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Power allocation in multi-node cooperative network in Rician fading channels

Power allocation in multi-node cooperative network in Rician...

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ieee international conference on Wireless and Mobile computing, Networking And Communications (WiMob)

作者： Mulugeta K. Fikadu Mohammed Elmusrati Reino Virrankoski Department of Computer Science Communication and System Engineering Group University of Vaasa Vaasa Finland

Cooperative communications have been recommended to exploit the inherent spatial diversity gains in multiuser wireless systems without the need of multiple transceivers at each node. this is achieved when wireless nodes help to each other to send multiple independent transmission paths to the destination. the advantage of cooperation can be exploited significantly by allocating the power of the system optimally. thus, in this paper we first derive the approximate symbol error rate (SER) for multi-node cooperative networks employing decode-and-forward (DF) protocol with a maximum ratio combining (MRC) at the receiving terminals in Racian fading channels. Using the approximated SER expression, optimal power allocation (OPA) scheme under different line-of-sight (LOS) scenarios is investigated. Numerical and simulation results are presented to illustrate the performance improvement due to OPA of the cooperative networks.

关键词： Relays Resource management Rician channels Cooperative systems Fading Signal to noise ratio Wireless sensor networks

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Cross-layer caching based optimization for wireless multimedia sensor networks

Cross-layer caching based optimization for wireless multimed...

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ieee international conference on Wireless and Mobile computing, Networking And Communications (WiMob)

作者： Nestor Michael C. Tiglao António M. Grilo EEEI University of Philippines Quezon Philippines INESC-ID/INOV/IST Lisboa Portugal

Traditional transport layer protocols have been designed to perform end-to-end error control transparently to the intermediate nodes (e.g., TCP). However, the resource constraints featured by Wireless sensor Network (WSN) require a different paradigm where intermediate nodes are able to cache packets and if possible retransmit them on-demand to avoid incurring costly end-to-end retransmissions. Lately, wireless multimedia sensor network (WMSN) is being considered as a new research area whereby WSNs are targeted for the delivery of multimedia traffic. In this paper, we propose a NACK-based repair mechanism coupled with an adaptive MAC layer retransmission scheme in order to improve the performance of the transport protocols. Specifically, our goal is to be able to reduce real-time end-to-end delay while maintaining reliability and energy efficiency in the presence of high channel error rates. Our simulation results show that the ensemble of both mechanisms provides better good-put performance while simultaneously improving energy efficiency. Furthermore, the improved protocol also achieves lower deadline miss ratios which makes it suitable for multimedia transport. While we demonstrate the effectiveness of the mechanisms by incorporating them into the basic distributed Transport for sensor Networks (DTSN) protocol, they are generic enough to be applicable to other WSN transport protocols.

关键词： Maintenance engineering Reliability Wireless sensor networks Protocols Receivers Multimedia communication Error analysis

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Optimal Trajectory Planning and Task Assignment for UAV-assisted Fog computing

Optimal Trajectory Planning and Task Assignment for UAV-assi...

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ieee international conference on High Performance computing and Communications (HPCC)

作者： Shuaijun Liu Jiaying Yin Zishu Zeng Jingjin Wu Department of Statistics and Data Science BNU-HKBU United International College Zhuhai China Li Ka Shing Faculty of Medicine The University of Hong Kong Pokfulam Hong Kong SAR China School of Engineering The Hong Kong University of Science and Technology Kowloon Hong Kong SAR China Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science

Fog computing is an emerging distributed computing model for the realization of the Internet of things (IoT). It extends computing and caching functions to the edge of wireless networks. Unmanned Aerial Vehicles (UAVs) provide effective support for fog computing, as UAVs can not only act as a relay between mobile users and physically remote edge devices to avoid costly long-range wireless communications, but also are equipped with computing facilities that can take over certain tasks. In this paper, we aim to optimize the energy efficiency of a fog computing system assisted by a single UAV, by planning the trajectories of the UAV and assigning computing tasks to different devices including the UAV itself. We propose two algorithms based on the classical Ant Colony and Particle Swarm Optimization techniques, and solve the problem by continuous convex approximation. Different from most existing studies where the trajectories are assumed to be straight lines, we account for the effect of obstacles, such as buildings, and deliberately avoid them during the trajectory planning phase. We demonstrate, through extensive simulation experiments, that our proposed approach can achieve significantly better energy efficiency compared to existing benchmark algorithms.

关键词： Trajectory planning Computational modeling Wireless networks Autonomous aerial vehicles Energy efficiency Trajectory Internet of things

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Integrating people-centric sensing with social networks: A privacy research agenda

Integrating people-centric sensing with social networks: A p...

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ieee Annual conference on Pervasive computing and Communications Workshops (PerCom)

作者： Ioannis Krontiris Felix C. Freiling Laboratory of Dependable Distributed Systems University of Mannheim Germany

During the last few years there has been an increasing number of people-centric sensing projects, which combine location information with other sensors available on mobile devices, such as the camera, the microphone or the accelerometer, giving birth to a different dimension in sensing our environment compared to the existing wireless sensor networks approach. In this paper, we envision a new scenario, where users develop their own participatory urban sensing projects at a large scale through the use of social networks. Consequently, users can participate in campaigns created by other users, according to their sensitivities and interests, exploiting the existing enormous social interconnections offered by existing social networking tools. We place our primary concern to protecting user privacy and address the need for new solutions in location anonymity and access control under this new complex and dynamic communication paradigm.

关键词： Irrigation

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Implementation technology software-defined networking in Wireless sensor Networks

Implementation technology software-defined networking in Wir...

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ieee international Workshop on Intelligent Data Acquisition and Advanced computing systems: Technology and Applications

作者： Marek Boguslav Aleksander Lesia Dubchak Vitalii Chyzh Artur Naglik Anton Yavorski Natalia Yavorska Mikolaj Karpinski State Higher Vocational School in Nowy Sacz Nowy Sącz Poland Ternopil National Economic University Ternopil Ukraine Ternopil Ivan Pul'uj National Technical University Ternopil Ukraine University of Bielsko-Biala Bielsko-Biala Poland

Recent advances in the micro electromechanical systems technology MEMS, wireless communications and digital electronics allowed to create inexpensive, low-powered, multi-functional nodes. they are small and "talk" directly with each other. Wireless sensor Network (WSN) is considered to be a distributed, self-organizing system of a large number of sensors and assistive devices that communicate with each other through the radio channel. sensor networks are based on the joint work of a large number of tiny nodes that consist of data collection and processing modules and a transmitter or a transceiver. Such networks have significant advantages over the set of traditional sensors. the main problem in sensor networks is a short stint due to high power consumption and the incompatibility of various hardware. Because of the absence of a clear standardization in sensor networks, there are several different platforms. All platforms meet the essential basic requirements for sensor networks: low power consumption, long operating time, low-power transmitters and presence of sensors. Each platform is in its own interest substantiated and has its own peculiarities. they will transmit the observation data to the central nodes where data collection, storing, and processing will be performed. the main purpose is to enhance the security wireless sensor networks.

关键词： Wireless sensor networks sensor phenomena and characterization Radio transmitters Protocols Data communication Routing

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Efficient. Scalable and Robust Data Shuffle Service for distributed MapReduce computing on Cloud

Efficient. Scalable and Robust Data Shuffle Service for Dist...

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ieee international conference on High Performance computing and Communications (HPCC)

作者： Rong Gu Xu Huang Haipeng Dai Xiaoyu Geng Xiaofei Chen Yihua Huang Fu Xiao Guihai Chen State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Nanjing University of Posts and Telecommunications Nanjing China

distributed Map Reduce computing frameworks, such as Hadoop, Spark, and Flink, are widely used in various domains which face big data challenges. Inside Map Reduce, Shuffle is a critical stage that bridges up the Map stage and Reduce stage through data partition and network transmission under the hood. With the rapidly growing scale of data and clusters, the all-to-all data transfer in Shuffle becomes inefficient and frequently fails, making Shuffle the bottleneck of many big data processing jobs. To improve the Shuffle efficiency, we propose a hybrid Shuffle model based on file pre-merging and partition reorganization mechanisms. To address the Shuf-fle stability issue, we design a novel data transmission model based on the replication mechanism. Finally, to support scalable Shuffle with high performance, we present a Shuffle parallelism degree tuning approach based on machine learning and searching techniques. We have implemented the proposed Shuffle models and strategies into the widely-used MapReduce-based big data platform Spark for evaluation. Experimental evaluation shows that, compared with the state-of-the-art systems, our proposed methods outperform them by 23% on average. As a practical application case, the proposed Shuffle service has been running in the real-world environment of ByteDance. Inc over one year with significant performance improvement.

关键词： Machine learning Parallel processing Big Data Data models Stability analysis Sparks Task analysis

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Aware: Adaptive distributed Training with Computation, Communication and Position Awareness for Deep Learning Model

Aware: Adaptive Distributed Training with Computation, Commu...

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ieee international conference on High Performance computing and Communications (HPCC)

作者： Yan Zeng Guangzheng Yi Yuyu Yin Jiyang Wu Meiting Xue Jilin Zhang Jian Wan Yunquan Zhang School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China School of Cyberspace Hangzhou Dianzi University Hangzhou China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China

the accuracy of the neural networks can usually be improved by increasing the size of the dataset and the layers or operators of the network, as it has strong composability. But, it makes a challenge to train these models efficiently, due to the limited resources of a single device, such as memory, computational resource and so on. For this challenge, it has become an inevitable trend to automatically implement model parallelism across multiple devices. this paper proposes Aware, an adaptive distributed parallel training method, to search distributed parallel strategy automatically for deep learning model. It firstly proposes an operator fusion strategy with computation and communication awareness to simplify the computational graph of deep learning model. And then, it introduces position-aware graph embedding algorithm to extract the structural features of models, which can make the searched parallel strategies to transplant to other networks with similar structures. On this basis, we use reinforcement learning algorithm to search distributed parallel strategy automatically. this paper makes experiments with neural networks such as Inception V3, NMT, GNM, NasNet and ResNet, and uses CIFAR10 and PTB datasets to compare the two methods of Hierarchical and Placeto. the results show that compared with Placeto, Aware achieves up to 5% reductions in runtime. Aware achieves more than 8% reductions in runtime compared with Hierarchical. Moreover, it has better transplantation and generalization capabilities, and supports pre-training for large-scale network parallel strategy search and accelerates convergence.

关键词： Deep learning Training Adaptation models Runtime Computational modeling Neural networks Reinforcement learning

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Evaluating the threat of epidemic mobile malware

Evaluating the threat of epidemic mobile malware

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ieee international conference on Wireless and Mobile computing, Networking And Communications (WiMob)

作者： Christian Szongott Benjamin Henne Matthew Smith Distributed Computing & Security Group Gottfried Wilhelm Leibniz University of Hannover

While mobile malware has played a relatively small role compared to the behemoth of desktop malware, the changes both in the capability as well as in the proliferation of the mobile devices will steadily increase the attractiveness of mobile devices as resources to be attacked. the increased usage and connectivity of mobile devices opens up a much larger set of attack vectors to compromise these devices. In this paper, we discuss how the new features of mobile devices opens up the capability to create a new generation of mobile malware which is capable of realistically spreading epidemically on a fully mobile infection vector. We present a prototype of such a mobile malware that uses these features to replicate itself and spread over a mobile device-to-device vector. Using simulations we give quantitative support for the number of mobile devices and conditions needed to for an epidemic spread of mobile malware and present infection scenarios in downtown Chicago. Our results show that the recent growth and market dominance of just a handful of mobile phone companies and the trend towards mobile operating systems monoculture has already created a viable substrate for epidemic mobile malware.

关键词： Malware Mobile communication Mobile handsets Mathematical model Batteries Internet ieee 802.11 Standards

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G-Update: A Group-based Update Scheme for Heterogenous Erasure-coded Storage systems

G-Update: A Group-based Update Scheme for Heterogenous Erasu...

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ieee international conference on High Performance computing and Communications (HPCC)

作者： Xuyu Zhao Bing Zhu Zhiwei Zeng Weiping Wang Kenneth W. Shum School of Computer Science and Engineering Central South University School of Science and Engineering Chinese University of Hong Kong (Shenzhen)

Erasure codes generate redundant encoded chunks to improve data reliability by encoding original data, among which wide stripe achieves extreme low storage redundancy to improve data storage efficiency. When original data need to be update, erasure codes spend long update time and high network consumption to update every encoded chunk. the frequent update of stored data in distributed storage systems has posed great challenges to the timeliness of data update. However, state-of-the-art works have mainly considered homogeneous storage environment. therefore we mainly consider the scheme of data update in the heterogeneous storage environment for multiple node update in wide stripe. In this paper, we propose a _Qroup-based Update scheme for heterogenous erasure-coded storage systems, called G- Update. G- Update divides update process into three stages: (i) grouping stage, which groups updated data nodes and parity nodes together with parity nodes as the group center, (ii) intra-group update stage, which transmits update deltas with maximum bandwidth link within the group, and (iii) inter-group update stage, which exchanges update deltas between groups. To evaluate the performance of G-Update, we conduct simulation experiments on different update schemes. Results show that G-Update can reduce the update time by 15.59% and 81.60% on average compared with S-Update and T-Update respectively.

关键词： Codes Redundancy distributed databases Memory Bandwidth Encoding Reliability

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BTDFS: B+ Tree-Based distributed File Storing Mechanism for Improving Small File Storage

BTDFS: B+ Tree-Based Distributed File Storing Mechanism for ...

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ieee international conference on High Performance computing and Communications (HPCC)

作者： Jingyu Zhang Jiachen Tian Lailong Luo School of Computer & Communication Engineering Changsha University of Science & Technology Changsha China Science and Technology on Information Systems Engineering Laboratory School of Systems Engineering National University of Defense Technology Changsha China

Hadoop is currently the most popular big data processing architecture, which provides a processing framework for managing and analyzing massive data. Hadoop distributed File System (HDFS) is the core component for storing data in the Hadoop systems. It performs well when storing and managing large-sized files. However, it shows extremely bad performance when dealing with a large number of small files, which is reflected in the consumption of a large amount of memory space of the NameNode node and the low efficiency of accessing small files. Archive file is proposed to solve this problem. It combines small files into larger merged files for storage, and uses index files to record the relevant information of small files in the merged files. However, archive files (e.g., Hadoop Archive, MapFile) all require additional processing and multiple I/O operations to obtain index information before actually accessing the file content, which reduces the efficiency of file access. this paper proposes a novel distributed file storing mechanism called B+ Tree-Based distributed File Storing mechanism (BTDFS), which combines a large number of small files into a merged file, records the index information of the small files in the merged file, and organizes the index information into a B+ tree for storage. Using BTDFS, while reducing the metadata consumption of the NameNode node, improves the access performance of a single small file with additional abilities, which provides convenience for analyzing a large number of small files. Finally, this paper designs corresponding experiments for the proposed BTDFS, and tests and analyzes the memory usage in N ameN ode and the access performance of small files. the experimental results show that the proposed BTDFS can effectively reduce the memory usage of the NameNode, and the efficiency of accessing small files is improved compared with state-of-the-art methods.

关键词： File systems Memory management distributed databases Big Data Metadata Indexing

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