To satisfy application information Quality (IQ) constraints in a sensor network, the efficient way is to choose the most appropriate sensor nodes and sensor modalities which would provide a required IQ for the current...
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ISBN:
(纸本)9781424415014
To satisfy application information Quality (IQ) constraints in a sensor network, the efficient way is to choose the most appropriate sensor nodes and sensor modalities which would provide a required IQ for the current state of the system. In this paper, two formulations of an activity recognition application are considered - the first based on static Bayesian Network (BN), and the second on Dynamic Bayesian Network (DBN) which allows temporal changes to the conditional probabilities of the system states. It is shown that for similar results, in the certainty of state estimation, the formulation based on DBN uses much less resources, because it relies significantly on the readings obtained in the past. Also DBN model is more robust since it greatly reduces the likelihood of selecting unnaturally drastic state changes.
This paper describes an adaptive error recovery mechanism for sink-to-sensors reliable data dissemination in multi hop wireless sensornetworks. The proposed error recovery mechanism(ONE) uses a cross layer variant of...
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ISBN:
(纸本)9781424415014
This paper describes an adaptive error recovery mechanism for sink-to-sensors reliable data dissemination in multi hop wireless sensornetworks. The proposed error recovery mechanism(ONE) uses a cross layer variant of the negative acknowledgement(NACK) based Selective Repeat scheme for retransmissions. The mechanism is further extended to multi hop topologies by adjusting the window parameters and applying an efficient buffer management strategy. We have shown that the adaptive behavior of the scheme enables optimization of system parameters that affect the total number of packets sent in a reliable session. The analysis of the proposed scheme is given and the effect of buffer size, density and loss ratio parameters on the overall performance is shown.
The wireless nature of the medium combined with energy constraints pose big challenges on the design of energy efficient and reliable protocols for wireless sensornetworks (WSN). In this paper, an energy efficient co...
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ISBN:
(纸本)9781424415014
The wireless nature of the medium combined with energy constraints pose big challenges on the design of energy efficient and reliable protocols for wireless sensornetworks (WSN). In this paper, an energy efficient communication strategy is proposed. First, a general energy consumption model is developed to investigate the traffic load with the multi-hop networking. Then, an energy efficient transmission protocol based on new developed optimization model is proposed, to find the optimal number of virtual nodes, optimal modulation, the optimal number of hops and best transmission range, while it must satisfy given throughput and delay requirements. Simulation results show the proposal model can save the energy and improve the lifetime of WSN significantly.
Mobile ad hoc networks (MANETs) are particularly vulnerable to Denial of Service (DoS) attacks. Existing DoS attack traceback approaches are not suitable for tracing the flooding attacks in MANETs. The challenges root...
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ISBN:
(纸本)9781424415014
Mobile ad hoc networks (MANETs) are particularly vulnerable to Denial of Service (DoS) attacks. Existing DoS attack traceback approaches are not suitable for tracing the flooding attacks in MANETs. The challenges root in several facts, such as the node mobility and the presence of address spoofing. In this work, we present a behavior-based traceback mechanism to identify flooding attack origins. In addition, we also propose an attack isolation scheme to alleviate the attack impact on the network. Simulations are conducted to evaluate the traceback and attack isolation performance.
In this paper we describe a data mining approach for detection of anomalous vessel behaviour The suggested approach is based on Bayesian networks which have two important advantages compared to opaque machine learning...
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ISBN:
(纸本)9781424415014
In this paper we describe a data mining approach for detection of anomalous vessel behaviour The suggested approach is based on Bayesian networks which have two important advantages compared to opaque machine learning techniques such as neural networks: 1) possibility to easily include expert knowledge into the model, and 2) possibility for humans to understand and interpret the learned model. Our approach is implemented and tested on synthetic data, where initial results show that it can be used for detection of single-object anomalies such as speeding.
In this paper, we present a sensor Abstraction Layer (SAL) which provides instrument middleware architectures with a consistent and uniform view of heterogenous sensornetworks regardless of the technologies involved....
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ISBN:
(纸本)9781424415014
In this paper, we present a sensor Abstraction Layer (SAL) which provides instrument middleware architectures with a consistent and uniform view of heterogenous sensornetworks regardless of the technologies involved. SAL is designed to run on sensor gateways (also referred to as base stations) and aggregates multiple sensing technologies. The many hardware disparities and specificities related to accessing, probing and piloting heterogenous sensors are hidden and abstracted by SAL, which in turn offers a single, stable and hardware-independent interface to manage the entire network. The result is a single software library which aggregates multiple heterogenous sensornetworks, hides their disparities, provides consistent access and control functions, and allows middleware software to be technology-independent.
Event detection and monitoring is an important application class for wireless sensornetworks. Traditionally, sensory data are collected and processed at the base-station. Conveying large amounts of multidimensional s...
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ISBN:
(纸本)9781424415014
Event detection and monitoring is an important application class for wireless sensornetworks. Traditionally, sensory data are collected and processed at the base-station. Conveying large amounts of multidimensional sensory data is however impractical in resource-constrained sensornetworks. In this paper we propose to convert event detection into pattern recognition that is particularly suited for sensornetworks. Individual sensory measurements of sensor nodes are integrated into high-level event pattern, and used for recovering the state of the monitored environment. The pattern storage and pattern recognition operations are performed in a distributed manner within the network. Furthermore, a sleep mode strategy is incorporated for improving performance and prolonging the lifetime of the sensor network.
With the extensive implementations of wireless sensornetworks in many areas, it is imperative to have better management of the coverage and energy consumption of such networks. These networks consist of large number ...
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ISBN:
(纸本)9781424415014
With the extensive implementations of wireless sensornetworks in many areas, it is imperative to have better management of the coverage and energy consumption of such networks. These networks consist of large number of sensor nodes and therefore a multi-agent system approach needs to be taken in order for a more accurate model. Three coordination algorithms are being put to the test in this paper: (i) fully distributed Q-learning which we refer to as independent learner (IL), (ii) Distributed Value Function (DVF) and (iii) an algorithm we developed which is a variation of the IL, Coordinated algorithm (COOrd). The results show that the IL and DVF algorithm performed for higher sensor node densities but at low sensor node densities, the three algorithms have similar performance.
Energy consumption in wireless sensornetworks is one of the most important challenges for designing appropriate middleware protocols for specific applications. Meanwhile, how to provide the maximal sensing coverage t...
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ISBN:
(纸本)9781424415014
Energy consumption in wireless sensornetworks is one of the most important challenges for designing appropriate middleware protocols for specific applications. Meanwhile, how to provide the maximal sensing coverage to the monitoring area is another key issue that has to be considered with both the sensors' communication connectivity and their power management strategy. In this paper we propose a novel sensor node working scheduling algorithm targeting to a typical surveillance system. We call it REactive sensor management and COverage Scheme(RECOS). The performance of the algorithm has been evaluated in terms of system lifetime, coverage rate of the monitoring area as well as the robustness of the system against un-expected sensor node failure.
In the case of ad hoc wireless networks, a packet transmitted by a node is received by all nodes in the neighborhood and within RF range. One of the problems is to minimize the total number of forward transmissions fo...
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ISBN:
(纸本)9781424415014
In the case of ad hoc wireless networks, a packet transmitted by a node is received by all nodes in the neighborhood and within RF range. One of the problems is to minimize the total number of forward transmissions for broadcasting. Though this problem is NP-complete some approximation approaches such as Gossip [4] and dominant pruning [9]have been proposed. We propose a new scheme for ad hoc networks based on neighbourhood information and a modified version optimized for sensornetworks. We define an efficiency metric and use it to compare the different broadcast schemes. We have simulated our approach using Scilab and verified that our theory is correct. Finally we also compute the energy consumed by the network and show how it can be minimized.
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