k-Nearest Neighbor Query Processing Algorithms for a Query Region in Road Networks

Recent development of wireless communication technologies and the popularity of smart phones are making location-based services (LBS) popular. However, requesting queries to LBS servers with users’ exact locations may threat the privacy of users. Therefore, there have been many researches on generating a cloaked query region for user privacy protection. Consequently, an effcient query processing algorithm for a query region is required. So, in this paper, we propose k-nearest neighbor query (k-NN) processing algorithms for a query region in road networks. To effciently retrieve k-NN points of interest (POIs), we make use of the Island index. We also propose a method that generates an adaptive Island index to improve the query processing performance and storage usage. Finally, we show by our performance analysis that our k-NN query processing algorithms outperform the existing k-Range Nearest Neighbor (kRNN) algorithm in terms of network expansion cost and query processing time.     

MSDA: multi-subset data aggregation scheme without trusted third party

Data aggregation has been widely researched to address the privacy concern when data is published,meanwhile,data aggregation only obtains the sum or average in an area.In reality,more fine-grained data brings more value for data consumers,such as more accurate management,dynamic price-adjusting in the grid system,etc.In this paper,a multi-subset data aggregation scheme for the smart grid is proposed without a trusted third party,in which the control center collects the number of users in different subsets,and obtains the sum of electricity consumption in each subset,meantime individual user’s data privacy is still preserved.In addition,the dynamic and flexible user management mechanism is guaranteed with the secret key negotiation process among users.The analysis shows MSDA not only protects users’privacy to resist various attacks but also achieves more functionality such as multi-subset aggregation,no reliance on any trusted third party,dynamicity.And performance evaluation demonstrates that MSDA is efficient and practical in terms of communication and computation overhead.     

EMAP: An efficient mutual authentication protocol for passive RFID tags

Radio frequency identification (RFID) system is a contactless automatic identification system, which uses small and low cost RFID tags. The primary problem of current security and privacy preserving schemes is that, in order to identify only one single tag, these schemes require a linear computational complexity on the server side. We propose an efficient mutual authentication protocol for passive RFID tags that provides confidentiality, untraceability, mutual authentication, and efficiency. The proposed protocol shifts the heavy burden of asymmetric encryption and decryption operations on the more powerful server side and only leaves lightweight hash operation on tag side. It is also efficient in terms of time complexity, space complexity, and communication cost, which are very important for practical large-scale RFID applications.     

Optimal Partitioning and Granularity of Uniform Task Graphs

Task partitioning is an important technique in parallel processing.In this paper,we investigate the optimal partitioning strategies and granularities of tasks with communications based on several models of parallel computer systems.Different from the usual approach,we study the optimal partitioning strategies and granularities from the viewpoint of minimizing T as well as minimizing NT^2,where N is the number of processors used and T is the program execution time using N processors.Our results show that the optimal partitioning strategies for all cases discussed in this paper are the same--either to assign all tasks to one processor or to distribute them among the processors as equally as possible depending only on the functions of ratio of running time to communication time R/C.     

Optimal Partitioning and Granularity of Uniform Task Graphs

Task partitioning is an important technique in parallel processing.In this paper,we investigate theoptimal partitioning strategies and granularities of tasks with communications based on several models ofparallel computer systems.Different from the usual approach,we study the optimal partitioning strate-gies and granularities from the viewpoint of minimizing T as well as minimizing NT~2,where N is thenumber of processors used and T is the program execution time using N processors.Our results showthat the optimal partitioning strategies for all cases discussed in this paper are the same——either to as-sign all tasks to one processor or to distribute them among the processors as equally as possible de-pending only on the functions of ratio of running time to communication time R/C.     

A Privacy Taxonomy for the Management of Ubiquitous Environments

Pervasive and ubiquitous environments must handle the detection and management of users, devices and services, while guaranteeing the privacy of both the users and the environment itself. Current techniques for handling privacy found in the literature treating the subject in various ways, while concentrating on the device management, communication protocols, user profiles and environmental access. This paper examines a control model for privacy in pervasive environments from the perspective of the environment. A prototype was devised and tested to validate the generic model of privacy which was also used to compare taxonomic concepts in the literature. Moreover, the prototype was devised and tested to validate the generic model of privacy for control and manage various users, devices and environments and so on. The prototype was based on Percontrol （a system for pervasive user management）, which was only intended to identify users using Wi-Fi, and now it is capable of managing temperature, luminosity and other preferences, measured by a WSN （wireless sensor network） embedded to Percontrol, and the data treatment is done by an ANN （artificial neural network）. Results confirmed the viability of device detection with Wi-Fi, Bluetooth and RFID （radio frequency identification） for an increases slight of the latency in registering new devices on the system.     

A Semi-Random Multiple Decision-Tree Algorithm for Mining Data Streams

Mining with streaming data is a hot topic in data mining. When performing classification on data streams, traditional classification algorithms based on decision trees, such as ID3 and C4.5, have a relatively poor efficiency in both time and space due to the characteristics of streaming data. There are some advantages in time and space when using random decision trees. An incremental algorithm for mining data streams, SRMTDS （Semi-Random Multiple decision Trees for Data Streams）, based on random decision trees is proposed in this paper. SRMTDS uses the inequality of Hoeffding bounds to choose the minimum number of split-examples, a heuristic method to compute the information gain for obtaining the split thresholds of numerical attributes, and a Naive Bayes classifier to estimate the class labels of tree leaves. Our extensive experimental study shows that SRMTDS has an improved performance in time, space, accuracy and the anti-noise capability in comparison with VFDTc, a state-of-the-art decision-tree algorithm for classifying data streams.     

Consensus of high-order dynamic multi-agent systems with switching topology and time-varying delays

This paper studies the consensus problems for a group of agents with switching topology and time-varying communication delays, where the dynamics of agents is modeled as a high-order integrator. A linear distributed consensus protocol is proposed, which only depends on the agent’s own information and its neighbors’ partial information. By introducing a decomposition of the state vector and performing a state space transformation, the closed-loop dynamics of the multi-agent system is converted into two decoupled subsystems. Based on the decoupled subsystems, some sufficient conditions for the convergence to consensus are established, which provide the upper bounds on the admissible communication delays. Also, the explicit expression of the consensus state is derived. Moreover, the results on the consensus seeking of the group of high-order agents have been extended to a network of agents with dynamics modeled as a completely controllable linear time-invariant system. It is proved that the convergence to consensus of this network is equivalent to that of the group of high-order agents. Finally, some numerical examples are given to demonstrate the effectiveness of the main results.     

Joint UAV trajectory and communication design with heterogeneous multi-agent reinforcement learning

Unmanned aerial vehicles(UAVs) are recognized as effective means for delivering emergency communication services when terrestrial infrastructures are unavailable. This paper investigates a multiUAV-assisted communication system, where we jointly optimize UAVs’ trajectories, user association, and ground users(GUs)’ transmit power to maximize a defined fairness-weighted throughput metric. Owing to the dynamic nature of UAVs, this problem has to be solved in real time. However, the problem’s non-co...     

Fuzzy Distance-Based Range Queries over Uncertain Moving Objects

Data obtained from real world are imprecise or uncertain due to the accuracy of positioning devices,updating protocols or characteristics of applications.On the other hand,users sometimes prefer to qualitatively express their requests with vague conditions and different parts of search region are in-equally important in some applications.We address the problem of efficiently processing the fuzzy range queries for uncertain moving objects whose whereabouts in time are not known exactly,for which the basic syntax is find objects always/sometimes near to the query issuer with the qualifying guarantees no less than a given threshold during a given temporal interval.We model the location uncertainty of moving objects on the utilization of probability density functions and describe the indeterminate boundary of query range with fuzzy set.We present the qualifying guarantee evaluation of objects,and propose pruning techniques based on the α-cut of fuzzy set to shrink the search space efficiently.We also design rules to reject non-qualifying objects and validate qualifying objects in order to avoid unnecessary costly numeric integrations in the refinement step.An extensive empirical study has been conducted to demonstrate the efficiency and effectiveness of algorithms under various experimental     

Using confidence interval to summarize the evaluating results of DSM systems

Distributed shared Memory(DSM) systems have gained popular acceptance by combining the scalability and low cost of distributed system with the ease of use of single address space.Many new hardware DSM and software DSM systems have been proposed in recent years.In general,benchmarking is widely used to demonstrate the performance advantages of new systems.Howerver,the common method used to summarize the measured results is the arithmetic mean of ratios,which is incorrect in some cases.Furthermore,many published papers list a lot of data only,and do not summarize them effectively,which confuse users greatly.In fact,many users want to get a single number as conclusion,which is not provided in old summarizing techniques.Therefore,a new data-summarizing technique based on confidence interval is proposed in this paper.The new technique includes two data-summarizing methods:(1) paried confidence interval method;(2) unpaired confidence interval method.With this new technique,it is concluded that at some confidence one system is better than others.Four examples are shown to demonstrate the advantages of this new technique.Furthermore,with the help of confidence level,it is proposed to standardize the benchmaks used for evaluating DSM systems so that a convincing result can be got,In addition,the new summarizing technique fits not only for evaluating DSM systems,but also for evaluating other systems,such as memory system and communication systems.     

Efficient indirect all-to-all personalized communication on rings and 2-D tori

All-to-All personalized communication is a basic communication operation in a parallel computing environment.There are a lot of results appearing in literature.All these communication algorithms can be divided into two kinds:direct communication algorithm and indirect communication algorthm.The optimal dircet all-to-all communication algorithm on rings and 2-D tori does exist.But,for indirect all-to-all communication algorithms,there is a gap between the time complexity of the already existing algorithm and the lower bound,In this paper an efficient indirect algorithm for all-to-all communication on rings and 2-D square tori with bidirection channels is presented.The algorithms is faster than any previous indirect algorithms.The main items of the time complexity of the algorithm is 2^2/8 and p^3/2/8 on rings and 2-D tori respectively,both reaching the theoretical lower bound,where p is the number of processors.     

环形互连并行系统上的任务分配

This paper is about distributed processing of a divisible task in a ring of communicating processors,all works are based on ring topology.Out distribution scheme aims to guarantee minimal finish time of the whole task,which is divided into parts (subtasks)and scheduled to the individual processors.In our model the communication startup time and delay time are both taken into consideration;we also discuss the cases of returning results or not as well as sending data in prallel or not,and returning results through the ring are our focus for discussion.The volume of subtask assigned to each processor is gotten after creating and solving the linear equations.At last the empirical results are presented.     

Resolution and parameters estimations for multiple maneuvering targets

Resolution and parameters estimations for multiple maneuvering targets in the same range cell is addressed in this work. The low-resolution radar cannot distinguish multiple targets in both distance and angle, but the detection of Doppler frequency variation of the multiple maneuvering targets can be used to resolve this problem. At present, most of researches on detection of Doppler frequency variation are carried out with time-frequency analysis methods, such as Fractional Fourier transformation （FRFT）, Adaptive Chirplet transformation （ACT）, and Wigner-Ville distribution （WVD） and so on, which need satisfy enough time duration and sampling theorem. This paper proposes a new method of resolution and parameters estimation for multiple maneuvering targets based on Compressive Sensing （CS） and clustering technique, which samples at low rate and short time duration without sacrificing estimation performance. Simulation results validate the effectiveness of the proposed algorithm, and also show that the performance of the proposed method is superior to that of FRFT in the condition of multiple targets.     

基于FPGA的IEEE802.11协议帧生成器的设计

IEEE 802.11, the most popular standard, defines the protocols which covers all of Ethernet based wireless communication. This paper presented an implementation of IEEE 802.11 Frame Generator, which used FPGA as a hardware platform. This generator constructs the 802.11 frame and supplied it to DSSS as signal to be sent. There are 3 modules in this design. The 1st is the global control module, the 2nd module is CRC- 32 check and the 3rd is used to produce frame serial number. The characteristic of this de- sign is that the signal process and the transmission are made at the same time, i.e. real time processing. That is important to the wireless network device, which has narrower bandwidth and lower process energy. The Verilog HDL codes, block diagram of the whole system, and the simulation results were described in this paper.     

A unified algorithm for mobility load balancing in 3GPP LTE multi-cell networks

3GPP long term evolution (LTE) is a promising candidate for the next-generation wireless network, which is expected to achieve high spectrum efficiency by using advanced physical layer techniques and flat network structures. However, the LTE network still faces the problem of load imbalance as in GSM/WCDMA networks, and this may cause significant deterioration of system performance. To deal with this problem, mobility load balancing (MLB) has been proposed as an important use case in 3GPP self-organizing network (SON), in which the serving cell of a user can be selected to achieve load balancing rather than act as the cell with the maximum received power. Furthermore, the LTE network aims to serve users with different quality-of-service (QoS) requirements, and the network-wide objective function for load balancing is distinct for different kinds of users. Thus, in this paper, a unified algorithm is proposed for MLB in the LTE network. The load balancing problem is first formulated as an optimization problem with the optimizing variables being cell-user connections. Then the complexity and overhead of the optimal solution is analyzed and a practical and distributed algorithm is given. After that, the proposed algorithm is evaluated for users with different kinds of QoS requirements, i.e., guaranteed bit rate (GBR) users with the objective function of load balance index and non-GBR (nGBR) users with the objective function of total utility, respectively. Simulation results show that the proposed algorithm leads to significantly balanced load distribution for GBR users to decrease the new call blocking rate, and for nGBR users to improve the cell-edge throughput at the cost of only slight deterioration of total throughput.     

Formal photograph compression algorithm based on object segmentation

Small storage space for photographs in formal documents is increasingly necessary in today＇s needs for huge amounts of data communication and storage. Traditional compression algorithms do not sufficiently utilize the distinctness of formal photographs. That is, the object is an image of the human head, and the background is in unicolor. Therefore, the compression is of low efficiency and the image after compression is still space-consuming. This paper presents an image compression algorithm based on object segmentation for practical high-efficiency applications. To achieve high coding efficiency, shape-adaptive discrete wavelet transforms are used to transformation arbitrarily shaped objects. The areas of the human head and its background are compressed separately to reduce the coding redundancy of the background. Two methods, lossless image contour coding based on differential chain, and modified set partitioning in hierarchical trees （SPIHT） algorithm of arbitrary shape, are discussed in detail. The results of experiments show that when bit per pixel （bpp）is equal to 0.078, peak signal-to-noise ratio （PSNR） of reconstructed photograph will exceed the standard of SPIHT by nearly 4dB.     

Achieving greater anonymity in network latency

Each lnternet communication leaves trails that can be followed back to the user. Notably, anonymous communication schemes are purposed to hide users＇ identity as to personal, source, destination location and content information. Notably, no network capability is in existence to completely negate anonymity leakage in network latency[~l, thus, the minimization of anonymity leakage in network latency becomes critically salient. The purpose of this paper is to investigate network latency anonymity leaks, and propose practical techniques for their reduction. In this direction, the author investigate the following technical question： What implementation techniques can be configured to truly reduce anonymity leaks using deployable systems and exploiting the popular Tor security strategies.     

On power allocation for a cognitive radio network with hybrid spectrum sharing

In this study we propose a hybrid spectrum sharing scheme based on power control by combining Overlay with Underlay schemes,to improve radio spectrum efficiency.In the scheme,the secondary users dynamically switch their operational states between Overlay and Underlay according to the spectrum occupancy.Thus the dynamics of the primary network is first modeled with a discrete-state Markov process to find the time fraction of secondary users in the Overlay state and that in the Underlay state,which leads to the capacity model of the hybrid spectrum sharing system.Under the criterion of maximizing capacity,the power allocation of the cognitive network is researched and the optimum power allocation for secondary users is deduced.As a result,the maximum achievable capacity of the cognitive network is obtained.Simulations are given to prove the analysis further.Theoretical and simulated results indicate that hybrid spectrum sharing based on power control provides a higher capacity than single Overlay and Underlay systems for the cognitive network,i.e.,hybrid spectrum sharing can further improve radio spectrum efficiency.