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Predictive Resource Management for Opportunistic Public Sensing Networks Using Fuzzy Logic

Predictive Resource Management for Opportunistic Public Sens...

引用

IEEE Conference on ALocal Computer Networks Workshops (LCN Workshops)

作者： Gina Younes Amr ElMougy German University Cairo

ISBN: (数字)9781728125619

ISBN: (纸本)9781728125626

As the number of deployed sensor networks globally increased to billions, data collection from these networks became quite a challenging task. The wide proliferation of smartphones provides an inexpensive solution for the data collection challenge through opportunistic connections with sensors. However, the varying and unreliable nature of opportunistic data collection may lead to significant waste in the limited resources of the sensors. Thus, efficient management of the resources of the sensors is critical to ensure balance between conserving the energy of the sensors and minimizing the redundancy in data transfer from the sensor to the smartphone to the cloud through the smartphones Internet connection. Accordingly, this paper proposes solutions for resource management in opportunistic sensor networks based on a novel sensor selection algorithm and fuzzy logic. The sensor selection algorithm is used to limit the redundancy in data collected from sensors within close proximity, thus saving their energy. On the other hand, fuzzy logic is used to predict the presence of opportunistic connections based on the history of the sensor. Performance evaluation through computer simulations show that these solutions combined lead to significant increase in network lifetime and minimization of redundancy in data collection.

关键词： wireless sensor network smartphones data collection lifetime of the network energy efficiency redundancy Smartphone management of resources Data Collection Methods redundancy Sensors Wireless sensor networks Fuzzy logic selection algorithm Energy efficiency

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A Proactive Risk-Aware Robotic Sensor Network for Critical Infrastructure Protection

A Proactive Risk-Aware Robotic Sensor Network for Critical I...

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IEEE International Conference on Computational lntelligence and Virtual Environments for Measurement Systems and Applications

作者： Jamieson McCausland George Di Nardo Rafael Falcon Rami Abielmona Voicu Groza Emil Petriu School of Electrical Engineering and Computer Science University of Ottawa Research & Engineering Larus Technologies Corporation

ISBN: (纸本)9781467347020

In this paper, a risk-aware robotic sensor network (RSN) is proposed in the context of Critical Infrastructure Protection. Such a network will be comprised of mobile sensor nodes that perceive various aspects of their environment and topologically reconfigure in order to secure a strategic area of interest. Risk awareness is provided through the application of a recently developed Risk Management Framework to the RSN. The risk level of each node is assessed in terms of their degree of distress, proximity factor, and terrain maneuverability. Risk monitoring alerts are issued whenever any given sensor node's quantitative risk metric exceeds a user-defined threshold value. At this point, a node-in-distress (NID) has been identified as the weak point of the securing structure around which the RSN is deployed. The NID can no longer be used with confidence and the effective perimeter coverage of the RSN has been reduced, thus creating potential security breaches in the area of interest. In response, the remaining nodes will self-organize to maximize the perimeter coverage while minimizing the cost of doing so. A limited set of contingency network topologies is produced via evolutionary multi-objective optimization using the Non-Dominated Sorting Genetic algorithm (NSGA-II) and then ranked according to a human-guided alternative selection algorithm. The security operator picks the most suitable topology, which is then effectuated upon the environment. Results indicate that NSGA-II is capable of producing feasible network topologies to satisfy maximum perimeter coverage, while reducing the energy required for topology reconfiguration. As far as we are concerned, this is the first time a RSN applied to a CIP scenario is self-organized in response to a risk analysis conducted on every sensor node on the basis of multiple risk features.

关键词： Robotic sensor networks Risk management Self-organization Critical infrastructure protection Territorial security Risk Management Sensor networks self-organization Network topology perimeter risk analysis Security hole INFRASTRUCTURE selection algorithm

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Expanding Cellular Network Capacity with Multi-Network Access

Expanding Cellular Network Capacity with Multi-Network Acces...

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IEEE Vehicular Technology Conference

作者： Nandi Zhang Jon M. Peha Marvin A. Sirbu Eng. & Public Policy Carnegie Mellon Univ. Pittsburgh PA USA

ISBN: (纸本)9781538663592;9781538663585

Traditionally, a cell phone remains on a single primary mobile network operator (MNO) as long as it is available, and uses another MNO only when the primary is unavailable and a roaming agreement exists. Multi-network access (MNA), where a cell phone can use any one of multiple MNOs at any point in space and time, can greatly increase cellular network capacity. This paper investigates how much MNA can improve cellular network capacity in the context of a multi-operator mobile virtual network operator (MO-MVNO), such as Google's Project Fi, and explores how the capacity gain varies with the MNOs' resource allocation scheme, and the MO-MVNO's market share and MNO selection algorithm. Simulations show that MNA can expand cellular network capacity by as much as 80% without additional spectrum or infrastructure. Resource allocation schemes affect both total capacity gain and how the gain is shared among operators. We also show that an MNO selection algorithm that is rational for an individual MO-MVNO subscriber can hurt the overall performance of both the MO-MVNO and MNOs.

关键词： cellular radio mobile computing mobile radio resource allocation network capacity cellular radio Mobile radios Resource utilization Mobile Computing Mobile phones Mobile Virtual Network Operator management of resources Gain selection algorithm Cells

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Coordinate Cache Management for Performance Improvement in Spark

Coordinate Cache Management for Performance Improvement in S...

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Image Processing, Electronics and Computers (IPEC), Asia-Pacific Conference on

作者： Weirong Xiu Jie Guo Yanrong Li School of Information Technology and Engineering Guangzhou College of Commerce Guangzhou China

ISBN: (数字)9781728160672

ISBN: (纸本)9781728160689

In big data parallel computing framework, I/O throughput dominates the performance, especially for data intensive workloads. As an outstanding solution of parallel computation, Spark cache Resilient Distribution Datasets (RDDs) in different nodes to speed up the process of computation. However, Spark does not have a good strategy to select reasonable RDDs to cache their partitions in limited memory. This paper proposed a novel cache management strategy, which comprised of selection algorithm and Cluster Global Cleanup algorithm (CSC). selection algorithm caching RDD's partitions in memory automatically order by the number of use for RDDs to speeds up data intensive computations. Nevertheless, when lots of new RDDs are chosen to cache in memory while limited memory has been out of mana, the system will adopt the Least Recently Used (LRU) replacement algorithm. LRU is not only a cleaner of worker but also a trigger of CSC. According to “full or nothing” property of parallel computation, CSC recycling wasted memory space of other workers. Experiment results show that Spark with our selection algorithm speeds up the data intensive workloads and CSC Contribute to the improvement of memory utilization.

关键词： parallel computing cache management Spark PARALLEL PROCESSING (COMPUTERS) Cache memory selection algorithm performance boost Memory Memory memory utilization big data memory space Workload

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LOW COMPLEXITY RST INVARIANT IMAGE RECOGNITION USING FOURIER MELLIN TRANSFORM

LOW COMPLEXITY RST INVARIANT IMAGE RECOGNITION USING FOURIER...

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European Signal Processing Conference

作者： P. Ayyalasomayajula S. Grassi P. A. Farine Institute of Microengineering Electronics and Signal Processing Laboratory

In this paper we propose a low complexity method for Rotation, Scale and Translation (RST) invariant content-based image retrieval, suitable for a handheld image recognition device. The RST compensation method is based on Fourier-Mellin Transform (FMT) which we implement efficiently using log-polar grid interpolation. This RST compensation method is used in conjunction with an image recognition algorithm based on Discrete Cosine Transform (DCT) phase matching. A pre-selection algorithm is also added for decreasing the complexity. This algorithm is based on color proportions within concentric circular zones encompassing the edge pixels. The resulting RST invariant image recognition system was tested on 1500 pictograms and 1000 pictures with different RST conditions, showing an average recognition accuracy of 95.2% for pictograms and 96.9% for pictures.

关键词： Radiosensitivity Testing image recognition algorithm Pictogram compensation method Image recognition selection algorithm picture images

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An Efficient Mobile Multicast Mechanism based on Media Independent Handover

An Efficient Mobile Multicast Mechanism based on Media Indep...

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IEEE Malaysia International Conference on Communications

作者： In-Seop Jang Won-Tae Kim Yong-Jin Park College of Information and Communications Hanyang University ETRI

ISBN: (纸本)9781424455317;9781424455324

In this paper fast mobile multicast mechanism based on IEEE 802.21 MIH (Media Independent Handover) is proposed. We solve long multicast handover delay time caused by L3 movement detection mechanism of the existing mobile multicast methods. The proposed architecture adopts multicast manager concept to MIH framework in order to efficiently perform mobile multicast handover, and adds the new MIH messages dedicated for mobile multicast. Multicast network selection algorithm is designed by means of terminal speed and fair selection algorithm named AHP/GRA. Finally the performance of the proposed architecture against the legacy mobile multicast mechanisms is evaluated in terms of signalling cost and multicast handover delay time.

关键词： Mobile multicast Handover Mobility MIH Melatonin Multicast Handover selection algorithm Mobile mobility

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Cognitive Tracking Radar

Cognitive Tracking Radar

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IEEE Radar Conference

作者： Simon Haykin Amin Zia Ienkaran Arasaratnam Yanbo Xue Cognitive Systems Laboratory McMaster University

ISBN: (纸本)9781424458110

For the first time ever, this paper presents the design and implementation of a next-generation of tracking radar systems: the cognitive tracking radar (CTR). At the heart of the CTR, we have a cognitive waveform-selection (CWS) algorithm that can optimally pick the transmit waveform from a prescribed library, in response to information fed back from the receiver to the transmitter. In accordance with dynamic programming, the waveform-selection algorithm seeks to minimize the expected tracking error over a horizon of prescribed length. Approximation of the problem is also studied to mitigate the burden of computational load. To evaluate the system, we introduce computer experiments on a classical ballistic target tracking problem, the results of which confirm the superiority of the CTR over a conventional radar with fixed waveform.

关键词： Horizon Receivers radar target tracking Transmitters Radar systems selection algorithm transmitter receivers waveforms CRITICAL TEMPERATURE RATIO Calcitonin receptors

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Energy Efficient Adaptive Transmission Strategy Using Cooperative Diversity for Wireless Sensor Networks

Energy Efficient Adaptive Transmission Strategy Using Cooper...

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IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications

作者： N. Atitallah H. Hakim K. Loukil A. M. Obeid M. Abid Digital Research Center of Sfax Technopark of Sfax COSIM Laboratory Higher School of Communication of Tunis National Electronics Comm. and Photonics Center King Abdulaziz City for Science and Technology

ISBN: (纸本)9781509032556

Energy saving strategies pose challenges for wireless Sensor Networks communication, as the nodes have limited energy resources and are battery powered. Thus, there is a strong interest in developing energy efficient transmission techniques. In this paper, we present a new approach to minimize the energy consumption of clustered wireless sensor networks, while achieving the required level of reliability. We consider clusters where sensors transmit monitored data to nearby cluster-head using cooperative communication. The goal of our approach is to minimize the transmit power energy based on Bit Error Probability (BEP) criterion for selective digital relaying (SDR) schemes whose closed form expression was recently derived in previous works. Therefore, the proposed scheme can efficiently allocate the least transmission power among the source and the relays that satisfy the predefined level of reliability while decreasing the energy consumption of the node. Simulation results show that our relay selection algorithm achieves significant energy savings (more than 50% compared with direct transmissions for moderate SNR values and up to 90% in high SNR regions).

关键词： Wireless sensor networks Energy sources energy consumption Energy efficiency energy saving Transmission techniques Adaptive transmission selection algorithm power transmission relay

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Dynamic tap-length estimation based low complexity acoustic echo canceller

Dynamic tap-length estimation based low complexity acoustic ...

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International Conference on Emerging Trends in Science, Engineering and Technology (INCOSET)

作者： Asutosh Kar Mahesh Chandra Dept. of Electronics and Telecommunication Engineering International Institute of Information Technology Bhubaneswar India Dept. of Electronics and Communication Engineering Birla Institute of Technology Mesra India

ISBN: (纸本)9781467351416

A low complexity Multiple Sub-Filters (MSF) parallel structure for monophonic acoustic echo cancellation (AEC) has been proposed where order of each MSF has been estimated dynamically using a new variable step least mean square (VLMS) based fractional order selection algorithm. The proposed length selection algorithm improves the overall performance of the adaptive filter searching the optimum order of each MSF dynamically with faster convergence in a time varying environment. The dynamic order estimation algorithm adapt the MSF to the desired optimum length makes the variable order adaptive filter more efficient by reducing the overall complexity in design and the adaptation noise. The performance analysis depicts that the proposed algorithm converge to the optimum value in mean. The convergence performance of the MSF based parallel structure is studied for common error and different error adaptive algorithms. Simulation results show that MSF with both adaptation algorithms provides better convergence and tracking performance over the conventional echo canceller i.e. a single long filter (SLF). The order adaptation reduces the total number of weights to model the system hence reduce the complexity in design and avoids the adaptation noise.

关键词： adaptation adaptive structure mass storage facility Echo cancellers Self tuning parallel configuration selection algorithm Best value Complexity adaptive filters Converge visual tracking

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The SDL Language Weaver Systems in the WMT12 Quality Estimation Shared Task 12

The SDL Language Weaver Systems in the WMT12 Quality Estimat...

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Workshop on Statistical Machine Translation

作者： Radu Soricut Nguyen Bach Ziyuan Wang SDL Language Weaver 6060 Center Drive Suite 101 Los Angeles CA USA

ISBN: (纸本)9781622765928;1622765923

We present in this paper the system submissions of the SDL Language Weaver team in the WMT 2012 Quality Estimation shared-task. Our MT quality-prediction systems use machine learning techniques (M5P regression-tree and SVM-regression models) and a feature-selection algorithm that has been designed to directly optimize towards the official metrics used in this shared-task. The resulting submissions placed 1st (the M5P model) and 2nd (the SVM model), respectively, on both the Ranking task and the Scoring task, out of 11 participating teams.

关键词： Language Weaver Systems specification description language weaver Language PREDICTION SYSTEM selection algorithm simple regression (model)

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