds. Particularly, the algorithm allows the network lifetime to scale linearly with the number of sensor nodes in the system. Thus it serves as an energy-efficient solution towards ensuring connected coverage in wireless sensor networks. I.
Biologically-inspired Self-deployable Heterogeneous Mobile Sensor Networks
"... Abstract — This paper studies the problem of self-deployment of heterogeneous mobile sensors using biologically-inspired principles and methodologies. The initial sensor deployment is assumed to be random, based on which two interrelated issues are investigated: the design of an optimal placement pa ..."
Abstract
-
Cited by 2 (0 self)
- Add to MetaCart
(Show Context)
Abstract — This paper studies the problem of self-deployment of heterogeneous mobile sensors using biologically-inspired principles and methodologies. The initial sensor deployment is assumed to be random, based on which two interrelated issues are investigated: the design of an optimal placement pattern of heterogeneous sensor platforms and the self configuration from the initial random state to the optimal state through intelligent sensor movement. We first develop an optimal placement algorithm based on the mosaic technique inspired by the retina mosaic pattern widely observed in both human and many animal visual systems. Different types of mobile sensors are organized into a mosaic pattern for both maximizing network coverage and reducing network cost. Secondly, in order to converge to the optimal state, we investigate the swarm intelligence (SI)-based sensor movement strategy with the assistance of local communications, through which the randomly deployed sensors can self-organize themselves to reach the optimal placement state. The proposed algorithm is compared with the random movement and the SIbased method without direct communication using performance metrics such as network coverage, redundancy, convergence time, and energy consumption. Simulation results are presented to demonstrate the effectiveness of the mosaic placement and the SI-based movement with local communication. Index Terms — Heterogenous sensor network, Coverage, Mosaick pattern, Swarm intelligence
