38794991
Localized Recursive Estimation in Wireless Sensor Networks
This paper proposes a localized recursive estimation scheme for parameter estimation in wireless sensor networks. Given any parameter occurred at some location and time, a number of sensors recursively estimates the parameter by using their local measurements of the parameter that is attenuated with the distance between a sensor and the target location and corrupted by noises. Compared with centralized estimation schemes that transmit all measurements to a sink (or a fusion center), the recursive scheme needs only to transmit the final estimate to a sink. When a sink is faraway from the sensors and multihop communications have to be used, using localized recursive estimation can help to reduce energy consumption and reduce network traffic load. Furthermore, the most efficient sequence of sensors for estimation is defined and the necessary condition for such a sequence is determined. Some numerical examples are also provided. By using some typical industrial sensor parameter values, it is shown that recursive scheme consumes much less energy when the sink is three hops or more faraway from the local sensors.
15401774
Information Coverage and Network Lifetime in Energy Constrained Wireless Sensor Networks
This paper studies the problem of how to maximize the network lifetime while preserving network coverage for an energy constrained wireless sensor network. We consider network coverage from an our recently proposed information coverage model [1] other than the conventional sensing disk model. The lifetime maximization problem is modeled as a nonlinear programming problem and is shown NP-Complete. We then propose a family of greedy algorithms to allocate sensors different roles such that different sensors may consume different amount of energies in different intervals to prolong network lifetime while still guaranteeing application requirements. Simulation results suggest that the algorithm with the best balancing between communication energy consumption and area coverage requirement has the highest network lifetime.
1588647
Coverage in Hybrid Mobile Sensor Networks
This paper considers the coverage problem for hybrid networks which comprise both static and mobile sensors. The mobile sensors in our network only have limited mobility, i.e., they can move only once over a short distance. In random static sensor networks, sensor density should increase as O(log L + k log log L) to provide k-coverage in a network with a size of L. As an alternative, an all-mobile network can provide k-coverage with a constant density of O(k), independent of network size L. We show that the maximum distance for mobile sensors is O( 1/radic(k) log 3/4(kL)). We then propose a hybrid network structure, comprising static sensors and a small fraction of O( 1/radic(k)) of mobile sensors. For this network structure, we prove that k-coverage is also achievable with a constant sensor density of O(k). Furthermore, for this hybrid structure, we prove that the maximum distance which any mobile sensor has to move is bounded as O(log(3/4)L). We then propose a distributed relocation algorithm, where each mobile sensor only requires local information in order to optimally relocate itself. We verify our analysis via extensive numerical evaluations and show an implementation of the mobility algorithm on real mobile sensor platforms.
7046093
Adaptive contact probing mechanisms for delay tolerant applications
In many delay tolerant applications, information is opportunistically exchanged between mobile devices who encounter each other. In order to effect such information exchange, mobile devices must have knowledge of other devices in their vicinity. We consider scenarios in which there is no infrastructure and devices must probe their environment to discover other devices. This can be an extremely energy consuming process and highlights the need for energy conscious contact probing mechanisms. If devices probe very infrequently, they might miss many of their contacts. On the other hand, frequent contact probing might be energy inefficient. In this paper, we investigate the trade-off between the probability of missing a contact and the contact probing frequency. First, via theoretical analysis, we characterize the trade-off between the probability of a missed contact and the contact probing interval for stationary processes. Next, for time varying contact arrival rates, we provide an optimization framework to compute the optimal contact probing interval as a function of the arrival rate. We characterize real world contact patterns via Bluetooth phone contact logging experiments and show that the contact arrival process is self-similar. We design STAR, a contact probing algorithm which adapts to the contact arrival process. Via trace driven simulations on our experimental data, we show that STAR consumes three times less energy when compared to a constant contact probing interval scheme.
121717769
Coverage for target localization in wireless sensor networks
Target tracking and localization are important applications in wireless sensor networks. Although the coverage problem for target detection has been intensively studied, few consider the coverage problem from the perspective of target localization. In this paper, we propose two methods to estimate the lower bound of sensor density to guarantee a bounded localization error over the sensing field. We first convert the coverage problem for localization to a conventional disk coverage problem, where the sensing area is a disk centered at the sensor. Our results show that the disk coverage model requires 4 times more sensors for localization compared to detection applications. We then introduce the idea of sector coverage to tighten the lower bound. The lower bound derived through sector coverage is 2 times less than through disk coverage. A distributed sector coverage algorithm is then proposed in this paper. Compared to disk coverage, sector coverage requires more computations. However, it provides more accurate density estimations than the disk model. Numerical evaluations show that the density bound derived through our sector coverage model is tight.
16422788
Trade-offs between mobility and density for coverage in wireless sensor networks
In this paper, we study the coverage problem for hybrid networks which comprise both static and mobile sensors. We consider mobile sensors with limited mobility, i.e., they can move only once over a short distance. Such mobiles are simple and cheap compared to sophisticated mobile robots. In conventional static sensor networks, for a random deployment, the sensor density should increase as <i>O</i>(log <i>L</i> + <i>k</i> log log <i>L</i>) to provide <i>k</i>-coverage in a network with a size of <i>L</i>. As an alternative, an all mobile sensor network can provide <i>k</i>-coverage over the field with a constant density of <i>O</i>(<i>k</i>), independent of network size <i>L</i>. We show that the maximum distance that any mobile sensor will have to move is <i>O</i>(1 over √<i>k</i> log <sup>3 over 4</sup> (<i>kL</i>)). We then propose a hybrid network structure, comprising static sensors and a small fraction of <i>O</i>(1 over √(<i>k</i>)) of mobile sensors. For this network structure, we prove that <i>k</i>-coverage is achievable with a constant sensor density of <i>O</i>(<i>k</i>), independent of network size <i>L</i>. Furthermore, for this hybrid structure, we prove that the maximum distance which any mobile sensor has to move is bounded as <i>O</i>(log<sup>3 over 4</sup> <i>L</i>). We then propose a distributed relocation algorithm, where each mobile sensor only requires local information in order to optimally relocate itself and characterize the algorithm's computational complexity and message overhead. Finally, we verify our analysis via extensive numerical evaluations.
15041216
Coding-based Join Algorithms for Structural Queries on Graph-Structured XML Document
In many applications, XML documents need to be modelled as graphs. The query processing of graph-structured XML documents brings new challenges. In this paper, we design a method based on labelling scheme for structural queries processing on graph-structured XML documents. We give each node some labels, the reachability labelling scheme. By extending an interval-based reachability labelling scheme for DAG by Rakesh et al., we design labelling schemes to support the judgements of reachability relationships for general graphs. Based on the labelling schemes, we design graph structural join algorithms to answer the structural queries with only ancestor-descendant relationship efficiently. For the processing of subgraph query, we design a subgraph join algorithm. With efficient data structure, the subgraph join algorithm can process subgraph queries with various structures efficiently. Experimental results show that our algorithms have good performance and scalability.
6007133
Ranking Outliers Using Symmetric Neighborhood Relationship
Mining outliers in database is to find exceptional objects that deviate from the rest of the data set. Besides classical outlier analysis algorithms, recent studies have focused on mining local outliers, i.e., the outliers that have density distribution significantly different from their neighborhood. The estimation of density distribution at the location of an object has so far been based on the density distribution of its k-nearest neighbors [2,11]. However, when outliers are in the location where the density distributions in the neighborhood are significantly different, for example, in the case of objects from a sparse cluster close to a denser cluster, this may result in wrong estimation. To avoid this problem, here we propose a simple but effective measure on local outliers based on a symmetric neighborhood relationship. The proposed measure considers both neighbors and reverse neighbors of an object when estimating its density distribution. As a result, outliers so discovered are more meaningful. To compute such local outliers efficiently, several mining algorithms are developed that detects top-n outliers based on our definition. A comprehensive performance evaluation and analysis shows that our methods are not only efficient in the computation but also more effective in ranking outliers.
34121335
Data-Aware Clustering Hierarchy for Wireless Sensor Networks
In recent years, the wireless sensor network (WSN) is employed a wide range of applications. But existing communication protocols for WSN ignore the characteristics of collected data and set routes only according to the mutual distance and residual energy of sensors. In this paper we propose a Data-Aware Clustering Hierarchy (DACH), which organizes the sensors based on both distance information and data distribution in the network Furthermore, we also present a multi-granularity query processing method based on DACH, which can estimate the query result more efficiently. Our empirical study shows that DACH has higher energy efficiency than Low-Energy Adaptive Clustering Hierarchy (LEACH), and the multi-granularity query processing method based on DACH brings more accurate results than a random access system using same cost of energy.
26642486
Computing Repairs for Inconsistent XML Document Using Chase
An XML document is inconsistent if it violates predefined integrity constraints. In this paper, we consider how to compute repairs for an inconsistent XML document. Here repair is defined as the data consistent with the integrity constraints, and also minimally differs from the original document. Based on a repair framework by introducing a chase method, in this paper, we discuss the repairs computing problem and implement a prototype. First we discuss some key points about mends generation and repairs chasing. Next we give a cost model for this repair framework, which can be used to evaluate the cost of each repair. Finally we implement prototypes of our method, and evaluate our framework and algorithms in the experiment.
2440328
Image transmissions with security enhancement based on region and path diversity in wireless sensor networks
Transmissions of large sized images can be a bottleneck for a wireless sensor network (WSN) due to its limited resources. Security can be another concern. This paper proposes a collaborative transmission scheme for image sensors to utilize inter-sensor correlations to decide the transmission and security sharing patterns based on the path diversities. Our proposed approach for secret image sharing on multiple node-disjoint paths for image delivery is to achieve high security without any key distribution and management, and thus the key management related problems do not exist. The energy efficiency is another major contribution made in this paper. This scheme does not only allow each image sensor to transmit optimal fractions of overlapped images through appropriate transmission paths in an energy-efficient way, but also provides unequal protection to overlapped image regions by path selections and adaptive bit error rate (BER) requirement. The simulation results show that the proposed scheme can achieve considerable gains in terms of network lifetime extension, image transmission security enhancement, image quality improvement, and energy efficiency for wireless sensor networks.