11683146
Collaborative Image Transmissions Based on Region and Path Diversity in Wireless Sensor Network
Many sensor applications such as monitoring and surveillance may require image sensor array to conduct collaborative image transmissions in wireless sensor networks (WSN). The large size image transmissions cause bottlenecks in WSN due to the limited energy resources and network capacity. In this paper, we propose a collaborative transmission scheme for image sensors to utilize inter-sensor correlations to decide transmission patterns based on transmission path diversities, which achieves minimal energy consumption, balanced sensor lifetime and required image quality. This optimization scheme not only allows each image sensor to transmit optimal fractions of the overlapped images through appropriate transmission paths in energy-efficient way, but also provides unequal protection on the overlap image regions through path selections and resource allocations to achieve good transmission image quality. The simulation results show that the proposed image transmission scheme can achieve considerable gains in terms of the network lifetime extension, image distortion reduction, and energy efficiency.
14352341
Energy-Distortion-Authentication Optimized Resource Allocation for Secure Wireless Image Streaming
Joint consideration of energy efficiency, multimedia quality and media authenticity has largely been overlooked in the studies of secure wireless multimedia streaming. In this paper, we propose an authentication - resource allocation framework for secure transmission of multimedia streaming over energy constrained wireless networks. The contributions of this research can be summarized in three aspects. Firstly, a hash chain based stream level authentication scheme compatible for JPEG2000 compression standard is proposed. Secondly, link layer energy- distortion is modeled, and the energy-distortion convex hull is efficiently identified, which significantly reduces optimization complexity. Finally, an authentication oriented resource allocation scheme is proposed based on the proposed authentication scheme and link layer energy-distortion convex hull, where the authenticated image quality is optimized according to energy budget constraints.
37619733
Taming Underlying Design for Energy Efficient Distributed Source Coding in Multirate Wireless Sensor Network
Signal processing applications such as Distributed Source Coding (DSC) in Wireless Sensor Network (WSN) are often multirate in nature, which provide additional significant opportunities in WSN design for achieving energy efficiency. In this paper, we analyze the DSC traffic for signal processing applications in multirate WSN and propose a novel rate oriented approach with MAC and PHY cross layer utilization to achieve high energy efficiency. Simulation results show that the proposed approach achieves significant energy efficiency by a factor of three while maintaining the transmission quality in WSN. This approach can be easily extended to other WSN MAC and PHY designs, providing multirate service to application layer to allow achieving higher energy efficiency
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.
8653895
The Implementation of an Energy Balanced Routing Protocol with Dynamic Power Scaling in TinyOS
In this paper, we study an energy balanced routing protocol based on dynamic power scaling techniques for wireless sensor networks. In the proposed protocol, each node maintains a list of neighboring nodes and their corresponding statistical residual energy information. The energy balanced routing distributes the levels of residue energy evenly throughout the network, while the dynamic power scaling scheme achieves further energy savings by adjusting transmission power to meet signal strength requirement at the receiver. In order to demonstrate the increased energy efficiency of the proposed protocol, we have conducted an experimental study. The results of our experimental study clearly show that the proposed energy balanced routing scheme with dynamic power improves energy efficiency while achieving energy balance as well
12735466
Position Based Unequal Error Protection for Image Transmission with Energy Constraint over Multirate XPD MIMO Sensor Networks
Multimedia delivery over Wireless Sensor Networks (WSNs) is energy critical. In this paper, we study an energy constrained cross layer optimization scheme to improve digital image quality in cross polarization discrimination (XPD) based Multiple Input Multiple Output (MIMO) WSNs. The contribution of this research can be summarized in three parts. First, link layer energy consumption and packet loss ratio in multirate XPD based MIMO WSN are modeled. Secondly, XPD based modulation optimization cross link and physical layer is proposed, achieving considerable energy efficiency. Finally, a new Position-Value (P- V) based Unequal Error Protection (UEP) scheme is studied and discussed in XPD MIMO WSNs, with more efficient resource allocation compared to traditional approaches. Simulation results show the proposed modulation optimization scheme improves energy efficiency considerably, and position based UEP achieves significant distortion-energy gain compared with traditional layer based resource allocation schemes in XPD MIMO WSNs.
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.
1232737
Extract Frequent Pattern from Simple Graph Data
Mining the frequent pattern from data set is one of the key success stories of data mining research. Currently, most of the efforts are focused on the independent data such as the items in the marketing basket. However, the objects in the real world often have close relationship with each other. How to gain the frequent pattern from these relations is the objective in this paper. We use graphs to model the relations, and select a simple type for analysis. Combining the graph-theory and algorithms to generate frequent patterns, a new structure SFP-Tree and an algorithm, which can mine these simple graphs efficiently, have been proposed. We evaluate the performance of the algorithm by experiments with synthetic datasets. The empirical results show that the SFP can do the job well. At the end of this paper, the potential improvement of SFP is mentioned.
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.
2673667
ApproxMAP: Approximate Mining of Consensus Sequential Patterns
Conventional sequential pattern mining methods may meet inherent difficulties in mining databases with long sequences and noise. They may generate a huge number of short and trivial patterns but fail to find interesting patterns approximately shared by many sequences. In this paper, we propose the theme of approximate sequential pattern mining roughly defined as identifying patterns approximately shared by many sequences. We present an efficient and effective algorithm, ApproxMAP, to mine consensus patterns from large sequence databases in two steps. First, sequences are clustered by similarity. Then, consensus patterns are mined directly from each cluster through multiple alignment. We use a real case study to illustrate the effectiveness of ApproxMAP.
14448228
Self-adaptive web intrusion detection system
The evolution of the web server contents and the emergence of new kinds of intrusions make necessary the adaptation of the intrusion detection systems (IDS). Nowadays, the adaptation of the IDS requires manual -- tedious and unreactive -- actions from system administrators. In this paper, we present a self-adaptive intrusion detection system which relies on a set of local model-based diagnosers. The redundancy of diagnoses is exploited, online, by a meta-diagnoser to check the consistency of computed partial diagnoses, and to trigger the adaptation of defective diagnoser models (or signatures) in case of inconsistency. This system is applied to the intrusion detection from a stream of HTTP requests. Our results show that our system 1) detects intrusion occurrences sensitively and precisely, 2) accurately self-adapts diagnoser model, thus improving its detection accuracy.