Forthcoming articles


International Journal of Wireless and Mobile Computing


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International Journal of Wireless and Mobile Computing (39 papers in press)


Regular Issues


  • Design and FPGA implementation of chaotic interleaver for IDMA system   Order a copy of this article
    by Brahim Boukholda 
    Abstract: The interleaver plays a very important role in a digital communication system. It is often used to improve the performance of forward error correcting codes. On the other side, the interleaver can be used in a multi-user transmission, especially in the interleave division multiple access (IDMA) technique. Indeed, in IDMA systems users are distinguished only by interleavers. Each user is identified by a specific interleaver. This paper proposes a method to generate a chaotic interleaver based on the generation of sequences having chaotic behaviour, using some chaotic maps such as logistic function and Henon map function. The paper studies the performance of chaotic interleavers with correlation analysis for IDMA system. A comparison between the proposed interleavers and others interleavers in terms of FPGA (textit{Field Programmable Gate Array}) resources and maximum operating frequency is presented. Simulations result show that the chaotic interleaver designed is simple to generate and outperforms other interleavers to require least amount of devices and best timing behaviour.
    Keywords: IDMA; multi user detection; chaotic maps; random interleavers; correlation; Memory requirements; FPGA.

  • Expected-mode augmentation method for group targets tracking using the random matrices   Order a copy of this article
    by Yun Wang, Guoping Hu, Hao Zhou 
    Abstract: In order to improve the estimation performance of interactive multiple models (IMM) tracking algorithm for group targets, a new EMA-VSIMM tracking algorithm is proposed in this paper. Firstly, by using the expected-mode augmentation (EMA) method, a more proper expected mode set has been chosen from the basic model set of group targets, which can make the selected tracking models match up to the unknown true mode availably. Secondly, in the filtering process of variable-structure interactive multiple model (VSIMM) approach, the fusion estimation of kinematic state and extension state have been implemented by using classical weighting method and scalar coefficients weighting method, respectively. We use the trace of the corresponding covariance matrix of extension state to calculate the weight coefficient. We calculate the prediction value of the extension state parameter by using a fuzzy reasoning approach to improve the estimation accuracy of the covariance matrix, which takes the elliptical area of extension and its change ratio as the input of the fuzzy controller. The performance of the proposed EMA-VSIMM algorithms is evaluated via simulation of a generic group targets manoeuvring tracking problem.
    Keywords: interactive multiple models; expected-mode augmentation; group targets; maneuvering tracking.

  • An incorporated constrained differential evolution algorithm and its application to parameter identification of machine joint surfaces   Order a copy of this article
    by Qing-Bo Lu, Li-Qin Liu, Xue-Liang Zhang 
    Abstract: In this paper, an incorporated constrained differential evolution algorithm based on Invasive Weed Optimisation (IWCDE) had been proposed. The IWCDE algorithm is based on the standard differential evolution algorithm and incorporates the invasive weed optimisation algorithm. The IWCDE algorithm proposes a new mutation strategy and the strategy of 'infeasible individual evolution'. The proposed algorithm is compared with several other evolutionary algorithms, and the results show that the proposed algorithm could overcome the premature convergence efficiently and has better global convergence and robustness. Finally, the paper establishes the optimisation model of parameter identification on machine joint surfaces, and solves the problem by the IWCDE algorithm.
    Keywords: constrained optimisation; differential evolution algorithm; invasive weed optimisation; infeasible individual evolution.

  • A hybrid algorithm for mining local outliers in categorical data   Order a copy of this article
    by Meiling Liu, Mingxuan Huang, Weidong Tang 
    Abstract: Outlier detection is an important task in data mining, and it has attracted much attention in recent years. Many approaches have been developed to detect outliers. However, most researches focus on global outlier detection. In many situations, the local outlier detection is more valuable than the global outlier detection. In this paper, the existing methods for outlier detection are discussed firstly, and then on the basis of these methods, the definition of local outlier and some formulas are given. Also a hybrid algorithm for mining local outlier is proposed which is based on clustering algorithm and standard deviation in statistics. The clustering algorithm used in this paper is based on the maximal frequent itemsets in association rule mining, and the properties of maximal frequent itemsets are used in clustering. According to maximal frequent itemsets, the objects which have the common frequent itemsets or features are grouped together. By calculating the standard deviation of a cluster with respect to a certain attribute and local outlier factor of an object in the cluster with respect to a certain attribute, we can identify that the clusters with higher standard deviation may have outliers, and the objects with higher local outlier factor can be recognised as outliers. Experimental results on real datasets show that the proposed algorithm is correct and effective for mining local outliers.
    Keywords: local outlier; standard deviation; local outlier factor; clustering; data mining.

  • Exploring factors affecting the adoption of users adoption intention: an integration of information intervention and cognition of internet logistic information platform   Order a copy of this article
    by Liang Xiao, Yeping Pan, Yuwen Xu 
    Abstract: This study develops and empirically tests a user adoption model of internet logistic information platform. From the perspective of information intervention, through a questionnaire of logistics enterprises, the influence mechanisms that different types of information intervention on user adoption intention of internet logistic information platform have been systematically studied. In particular, this study is based on systematic definition and measurement of four independent information intervention variables (i.e., news propaganda, platform training, platform open source, and information input) and three intermediate variables (i.e., strategic value perception, operational value perception and implementation cost perception). The results indicate that the impacts of different types of information intervention on the logistics enterprises in the adoption intention of logistics information platform have significant differences. Furthermore, information input has a much stronger impact than platform training and platform open source; news propaganda has the minimum impact.
    Keywords: information intervention; operational value; strategic value; operational costs; technology adoption.

  • Optimisation and fabrication by 3D printing of a ceiling antenna for communication applications   Order a copy of this article
    by Yuhong Jiang, Sanyou Zeng, Liting Zhang, Xi Li 
    Abstract: This paper presents a new ceiling antenna optimised by applying differential evolution (DE) and fabricated by 3D printing. The frequency band of the antenna ranges from 0.75 GHz to 3 GHz. The geometric structure refers to volcano smoke antenna, which contains a teardrop as the radiating element and a curved ground plane. Curves in the structure are determined by cubic spline interpolation function. The antenna design problem is converted into a constrained optimisation problem (COP), which is solved by DE next. Some optimised antennas are found, and one of them is presented in this paper. The measured result basically meets the antenna requirement, which means the ceiling antenna proposed in this article could work for 2G, 3G and 4G LTE bands and also for WiFi frequency bands theoretically. For this complex-shaped three-dimensional antenna, we choose 3D printing to fabricate. The measured result almost matches the simulation.
    Keywords: ceiling antenna; 3D printing; constrained optimisation problem; differential evolution.

  • Heterogeneous multi-subswarm particle swarm optimisation for numerical and parameter estimation of a permanent magnet synchronous motor   Order a copy of this article
    by Guohan Lin, Qin Wan 
    Abstract: A heterogeneous multi-subswarm coevolution particle swarm optimisation (HMSCPSO) is proposed for numerical optimisation and parameter identification of the permanent magnet synchronous motor. To improve the algorithms dynamic optimal performance, the HMSCPSO consists of one adaptive subswarm and several basis subswarms. During the iteration, the best individual in the basic subswarms and adaptive subswarms are selected as a candidate to construct the elite subswarm. Heterogeneous search was adopted in the basic subswarms and adaptive subswarms. The migration scheme is employed for information exchange among subswarms. The adaptive inertia weight strategy can maintain a balance between exploration and exploitation to ensure the algorithm converges to stable points. To accelerate the convergence rate, an immune clonal selection operator with wavelet mutation is applied to the elite subswarm. The performance of the proposed algorithm is extensively evaluated on a suite of numerical optimisation functions. The results demonstrate good performance of the HMSCPSO in solving numerical problems when compared with other recent variants of PSO. The performance of HMSCPSO is further evaluated by its application to the parameter identification of the PMSM. The experimental results show that the HMSCPSO can simultaneously identify stator resistance, dq axis inductances and the permanent magnet flux accurately.
    Keywords: particle swarm optimisation; coevolution; heterogeneous search; parameter identification; permanent magnet synchronous motor.

  • Handover management with call admission control in integrated femtocell-macrocell network   Order a copy of this article
    by Kranti Bhoite, Sachin Gengaje 
    Abstract: For achieving high data rate and better indoor coverage and to fulfil high capacity demand, a low power-low cost femtocell network is very good option. For successful deployment of femtocells, smooth integration of femtocell network in macrocell network and seamless communication between macrocell and femtocell networks is very important. Conventional handoff algorithms used in macrocell networks need some modifications to satisfy handover management in integrated macrocell-femtocell networks. In this article, we propose a new hybrid handover approach with call admission control policy that takes care of seamless communication between integrated femtocell-macrocell networks, with effective use of femtocells, and avoids unnecessary handovers.
    Keywords: femtocell; macrocell; CAC; handover management; Markov chain.

  • PAPR reduction in OFDM system using hybrid PTS-RCMN scheme   Order a copy of this article
    by Alok Joshi, Sanil Jain, Shivam Saxena 
    Abstract: Orthogonal Frequency Division Multiplexing (OFDM) is a widely used multi-carrier transmission scheme that is used for high data rate applications such as Long Term Evolution (LTE). It offers higher data transmission rate by efficient bandwidth usage. OFDM offers greater resistance and immunity towards intersymbol interference and intercarrier interference. However, the major drawback associated with OFDM is a high Peak to Average Power Ratio (PAPR), which forces the high power amplifier to work in the nonlinear region, resulting in harmonic distortions in the output. Partial transmit sequence (PTS) is a widely employed and tested method for PAPR reduction in 4G systems. In this paper, we propose a novel scheme that uses a combination of PTS and reduced complexity maximum norm method to improve PAPR reduction performance of the PTS system. This scheme has effectively reduced PAPR as compared with the conventional PTS technique with an insignificant increase in computational complexity.
    Keywords: orthogonal frequency division multiplexing; partial transmit sequence; reduced complexity maximum norm; peak to average power ratio.

  • Adapting radio resources in multicarrier cognitive radio using discrete firefly approach   Order a copy of this article
    by Naziha Ali Saoucha, Badr Benmammar 
    Abstract: The user resource allocation has attracted research attention in the context of the Cognitive Radio (CR) paradigm. Aiming at fully exploiting the frequency band unused by the primary users, it enables the secondary users to tune their transmission parameters and communicate within this band with a good Quality of Service (QoS). This paper targets the issue of radio resource adaptation according to the priority and the needs of the active users, the channel state and the availability of the frequency, in multicarrier transmission. The adaptation of such resources has been previously investigated, and Particle Swarm Optimization (PSO) and Cross Entropy (CE) approaches were shown to outperform their counterparts in terms of the convergence rate and the quality of the solution. Motivated by the great promise held by the newly proposed firefly approach, we have adapted its application as a multi-objective approach to optimise the communication quality of secondary users in a multicarrier system. The performance superiority of the proposed approach over PSO and CE techniques is assessed in terms of convergence speed, quality of solution and stability.
    Keywords: cognitive radio; firefly; multicarrier; resource adaptation.

  • Research on visual background extractor to identify the vehicles based on edge similarity   Order a copy of this article
    by Yong Liu, Daopin Xia, Qinjun Qiu, Dawei Cai 
    Abstract: By combining Visual Background extractor with Canny operator, a new approach to identify the vehicles in a complex traffic environment is proposed. Firstly, the foreground object is extracted by the ViBe algorithm and the background difference algorithm, then the 'ghost' is removed by means of edge similarity. Next, the complete moving objects can be obtained by using morphological processing for the foreground object, which can be used to detect vehicles by combining with motion analysis. Experiments showed that the whole region of vehicle objects in complex traffic environments can be extracted exactly and effectively by using this method. In addition, problems due to ghosts and the variation of background can be well handled with low computation complexity, which can fulfil the needs of real-time operation.
    Keywords: vehicle detection; ViBe algorithm; ghost; motion analysis.

  • A signal fading-aware and data transmission estimation assisted handover mechanism in LTE Networks   Order a copy of this article
    by Fu-Min Chang, Hsiu-Lang Wang, Wei-Hong You, Shang-Juh Kao 
    Abstract: In Long-Term Evolution (LTE) networks, the connection between user equipment and base station may be lost when the user equipment moves out of the signal coverage by its service base station, and this results in data loss. This paper proposes a radio signal fading-aware and data transmission estimation assisted handover mechanism in LTE networks in order to decrease the number of unnecessary handovers and data loss rate. Signal fading-aware mechanism is triggered to filter out interfered signal caused by fading in order to obtain the expected signal strength and thereby determine whether handover should be performed. The amount of data loss associated with signal fading is compared with the data loss associated with the handover in order to determine whether the handover procedure should be executed. Thus, if the user equipment performs a handover that is not triggered by signal fading, the handover wait time can be bypassed, whereas in the event of signal fading, handover is performed with the aim of minimising losses in data transmission. Simulation results demonstrate that 30% average handover times and 8% data loss rate are reduced, compared with standard handover schemes.
    Keywords: LTE networks; handover; data sharing; signal fading; data transmission estimation.

  • Medical images segmentation based on improved three-dimensional pulse-coupled neural network   Order a copy of this article
    by Maxin Wang, Xinzheng Xu, Guanying Wang, Shifei Ding, Tongfeng Sun 
    Abstract: Pulse-coupled neural network (PCNN) is the third-generation model of artificial networks, which is based on the construction of the cat visual principle. It has some features, such as sync pulse distribution and the global coupling. When processing the image, it has a unique advantage, and PCNN is widely used in various fields, especially in the aspect of image segmentation, image fusion, and so on. However, the traditional PCNN model has a lot of problems, such as multi-parameters and parameter setting. Moreover, the exponential decay mechanism will sometimes bring certain difficulty for image segmentation, etc. To solve these problems, a simplified and improved 3D-PCNN model is proposed in this paper, through which the whole 3D brain image segmentation is achieved. The experimental results show that the 3D-PCNN algorithm reduced the segmentation time and improved the efficiency of segmentation when compared with the traditional 2D-PCNN model, the traditional 3D-PCNN algorithm and the 3D Otsu algorithm.
    Keywords: pulse-coupled neural network; three-dimensional model; medical image segmentation.

  • Optimum path routing algorithm using ant colony optimisation to solve the travelling salesman problem in wireless networks   Order a copy of this article
    by Ankit Verma, Jay Shankar Prasad 
    Abstract: This paper proposes an enhanced clustering ant colony routing modified algorithm for use in solving standard difficulties of the travelling salesman problem of wireless networks while keeping quality parameters such as optimum time, optimum distance and optimum path designed for comparison with other algorithms. The algorithm works on the field of ant colony optimisation, which is a vast area in swarm intelligence that is widespread for solving complex problems of information technology. The algorithm selects the optimum route by keeping the optimum time and optimum distance as major parameters, and solves the principles of optimum path routing.
    Keywords: optimum path routing; wireless sensor network; mobile computing; travelling salesman problem.

  • Improvement and analysis on the experiment of the third harmonic suppression in the low-voltage distribution power network   Order a copy of this article
    by Liu Jiandong, Xin-quan Zhu, Wei Zhanhong, Wang Yequan, He Yihong 
    Abstract: In order to deal with the problem of the growth of harmonic amount in the low-voltage distribution power network, this paper takes a 315KVA transformer distribution network to design an experimental scheme for retraining the third harmonic amount in the three-phase four-wire system. The scheme can limit the third harmonic under the condition of three-phase four-wire system and measure the impact of the limitation on current, voltage, current distortion rate, active power and distortion power. Experimental results show that limiting the third harmonic current can notably reduce the distortion power of low-voltage distribution power system, thus the electricity quality is improved, but there's no significant power-saving effect.
    Keywords: third harmonic; neutral harmonic filter; harmonic suppression; power saving; power quality.

  • A comparison of different transfer functions for binary version of the Grey Wolf Optimiser   Order a copy of this article
    by Shuqin Wang, Gang Hua, Guosheng Hao, Chunli Xie 
    Abstract: The Grey Wolf Optimizer (GWO) is the recently proposed metaheuristic algorithm inspired by grey wolves. The original version of GWO was proposed to solve problems in continuous search spaces. However, there are many optimisation problems in discrete binary search spaces, such as feature selection and dimensionality reduction. We applied eight transfer functions in our binary GWO and compared their performances. The test functions whose minimum points are obtained at 0 are selected as benchfunctions, but also those functions with minimum values at 1.
    Keywords: Grey Wolf Optimiser; binary optimisation; transfer function.

  • Learning automata based multi-flow opportunistic routing algorithm in wireless mesh networks   Order a copy of this article
    by Debasis Das, Amritesh Kumar 
    Abstract: Multi-hop Wireless Mesh Networks (WMNs) is a promising new technique for communication with routing protocol designs being critical to the effective and efficient use of these WMNs. A common approach for routing traffic in these networks is to select a minimal distance from the source to the destination, as in wireless networks. Opportunistic Routing (OR) makes use of the broadcasting ability of wireless networks and is especially very helpful for WMN because all nodes are static. Our proposed scheme of Multicast Opportunistic Routing (MOR) in WMNs is based on the broadcast transmissions and Learning Automata (LA) to expand the potential candidate nodes that can aid in the process of retransmission of the data. The receivers are required to be in sync with one another in order to avoid duplicated broadcasting of data, which is generally achieved by formulating the forwarding candidates according to some LA-based metric. The most useful aspect of this protocol is that it intelligently learns from past experience and improves its performance. The results obtained via this approach of MOR show that the proposed scheme outperforms existing schemes and is an improved and more effective version of OR in a mesh network.
    Keywords: wireless networks; opportunistic routing; routing metric; candidate selection algorithms; candidate coordination.

  • A fast search strategy to optimise path founding in big data graph computing environments   Order a copy of this article
    by Wentian Qu, Dawei Sun 
    Abstract: In big data graph computing environments, the shortest path problem is very important and widely applied in various scenarios. But sometimes, in order to find the shortest path, there is a lot of cost. So, weighing the various aspects of the problems, its a good choice to find optimal path. In this paper, an improved A-star algorithm is proposed to define the optimal path. A-star algorithm has two kinds of parameter, actual cost and estimated cost, and the second one plays an important part in the algorithm. Based on the traditional A-star algorithm, this paper will propose new parameters and improved heuristic function to enhance the performance of the A-star algorithm. Compared with the traditional A-star algorithm, the simulation experiment shows that the improved A-star algorithm runs in a highly efficient manner. Two factors that affect the best situation are also discussed in the end of this paper.
    Keywords: improved A-star; optimal path; estimated cost; graph computing; big data.

  • Novel authentication mechanism for checking node reliability in web vehicular ad hoc networks   Order a copy of this article
    by M. Milton Joe, B. Rama Krishnan 
    Abstract: Web Vehicular Ad Hoc Networks (WVANET) provide efficient communication performance among the nodes through web technology. This recently introduced WVANET communication model should be enhanced with various security parameters to protect the architecture from security threats. The fundamental security concern in any ad hoc network is authentication. Every vehicle in the WVANET communication architecture should be authenticated for checking the reliability of the nodes efficiently to secure the communication from malicious nodes. In WVANET communication architecture, it is possible for malicious nodes to steal the identity of other nodes to broadcast false information among the nodes in order to collapse the network communication. However, it has been observed that no research on authentication for checking the reliability of the nodes has been carried out in WVANET so far. For the first time, as an initial step, this paper proposes an efficient authentication mechanism to authenticate the nodes WVANET. The proposed authentication mechanism functions with the combination of web-based Road Side Units (RSU) known as WiMAX tower and the authentication centre. The authentication centre assigns the authentication parameter to each node within the network topology and all the vehicles are authenticated in the background at the regular periodic internal time. The assigned authentication parameter would change as the vehicle overtakes another vehicle and the new parameter will be assigned by the authentication centre. All the assigned authentication parameters for each node will be stored in the authentication centre for authenticating the nodes for its trustworthiness. In WVANET, authentication is carried out as three phases, which ensures that the proposed authentication mechanism is secure enough and if a malicious node is found the particular vehicle is temporarily blocked from the communication architecture and such a node is monitored for its further behaviour.
    Keywords: web vehicular ad hoc network; VANET; authentication; security; WiMAX; RSU; OBU.

  • Capacity of dual-branch MRC system over correlated Nakagami-m fading channels with non-identical fading parameters and imbalanced average SNRs   Order a copy of this article
    by Pukhrambam Bijaya Devi, Amujao Yengkhom, Mohammad Irfanul Hasan, Gitanjali Chandwani 
    Abstract: We present the closed-form expressions for the capacity with correlated, non-identical fading parameters and imbalanced average SNRs (signal-to-noise ratio) of dual-branch MRC (Maximal Ratio Combining) diversity system over Nakagami-m fading channels. This capacity is evaluated for ORA (optimum rate adaptation with constant transmit power) and CIFR (channel inversion with fixed rate) schemes. Numerical results have been presented and compared with the available capacity results of ORA and CIFR schemes in the literature. The effect of different practical constraints, e.g. non-identical fading parameters, fade correlation and level of imbalanced in average SNRs, on the channel capacity of the systems is analysed.
    Keywords: channel capacity; channel inversion with fixed rate; dual-branch; imbalanced; maximal ratio combining; optimum rate adaptation with constant transmit power.

  • Group maintenance strategy for stochastic selective maintenance   Order a copy of this article
    by Jianchao Zeng, Jing Zhao 
    Abstract: Selective maintenance is often applied to many industrial environments in which the maintenance actions are performed between sequence missions. When the length of maintenance or work mission time is stochastic and there are multiple maintenance workers with different capacities, previous works that determine maintenance and mission time are unsuitable. Assuming that the time of work mission is random and maintenance time is determined, to maximise system reliability of the next work mission, this paper proposes a stochastic model for a two-state system comprising several series-parallel components with multiple maintenance workers under the maintenance time limit. The optimal maintenance plan is obtained by hybrid intelligent optimisation algorithm. The validity and feasibility of the model are verified by the simulation.
    Keywords: stochastic model; stochastic selective maintenance; mission time; maintenance time; group maintenance.

  • A layer-dividing task cooperation model of multi-robots   Order a copy of this article
    by Wu Chun-ying, Ke Wen-de, Li Xiao-guang 
    Abstract: To tackle the problems of dynamic relative mental layer, learning ability and moving time optimisation in the cooperation of multi-robots, a layer-dividing task cooperation model is proposed. First, the changing features of the mental layer in a dynamic environment is shown through the belief, target, intention and knowledge. Secondly, the strategy learning and task planning under the condition of maximum united rewards is constructed by combining the reinforcement learning and particle swarm optimisation. Thirdly, the robots fast moving method is designed based on the basic movement states and Bezier curve track. The validity of model is proved through experiments.
    Keywords: multi-robots; cooperation; layer division; learning.

  • A dual population based firefly algorithm and its application on wireless sensor network coverage optimization   Order a copy of this article
    by Gan Yu 
    Abstract: Firefly algorithm (FA) has shown good performance on many engineering optimisation problems. Recent studies have pointed out that FA suffers from slow convergence. To enhance the performance of FA, this paper presents a dual population based FA (called DPFA). In DPFA, the entire population consists of two subpopulations. A memetic FA (MFA) and the standard differential evolution are used to generate new solutions in different subpopulations. To verify the performance of DPFA, we test it on nine benchmark functions. Simulation results show that DPFA outperforms MFA and another improved FA algorithms. Finally, we use the proposed DPFA to solve the wireless sensor network coverage optimisation problem. Results show that DPFA can also achieve promising solutions.
    Keywords: firefly algorithm; dual population; wireless sensor network optimisation; global optimisation.

  • An adaptive firefly algorithm for blocking flow shop scheduling problem   Order a copy of this article
    by Wenjun Wang 
    Abstract: In this paper, we present an adaptive firefly algorithm (AFA) for solving the blocking flow shop scheduling problem (BFSSP). It is known that the basic firefly algorithm (FA) works on continuous search space, while the BFSSP is a discrete problem. To handle discrete variables, the smallest position value (SPV) rule is employed. An adaptive parameter strategy is used to reduce the dependence on parameters. Furthermore, two local search operators are used to improve the quality of solutions. To save computational time, a random attraction model is used to decrease the number of attractions among fireflies. Experiments are conducted on a set of Taillard's benchmark instances. Simulation results show that the proposed AFA achieves better solutions than the basic FA and four other algorithms.
    Keywords: firefly algorithm; adaptive parameters; random attraction model; flow shop scheduling problem; discrete optimization.

  • Using GSW FHE to provide stronger privacy protection for searchable encryption   Order a copy of this article
    by Huaiyu Zheng, Baojia Zhang 
    Abstract: Nowadays, more and more people choose to encrypt their data, and then outsource it to the server with increasingly strong awareness of privacy protection. But how to search the encrypted data is a challenging problem in this situation. Many people study this problem, not only for the reason of the fundamental property of this question, but also for a practical issue that the volume of data is so big that it is impractical for users to download the whole data and search on it. One popular solution is to build a inverted index using special algorithm, and support searchable algorithm on the encrypted data. But this causes another problem: the privacy will be leaked to the data owner when the owner and user are not the same person. In this paper, we design a novel scheme to solve this problem. We provide stronger privacy protection for users when they search on the data, the scheme can protect the privacy of inverted index table and content of data. Besides,the data owner cant get any information about the query messages searched by users. Also,we analyse the security of our scheme, and simulation demonstrate the good performance of our scheme.
    Keywords: fully homomorphism encryption,searchable encryption,cloud computing; privacy.

  • An improved memetic differential evolution for college students comprehensive quality evaluation   Order a copy of this article
    by Yuan Wang, Zhenguo Ding, Mingchen Zuo, Lei Peng 
    Abstract: The evaluation for the comprehensive quality of college students is a key problem in the management of college student affairs. In this paper, we present an improved memetic differential evolution algorithm to get the best weights of the College Students Comprehensive Quality Evaluation (CSCQE) problem. The proposed algorithm, called Uniform Memetic Differential Evolution (UMDE), hybridises differential evolution (DE) with a local search (LS) operator and a periodic uniform design re-initialisation scheme to balance the exploration and exploitation. UMDE is compared with five well-known evolutionary algorithms on 21 benchmark functions. The results show that UMDE can obtain better, or at least comparable, results than the compared algorithms. And then, UMDE is used to solve CSCQE problem. The results show that UMDE can find better weights of the index system.
    Keywords: differential evolution; uniform design; local search; comprehensive quality evaluation.

  • Firefly algorithm with dynamic attractiveness model and its application to wireless sensor networks   Order a copy of this article
    by Wang Jing 
    Abstract: Firefly algorithm (FA) is a new population-based meta-heuristic algorithm which has outstanding performance on many optimisation problems. However, in standard FA, the attractiveness will quickly approach to a constant in the middle period of the iterations. It may be very detrimental to the search ability of the algorithm. So we proposed a new variant FA(DFA) with a dynamic attractiveness model, which can linearly adjust the rate of change of attractiveness as the number of iterations grows. Thirteen well-known benchmark functions are used to verify the performance of our proposed method, and the computational results show that DFA is more efficient than many other FA algorithms. We also successfully used DFA to solve the wireless sensor network node distribution optimisation problem. The results of the coverage statistics further validate the effectiveness of the proposed algorithm.
    Keywords: firefly algorithm; meta-heuristic algorithm; global optimization; wireless sensor network; node distribution optimisation.

  • Artificial bee colony with dynamic updating strategy and its application on node localisation   Order a copy of this article
    by Xiaoman He, Yijun Liu 
    Abstract: There are many optimisation problems in the real world. To solve these problems, different intelligent optimisation techniques/algorithms have been developed in the past several years. Among these algorithms, artificial bee colony (ABC) has received much attention. Compared with other similar algorithms, ABC has fewer control parameters. However, ABC shows poor local search ability and slow convergence rate. In this paper, we propose a novel ABC variant, called DyGABC, which employs two strategies including the global best solution guided solution model and a dynamic model for dimension updating. Experiments on 12 optimisation problems show that our DyGABC is better than the standard ABC and another improved ABC algorithm. In addition, DyGABC is used to improve the accuracy performance of node localisation in wireless sensor networks. Simulation results demonstrate that our approach is better than the original distance vector-hop (DV-Hop) algorithm.
    Keywords: artificial bee colony; global best; dynamic updating model; optimisation; continuous optimisation.

  • A sine cosine mutation based differential evolution algorithm for solving node location problem   Order a copy of this article
    by Chong Zhou, Liang Chen, Zhikun Chen, Xiangping Li 
    Abstract: Differential Evolution Algorithm (DE) is known in evolutionary computation. However, DE with DE/best/1 mutation has some drawbacks, such as premature convergence and local optimum. To address these drawbacks, we improve the DE/best/1 mutation operator and propose a sine cosine mutation based differential evolution algorithm, named SCDE. In the proposed method, a new sine cosine mutation operator inspired by sine cosine algorithm (SCA) is adopted to balance exploration and exploitation. In the experimental simulation, the proposed algorithm is compared with three state-of-the-art algorithms on the well-known benchmark test functions. The results of test functions and performance metrics show that the proposed algorithm is able to avoid local optima and converge towards the global optimum. In addition, the proposed algorithm is used to solve sensor node location in wireless sensor network. Results show that our algorithm is effective.
    Keywords: differential evolution algorithm; sine cosine algorithm; sine cosine mutation; local optimum; sensor node location problem.

  • Research on HAS video QoE assessment technology   Order a copy of this article
    by Wen-ming Zhu, Qi Hong 
    Abstract: As internet video applications, especially HTTP Adaptive Streaming (HAS), have gained popularity all around the world, monitoring and assessment technologies of video related quality of experience (QoE) have gained in importance during the last few years. The paper introduces the system architecture and procedures that support HAS video application, and analyses the difference of QoE technologies between traditional streaming video and HAS video. It also reviews the QoE models for current video services, and spots the possible future research directions and challenges, from the points of view of client, network and server, respectively, on how HAS QoE would be built and applied in practical employment.
    Keywords: HAS; QoE; HTTP adaptive streaming media.

  • Reviews and challenges on applying status of the big data technology in the publishing industry   Order a copy of this article
    by Yeli Li, Xindong You, Likun Lu, Chuan Zhu 
    Abstract: The big data era is here, which will make or is making an impact on every walk of our life. The publishing industry is one of the technology intensive industries. The papermaking technology, the printing technology and the internet technology have profoundly impacted it once before. Therefore, the big data technology is making and will make a tremendous impact on the publishing industry, and many publishing industries have applied the big data technology on the different production links during publishing and gain its profit. In this paper, we summarise the current application status of big data technology in the different types of publishing industry in China and abroad (the mass publishing industry, the education publishing industry, the academic speciality publishing industry, news and press publishing industry, new-pattern internet publishing industry). We analyse how they use the big data technology to convert or remake the publishing procedures successfully. We identify the different features of the different publishing industry types, and the different application emphasis on the different links. The possibility of using for references each other is also be discussed. Reviews on the application status of the big data technology will clarify the process to employ the technology on transforming the procedures of the publishing industry, and provide ideas and methods to the publishing industry to use the advantages of the technology.
    Keywords: big data; application status; publishing industry; publishing link; publishing procedure.

  • Firefly algorithm guided by general centre particle and its application in node localisation of wireless sensor networks   Order a copy of this article
    by Li Lv, Hongmin Tian, Jia Zhao, Zhifeng Xie, Tanghuai Fan, Longzhe Han 
    Abstract: Firefly algorithm (FA) is a kind of swarm intelligence algorithm that was developed by simulating the fireflies glowing characteristics. FA shows simple model and high optimisation efficiency and is easily implemented, which now has been widely applied in various optimisation problems. During the evolution process, each firefly would learn from the other fireflies with better performances based on full-attraction model, and thus, FA is strongly targeted and characterised by fast convergence. Nevertheless, only the particles (i.e., the fireflies) with better performances were used, while the particles with poor performances were generally discarded; in particular, the optimal firefly in a population would also be discarded since it showed no information for learning, which would greatly reduce FAs learning and detection abilities. This article proposes an improved FA, namely, firefly algorithm guided by general centre particle (GCPFA), in which the general centre particle (GCP) is generated by sharing each particles historically optimal position information, and each particle would learn from GCP after it learns from the other particles with better performances. Accordingly, after the introduction of GCP, the information sharing and communication among populations are enhanced and the optimisation accuracy is also improved. The simulation results on 12 benchmark test functions also revealed GCPFAa superiority to the other six famous FAs. In order to improve the unreasonable distribution of sensor nodes randomly and improve the network coverage rate, the above algorithm is applied to optimise the coverage of wireless sensor networks and achieve better optimisation effect
    Keywords: firefly algorithm; general cente particle; information sharing; guidance.

  • A hybrid harmony search algorithm for node localisation in wireless sensor networks   Order a copy of this article
    by Zhaolu Guo, Shenwen Wang, Baoyong Yin, Songhua Liu, Xiaosheng Liu 
    Abstract: Harmony search (HS) has been widely used in the field of wireless sensor networks. However, the search strategy of the basic HS has excellent exploration capability but weak exploitation capability. To enhance the search capability of HS, this paper presents a hybrid harmony search algorithm (HBHS) for node localisation in wireless sensor networks. The proposed HBHS employs the best solution to enhance the exploitation capability. Moreover, HBHS uses an adaptive search step-size scheme to further enhance the search capability. To verify the search performance, HBHS is compared with two HS algorithms on a suite of classical benchmark problems. The comparisons confirm that HBHS can achieve better performance than the compared HS algorithms on the most of the benchmark problems. Further, HBHS is applied for node localisation in wireless sensor networks.
    Keywords: wireless sensor networks; localisation; harmony search; hybrid strategy.

  • Distribution route multi-objective optimisation of dangerous goods considering the time reliability   Order a copy of this article
    by Ruichun He, Changxi Ma, Xiaoyan Jia, Qiang Xiao, Lei Qi 
    Abstract: In view of the increasingly prominent security issues of dangerous goods transportation, a distribution route optimisation model of dangerous goods is proposed. Firstly, the travel time reliability model and transportation risk model are established. Besides, the multi-objective optimisation model of dangerous goods route is built based on the travel time reliability. Secondly, a genetic algorithm is designed to solve the optimisation model. Finally, a numerical case is used to verify the feasibility and effectiveness of the model and algorithm. Study results show that the distribution route optimisation model of dangerous goods has an important theoretical value and practical significance of reducing the accident risk, increasing the time reliability, and ensuring dangerous goods transportation safety.
    Keywords: distribution route; optimisation; genetic algorithm; dangerous goods transportation.

  • Rapid identification model of mine water inrush sources based on extreme learning machine   Order a copy of this article
    by Ya Wang, Mengran Zhou, Pengcheng Yan, Feng Hu, Wenhao Lai, Yong Yang, Yanxi Zhang 
    Abstract: In the process of disaster prevention of coal mine water inrush, it is necessary to quickly and accurately identify the types of water inrush sources. Based on the high sensitivity, rapid and accurate monitoring characteristics of laser-induced fluorescence technology, the fluorescence spectra of water samples were collected on the experimental platform of water sample detection. After pre-processing spectra and extracting features, the multi-classification learning model is established by the extreme learning machine (ELM) algorithm. In this paper, we determine the sigmoid function as a hidden layer activation function, and obtain the optimal number of hidden layer nodes by the method of cross-validation. ELM is compared with the conventional neural network classification model in different parts, such as the average time and the average classification accuracy. The average classification accuracy of ELM combined with principal component analysis is about 98% and 93% in the training and testing sets, respectively. The classification learning time is greatly improved. Therefore, the model is more suitable for rapid and accurate classification of water inrush sources.
    Keywords: mine water inrush; water sources identification; laser induced fluorescence spectra; principal component analysis; extreme learning machine.

  • DRSO-EGSM: data replication strategy oriented to automatic energy gear-shifting mechanism   Order a copy of this article
    by Xindong You, Yeli Li, Zhenyang Zhu 
    Abstract: Recently, more and more attention has been paid on research of cloud storage system. However, with the rapid growth of data volume, the problems of high energy consumption and low efficiency have become the key factors for restricting its development. In order to provide better support for the energy gear-shifting mechanism, we designed an energy effective data replicating strategy (DRSO-EGSM). First, data is classified into two categories, based on which the number of replicas is determined. Then the replica placement strategy oriented to energy efficiency is designed. Corresponding performance model and energy consumption model are established for data partitioning strategy. Meanwhile, the energy effectiveness of the DSRO-EGSM is evaluated in GridSim simulator. Compared with current existing similar mechanisms TDCS and the default replication strategy of HDFS, substantive results obtained from simulation experiments show that DSRO-EGSM can have more advantages in reducing energy consumption while guaranteeing the system performance.
    Keywords: data classification; data replication; energy efficiency; cloud storage system; energy management.

  • Quantum flower pollination algorithm for optimal multiple relay selection scheme   Order a copy of this article
    by Hongyuan Gao, Yanan Du, Shibo Zhang 
    Abstract: In order to obtain optimal selection scheme with multiple source-destination pairs and multiple potential relays in cooperative relay networks, an optimal relay selection scheme is designed in cooperative relay networks considering co-channel interference (CCI). It is an integer optimisation problem for selecting suitable relay nodes to obtain optimal system performance. To get the optimal estimation performance with low computing complexity, a quantum flower pollination algorithm (QFPA) is proposed to resolve the difficulties of optimal relay selection, and the proposed optimal relay selection scheme is called as quantum flower pollination algorithm based optimal relay selection (QFPA-ORS). The proposed QFPA combines the advantages of quantum evolutionary theory and flower pollination algorithm (FPA). So QFPA has the capability to search the optimal solution. Simulation results show that QFPA-based relay selection scheme has the ability to search global optimal solution compared with other relay selection schemes based on classical algorithm, and performs better than three other previous intelligent algorithms.
    Keywords: cooperative relay networks; multiple relay selection; quantum flower pollination algorithm; co-channel interference.

  • An enhanced virtual backoff algorithm for wireless sensor networks   Order a copy of this article
    by Ramesh Babu Palamakula, Venkata Krishna Parimala, Naga Raju Dasari, Saritha Vankadara, M. Pounambal 
    Abstract: In wireless sensor networks, the MAC layer plays a crucial role in the performance enhancement. Therefore, this paper develops an enhanced virtual backoff algorithm to route the packets to the queue based on the delay as well as ant colony optimisation algorithm for selecting the best nodes from the available nodes. The node counters are maintained for each node to calculate the success rate, and a sleep schedule is introduced to reduce the energy consumption and to improve the lifetime of the network. The experimental results proved that the proposed model is efficient in preserving the energy, decreasing the node collisions and improving the packet delivery ratio.
    Keywords: bioinspired mechanism; virtual backoff algorithm; node collision and channel allocation.

  • Adaptive fuzzy sliding mode control algorithm simulation for 2-DOF articulated robot   Order a copy of this article
    by Feng Du, Ying Sun, Gongfa Li, Guozhang Jiang, Jianyi Kong, Du Jiang, Zhe Li 
    Abstract: Chattering phenomena occur in conventional sliding mode control algorithm of articulated robots. Therefore a robotic adaptive fuzzy sliding mode control algorithm is proposed, designed with an adaptive single input and output fuzzy system to calculate the control gain. Meanwhile, the mathematical proof is carried out on systems stability and astringency by Lyapunov theorys adaptive law. The adaptive fuzzy sliding mode control is simulated in Simulink, and the simulation results show that when the chattering becomes weaker, the function of the system is promoted. The fuzzy sliding mode controller can be changed and adjusted with the transformation of the systems state. Steady-state convergence is constant, and the adaptive fuzzy sliding mode control algorithm retains good robustness under the conditions that the articulated robots parameters are uncertain and there is external interference.
    Keywords: adaptive fuzzy sliding mode control; articulated robot; chattering phenomena; position tracking.