In modern complex environments, achieving accurate and efficient target localization is essential in numerous fields. However, existing systems often face limitations in both accuracy and the ability to recognize small targets. In this study, we propose a bionic stabilized localization system based on CA-YOLO, designed to enhance both target localization accuracy and small target recognition capabilities. Acting as the ”brain” of the system, the target detection algorithm emulates the visual focusing mechanism of animals by integrating bionic modules into the YOLO backbone network. These modules include the introduction of a small target detection head and the development of a Characteristic Fusion Attention Mechanism (CFAM). Furthermore, drawing inspiration from the human Vestibulo- Ocular Reflex (VOR), a bionic pan-tilt tracking control strategy is developed, which incorporates central positioning, stability optimization, adaptive control coefficient adjustment, and an intelligent recapture function. The experimental results show that CA-YOLO outperforms the original model on standard datasets (COCO and VisDrone), with average accuracy metrics improved by 3.94%and 4.90%, respectively. Further time-sensitive target localization experiments validate the effectiveness and practicality of this bionic stabilized localization system.

Huanhuan Wei, Xiao Luo, Hongyi Yu, Jinping Liang, Luning Yang, Lixing Lin, Alexandra Popa, Xiting Yan. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2025.

ABSTRACT Aiming at the technical challenges of low latency and high reliability in the complex communication environment of the intelligent industrial network, and the trend of the current Internet of Things architecture is increasingly IP‐based, this paper proposes a fast and accurate IP packet forwarding method applied to the routing node, aiming at dealing with the header control packet error problem under high bit error conditions. This method breaks through the limitations of traditional retransmission mechanism and artificially adding redundant information, and only uses the natural redundant characteristics of the protocol itself to realize the correct separation of the session flow in high error environment. The test results on the public data set show that the proposed method can complete the separation of the session stream with a probability of not less than 99% at the bit error rate of by sacrificing part of the complexity, which provides a new idea and technical means for the fault‐tolerant receiving processing of the header five‐tuple field in complex communication environments.

This letter provides a cross-layer perspective for the de-aggregation of aggregated packets. First, we analyze the natural redundancy in protocols that can be leveraged for delimitation. Second, we propose a new path metric, focusing on maximizing the likelihood of all potential redundant protocol fields. Subsequently, a Viterbi-based path search algorithm is developed to achieve the theoretical optimum. When repeated fields are available in the protocol stack, we introduce a decision feedback mechanism to further enhance performance. Tests conducted on aggregated High-Level Data Link Control (HDLC) protocol packets demonstrate that our method can approach the approximate performance upper limit with significantly reduced complexity and improved operability.

Mainstream wireless communication networks mostly adopt the layered protocol encapsulation mechanism, which inevitably introduces natural redundancy into protocols. To fully exploit the abundant natural redundancy in protocols (NRP), this paper provides a novel cross-frame and cross-layer perspective for channel coding and decoding (CCD). First, a generalized CCD architecture is developed for the first time to describe the NRP and artificial redundancy in channel codes (ARC) uniformly. The concept of equivalent code rate is proposed correspondingly to evaluate the potential gain of NRP. Second, we summarize the types of NRP, and for each of them, factor graphs and sum-product algorithms (SPAs) are adopted to model and solve the correlation between it and ARC. On this basis, the joint decoding of multi-class NRP and ARC is further considered, and a general SPA-based joint protocol-channel decoding (JPCD) scheme is presented. Finally, tests on the 802.11n TCP/IP/MAC protocol stack demonstrate that the JPCD scheme can significantly improve the decoding performance of both the packet header and payload with a relatively small computational cost. Our work shows great promise in reducing error retransmission, bandwidth overhead, and the difficulty of source recovery.

Malicious websites are considered one of the top threats to the modern Internet. Thus, it is critical to effectively detect malicious websites for the security of the Internet. Conventional technologies typically rely on URL blacklists, or static and dynamic code analysis, which are known to have limitations. In order to effectively detect malicious websites, in this paper, we study malicious websites from the perspective of system provenance analysis for the first time. We first conduct a systematic feature engineering study on thousands of benign and malicious websites from the perspective of system provenance data. In our study, we discover eight useful features for malicious website detection. Based on these eight features, we propose ProvWeb, a novel non-intrusive system provenance-based tool, for malicious website detection. In our evaluation, ProvWeb can achieve an F1 score of 93.7% ∼ 99.7% for the four combinations of browsers and OSes (Windows Chrome, Windows Firefox, Linux Chrome, Linux Firefox). This result confirms that the features discovered in provenance graphs are effective in detecting malicious websites.

Abstract The current wireless communication system has higher performance demands for receivers. This paper considers exploiting the natural redundancy (NR) that is widely existed in the transmission sources to improve the receiver's performance of sequence detection. The type of NR discussed in this paper is the inherent redundancy in data caused by the correlation between symbols in the memory sources. Since the correlation between transmitted symbols is too challenging to obtain, deep learning (DL) is introduced into sequence detection, which has a powerful ability to extract complex patterns from data. Specifically, intended for a specific memory source that is convenient for performance analysis, namely the Markov source, an iterative sequence detection algorithm based on the long short‐term memory network is proposed. Simulation results demonstrate that the receiver's performance can be improved by exploiting the NR and the proposed DL‐based sequence detection scheme can obtain optimal bit error rate performance with blind state transition probability of the transmitted Markov source.

A high-performance communication receiver desires a sufficient and accurate recognition of transmitted sources. In this paper, we propose a sequential decoding algorithm for the robust reception of sources with natural redundancy (NR) over the AWGN channel. To fully exploit the abundant NR in the exemplified English text sources, a causal language modeling (CLM) with a powerful Transformer decoder neural network (NN) structure is adopted for modeling the joint probability distribution. For versatility of byte-level tokenization, the UTF-8 encoding scheme is considered for the Wikipedia corpus, namely the English edition of the Wiki-40B dataset. The tree search-based M-algorithm (MA) is integrated with CLM, denoted as CLM-MA algorithm, to synthesize the a priori probability of information sequence and likelihood values of polluted symbols. Both simulation experiments and hardware platform evaluations are conducted to analyze the performance of the CLM-MA algorithm. With an adequately large M value, tremendous performance profit is achievable, especially for high-efficiency modulation levels and extremely noisy conditions. This mechanism of adopting the pre-trained NN model merely desires self-supervised learning architecture and eliminates the requirement of high-cost and accurate labels, which paves a new way for communication receiver design.

Abstract Numerous researches on communication receiver design with deep learning algorithms have been implemented effectively recently. In this paper, an innovative scheme is proposed to construct an end‐to‐end neural network (NN) receiver to directly recover information bits from unsynchronized waveform sequences. Considering the correlation between samples, multiple bidirectional long‐short term memory (BiLSTM) layers to process oversampled signals. Then, shifted binary cross‐entropy (SBCE) function is devised to tackle the overfitting issue and eliminate instances with abnormal bit error rate (BER), which originate from standard binary cross‐entropy (BCE) loss function. Substantial simulation results demonstrate that the trained NN receiver can achieve theory BER values under excellent conditions for transceivers. Compared with traditional synchronization algorithms, the proposed method can obtain significant BER performance gain under harsh conditions, such as low oversample rate, small roll‐off factor, short frame length.

In this paper, we design energy-efficient space constellations for multiuser multi-input single-output visible light communication broadcast systems with channel state information (CSI) at the receiver in the three scenarios: 1) with CSI at the transmitter (CSIT); 2) with statistical CSIT; and 3) without CSIT. By utilizing the cooperation of multiuser interference, optimal multidimensional additively uniquely decomposable constellation groups are designed to optimize the received worst case performance metrics of all users subject to two commonly used power constraints, i.e., average and peak optical power constraints. The resulting optimal designs are proved to be pulse amplitude modulated with an optimal beamformer, which can be efficiently attained by numerical search for Scenarios 1 and 2 and be given in a closed form for Scenario 3. One of the common significant advantages of these designs is the fast demodulation of the sum signal from a noisy received signal, since these optimal designs result in an equivalent ideal scalar AWGN channel. Comprehensive computer simulations demonstrate that our designs significantly outperform traditional zero-forcing, minimum mean square error, and time-division methods.

In this paper, we propose an optimized cooperative finite-alphabet relaying strategy for two-way relay visible light communication (VLC) systems, in which the relay node has its own information to be transmitted. In the multiple access (MAC) stage, for fixed transmission bit rate of each user, an optimal power control strategy is developed to manage the non-negative finite-alphabet multiuser interference. Under this strategy, it is proved that the received signal constitutes an equally spaced pulse amplitude modulation constellation, which admits low-complexity maximum likelihood detection. In addition, for given overall transmission bit rate of MAC stage, we derive a closed-form solution for optimal bit loading to further improve the energy-efficiency of MAC stage. In the broadcast stage, owing to the fact that each buffer-aided user node knows the signals transmitted to the relay node in the MAC stage, we design a buffer-aided optimal encoding constellation, which can obtain significant performance gains. Intended for this transmitted constellation, we develop two low-complexity detection algorithms. Both the analytical results and computer simulations demonstrate that our proposed design has substantial performance advantage over the currently available time orthogonal transmission scheme for this application.

In this paper, we investigate the design of energy-efficient space-time modulation for peak-limited MISO broadcast visible light communication (VLC) systems by cooperatively managing the non-negative multiuser interference. We first characterize a constellation-optimal structure that maximizes the worst-case minimum Euclidean distance of all users for a general space-time modulation design. It turns out that the optimal space-time constellation can be constructed via the spatial repetition of the optimal multidimensional constellation in time dimension over ideal additive white Gaussian noise channels. Then, based on this structure, we specifically design two classes of energy-efficient time-dimensional constellations: 1) for the integer overall bit rate, we design the optimal linear precoded block design, which admits fast maximum likelihood demodulation algorithms. 2) for the non-integer case, we propose a nonlinear precoding scheme called block coded modulation, which sums the code word sets of the optimal linear design and a block channel code. In addition, we show that these two classes of designs are addition-unique, thus, generating an energy-efficient mapping from users' data to the transmitted constellations. This property enables the efficient demodulation of the sum signal from a noisy received signal as well as the decoding of individual signal from the estimated sum signal. Extensive computer simulations indicate that our addition-unique designs have remarkable performance gains over the currently available zero-forcing, minimum mean square error and time-division multiple access methods for the multiuser multi-input-single-output VLC broadcast systems.

This paper investigates the artificial noise (AN) aided physical layer security (PLS) for energy-based massive multi-input multi-output multi-access channels with finite-alphabet data inputs, where both the legitimate base station (Bob) and the passive eavesdropper (Eve) are equipped with large antenna arrays and each user has multiple antennas. For such system, the main challenge is how to allocate power between the transmitted constellation of finite size and AN for both interference management and PLS enhancement. To this end, we first characterize a distance-optimal (DO) constellation structure that maximizes the minimum Euclidean distance of the received signals with energy detection. It turns out that the DO multiuser constellations constitute a commonly-used pulse amplitude modulation (PAM) constellation at the receiver side. Then, we specifically design an energy-efficient PAM-constellation alignment to form a received sizeable PAM constellation by adaptively aligning the power of multi-users' PAM sub-constellations. This design provides us with a new finite-alphabet non-orthogonal multi-access scheme as well as with a stepped water filling (SWF) power allocation between the constellation and AN for each user, which can provide the power-domain freedom for PLS. To spatially exploit this freedom, a SWF-based product-constant AN generation algorithm is developed such that the product of Bob's channel and the AN is a constant which can be inferred by Bob, and the channel-noise product for Eve cannot be uniquely determined, even for noise-free channels. Simulations indicate that for SWF, Bob's error rate will vanish when the number of the receiver antennas goes to large, but Eve's error rate has a non-vanishing lower-bound, even with an unlimited number of antennas. In addition, PAMA, as a new finite-alphabet NOMA scheme, has significant advantages in both security and communication error performance over the time division multi-access.

This paper considers low-complexity transmit beamforming schemes for signal-to-interference-plus- noise ratio (SINR) balancing problem in the Gaussian multiple-input single-output multi-receiver wiretap channel (MISO-MRWC). The formulated max-min-fair problem are shown to be non-convex. To overcome the computational complexity, we develop the leakage-based and zero forcing (ZF) based beamforming algorithms for finding the local optimum transmit beamformers. Extensive simulation results illustrate that the proposed beamforming algorithms achieve low computational complexity without serious performance deterioration.

This letter deals with frequency domain equalization (FDE) in the presence of residual timing offsets. A novel iterative decision feedback equalizer for single-carrier FDE systems is proposed. Different from conventional schemes based on explicit point time-delay estimates, the proposed scheme operates directly on the oversampled matched filter output. For each iteration, FDE is performed first, and based on which, joint posterior distribution of the channel and timing parameters is obtained. A set of weights obtained from the corresponding posterior distribution, rather than explicit point time-delay estimate, are utilized for the time-delay compensation, eliminating the need of fine timing synchronization. Simulation results show that the proposed scheme enables evident performance improvement in terms of symbol error rate compared with conventional schemes under relative low sampling rate.

In this paper, we consider a multiple-input-multiple-output optical wireless communication (MIMO-OWC) system in the presence of log-normal fading. In this scenario, a general criterion for the design of full-diversity space code (FDSC) with the maximum likelihood detector is developed. This criterion reveals that in a high signal-to-noise ratio regime, MIMO-OWC offers both large-scale diversity gain, governing the exponential decay of the error curve, and small-scale diversity gain, producing traditional power-law decay. Particularly for a two by two MIMO-OWC system with unipolar pulse amplitude modulation, a closed-form solution to the design problem of a linear FDSC optimizing both diversity gains is attained by taking advantage of the available properties on the successive terms of Farey sequences in number theory as well as by developing new properties on the disjoint intervals formed by the Farey sequence terms to attack the continuous and discrete variables mixed max-min design problem. In fact, this specific design not only proves that a repetition code is the optimal linear FDSC optimizing both the diversity gains but also uncovers a significant difference between MIMO radio frequency communications and MIMO-OWC that space dimension alone is sufficient for a full large-scale diversity achievement. Computer simulations demonstrate that FDSC substantially outperforms uncoded spatial multiplexing with the same total optical power and spectral efficiency, and the latter provides only the small-scale diversity gain.

Multi-Input Multi-Output (MIMO) holds great potential in the high-speed transmission of Visible Light Communication (VLC). However, the inter- channel interference (ICI) in the MIMO-VLC channel is directly related to the geometrical locations of transmitters and receivers, which brings a challenge to the receiver mobility. In this paper, a general design criterion of the channel-adapted space- collaborative constellation (CASCC) is established by making the uncontrollable ICI controllable, whilst considering the channel into our optimization model. Under the prescribed criterion, a regular CASCC is particularly designed for 2 × 2 MIMO-VLC systems in terms of the basic 4-point constellation and the high-order constellation. By developing the properties within our criterion, the computational complexity of the CASCC design is reduced. Furthermore, the performance of CASCC is discussed through extensive theoretical and simulation analysis. The results show that our proposed CASCC obtains higher SER performance gains and more robustness compared with the conventional MIMO-VLC schemes, for a broad range of channels discussed in this paper.

This paper studies the beamforming design for sum secrecy rate (SSR) maximization in the Gaussian multiple-input single-output multi-receiver wiretap channel (MISO-MRWC). The optimization problem of finding the optimal beamforming algorithm is non-convex and intractable to solve using low-complexity methods. Motivated by the thinking of zero-forcing (ZF) and signal-to-leakage-plus-noise ratio (SLNR), we propose three low-complexity beamforming algorithms for finding a local SSR optimum. The simulation results show that the SLNR-based beamforming algorithm outperforms the other two algorithms with ZF preprocessing.

This paper investigates the design of optimal space signaling for an intensity modulated direct detection multi-input-multi-output optical wireless communication system with independent and non-identically log-normal distributed channel coefficients. In order to optimize both large-scale diversity and small-scale diversity gains with a maximum likelihood detector, the design problem is formulated into a max-min optimization problem with continuous-discrete mixed design variables. Two techniques are proposed to solve the problem: 1) by taking advantage of the full large scale diversity condition, all spatial codewords are properly sorted to simplify the inner minimization problem with the discrete design variables; and 2) a novel geometrically weighted inequality is established to carefully deal with a specific objective function of the power products in the outer maximization problem with the continuous variables. Among all the high dimensional nonnegative space signaling vectors, we rigorously prove that the spatial repetition signaling (RS) with an optimal power allocation is optimal under an average optical power constraint. Simulation results indicate that in a high signal to noise ratio regime, our optimally designed space signaling has better error performance than RS, which is the best space signaling available in literature for this application.

Protocol message format extraction is a principal process of automatic network protocol reverse engineering when target protocol specifications are not available. However, binary protocol reverse engineering has been a new challenge in recent years for approaches that traditionally have dealt with text‐based protocols rather than binary protocols. In this study, the authors propose a novel approach called PRE‐Bin that automatically extracts binary‐type fields of binary protocols based on fine‐grained bits. First, a silhouette coefficient is introduced into the hierarchical clustering to confirm the optimal clustering number of binary frames. Second, a modified multiple sequence alignment algorithm, in which the matching process and back‐tracing rules are redesigned, is also proposed to analyse binary field features. Finally, a Bayes decision model is invoked to describe field features and determine bit‐oriented field boundaries. The maximum a posteriori criterion is leveraged to complete an optimal protocol format estimation of binary field boundaries. The authors implemented a prototype system of PRE‐Bin to infer the specification of binary protocols from actual traffic traces. Experimental results indicate that PRE‐Bin effectively extracts binary fields and outperforms the existing algorithms.

In this paper, we consider a multiple-input-multiple-output optical wireless communication (MIMO-OWC) system suffering from log-normal fading. In this scenario, a general criterion for the design of full large-scale diversity space code (FLDSC) with the maximum likelihood (ML) detector is developed. Based on our criterion, FLDSC is attained if and only if all the entries of the space coding matrix are positive. Particularly for 2×2 MIMO-OWC with unipolar pulse amplitude modulation (PAM), a closed-form linear FLDSC satisfying this criterion is attained by smartly taking advantage of some available properties as well as by developing some new interesting properties on Farey sequences in number theory to rigorously attack the continuous and discrete variables mixed max-min problem. In fact, this specific design not only proves that a repetition code (RC) is the best linear FLDSC, but also uncovers a significant difference between MIMO radio frequency (RF) communications and MIMO-OWC that space-only transmission is sufficient for a full diversity achievement. Computer simulations demonstrate that FLDSC substantially outperforms spatial multiplexing with the same total optical power and spectral efficiency and the latter obtains only the small-scale diversity gain.

There are two important factors which impact the performance of phase‐based frequency estimation algorithms remarkably: the approximations of noise phase model and imperfections in phase unwrapping process. Support vector regression (SVR) exits excellent capabilities for learning unknown data and forecasting the future ones, especially under the small sample condition. Therefore, the authors introduce it to predict the variation trend of instantaneous phase and unwrap phases efficiently. Even though with that being the case, errors still exist in phase unwrapping process because of its ambiguous phase characteristic. Furthermore, a SVR‐based frequency estimation algorithm is proposed and makes it immune to these error phases by means of setting the SVR's parameters properly. The results show that, compared with other phased‐based algorithms, not only does the proposed one maintain a wide estimation range and quality capabilities at low frequencies, but also improves accuracy at high frequencies and decreases the impact with the initial phase. The proposed algorithm is fit for not only linear phase signal but also polynomial phase signal, under both the Gaussian and non‐Gaussian condition.

This study re‐examines the spectrum of quantisation noise and studies the quantisation noise within signal band for sinusoid signals and for uniform quantiser. Both the process of sampling and folding which have not been fully taken into account in previous analysis are considered theoretically. The authors’ results show that the quantisation noise within signal band for sinusoid input decreases in broken line as the sampling rate increases, which suggests that a higher signal to in‐band quantisation noise ratio will be obtained if the sinusoid signal is sampled at odd multiple of its fundamental frequency. Moreover, the effects of quantisation step size and the amplitude of sinusoid signal to in‐band quantisation noise are presented by computer simulations.

Wireless multimedia sensor networks (WMSN) emerges as an important category of Wireless Sensor Networks, which retrieves real-time information such as video and audio streams, still images etc. One of the prominent characteristics of WMSN is severe bandwidth limitation which has great impact on design of routing algorithm. In traditional routing protocols, path(s) are selected aiming at providing optimal transmission performance for the current flow while little attention is paid to bandwidth efficiency. This greedy strategy results in the existence of large amounts of bandwidth fragments which can't be fully used so that the networks capability to carry real-time flows is degraded. In this paper, bandwidth efficient Collaborative Quality of service Routing (CQR) is proposed. The defining aspect of CQR is to collaboratively optimize the path selections of multiple flows over the networks. The CQR problem is formulized as linear programming. Resource allocation vector is constructed to decouple the inherently dependent path selections between different flows and sub-gradient based searching algorithm is proposed to get the optimal solution. Simulation results show that CQR achieves higher call admission rate for real-time flow comparing to existed algorithm, under heavy load CQR outperforms traditional algorithms about 40% in call admission rate and has similar transmission cost.

This paper focuses on carrier frequency recovery for BPSK burst transmissions over AWGN channel. Semi-data- aided (SDA) nonlinear frequency estimation algorithms based on maximum-likelihood (ML) principle are derived. According to the algorithms, fewer pilot symbols and some unknown data symbols can be used together for frequency estimation in order that both estimation accuracy and spectral efficiency can be satisfied simultaneously. Simulations are employed to assess the performance of the algorithms. The corresponding Cramer-Rao bounds are discussed. The theoretical analysis of the threshold effect of one estimator is also presented and compared with simulation results.

The estimation of a time-varying fading channel in multiple-input multiple-output (MIMO) wireless systems is a difficult task for the receiver. Its performance can be improved if an appropriate channel estimation filter is used according to the prior knowledge of the fading channel. The authors propose an algorithm which uses the Kalman filter based on Clarke's model to track the MIMO time-varying fading channel by using superimposed periodic training sequences. To reduce the complexity of the high-dimensional Kalman filter for channel estimation of the paths, the authors use a low-dimensional Kalman filter for the estimation of each path. An analytical formula for the estimation error due to the temporal variation of the channel coefficients is given and verified by link level simulations based on synthetic and measured impulse responses. Simulation results show this algorithm is effective for the estimation of the time-varying fading channel in MIMO system when the performance of the channel estimation is presented in terms of the mean-square error (MSE).

In wireless sensor networks, the most significant traffic pattern is data gathering from sensor nodes to sink through multihop paths forming a tree structure. This paper presents an energy-efficient MAC protocol based on routing information, EBRI-MAC, designed for such traffic pattern. In EBRI-MAC, an idea of clustering based on data deliveries on the tree is proposed, in which a parent node and its child nodes form a virtual cluster. Based on this structure, a medium access scheme of chain-invitation combined CSMA/CA and a scheme of active/sleep schedule synchronization within each virtual cluster are designed in order to save energy. Considering the major sources of energy waste, the parameter nEis defined to evaluate the energy efficiency, and the theoretical analysis has been performed. By comparison results through ns-2 simulation, it has been verified that EBRI-MAC can win better energy-efficiency than IEEE802.11 DCF and S-MAC under the traffic pattern of each node being time-correlated.

An energy efficient cooperative density control algorithm, EECDC, is proposed in this paper. EECDC is based on a new sensing model - cooperative sensing model (CSM) other than traditional Boolean sensing model (BSM), and multi-sensors' cooperative exploration is considered in it. According to CSM, serials of nonlinear constrained programming models are developed to find the optimal conditions for full coverage with minimal sensor nodes. A mathematical iterative algorithm is employed to solve the problems. Based on the findings, EECDC selects sensor nodes as close to optimal locations as possible to be the working nodes. Simulations show that EECDC outperforms traditional optimal density control algorithm in term of number of working nodes needed, and achieves almost the same coverage. As a result, it achieves higher energy efficiency and longer network lifetime.

Energy efficient routing is an important measure to promote the energy efficiency of wireless sensor networks (WSN). In this paper, we proposed a minimum energy consumption (MEC) routing algorithm for WSN, GLB-DMECR. This algorithm exploits the utility of sensor nodes’ geographical location information to calculate the ideal MEC route and use the ideal MEC path to guide the routing procedure, thus to find an practical MEC path. Moreover, GLB-DMECR adopts a localized and decentralized routing decision mechanism and has good scalability and stability, which are more suitable for some special characters of WSN such as free of centralized control, nodes’ vulnerability to failure, large network dimension, and etc. The implementation of GLB-DMECR is relatively simple, and it has been verified by simulation that GLB-DMECR outperforms or equivalent to many other present algorithms in MEC performance under wide network circumstance. Therefore, it will have bright future in WSN.

Coverage and energy efficiency are two important concerns in wireless sensor networks. In this paper, a coverage and energy efficient (CEE) task assigning strategy is presented. The basic idea of CEE is to assign tasks according to node’s coverage degree and remaining energy. Based on this idea, grid-based coverage and energy efficient (GCEE) information gathering protocol is designed. GCEE is simulated with NS-2. How the various parameters affect the fraction of the survived nodes and the area energy balancing of the network is shown in simulation results.

Wireless sensor networks (WSNs) are important for a number of strategic applications. Target localization is an important task in WSNs. In this paper, a distributed and cooperative target localization algorithm in wireless distributed sensor network system is presented. Based on the signal energy decay model, the distances between the target and sensors are obtained, and then a distributed and simplified localization algorithm is used to locate the target. Extensive simulation results show that this new approach is accurate and robust. Besides, it can reduce the complexity of the processing. Therefore, it is a feasible and attractive localization method for the wireless sensor network system.

Location theory on networks has been widely investigated by researchers from different fields for more than thirty years due to its significance and practical value. Among various location problems, the p-center and the p-median problems are the most common. The p-facility k-centrum problem, introduced by Slater (1978), is a generalization of the above two problems. The objective is to minimize the sum of the k largest service distances from clients to their nearest servers. When p is an arbitrary integer, the problem is NP-hard on general networks. Therefore, most researchers have devoted to the single-facility case, i.e. p=1, or the case that the networks under consideration are trees. This paper focuses on the single-facility k-centrum problem on a tree. For this problem, Tamir (1996) had an O(nlog/sup 2/ n) time algorithm. In this paper, an O(nlog n) time algorithm with is proposed.