Catálogo de publicaciones - libros

We present a simple and efficient distributed method for determining the transmission power assignment that maximises the lifetime of a data-gathering wireless sensor network with stationary nodes and static power assignments. Our algorithm determines the transmission power level inducing the maximum-lifetime spanning subgraph of a network by means of a distributed breadth-first search for minmax-power communication paths, i.e. paths that connect a given reference node to each of the other nodes so that the maximum transmission power required on any link of the path is minimised. The performance of the resulting Maximum Lifetime Spanner () protocol is validated in a number of simulated networking scenarios. In particular, we study the performance of the protocol in terms of the number of required control messages, and compare it to the performance of a recently proposed Distributed Min-Max Tree () algorithm. For all network scenarios we consider, outperforms significantly. We also discuss bringing down the message complexity of our algorithm by initialising it with the Relative Neighbourhood Graph (RNG) of a transmission graph rather than the full graph, and present an efficient distributed method for reducing a given transmission graph to its .

This paper presents an energy-efficient distributed target coverage algorithm(EDTC) for heterogeneous wireless sensor networks(HWSN) with multiple sensing units. In order to utilize the energy more efficiently, the sensor priority is introduced in this paper to integrate the sensing ability and the remaining energy together. EDTC is locally and simultaneously carried out at each sensor in a rounding fashion. Each sensor decides the on/off status of its sensing units at the beginning of each round, and then broadcasts the decision to its one-hop neighbors. The higher the priority of a sensor is, the shorter the decision time it needs. Simulation results show that compared with Energy First(EF) scheme and Integer Linear Programming(ILP) solution, EDTC has longer network lifetime than EF, and the performance difference between EDTC and ILP solution is confined within 10%.

Appling security to messages traveling over wireless links in sensor nodes requires additional energy. This paper describes our suggestions on balancing the level of security and energy consumption based on our measurements using CrossBow and Ember sensor nodes. It was found that the node microcontroller’s CPU operates for substantially longer times for both hashing and encryption operations compared to the time for handling messages without any security. However, this has little overall impact on energy consumption. The longer high-power radio transmission times due to hashing were especially costly. For the full operational mode, with CPU processing and also radio transmission of messages, our results indicate that the lifetime of a transmitting node in a security regime is only about one-half of the lifetime without security. Hence, we provided design guidelines to apply security with energy consideration for WSN. They include 2 to 8 bytes MACs for integrity and authentication instead of SHA-1, and the size of messages should match the steps of encryption algorithms.

In MANET, Node misbehavior due to selfish or malicious reasons can significantly degrade the performance of ad hoc networks. To cope with misbehavior in such self-organized networks, an incentive mechanism must be in place. In this study, a trust-based incentive model on a self-policing mechanism is proposed to make collaboration rational for selfish/malicious nodes. This trust system makes them evaluate the trust of their neighbor locally to mitigate contamination by direct observation and the use of second-hand information available. In our approach, every node maintains a trust rating about every node else they care about. Meanwhile, trust fading and redemption are brought about by update and re-establishment of the trust to show robustness. Performance by simulation reveals that in the case of existing malicious nodes, Dynamic Source Routing (DSR) with proposed trust-based node incentive mechanism performs better than DSR in terms of packet successful delivery ratio and mean number of packets dropped.

Apply the theory of vector quantization and LBG algorithm in the Information Theory and Data Compress,this paper present a one by one relationship between the cluster and cell,the cluster head and code vector,the node and vector,turn the process of clustering into the process of cell segmenting.Then design a new clustering algorithm aiming high stability in cluster structure and good performance in load balancing of cluster head.It has been proved that this algorithm has good performance in load balancing and the structure of the cluster has high stability after the simulation.

Cooperative transmission breaks away from traditional transmission which only has single transmitter and single receiver in wireless networks, which enable single antenna mobiles in a multi-user environment to share their antennas and generate a virtual multiple-antenna transmitter in order to achieve transmit diversity. Space-time block coding (STBC) is an attractive transmission diversity technique because of its linear complexity. Furthermore, signal space diversity can increase the diversity order through interleaving over coordinates and choosing a proper signal constellation. In this paper, cooperative transmissions for wireless sensor networks are considered. In order to improve the system performance, a new cooperative transmission scheme without perfect synchronization using both signal space diversity and STBC is proposed. It is shown by simulation that compared to the traditional transmission scheme with signal space diversity and the STBC-encoded cooperative transmission scheme without signal space diversity, the new scheme can provide further performance improvement by increasing the diversity order, and can save more energy in wireless sensor networks.

One of the important sensor network applications is monitoring inaccessible environments. The noisy environment and energy constraints, however, challenge the event detection problem. Most of recently proposed fault-tolerant event detection algorithms are only based on the spatial correlation. In these algorithms, the frequent exchanges of measurements among nearby sensor nodes give rise to much energy dissipation. Moreover, detection accuracy is poor at the boundary of event region and the edge of sensor networks. In this paper, we propose a temporal-spatial correlation based fault-tolerant event region detection algorithm. In order to improve the performance, both spatial correlated information and temporal correlated information are employed in the event detection. It is validated through simulations that, the proposed temporal-spatial correlation based algorithm outperforms the spatial correlation based scheme in terms of detection accuracy and energy dissipation, thus making the proposed algorithm attractive in energy-efficient event region detection applications.

In mobile wireless sensor networks, sensors can move randomly or keep static temporarily. Mobility makes the sensor networks better acquire information, but also makes accurate localization more difficult since the network environment changes continually. In this paper, an energy-efficient dynamic simulation based localization (DSL) algorithm is introduced that uses range measurement information to restrict sample region and establishes a dynamic filtering mechanism to improve the localization performance and efficiency. Analytical and simulation results are provided to study the localization cost and location accuracy in different mobility models and various environmental settings. The results indicate that our algorithm outperforms the best known simulation based localization schemes under a wide range of conditions, with localization accuracy improved by an average of 24% and computation cost reduced significantly for a similar high localization accuracy.

In wireless sensor networks, time synchronization is a critical problem. In this paper, we propose SLTP, a Scalable Lightweight Time-synchr-onization Protocol for wireless sensor networks. By using passive clustering and linear regression SLTP can reduce the energy consumption of network nodes and also decrease the overhead of creating and maintaining the clusters. Moreover SLTP uses linear regression to compute the time. Therefore, it can calculate the clock skew and offset between each node and its cluster head in order to estimate the local time of remote nodes in the future or the past. Simulation results show that by this we can gain considerable improvements in power consumption, accuracy and scalability in comparison to similar algorithms.

Success of Wireless Sensor Networks largely depends whether the deployed network can provide desired coverage with acceptable network lifetime. This paper proposes a distributed protocol for ensuring area coverage using a combination of mobile and static sensor nodes. Most of the assumptions made in our approach are realistic (sensing model, movement thresholds based on real radio characteristics etc.) and implementable in real-life applications. We demonstrate that, for different type of initial deployments, our proposed movement algorithms consume only 30-40% of the energy consumed by the basic virtual force algorithm. We formulated our problem as Integer Linear Program to arrive at idealistic optimal solutions that form basis of our performance comparison. We validated our results through extensive discrete event simulations.