Collaborative signal processing is one of the most promising applications that are currently being investigated for sensor networks. In this paper, we use FTT computation as a vehicle to highlight the issues involved ...
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ISBN:
(纸本)1424402115
Collaborative signal processing is one of the most promising applications that are currently being investigated for sensor networks. In this paper, we use FTT computation as a vehicle to highlight the issues involved in realizing distributed computations over sensor networks that have global and local communication and synchronization characteristics. We present a power efficient algorithm for computing I-D Fast Fourier Transform (FFT) over single and multi-hop, wireless sensor networks. The proposed algorithm reduces the number of transmissions, eliminates typical redundant computations in a distributed FFT algorithm and uniformly maps complex multiplications over all *** nodes by introducing an extra bit-complement permutation stage after first (log(2)N)/2 iterations. We show that the proposed algorithm improves energy consumption by 36% on the average on multi-hop sensor networks. This saving in energy consumption significantly, improves the battery life of the sensor nodes thereby, increasing lifetime of the sensor network.
The determination of the solution for simultaneous localization and mapping (SLAM) problems has gained significant research momentum in recent times. Although extended Kalman filters have been extensively employed to ...
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ISBN:
(纸本)9781424401956
The determination of the solution for simultaneous localization and mapping (SLAM) problems has gained significant research momentum in recent times. Although extended Kalman filters have been extensively employed to solve these problems in mobile robots, the performance of the EKF can degrade significantly, if the correct a priori knowledge of process and sensor/measurement noise covariance matrices (Q and R respectively) is not available. Hence, the present paper proposes the development of a new robust solution method for SLAM problems where we employ a neuro-fuzzy system to supervise the performance of the EKF for SLAM problems and take necessary corrective actions by adapting the sensor statistics online, so that the degradation in system performance can be arrested. The free parameters of the neuro-fuzzy system are learned offline, by employing particle swarm optimization in the training phase. The system hence proposed is successfully evaluated by employing it to localize a mobile robot and simultaneously acquire the map of the environment;under benchmark environment situations with varying landmarks and with wrong knowledge of sensor statistics.
The nodes in wireless sensor networks are energy-constrained and have limited bandwidth. In addition, communication links between nodes are unpredictable and unstable. These factors make the design of routing protocol...
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ISBN:
(纸本)3540380914
The nodes in wireless sensor networks are energy-constrained and have limited bandwidth. In addition, communication links between nodes are unpredictable and unstable. These factors make the design of routing protocols for such a network very challenging. We propose a scalable, efficient and reliable routing protocol called EAR that provides reliable data delivery from nodes to hubs in a wireless sensor network. Simulation results have shown EAR outperforming existing routing protocols.
We propose a distributed scheme called ADAPTIVE-GROUP-MERGE for sensor networks that, given a parameter k, approximates a geometric shape by a k-vertex polygon. The algorithm is well suited to the distributed computin...
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The way computer systems are built dramatically changed over time. Starting from huge monolithic systems for many users up to ubiquitous computer environments with a lot of distributed and embedded computing power. Al...
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ISBN:
(纸本)354038619X
The way computer systems are built dramatically changed over time. Starting from huge monolithic systems for many users up to ubiquitous computer environments with a lot of distributed and embedded computing power. Also the way these systems are configured has changed. The Autonomic and Organic computing initiatives try to solve the upcoming management of complexity problems by utilizing biologically or sociologically inspired methods. One of the demands to the systems is self-configuration. This paper proposes a self-configuration process for the networked nodes of the AMUN middleware based on a social behavior. Aim of the self-configuration is to find a good distribution of services by calculating a quality of service based on the given resources and the required resources of the services. A configuration specification is provided and flooded into the network to start the cooperative job assignment algorithm. A terminal verification step guarantees the correctness of the found configuration. Evaluations of the completely distributed self-configuration process are provided.
The TMO (Time-triggered Message-triggered Object) model is a real-time object model for real-time distributedcomputing. A TMO instance is a kind of autonomous object having two special types of member threads. The fi...
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ISBN:
(纸本)3540380914
The TMO (Time-triggered Message-triggered Object) model is a real-time object model for real-time distributedcomputing. A TMO instance is a kind of autonomous object having two special types of member threads. The first type is a group of time-triggered threads activated by pre-defined timing constraints such as periods and deadlines. And the second type is a group of message-triggered threads that are activated by distributed IPC messages from remote TMO's and finish their computing within pre-given deadlines. With these properties of the TMO, ubiquitous and real-time distributed applications can be easily organized as a logical network of TMO's. Since the TMO model has been proposed, there have been many successful progresses in developing TMO engines based on open-source kernel platforms. The kernels are TMO-Linux for general embedded systems and TMO-eCos for small embedded/ubiquitous systems. In this paper, after introducing the general architectures and functions of the developed TMO kernels for embedded systems, some comparisons of their characteristics are also given to specify their suitable usage domains.
sensor networks are widely used in a variety of commercial and military applications due to their self-organization characteristics and distributed nature. As a fundamental requirement for providing security functiona...
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ISBN:
(纸本)3540380914
sensor networks are widely used in a variety of commercial and military applications due to their self-organization characteristics and distributed nature. As a fundamental requirement for providing security functionality in sensor networks, key predistribution plays a central role in authentication and encryption. In this paper, we describe the hexagon-based key predistribution scheme and show how it can improve the performance of key predistribution in sensor network through the use of bivariate polynomials in a hexagonal coordinate system based on the deployment information about the expected locations of the sensor nodes. More specifically, we show that the hexagon-based key scheme can improve the probability of establishing pairwise keys between sensor nodes by more than 40% over previous schemes.
Fairness is an important design purpose for shared channel contention based MAC protocols, such as ieee 802.11 in wireless networks. It is a complex problem due to its many dimensions that include consideration of loc...
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ISBN:
(纸本)3540380914
Fairness is an important design purpose for shared channel contention based MAC protocols, such as ieee 802.11 in wireless networks. It is a complex problem due to its many dimensions that include consideration of location-dependent contention, spatial reuse of channels, and desire to achieve fully distributed scheduling in the wireless communication systems. This paper presents a distributed fairness supported scheduling algorithm (DFSS), which accounts for the received service of each flow and adjusts it's backoff time to ensure getting a fair service. In DFSS, each node exchanges the flow's average service index with neighbors as one parameter of determining backoff time. The main advantage of DFSS is that nodes only need to exchange little information to achieve global and local fairness.
High quality healthcare environment is an important aspect of modern society. We investigate security and networking architecture of clinical information system, with emphasis on the wireless hop which includes sensor...
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The Energy Driven Cluster-Head Rotation (EDCR) Algorithm proposed in [1] has been shown to out performed existing clustering algorithms such as LEACH [2], HEED [3], ANTCLUST based [4] and SEP [5] in terms of FND and P...
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ISBN:
(纸本)9781424403394
The Energy Driven Cluster-Head Rotation (EDCR) Algorithm proposed in [1] has been shown to out performed existing clustering algorithms such as LEACH [2], HEED [3], ANTCLUST based [4] and SEP [5] in terms of FND and PNA (95%) lifetime metrics in a distributed wireless sensor network (WSN). In this paper we present theoretical analysis of the performance parameters such as the optimum transmission range (R-opt) and the clustering trigger threshold value (lambda i) of EDCR in terms correctness and complexity of the algorithm. Further we explain how to find the optimal values for such parameters in order to maximize the network lifetime.
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