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IEEE INFOCOM 2010

作者： Wang, Yun Li, Kai Wu, Jie School of Computer Science and Engineering Southeast University Key Lab. of Computer Network and Information Integration Nanjing 210096 China Department of Computer and Information Sciences Temple University Philadelphia PA 119122 United States

ISBN: (纸本)9781424458363

Distance estimation is fundamental for many functionalities of wireless sensor networks and has been studied intensively in recent years. A critical challenge in distance estimation is handling anisotropic problems in sensor networks. Compared with isotropic networks, anisotropic networks are more intractable in that their properties vary according to the directions of measurement. Anisotropic properties result from various factors, such as geographic shapes, irregular radio patterns, node densities, and impacts from obstacles. In this paper, we study the problem of measuring irregularity of sensor networks and evaluating its impact on distance estimation. In particular, we establish a new metric to measure irregularity along a path in sensor networks, and identify turning nodes where a considered path is inflected. Furthermore, we develop an approach to construct a virtual ruler for distance estimation between any pair of sensor nodes. The construction of a virtual ruler is carried out according to distance measurements among beacon nodes. However, it does not require beacon nodes to be deployed uniformly throughout sensor networks. Compared with existing methods, our approach neither assumes global knowledge of boundary recognition nor relies on uniform distribution of beacon nodes. Therefore, this approach is robust and applicable in practical environments. Simulation results show that our approach outperforms some previous methods, such as DV-Distance and PDM. ©2010 IEEE.

关键词： Anisotropy

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A Meta Meeting Mountain based opportunistic message forwarding strategy

A Meta Meeting Mountain based opportunistic message forwardi...

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作者： Tu, Jinbin Wang, Yun Liu, Yichuan Li, Qing School of Computer Science and Engineering Southeast University Nanjing China Key Lab of Computer Network and Information Integration MOE Nanjing China

The opportunistic network is a type of ad hoc network that relies on the chance encounters between nodes to transmit messages. It also uses store-and-carry-forward techniques for data transfer between nodes. Developing effective message forwarding strategies based on opportunistic network characteristics and node behavior poses a significant challenge. In this paper, we delve into the mobility and social characteristics of nodes using historical encounter information. Furthermore, we calculate the migration degree and community relations to build the Meta Meeting Mountain, which representing node encounter characteristics. Moreover, we introduce the concept of Forwarding Degree to measure the nodes’ ability to deliver messages, enhancing the predictability of message delivery. Furthermore, a new forwarding strategy is proposed, which is equipped with Meta Meeting Mountain and Forwarding degree to improve the delivery rate. Our experimental scenarios include Infocom06, Rome taxi, and Helsinki. Therefore, the impact of buffer size and TTL is discussed in detail regarding the different opportunistic routing algorithms. Finally, extensive experimental results show that the proposed algorithm outperforms UBPR, MaxProp, PRoPHET, Spray And Wait and RAPAR in terms of delivery rate in the above scenarios by 127.905%, 93.7525%, 138.6888%, 175.3663%, and 281.4625%, respectively, while keeping the hopcount value less than 5. © 2023 Elsevier B.V.

关键词： Data transfer

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Funny words detection via Contrastive Representations and Pre-trained Language Model 2

Funny words detection via Contrastive Representations and Pr...

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2nd International Seminar on Artificial Intelligence, networking and information Technology, AINIT 2021

作者： Du, Yiming Tian, Zelin Key Lab of Computer Network and Information Integration Nanjing China University of British Columbia Dept. Computer Science Vancouver Canada

ISBN: (纸本)9781665412964

Funniness detection of news headlines is a challenging task in computational linguistics. However, most existing works on funniness detection mainly tackle the scenario by simply judging whether a sentence is humorous, whose result is unstable due to factors such as sentence length. To solve this issue, in this paper, our idea is to fine-grained mine the detailed information of the words and the contextual relationship between different words in the sentence, which help to evaluate the correlation between keywords and the funniness of news headlines quantitatively. Specifically, we propose a funny words detection algorithm based on the contrastive representations learning and BERT model. To quantify the impact of different words on the degree of humor, we first subtract the funniness grades of the original news headlines and the funniness grades of the original news headlines with a single word replaced. Both funniness grades are predicted with a pre-trained model, which is supervised by a a threshold to limit the amount of data and ensure the validity of data. To ensure the accuracy of our prediction, we further introduce the contrastive learning to constrain the differences of news headlines before and after word replacement. Finally, according to the Root Mean Square Error (RMSE) matrix in our experiment, we develop a BERT model with mixed sequence embedding to generate a table about words and their corresponding funniness improvement about the news headlines. © 2021 IEEE.

关键词： Mean square error

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D-TDMA: An approach of dynamic TDMA scheduling for target tracking in wireless sensor networks

D-TDMA: An approach of dynamic TDMA scheduling for target tr...

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2010 IEEE/ACM International Conference on Green Computing and Communications, GreenCom 2010, 2010 IEEE/ACM International Conference on Cyber, Physical and Social Computing, CPSCom 2010

作者： Wang, Yun Shi, Peizhong Li, Kai Chen, Zhikui Department of Computer Science and Engineering Southeast University Key Lab. of Computer Network and Information Integration Nanjing 210096 China School of Software Technology Dalian University of Technology Dalian 116024 China

ISBN: (纸本)9780769543314

In the application of target tracking based on dynamic convey tree-based collab.ration (DCTC) in wireless sensor networks, collisions and interferences among nodes pose a challenge for data aggregation. In this paper, we refine slot allocation to the nodes in dynamic convey tree and design an energy efficient MAC protocol called D-TDMA, which avoids collisions and interferences and allocates contiguous active slots to nodes as far as possible during data aggregation from leaf nodes to a root node. As a result, the energy consumption in switching from sleeping to active state is saved. Simulation results show that D-TDMA not only gets rid of the impact of collisions and interferences among nodes in dynamic convey tree, but also performs similar throughput to that of CSMA-like mechanism where nodes work without active/sleep scheduling strategy. Our protocol outperforms ESR in both energy efficiency and low delay. © 2010 IEEE.

关键词： Time division multiple access

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A link analysis for passive UHF RFID system in LOS indoor environment

A link analysis for passive UHF RFID system in LOS indoor en...

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2008 International Conference on Wireless Communications, networking and Mobile Computing, WiCOM 2008

作者： Hong, Gang Wang Chang, Xing Petitioner Chang, Hua Zhu Ministry of Education Key Lab. Computer Network and Information Security Xidian University Xi'an China

ISBN: (纸本)9781424421084

A link analysis model for passive UHF RFID system in LOS indoor environment is developed and demonstrated. Using this model, the power received by tag and the read performance are investigated. The multipath fading and RMS delay spread for UHF RFID system are analyzed by a 5-ray model with different polarization, e.g., horizontal polarization, vertical polarization, and circular polarization. A practical test is developed on an indoor balcony of an office building. In addition, the electric field environment is simulated using the tool of Ansoft HFSS for the analysis of multipath degradation. The results of theoretical analysis, simulation and test are almost conformable, and the small scale fading and the field nulls are observed. Multipath degradation affects the UHF RFID system so much on read performance, and it is still a key limitation on system performance. More research on anti-multipath interference should be developed, e.g., high gain antenna, high sensitivity tag and reader receiver, and more effective protocols, and so on. © 2008 IEEE.

关键词： Time delay

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Temporally or spatially dispersed joint RFID estimation using snapshots of variable lengths 15

Temporally or spatially dispersed joint RFID estimation usin...

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16th ACM International Symposium on Mobile Ad Hoc networking and Computing, MobiHoc 2015

作者： Xiao, Qingjun Chen, Min Chen, Shigang Zhou, Yian Key Lab of Computer Network and Information Integration Southeast University Ministry of Education China Department of Computer and Information Science and Engineering University of Florida GainesvilleFL United States

ISBN: (纸本)9781450334891

Radio-frequency identification (RFID) technology has been widely used in applications such as inventory control, object tracking, supply chain management. An important research is to estimate the number of tags in a certain area covered by readers. This paper extends the research in both temporal and spatial dimensions to provide much richer information for monitoring the dynamics of distributed RFID systems. More specifically, we are interested in estimating the joint properties of any two snapshots taken at arbitrary locations and arbitrary times in a system. With many practical applications, there is however little prior work on this problem. We propose a joint RFID estimation protocol based on a simple yet versatile snapshot construction. Given the snapshots of any two tag sets, although their sizes may be very different, we design a way to combine their information and more importantly derive formulas to extract the joint properties of the two tag sets from the combined information, with an accuracy that can be arbitrarily set. Through formal analysis, we determine the optimal system parameters that minimize the execution time of taking snapshots, under the constraints of a given accuracy requirement. Our simulation results show that the proposed protocol can reduce the execution time by multifold when comparing with the best alternative approach in the literature. Copyright © 2015 ACM.

关键词： Inventory control

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Person video alignment with human pose registration

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Frontiers of computer Science 2023年第4期17卷 229-231页

作者： Yu ZHANG Zihua WANG Jingyang ZHOU Siya MI School of Computer Science and Engineering and the Key Lab of Computer Network and Information Integration(Ministry of Education)Southeast UniversityNanjing 211189China School of Cyber Science and Engineering Southeast UniversityNanjing 211189China Purple Mountain Laboratories Nanjing 211111China

1 Introduction and main *** alignment,especially human action alignment,is a challenging *** purpose is to develop an algorithm to match the same process so that videos can be *** the progress that has been made in image recognition,it is still a difficult problem for distinguishing from similar frames for alignment without context information.

关键词： alignment video frames

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Hyper-compact virtual estimators for big network data based on register sharing

Hyper-compact virtual estimators for big network data based ...

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ACM SIGMETRICS International Conference on Measurement and Modeling of computer Systems, SIGMETRICS 2015

作者： Xiao, Qingjun Chen, Shigang Chen, Min Ling, Yibei Department of Computer and Information Science and Engineering University of Florida GainesvilleFL United States Key Lab. of Computer Network and Information Integration Southeast University Ministry of Education China Telcordia Technologies and Applied Research Ericsson United States

ISBN: (纸本)9781450334860

Cardinality estimation over big network data consisting of numerous flows is a fundamental problem with many practical applications. Traditionally the research on this problem focused on using a small amount of memory to estimate each flow's cardinality from a large range (up to 109). However, although the memory needed for each flow has been greatly compressed, when there is an extremely large number of flows, the overall memory demand can still be very high, exceeding the availab.lity under some important scenarios, such as implementing online measurement modules in network processors using only on-chip cache memory. In this paper, instead of allocating a separated data structure (called estimator) for each flow, we take a different path by viewing all the flows together as a whole: Each flow is allocated with a virtual estimator, and these virtual estimators share a common memory space. We discover that sharing at the register (multi-bit) level is superior than sharing at the bit level. We propose a framework of virtual estimators that allows us to apply the idea of sharing to an array of cardinality estimation solutions, achieving far better memory efficiency than the best existing work. Our experiment shows that the new solution can work in a tight memory space of less than 1 bit per flow or even one tenth of a bit per flow-a quest that has never been realized before. © Copyright 2015 ACM.

关键词： Cache memory

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Web service selection with quantitative and qualitative user preferences

Web service selection with quantitative and qualitative user...

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2011 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2011

作者： Wang, Hongbing Liu, Weihong Key Lab of Computer Network and Information Integration School of Computer Science and Engineering Southeast University 211189 China School of Computer Science Anhui Unversity of Technology 243002 China

ISBN: (纸本)9780769545134

Most existing approaches of Web service selection with user preferences are either quantitative or qualitative. However, using a qualitative or quantitative approach alone cannot handle all the non-functional properties(NFPs). To solve this problem, we present an approach of service selection with quantitative and qualitative user preferences, where qualitative preferences are modeled as a TCP-net and quantitative preferences are specified by using arbitrary positive numbers. Our approach consists of two steps, that is, qualitative selection based on qualitative preferences and quantitative selection based on quantitative preferences. We prove its effectiveness and verify its efficiency through extensive experiments. © 2011 IEEE.

关键词： Websites

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Logistic boosting regression for lab.l distribution learning?

Logistic boosting regression for label distribution learning...

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2016 IEEE Conference on computer Vision and Pattern Recognition, CVPR 2016

作者： Xing, Chao Geng, Xin Xue, Hui Key Lab of Computer Network and Information Integration Ministry of Education School of Computer Science and Engineering Southeast University Nanjing211189 China

ISBN: (纸本)9781467388511

lab.l Distribution Learning (LDL) is a general learning framework which includes both single lab.l and multi-lab.l learning as its special cases. One of the main assumptions made in traditional LDL algorithms is the derivation of the parametric model as the maximum entropy model. While it is a reasonable assumption without additional information, there is no particular evidence supporting it in the problem of LDL. Alternatively, using a general LDL model family to approximate this parametric model can avoid the potential influence of the specific model. In order to learn this general model family, this paper uses a method called Logistic Boosting Regression (LogitBoost) which can be seen as an additive weighted function regression from the statistical viewpoint. For each step, we can fit individual weighted regression function (base learner) to realize the optimization gradually. The base learners are chosen as weighted regression tree and vector tree, which constitute two algorithms named LDLogitBoost and AOSO-LDLogitBoost in this paper. Experiments on facial expression recognition, crowd opinion prediction on movies and apparent age estimation show that LDLogitBoost and AOSO-LDLogitBoost can achieve better performance than traditional LDL algorithms as well as other LogitBoost algorithms.

关键词： Face recognition

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