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.
7941937
Scheduling Sensor Activity for Point Information Coverage in Wireless Sensor Networks
An important application of wireless sensor networks is to perform the monitoring missions, for example, to monitor some targets of interests at all times. Sensors are often equipped with non-rechargeable batteries with limited energy and energy saving is a critical aspect for wireless sensor networks. If a target is monitored simultaneously by serval sensors, some of them can be switched off to save energy without causing mission failure and by which their operational times as well as the network lifetime can be prolonged. In this paper, we study the problem of scheduling sensor activity to cover a set of targets with known locations such that all targets can be monitored all the time and the network can operate as long as possible. A solution to this scheduling problem is to partition all sensors into sensor covers such that each cover can monitor all targets and the covers are activated successively. In this paper, we propose to use the notion of information coverage which is based on the estimation theory to exploit the collaborative nature of wireless sensor networks, instead of using the conventional definition of coverage. Due to the use of information coverage, a target that is not within the sensing disk of any single sensor can still be considered to be monitored (information covered) by the cooperation of more than one sensor.
20581508
Scheduling sensor activity for information coverage of discrete targets in sensor networks
In this paper, we study the problem of scheduling sensor activity to cover a set of targets with known locations such that all targets can be monitored all the time and the network can operate as long as possible. A solution to this scheduling problem is to partition all sensors into some sensor covers such that each cover can monitor all targets and the covers are activated sequentially. In this paper, we propose to provide information coverage instead of the conventional sensing disk coverage for target. The notion of information coverage is based on estimation theory to exploit the collaborative nature of geographically distributed sensors. Due to the use of information coverage, a target that is not within the sensing disk of any single sensor can still be considered to be monitored (information covered) by the cooperation of more than one sensor. This change of the problem settings complicates the solutions compared to that by using a disk coverage model. We first define the target information coverage (TIC) problem and prove its NP-completeness. We then propose a heuristic to approximately solve our problem. Simulation results show that our heuristic is better than an existing algorithm and is close to the upper bound when only the sensing disk coverage model is used. Furthermore, simulation results also show that the network lifetime can be significantly improved by using the notion of information coverage compared with that by using the conventional definition of sensing disk coverage. Copyright © 2008 John Wiley & Sons, Ltd.
5517318
Power Control for Distributed MAC Protocols in Wireless Ad Hoc Networks
In centralized wireless networks, reducing the transmission power normally leads to higher network transport throughput. In this paper, we investigate power control in a different scenario, where the network adopts distributed MAC layer coordination mechanisms. We first consider widely adopted RTS/CTS based MAC protocols. We show that an optimal power control protocol should use higher transmission power than the "just enough" power in order to improve spatial utilization. The optimal protocol has a minimal transmission floor area of Theta(dijdmax), where dmax is the maximal transmission range and dij is the link length. This surprisingly implies that if a long link is broken into several short links, then the sum of the transmission floors reserved by the short links is still comparable to that reserved by the long link. Thus, using short links does not necessarily lead to higher throughput. Another consequence of this is that, with the optimal RTS/CTS based MAC, rate control can at best provide a factor of 2 improvement in transport throughput. We then extend our results to other distributed MAC protocols which uses physical carrier sensing or busy-tone as the control signal. Our simulation results show that the optimal power controlled scheme outperforms other popular MAC layer power control protocols.
876538
Dependent link padding algorithms for low latency anonymity systems
Low latency anonymity systems are susceptive to traffic analysis attacks. In this paper, we propose a dependent link padding scheme to protect anonymity systems from traffic analysis attacks while providing a strict delay bound. The covering traffic generated by our scheme uses the minimum sending rate to provide full anonymity for a given set of flows. The relationship between user anonymity and the minimum covering traffic rate is then studied via analysis and simulation. When user flows are Poisson processes with the same sending rate, the minimum covering traffic rate to provide full anonymity to m users is O(log m). For Pareto traffic, we show that the rate of the covering traffic converges to a constant when the number of flows goes to infinity. Finally, we use real Internet trace files to study the behavior of our algorithm when user flows have different rates.
18851667
Sensor Density for Complete Information Coverage in Wireless Sensor Networks
Coverage is a very important issue in wireless sensor networks. Current literature defines a point to be covered if it is within the sensing radius of at least one sensor. This is a conservative definition of coverage and we have previously proposed a new notion of information coverage. Compared with the conventional definition of coverage, a point can still be information covered even if it is not within the sensing disk of any sensor. The density requirements for complete information coverage of a field are analyzed and simulated for a random sensor deployment. Our results show that significant savings in terms of sensor density can be achieved with information coverage.
10774024
Accurate Classification of Protein Structural Families Using Coherent Subgraph Analysis
Protein structural annotation and classification is an important problem in bioinformatics. We report on the development of an efficient subgraph mining technique and its application to finding characteristic substructural patterns within protein structural families. In our method, protein structures are represented by graphs where the nodes are residues and the edges connect residues found within certain distance from each other. Application of subgraph mining to proteins is challenging for a number reasons: (1) protein graphs are large and complex, (2) current protein databases are large and continue to grow rapidly, and (3) only a small fraction of the frequent subgraphs among the huge pool of all possible subgraphs could be significant in the context of protein classification. To address these challenges, we have developed an information theoretic model called coherent subgraph mining. From information theory, the entropy of a random variable X measures the information content carried by X and the Mutual Information (MI) between two random variables X and Y measures the correlation between X and Y. We define a subgraph X as coherent if it is strongly correlated with every sufficiently large sub-subgraph Y embedded in it. Based on the MI metric, we have designed a search scheme that only reports coherent subgraphs. To determine the significance of coherent protein subgraphs, we have conducted an experimental study in which all coherent subgraphs were identified in several protein structural families annotated in the SCOP database (Murzin et al, 1995). The Support Vector Machine algorithm was used to classify proteins from different families under the binary classification scheme. We find that this approach identifies spatial motifs unique to individual SCOP families and affords excellent discrimination between families.
13485709
Three-dimensional conceptual model for service-oriented simulation
In this letter, we propose a novel three-dimensional conceptual model for an emerging service-oriented simulation paradigm. The model can be used as a guideline or an analytic means to find the potential and possible future directions of the current simulation frameworks. In particular, the model inspects the crossover between the disciplines of modeling and simulation, service-orientation, and software/systems engineering. Finally, two specific simulation frameworks are studied as examples.
24887227
Cross-layer routing optimization in multirate wireless sensor networks for distributed source coding based applications
The advancement in distributed source coding (DSC) for mission-driven wireless sensor networks (WSNs) has opened a new vista for its wide applications in multiple correlated sensor networks such as real time target tracking and environment monitoring. The features of the DSC applications offer many potential opportunities for sensor networks to utilize multirate transmissions for network performance enhancement. In this paper, we propose a methodology for cross-layer optimization between routing and DSC in WSNs, and we introduce a multirate based routing scheme for mission-driven DSC applications that can considerably extend network lifetime. The proposed scheme adopts the rate assignment based on residual energy and employs a joint rate and energy scheduling mechanism to meet the end-to-end transmission rate demand, information precision requirement, and energy constraints in the networks adopting DSC. This approach is different from the traditional multirate research in link adaptation, where the focus was to increase channel throughput based on rate adaptation from variable channel conditions. The objective of this work is not to utilize multirate for increasing channel throughput, but to exploit multirate capability for routing optimization in DSC based applications with consideration for energy consumption. We also introduce the concept of "Energy Usage Scheduling (EUS)" to optimize the energy usage based on the rate constraints and DSC application needs. Simulation results show that the proposed scheme can achieve a significantly longer network lifetime than that reported in the literature.
2285434
Towards multidimensional subspace skyline analysis
The skyline operator is important for multicriteria decision-making applications. Although many recent studies developed efficient methods to compute skyline objects in a given space, none of them considers skylines in multiple subspaces simultaneously. More importantly, the fundamental problem on the semantics of skylines remains open: Why and in which subspaces is (or is not) an object in the skyline? Practically, users may also be interested in the skylines in any subspaces. Then, what is the relationship between the skylines in the subspaces and those in the super-spaces? How can we effectively analyze the subspace skylines? Can we efficiently compute skylines in various subspaces and answer various analytical queries?In this article, we tackle the problem of multidimensional subspace skyline computation and analysis. We explore skylines in subspaces. First, we propose the concept of Skycube, which consists of skylines of all possible nonempty subspaces of a given full space. Once a Skycube is materialized, any subspace skyline queries can be answered online. However, Skycube cannot fully address the semantic concerns and may contain redundant information. To tackle the problem, we introduce a novel notion of skyline group which essentially is a group of objects that coincide in the skylines of some subspaces. We identify the decisive subspaces that qualify skyline groups in the subspace skylines. The new notions concisely capture the semantics and the structures of skylines in various subspaces. Multidimensional roll-up and drill-down analysis is introduced. We also develop efficient algorithms to compute Skycube, skyline groups and their decisive subspaces. A systematic performance study using both real data sets and synthetic data sets is reported to evaluate our approach.
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.