Sanglu Lu

Nanjing University, Nan-ching, Jiangsu Sheng, China

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Publications (119)28.24 Total impact

  • 08/2014;
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    ABSTRACT: With the rapid proliferation of RFID-based applications, RFID tags have been deployed into pervasive spaces in increasingly large numbers, e.g., the shelves of super markets are filled with tag-labeled items. Conventional localization schemes usually leverage precise anchor nodes to help compute the position of objects. However, it is usually difficult to find or deploy enough anchor nodes for accurate localization. In this paper, we propose solutions to locate the mobile users based on imprecise anchors in RFID systems. A large number of tags with approximate locations are used as anchor nodes to compute the user's locations. We thus present a time-efficient localization scheme to continuously tracking the mobile users. Experimental results indicate that our solutions can accurately locate the mobile users in a real-time approach. The improved method's accuracy is more than 30% better than the base solution.
    ICC 2014 - 2014 IEEE International Conference on Communications; 06/2014
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    ABSTRACT: Today's public cloud providers typically deploy their small sized data centers in multiple geographically different locations, so as to improve data center power usage effectiveness and locate resources closer to users. A major challenge is resource allocation. Many results have been reported regarding this issue from the perspectives of virtual machine consolidation, network-aware virtual machine placement, traffic engineering, dynamic capacity provisioning, and so on. However, there has not been any focus on stable resource allocations, where no resource request or data center has any migration incentives. To the best of our knowledge, this paper is the first attempt at gaining a better understanding of the structure of the Stable rEsource Allocation (SEA) problem. We introduce a formal problem statement and develop two algorithms for the 1-dimensional (1-D) and 2-D cases, respectively. Simulation results show that the proposed algorithms have good scalability and convergence.
    ICC 2014 - 2014 IEEE International Conference on Communications; 06/2014
  • Lei Xie, Hao Han, Qun Li, Jie Wu, Sanglu Lu
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    ABSTRACT: Collecting histograms over RFID tags is an essential premise for effective aggregate queries and analysis in large-scale RFID-based applications. In this paper we consider efficient collection of histograms from the massive number of RFID tags without the need to read all tag data. We first consider the problem of basic histogram collection and propose an efficient algorithm based on the idea of ensemble sampling. We further consider the problems of advanced histogram collection, respectively, with an iceberg query and a top-k query. Efficient algorithms are proposed to tackle the above problems such that the qualified/unqualified categories can be quickly identified. Experiment results indicate that our ensemble sampling-based solutions can achieve a much better performance than the basic estimation/identification schemes.
    IEEE INFOCOM 2014 - IEEE Conference on Computer Communications; 04/2014
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    ABSTRACT: Network virtualization has emerged as a promising approach to overcome the ossification of the Internet. A major challenge in network virtualization is the so-called virtual network embedding problem, which deals with the efficient embedding of virtual networks with resource constraints into a shared substrate network. A number of heuristics have been proposed to cope with the NP-hardness of this problem; however, all of the existing proposals reserve fixed resources throughout the entire lifetime of a virtual network. In this paper, we re-examine this problem with the position that time-varying resource requirements of virtual networks should be taken into consideration, and we present an opportunistic resource sharing-based mapping framework, ORS, where substrate resources are opportunistically shared among multiple virtual networks. We formulate the time slot assignment as an optimization problem; then, we prove the decision version of the problem to be NP-hard in the strong sense. Observing the resemblance between our problem and the bin packing problem, we adopt the core idea of first-fit and propose two practical solutions: first-fit by collision probability (CFF) and first-fit by expectation of indicators' sum (EFF). Simulation results show that ORS provides a more efficient utilization of substrate resources than two state-of-the-art fixed-resource embedding schemes.
    IEEE Transactions on Parallel and Distributed Systems 01/2014; 25(3):816-827. · 1.80 Impact Factor
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    ABSTRACT: The advances of Radio-Frequency Identification (RFID) technology have significantly enhanced the capability of capturing data from pervasive space. It becomes a great challenge in the information era to effectively understand human behavior, mobility and activity through the perceived RFID data. Focusing on RFID data management, this article provides an overview of current challenges, emerging opportunities and recent progresses in RFID. In particular, this article has described and analyzed the research work on three aspects: algorithm, protocol and performance evaluation. We investigate the research progress in RFID with anti-collision algorithms, authentication and privacy protection protocols, localization and activity sensing, as well as performance tuning in realistic settings. We emphasize the basic principles of RFID data management to understand the state-of-the-art and to address directions of future research in RFID.
    IEEE Communications Surveys &amp Tutorials 01/2014; 16(3):1294-1311. · 4.82 Impact Factor
  • Xi Chen, Lei Xie, Chuyu Wang, Sanglu Lu
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    ABSTRACT: In many pervasive applications like the intelligent bookshelves in libraries, it is essential to accurately locate the items to provide the location-based service, e.g., the average localization error should be smaller than 50 cm and the localization delay should be within several seconds. Conventional indoor-localization schemes cannot provide such accurate localization results. In this paper, we design an adaptive, accurate indoor-localization scheme using passive RFID systems. We propose two adaptive solutions, i.e., the adaptive power stepping and the adaptive calibration, which can adaptively adjust the critical parameters and leverage the feedbacks to improve the localization accuracy. The realistic experiment results indicate that, our adaptive localization scheme can achieve an accuracy of 31 cm within 2.6 seconds on average.
    2013 International Conference on Parallel and Distributed Systems (ICPADS); 12/2013
  • Hao Ji, Lei Xie, Yafeng Yin, Sanglu Lu
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    ABSTRACT: As a supporting technology for most pervasive applications, indoor localization and navigation has attracted extensive attention in recent years. Conventional solutions mainly leverage techniques like WiFi, cellular network etc. to effectively locate the user for indoor localization and navigation. In this paper, we investigate into the problem of indoor navigation by using the RFID-based delay tolerant network. Being different from the previous work, we aim to efficiently locate and navigate to a specified mobile user who is continuously moving within the indoor environment. We respectively propose a framework to schedule the tasks and manage the resources in the network and a navigation algorithm to locate and navigate to the moving target. Experiment results show that our solution can efficiently reduce the average searching time for indoor navigation.
    GLOBECOM 2013 - 2013 IEEE Global Communications Conference; 12/2013
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    ABSTRACT: Network virtualization currently becomes an important technology in optimizing resource management in a datacenter. The major research issue in this area is the virtual network embedding problem (VNEP) concerned with mapping virtual networks (VNs) onto a shared substrate network (SN) with some constrains satisfied. In this paper, by proposing the new concepts of “node sharing” and “partially accepting”, we try to break the “atomicity” of the traditional solutions of VNEP, which usually treat a VN request as an inseparable whole. We consider a more realistic scenario where virtual nodes in a VN request are of different importance and accordingly devise a mapping algorithm called Best Effort Algorithm (BEA). Our algorithm can make the most of the resources through node sharing at idle period of the substrate network and provide the best-effort mapping by partially accepting VN requests when physical resources become scarce. Final simulations demonstrate the effectiveness of our algorithm and show that our novel ideas can lead to higher acceptance ratio and long-term average revenue.
    GLOBECOM 2013 - 2013 IEEE Global Communications Conference; 12/2013
  • Zhen Wang, Zhuzhong Qian, Sanglu Lu
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    ABSTRACT: In a social network, information runs from word-of-mouth based on the relationship of the users. The influence maximization is to find a limited number of initial users (nodes) to spread the information, so that the maximum number of other users could accept the information, which is a useful technique for marketing, information monitoring and advertising in a social network. Diffusion model of social networks imitates the process of information spreading in social networks, and Independent Cascade (IC) Model and Linear Threshold (LT) Model, are well-known stochastic information influence models. In this paper, we extend the classical IC model according to the observation of users' behaviors in social networks and propose an effective influence maximization algorithm based on this extended IC model. This novel algorithm calculates the influence probability of each node in sub-graphs that other nodes can engendered to it iteratively. The simulation experiments on real social network datasets show that our algorithm is much faster than the greedy hill-climbing algorithm, while the results are very close to the greedy algorithm and out-perform the other heuristic algorithms.
    10/2013;
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    ABSTRACT: It is a tedious task to search and locate a specific food from a massive number of foods arbitrarily placed in a fridge. In this paper, we develop iFridge, an intelligent system which allows the user to effectively manage and accurately locate the foods stored inside the fridge. By leveraging the RFID technology, iFridge is able to automatically collect the food information, perceive the user's activities and locate the specified foods. We develop a smart application "cooking recipe recommendation" by sensing the user's daily eating habits. Moreover, by specifying those foods with roughly known locations as anchor nodes, we are able to locate the specified food by using cluster analysis.
    Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication; 09/2013
  • Bin Tang, Baoliu Ye, Sanglu Lu, Song Guo
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    ABSTRACT: In recent years, OFDMA relay networks have become a key component in the 4G standards (e.g., IEEE 802.16j, 3GPP LTE-Advanced) for broadband wireless access. When numerous bidirectional flows pass through the relay stations in an OFDMA relay network that supports various interactive applications, plenty of network coding opportunities arise and can be leveraged to enhance the throughput. In this paper, we study the proportional-fair scheduling problem in the presence of network coding in OFDMA relay networks. Considering the tradeoff between performance and overhead, we propose two models, global approach (GA) and local approach (LA), under which the corresponding problems are shown both NP-hard. For the GA model, we show that it cannot be approximated within some constant factor. Hence, we propose a heuristic algorithm with low time complexity. For the LA model, we propose a theoretical polynomial time approximation scheme (PTAS), and also present a practical greedy algorithm with approximation factor of 1/2. Simulation results show that our algorithms can achieve significant throughput improvement over a state-of-the-art noncoding scheme.
    IEEE Transactions on Parallel and Distributed Systems 09/2013; 24(9):1727-1740. · 1.80 Impact Factor
  • Sheng Zhang, Jie Wu, Sanglu Lu
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    ABSTRACT: This paper poses the following problem: given a task that originates at some node in a Delay Tolerant Network (DTN), how are we to disseminate the workload during pairwise contacts to minimize the makespan? We first investigate the scenario in which each node has access to an oracle that knows global and future knowledge of node mobility, and we propose a centralized polynomial-time optimal algorithm. We then develop a distributed dissemination protocol, D2, which maintains r-hop neighborhood information at individual nodes. D2 makes dissemination decisions based on the estimations of the potential computational capacities and the future workloads of DTN nodes. Using trace-driven simulations, we show that, D2 with only 1-hop information is already near-optimal in a wide variety of environments, and the performance gap becomes smaller as the amount of information maintained at individual nodes increases.
    Proceedings of the fourteenth ACM international symposium on Mobile ad hoc networking and computing; 07/2013
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    ABSTRACT: In this paper, we show the first comprehensive experimental study on mobile RFID reading performance based on a relatively large number of tags. By making a number of observations regarding the tag reading performance, we build a model to depict how various parameters affect the reading performance. Through our model, we have designed very efficient algorithms to maximize the time-efficiency and energy-efficiency by adjusting the reader's power and moving speed. Our experiments show that our algorithms can reduce the total scanning time by 50\% and the total energy consumption by 83\% compared to the prior solutions.
    Proceedings of the fourteenth ACM international symposium on Mobile ad hoc networking and computing; 07/2013
  • Source
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    ABSTRACT: Chunked codes are a variation of random linear network codes with low computational complexities in terms of encoding and decoding, where the input packets are grouped into small (non-overlapped or overlapped) chunks, and random linear coding are performed within each chunk. In this paper, we focus on chunked codes with a constant chunk size. We first highlight the importance of precoding for chunked codes to achieve non-vanishing rates, and then analyze the achievable rates of the non-overlapped chunked (NOC) codes with precoding. We further introduce a new class of chunked codes, called Expander Chunked (EC) codes, which use expander graphs to form (overlapped) chunks, and derive their achievable rates using a tree-based analysis as well as some expander arguments. Numerical results reveal that EC codes perform near-optimally, and achieve significantly higher rates than NOC codes. Also, simulation results show that for finite number of input packets, EC codes incur much lower transmission overhead to recover the whole input packets than other state-of-the-art chunked codes.
    07/2013;
  • 8th IEEE symposium on Computers and Communications (ISCC 2013); 07/2013
  • Source
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    ABSTRACT: Many emerging online stream processing services require the consideration of quality of service (QoS), which is highly dependent on the placement of services at various hosts. This paper investigates the QoS-aware placement problems of stream processing services under different contexts. On condition that the client demands are stable, the QoS-aware placement problem aiming to minimize the cost when servers are CPU-uncapacitated, is equivalent to the set cover problem, and can be solved by a greedy algorithm with approximation factor O(log n), where nis the number of clients. However, when CPU capacity constraints on servers are taken into account, the QoS-aware placement problem cannot be approximated unless P=NP. Therefore, we propose two heuristic algorithms: (1) ISCA (Iterated Set Cover-based Algorithm) and (2) KBA (Knapsack-Based Algorithm). We also consider the placement problem of client demands increasing over time. Two objectives, called extension factor and system lifetime, are proposed for demand increment-blind and increment-aware models respectively. Both of them can be solved by extending ISCA and KBA. The experimental results show that ISCA and KBA have distinct effects on different demand sizes. ISCA is more efficient when client demands are relatively small, while KBA performs better for larger demands. KeywordsStream processing service–Service placement–QoS-aware
    The Journal of Supercomputing 06/2013; · 0.92 Impact Factor
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    ABSTRACT: The past few years have witnessed an explosive popularity of mobile services, especially in the form of smart phone applications. To cope with the limited batteries and computational capacities of mobile devices, prior studies suggest to deploy service instances in clouds for accomplishing most of the computation-intensive tasks. Service composition, which compensates for the simplicity of single service, is an effective way to utilize the plentiful services on the clouds all over the world. In this paper, we focus on the problem of service instance selection with service instance replica limitation constraint. The objective is to select the optimal set of service instances, which composes the integrated service and brings out the optimal QoS (quality of service), in terms of service response time. To characterize the problem, we establish a new QoS model, which considers the comprehensive quality over all users, not just for any single user or service instance. We prove that the problem is NP-hard, since many functionally equivalent service instances spread all over the distributed clouds. To address the problem, we classify the problem into three cases, including two special cases and the general case. We present two effective heuristic algorithms to determine the service instances selection for the two special cases, which are still NP-hard. The two special cases provide empirical bounds for the general case. We propose an algorithm that simulates a vote procedure for the users in the general case. The selected service instances, which come from the vote procedure, can satisfy a majority of users. We conduct extensive simulations for all of the algorithms. The simulation results show that our algorithms work efficiently on service response time reduction.
    International Journal of Information Management 01/2013; · 2.04 Impact Factor
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    ABSTRACT: Energy efficiency is a critical issue for cloud computing as more and more Internet services are deployed in data centers. It is observed that the energy consumption increases significantly as the CPU frequency gets higher. To reduce the total energy, Dynamic Voltage and Frequency Scaling (DVFS) technique is proposed to make the CPUs working at proper frequencies. However, lower frequency will reduce the computing capacity of the servers, which leads to using more servers. It is a challenging problem to make a tradeoff between the number of servers and the frequency of each server for a given workload. In this paper, we prove that the problem of dynamic resource allocation based on DVFS with the target of minimizing energy consumption is NP-Hard. And we propose two algorithms based on different basic ideas to solve this problem. We also compare our algorithms to the well-known First Fit Decreasing (FFD) algorithm, and the simulation results show that we can get 12%-14% power saving on average although we use 1.2x-1.3x number of servers compared to FFD.
    Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), 2013 Seventh International Conference on; 01/2013
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    ABSTRACT: Although the capacity of wireless ad hoc networks has been extensively studied under different mobility models and network settings, few work has been done on the effect of heterogeneous mobile nodes and correlated mobility. In this paper, we consider the heterogeneous wireless networks consisting of two types of nodes, called user nodes and master nodes. Specifically, user nodes are combined into groups and each group is equipped with a more powerful master node serving as relay for packet transmissions among groups. By proposing a simple, asymptotically optimal scheduling and routing scheme, we present the maximum per-node throughput and the end-to-end delay in order sense, respectively. We also explore the trade-offs between capacity and delay by adjusting network settings.
    Wireless Communications and Networking Conference (WCNC), 2013 IEEE; 01/2013

Publication Stats

203 Citations
28.24 Total Impact Points

Institutions

  • 2004–2014
    • Nanjing University
      • • State Key Laboratory for Novel Software Technology
      • • Department of Computer Science & Technology
      Nan-ching, Jiangsu Sheng, China
  • 2010–2011
    • Temple University
      • Department of Computer and Information Science
      Philadelphia, PA, United States
    • College of William and Mary
      • Department of Computer Science
      Williamsburg, VA, United States
  • 2009
    • University of Electronic Science and Technology of China
      • School of Computer Science and Engineering
      Chengdu, Sichuan Sheng, China
  • 2007–2009
    • The University of Aizu
      • School of Computer Science and Engineering
      Fukushima-shi, Fukushima-ken, Japan
    • Nanjing Audit University
      Nan-ching, Jiangsu Sheng, China
  • 2008
    • The University of Hong Kong
      • Department of Computer Science
      Hong Kong, Hong Kong
  • 2000
    • Ecole Nationale Supérieure d'Informatique
      Alger, Alger, Algeria
    • University of Queensland
      Brisbane, Queensland, Australia