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Omnidirectional chargability with directional antennas

Omnidirectional chargability with directional antennas

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International Conference on Network Protocols

作者： Haipeng Dai Xiaoyu Wang Alex X. Liu Fengmin Zhang Yang Zhao Guihai Chen State Key Laboratory for Novel Software Technology Nanjing University Nanjing Jiangsu CHINA Department of Computer Science and Engineering Michigan State University East Lansing MI USA Shanghai key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai CHINA

ISBN: (纸本)9781509032822

Wireless Power Transfer (WPT) has received more and more attentions because of its convenience and reliability. In this paper, we first propose the notion of omnidirectional charging by which an area is omnidirectionally charged if a device with directional antennas at any position in the area with any orientation can be charged by directional chargers with power being no smaller than a given threshold. We present our empirical charging model based on field experimental results using off-the-shelf WPT products. Next, we consider the problem of detecting whether the target area achieves omnidirectional charging given a deterministic deployment of chargers. We develop piecewise constant approximation and area discretization techniques to partition the target area into subareas and approximate powers from chargers as constants. Then we propose the Minimum Coverage Set extraction technique which reduces the continuous search space to a discrete one and thereby allows a fast detection algorithm. Moreover, we consider the problem of determining the probability that the target area achieves omnidirectional charging given a random deployment of chargers. We first replace the target area by grid points on triangular lattices to reduce the search space from infinite to finite, then approximate chargers' power with reasonable relaxation, and derive an upper bound of the omnidirectional charging probability. Finally, we conduct both simulation and field experiments, and the results show that our algorithm outperforms comparison algorithms by at least 120%, and the consistency degree of our theoretical results and field experimental results is larger than 93.6%.

关键词： Wireless sensor networks Wireless communication Directional antennas Adaptation models Joining processes Conferences Protocols

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Practical private shortest path computation based on Oblivious Storage

Practical private shortest path computation based on Oblivio...

引用

International Conference on Data Engineering

作者： Dong Xie Guanru Li Bin Yao Xuan Wei Xiaokui Xiao Yunjun Gao Minyi Guo Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University China School of Computer Engineering Nanyang Technological University Singapore College of Computer Science Zhejiang University China

ISBN: (纸本)9781509020218

As location-based services (LBSs) become popular, location-dependent queries have raised serious privacy concerns since they may disclose sensitive information in query processing. Among typical queries supported by LBSs, shortest path queries may reveal information about not only current locations of the clients, but also their potential destinations and travel plans. Unfortunately, existing methods for private shortest path computation suffer from issues of weak privacy property, low performance or poor scalability. In this paper, we aim at a strong privacy guarantee, where the adversary cannot infer almost any information about the queries, with better performance and scalability. To achieve this goal, we introduce a general system model based on the concept of Oblivious Storage (OS), which can deal with queries requiring strong privacy properties. Furthermore, we propose a new oblivious shuffle algorithm to optimize an existing OS scheme. By making trade-offs between query performance, scalability and privacy properties, we design different schemes for private shortest path computation. Eventually, we comprehensively evaluate our schemes upon real road networks in a practical environment and show their efficiency.

关键词： Privacy Roads Servers Outsourcing Scalability Protocols Computational modeling

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Radiation constrained wireless charger placement

Radiation constrained wireless charger placement

引用

IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Haipeng Dai Yunhuai Liu Alex X. Liu Lingtao Kong Guihai Chen Tian He State Key Laboratory for Novel Software Technology Nanjing University Nanjing Jiangsu CHINA Third Research Institute of Ministry of Public Security Shanghai CHINA Shanghai key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai China Computer Science and Engineering University of Minnesota Minneapolis MN USA Department of Automation Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781467399548

Wireless Power Transfer has become a commercially viable technology to charge devices because of the convenience of no power wiring and the reliability of continuous power supply. This paper concerns the fundamental issue of wireless charger placement with electromagnetic radiation (EMR) safety. Although there are a few wireless charging schemes consider EMR safety, none of them addresses the charger placement issue. In this paper, we propose PESA, a wireless charger Placement scheme that guarantees EMR SAfety for every location on the plane. First, we discretize the whole charging area and formulate the problem into the Multidimensional 0/1 Knapsack (MDK) problem. Second, we propose a fast approximation algorithm to the MDK problem. Third, we optimize our scheme to improve speed by double partitioning the area. We prove that the output of our algorithm is better than (1 - ϵ) of the optimal solution to PESA with a smaller EMR threshold (1 - ϵ/2)Rt and a larger EMR coverage radius (1 + ϵ/2)D. We conducted both simulations and field experiments to evaluate the performance of our scheme. Our experimental results show that in terms of charging utility, our algorithm outperforms the prior art by up to 45.7%.

关键词： Safety Wireless communication Wireless sensor networks Approximation algorithms Partitioning algorithms Inductive charging Aggregates

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On Maximizing Reliability of Lifetime Constrained Data Aggregation Tree in Wireless Sensor Networks

On Maximizing Reliability of Lifetime Constrained Data Aggre...

引用

International Conference on Parallel Processing (ICPP)

作者： Mengfan Shan Guihai Chen Fan Wu Xiaobing Wu Xiaofeng Gao Pan Wu Haipeng Dai State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University China

Tree-based routing structures are widely used to gather data in wireless sensor networks. Along with tree structures, in-network aggregation is adopted to reduce transmissions, to save energy and to prolong the network lifetime. Most existing works that focus on the lifetime optimization for data aggregation do not take the link quality into consideration. In this paper, we study the problem of Maximizing Reliability of Lifetime Constrained data aggregation trees (MRLC) in WSNs. Considering the NP-completeness of the MRLC problem, we propose an algorithm, namely Iterative Relaxation Algorithm (IRA), to iteratively relax the optimization program and to find the aggregation tree subject to the lifetime bound with a sub-optimal cost. To adapt to the distributed nature of the WSNs in practice, we further propose a Prufer code based distributed updating protocol. Through extensive simulations, we demonstrate that IRA outperforms the best known related work in term of reliability.

关键词： Wireless sensor networks Reliability Energy consumption Data collection Approximation algorithms Wireless communication Approximation methods

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Comprehensive understanding of operation cost reduction using energy storage for IDCs

Comprehensive understanding of operation cost reduction usin...

引用

IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Haihang Zhou Jianguo Yao Haibing Guan Xue Liu Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai China School of Computer Science McGill University Montreal Canada

To reduce the operation cost incurred by the rapidly growing energy consumption in internet data centers (IDCs), more and more internet service providers have spontaneously started using energy storage in various forms. The approach of energy storage is used to store cheap electricity energy when the electricity price from smart gird is low or the renewable energy is used. There are two typical forms of energy storage equipped in many IDCs, i.e., the battery storage and thermal energy storage. Recent work shows the energy storage can significantly reduce the operation cost for IDCs. However, the cost of the energy storage devices are still at a high level, and it may increase the operation cost for IDCs. In this paper, we investigate the comprehensive understanding on the operation cost reduction for IDCs using the energy storage. To this end, we conduct a quantitative analysis on the normalized electricity price in the two energy storage forms. The experiments demonstrate that the cost of the storage devices and renewable energy supply are largely affected by the storage capacity and the location of data centers, and we conclude that it does not always reduce operation cost using energy storage for IDCs.

关键词： Batteries Optimization Smart grids Discharges (electric) Thermal energy Renewable energy sources

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FDRC: Flow-Driven Rule Caching Optimization in software Defined Networking

FDRC: Flow-Driven Rule Caching Optimization in Software Defi...

引用

IEEE International Conference on Communications

作者： He Li Song Guo Chentao Wu Jie Li School of Computer Science and Engineering The University of Aizu Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science & Engineering Shanghai Jiao Tong University

ISBN: (纸本)9781467364300

With the sharp growth of cloud services and their possible combinations, the scale of data center network traffic has an inevitable explosive increasing in recent years. software defined network (SDN) provides a scalable and flexible structure to simplify network traffic management. It has been shown that Ternary Content Addressable Memory (TCAM) management plays an important role on the performance of SDN. However, previous literatures, in point of view on rule placement strategies, are still insufficient to provide high scalability for processing large flow sets with a limited TCAM size. So caching is a brand new method for TCAM management which can provide better performance than rule placement. In this paper, we propose FDRC, an efficient flow-driven rule caching algorithm to optimize the cache replacement in SDN-based networks. Different from the previous packet-driven caching algorithm, FDRC is characterized by trying to deal with the challenges of limited cache size constraint and unpredictable flows. In particular, we design a caching algorithm with low-complexity to achieve high cache hit ratio by prefetching and special replacement strategy for predictable and unpredictable flows, respectively. By conducting extensive simulations, we demonstrate that our proposed caching algorithm significantly outperforms FIFO and least recently used (LRU) algorithms under various network settings.

关键词： Flexible structures Prefetching Switches Silicon

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Crowdsourcing with Tullock contests: A new perspective

Crowdsourcing with Tullock contests: A new perspective

引用

IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Tie Luo Salil S. Kanhere Hwee-Pink Tan Fan Wu Hongyi Wu Institute for Infocomm Research A STAR Singapore School of Computer Science and Engineering The University of New South Wales Australia Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University China Center for Advanced Computer Studies University of Louisiana at Lafayette USA

Incentive mechanisms for crowdsourcing have been extensively studied under the framework of all-pay auctions. Along a distinct line, this paper proposes to use Tullock contests as an alternative tool to design incentive mechanisms for crowdsourcing. We are inspired by the conduciveness of Tullock contests to attracting user entry (yet not necessarily a higher revenue) in other domains. In this paper, we explore a new dimension in optimal Tullock contest design, by superseding the contest prize - which is fixed in conventional Tullock contests - with a prize function that is dependent on the (unknown) winner's contribution, in order to maximize the crowdsourcer's utility. We show that this approach leads to attractive practical advantages: (a) it is well-suited for rapid prototyping in fully distributed web agents and smartphone apps; (b) it overcomes the disincentive to participate caused by players' antagonism to an increasing number of rivals. Furthermore, we optimize conventional, fixed-prize Tullock contests to construct the most superior benchmark to compare against our mechanism. Through extensive evaluations, we show that our mechanism significantly outperforms the optimal benchmark, by over three folds on the crowdsourcer's utility cum profit and up to nine folds on the players' social welfare.

关键词： Crowdsourcing Benchmark testing Bayes methods Computers Cost accounting Conferences Games

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Supervised hashing with latent factor models 14

Supervised hashing with latent factor models

引用

37th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2014

作者： Zhang, Peichao Zhang, Wei Li, Wu-Jun Guo, Minyi Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University China National Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University China

ISBN: (纸本)9781450322591

Due to its low storage cost and fast query speed, hashing has been widely adopted for approximate nearest neighbor search in large-scale datasets. Traditional hashing methods try to learn the hash codes in an unsupervised way where the metric (Euclidean) structure of the training data is preserved. Very recently, supervised hashing methods, which try to preserve the semantic structure constructed from the semantic labels of the training points, have exhibited higher accuracy than unsupervised methods. In this paper, we propose a novel supervised hashing method, called latent factor hashing (LFH), to learn similarity-preserving binary codes based on latent factor models. An algorithm with convergence guarantee is proposed to learn the parameters of LFH. Furthermore, a linear-time variant with stochastic learning optimization is proposed for training LFH on large-scale datasets. Experimental results on two large datasets with semantic labels show that LFH can achieve superior accuracy than state-of-the-art methods with comparable training time. Copyright 2014 ACM.

关键词： Big data

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Large-scale supervised multimodal hashing with semantic correlation maximization 28

Large-scale supervised multimodal hashing with semantic corr...

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28th AAAI Conference on Artificial Intelligence, AAAI 2014, 26th Innovative Applications of Artificial Intelligence Conference, IAAI 2014 and the 5th Symposium on Educational Advances in Artificial Intelligence, EAAI 2014

作者： Zhang, Dongqing Li, Wu-Jun Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University China National Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University China

ISBN: (纸本)9781577356790

Due to its low storage cost and fast query speed, hashing has been widely adopted for similarity search in multimedia data. In particular, more and more attentions have been payed to multimodal hashing for search in multimedia data with multiple modalities, such as images with tags. Typically, supervised information of semantic labels is also available for the data points in many real applications. Hence, many supervised multimodal hashing (SMH) methods have been proposed to utilize such semantic labels to further improve the search accuracy. However, the training time complexity of most existing SMH methods is too high, which makes them unscalable to large-scale datasets. In this paper, a novel SMH method, called semantic correlation maximization (SCM), is proposed to seamlessly integrate semantic labels into the hashing learning procedure for large-scale data modeling. Experimental results on two real-world datasets show that SCM can significantly outperform the state-of-the-art SMH methods, in terms of both accuracy and scalability. Copyright © 2014, Association for the Advancement of Artificial Intelligence.

关键词： Semantics

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Unique Lock Identification Using scalable Pointer Analysis

Unique Lock Identification Using Scalable Pointer Analysis

引用

2012 International Conference on Applied Informatics and Communication(ICAIC 2012)

作者： Di Zhang Shanghai Key Laboratory of Scalable Computing and Systems School of SoftwareShanghai Jiao Tong University

In this multi-core world,current programs are becoming more and more ***,it is difficult for programmers to write multi-threaded programs without underling *** all kinds of errors,mishandle of lock is very common and hard to *** analysis is a classic approach to verify the correctness of lock usage [1].Imprecision could arise in such analysis without knowing the real execution state of the *** this case,it is not possible for tools to realize different instructions actually manipulate the same *** paper describes a technology for identifying unique lock to assist the static *** alias analysis based approach is very scalable,and can be applied to large server programs.

关键词： Static analysis,Lock analysis,Concurrent program,Pointer analysis,Alias analysis,Llvm

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