International Journal of Wireless and Mobile Computing (43 papers in press)
Expected-mode augmentation method for group targets tracking using the random matrices
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.
Packet Loss Minimizing Approach Based on Traffic Prediction for Multi-streaming Communication over MANET
by Vivekananda GN, Chenna Reddy P
Abstract: Wireless networks are extensively used for communication. Most of the devices that we use for communication are equipped with the wireless network interface and are capable of streaming data efficiently to the device within the communication range. Stream Control Transmission Protocol (SCTP) is designed for multi-streaming service. In this paper, a Packet Loss Minimizing Approach (PLMA-SCTP) based on traffic prediction for multi-streaming application is proposed for the Mobile Ad hoc Networks (MANETs) environment. The objective is to reduce data loss and delay in multi-streaming communication. The PLMA-SCTP method aims to provide an efficient route with optimal overhead and delay. Our simulation studies prove that PLMA-SCTP improves the various performance metrics of multi-streaming applications.
Keywords: Congestion control; MANET; Multi-streaming; SCTP; Traffic-prediction.
Evaluation on multithreaded queue test data for multi-channel filter rod forming machine
by Jianhong Cao, Xu Kong, Qi Ji, Min Zhang
Abstract: This paper takes the real-time problems of cigarette industry multithreaded queue test data for multi-channel filter rod forming machine, under the existing evaluation system has not adapted the premise of the entire inspection business, through the information technology tools to assist in establishing business operational standards, and processes involved in the production and business management, based on dynamic statistics analysis the multi-threaded process for different queues to ensure the output results in real time. This method guarantees the DF10 double pole filter rod forming machine 1000 metres per minute production quality control, real-time visualisation of process quality, and fills the trade gap in this technically area.
Keywords: cigarette equipment; multithread; queue; testing data.
Low financial cost with ant colony optimisation in intelligent agriculture
by Xu Gaofeng
Abstract: With the development of wireless sensor networks, industrial automation and other computer and information related high technologies, a lot of practical IoT applications have greatly increased the productivity. Currently, more and more capital is being invested in IoT, especially intelligent agriculture as many countries begin to pay more attention to basic and intelligent agriculture. For large intelligent agriculture systems, it will cost a lot of time and energy (which further will cost investors' money) for the mobile sink to collect all the data of the sensing system with the help of cluster head node. In this paper, we try to solve this issue that minimizes the data collection path of the mobile sink, with the help of the ant colony optimisation algorithm. We implement the algorithm in Python and conduct two experiments that show that we can get the best path of the given example and show how the efficiency changes when the numbers of ants and loops increase. The better the optimal path becomes, the less financial cost we can achieve.
Keywords: financial cost; wireless sensor network; ant colony optimisation; intelligent agriculture.
An evolutionary model of urban comprehensive service function based on cooperative development
by Bo Wei, Hui Zheng, Gang Chen, Xianliang Zong, Fuying Zhang
Abstract: The level of urban comprehensive service function reflects the state of a city's sustained, coordinated and healthy development. It is the essence of a city's competitiveness. With continuous expansion of a citys scale, finding key driving forces to enhance urban comprehensive service function, and developing its subsystems and elements coordinately have become an important basis for government decision making, especially for making industrial development policies. An urban comprehensive service function mainly includes five subsystems: transportation, financial, trade and business, high-end manufacturing and social environment service. Interactions among these subsystems are generally nonlinear and constrained by external factors. In this study, firstly, theoretical analysis and expert consultation method are used to select state parameters which are representative, available and reliable. Through calculating correlation degree of these parameters by canonical correlation analysis, parameters with higher correlation coefficient are selected as the state parameters of urban comprehensive service function system. Then, by establishing a collaborative development model, we quantitatively describe the nonlinear interaction among the five subsystems, and obtain order parameters-main forces behind coordinated development of urban comprehensive service function. In this study, a northern China city, Tianjin, is selected to illustrate the mathematical model. The calculation results show that the decisive order parameters of urban comprehensive service function for Tianjin are: available tonnage of civil aviation, domestic and foreign currency deposits per capita, scale of social financing, gross import and export value of customs per capita, output value of high-tech industry, number of patent authorisation per capita and annual volume of urban garbage disposal. This result corresponds to the actual development of the city in recent years
Keywords: urban comprehensive service function; collaborative development model; self organisation; order parameter.
Demand estimation of water resources via bat algorithm
by Xiangdong Pei, Youqiang Sun, Yeqing Ren
Abstract: In the process of urban water resources planning, the demand estimation of urban water consumption is one of the important basic contents. In this paper, a hybrid of a linear estimation model and an exponential estimation model is proposed to forecast the water consumption. The bionic intelligent algorithms are widely used in industrial engineering, so we use intelligent algorithms to solve the proposed model including Bat Algorithm (BA) and modified Bat Algorithm (FTBA). FTBA improves the global search capability, and the improvements increase the probability of solving the optimal value. In the simulation experiments, we use the data from Nanchang city during 2003 to 2015. The data from 2003 to 2012 are used to find the optimal weights, and the remaining data (2013-2015) are used to test the model. Simulation results show that the modified BA (FTBA) is superior to the standard algorithm and achieves higher accuracy in prediction.
Keywords: demand estimation; water resource; hybrid model; bat algorithm.
Mobility pattern of individual users in a dynamic mobile phone network using call data record
by Smita Parija, Prasanna Sahu, Sudhansu Singh
Abstract: The pervasiveness of cellular telephones, along with rapid advancement in cellular technology, wireless networks and mobile applications, has made them increasingly effective in our daily lives. Individual human activity with respect to travel behaviour is still in a less explored stage. In the past few decades, travel patterns and human activity have become more complex and exhibit a high degree of variations in space and time. In this study, how and to what extent call data records (CDRs) from mobile phones provide the underlying activities of anonymised customers when a user initiates or receives a voice call or message is investigated in detail. Thus, this paper attempts to discover personal human mobility patterns where location, duration and days are the essential attributes in the interpretation of results. A profile-based paging algorithm is proposed based on the individual human travel pattern. The finding suggests that the proposed algorithm is three times more efficient than conventional paging (blanket paging) and two times more effective than various other intelligent paging algorithms. Further, a substantial saving of about 35% in bandwidth is also obtained from the validation results.
Keywords: mobility management; mobile communication; profile-based paging; call data record; optimisation of resources.
An enhanced gravitational search algorithm for node deployment in wireless sensor networks
by Zhaolu Guo, Jing Peng, Baoyong Yin, Shenwen Wang, Xuezhi Yue, Xiaosheng Liu
Abstract: Node deployment is a fundamental technique in wireless sensor networks, which can be converted into an optimisation issue. Gravitational search algorithm (GSA) is an popular optimisation method, which has exhibited promising performance for node deployment. However, the traditional GSA may show poor convergence when tackling some complicated node deployment issues. To improve the search efficiency, an enhanced GSA (NDGSA) is introduced in this paper for the node deployment issue in wireless sensor networks. NDGSA creates new solutions according to a linear combination of the current solution and the value drawn from Gaussian distribution. In the experiments, NDGSA is compared with the traditional approaches to the node deployment issue. The comparisons validate the efficiency of NDGSA.
Keywords: wireless sensor networks; node deployment; global optimisation; gravitational search algorithm.
Effective beaconing for better throughput in MANET
by Neelagiri Palanisamy, Murali V. Bhaskar
Abstract: The beaconing approach is the key function in geographic routing to disseminate the location. However, the node mobility is a prominent challenge to the beacon-based location broadcasting schemes, resulting in high routing overhead. The conventional methods allow some errors on location prediction. As a result, the mobile nodes update their location when the predicted location exceeds the allowable error range. However, the prediction error is more sensible for boundary nodes than adjacent nodes, as the boundary nodes located in the proximity area act as greedy nodes. Consequently, allowing the static prediction-error for all nodes does not efficiently reduce the overhead while maintaining the neighbour list accuracy. To deal with these issues, this work proposes MObility pattern-free Dynamic and Effective Location update (MODEL) protocol for the maintenance of the trade-off between overhead and precision. The main components considered in the MODEL protocol are beaconing importance and dynamic location prediction-error measurement. The beaconing importance reflects the changes in local topology, and that varies depending on the self and neighbour stability. According to the beaconing importance, the MODEL protocol employs location prediction methodology on neighboring nodes. Instead of allowing the static prediction-error, the Dynamic Acceptance Error Rate (DAR) in the MODEL protocol dynamically calculates the error range to the boundary and adjacent nodes, and enhances the neighbour list accuracy with routing overhead. Owing to the sensitivity of boundary nodes to the location being accurate, the MODEL protocol efficiently exploits the fuzzy algorithm to allow a minimum error in predicting location rather than in adjacent nodes. This work simulates the proposed MODEL protocol in NS2 simulator and compares the performance of the existing Load Balanced-Dynamic Beaconing Greedy Perimeter Stateless Routing (LB-DB-GPSR). The simulation results show a better performance of the proposed MODEL protocol in terms of overhead, neighbour list accuracy, and throughput.
Keywords: MANET; location update; geographic routing; node stability; beaconing importance; prediction-error; fuzzy algorithm.
A prediction model for piggery ammonia concentration based on least squares support vector regression using fruit fly optimisation algorithm
by Chong Chen, Liu Xingqiao
Abstract: In order to predict the variation trend of ammonia (NH3) concentration accurately in a piggery and reduce the risk to livestock breeding, a prediction model is established. Because NH3 has a great influence on the health of pigs, a prediction model can provide an effective way for pig industries to determine the environmental control strategy and take effective measures to evaluate the air quality of a piggery. When the predicted value of the NH3 concentration is above the warning value, farmers can start fans in advance to maintain the health of pigs. The proposed NH3 concentration prediction model is based on least squares support vector regression (LSSVR) model with fruit fly optimisation algorithm (FOA) to search the optimal parameters γ and σ of LSSVR. As the performances of LSSVR are greatly affected by the two parameters, three optimisation algorithms, particle swarm optimisation (PSO) algorithm, genetic algorithm (GA) and traditional LSSVR, are used to compare with FOA. The calculated mean absolute percentage errors of the four prediction models are 0.81%, 2.95%, 4.04% and 5.92%, respectively. The prediction model was used in a livestock breeding base in Zhenjiang City, China, and it performed well. The FOA-LSSVR prediction model can serve as an effective strategy applied in multivariable and nonlinear piggery environmental control systems.
Keywords: ammonia concentration; prediction model; LSSVR; FOA; parameter optimisation.
User-based collaborative filtering recommendation method combining with privacy concerns intensity in mobile commerce
by Qibei Lu, Feipeng Guo
Abstract: Existing personalised recommender systems give little consideration to users' privacy concern in mobile commerce. In order to address this issue and some other shortcomings in item recommendations, this paper proposes a novel user-based collaborative filtering recommendation method combined with privacy concerns intensity, and introduces the users six dimensions privacy concerns factors, such as privacy tendency, internal control point, openness, extroversion, agreeableness, and social group influence. The paper puts forward the metric method of privacy concerns intensity with these privacy concerns influence factors, which is used to obtain the similarity preference of users for collective filtering recommendation. Experiments show that this method is more advantageous than other algorithms. More importantly, a combination of subjective privacy concern and objective recommendation technology can reduce the influence of users privacy concerns on their acceptance of mobile personalised service.
Keywords: influence factors of privacy concerns; privacy concerns intensity; online user’s preference; collective filtering; personalised recommendation.
Multi-objective cross-layer approach for 802.11e over MANETs
by Mahadev Gawas
Abstract: The IEEE 802.11e protocol, which provides QoS support to real-time multimedia applications at the MAC layer, has not adequately addressed the issue of handling the data flows through congestion-based mobile ad hoc networks (MANETs), which results in high data loss, link breakage and re-transmissions, causing performance deterioration. The static nature of resource allocation specified in IEEE 802.11e is the main reason for this suboptimal behaviour. In this paper, we propose a multi-objective cross-layer optimisation (MOCLO) between the PHY-MAC-Network layer after conducting a thorough study of 802.11e behaviour over MANETs. First, we implement each of the queues in 802.11e as a priority queue scheduler rather than the classical FIFO queue to prioritise the transmission of the traffic flow. Next, we propose a congestion-aware QoS metric-based disjoint multipath routing scheme to route the priority traffic through the most efficient path. Using the mapping function between the MAC and network layer, the traffic is split into a set of efficient paths based on priority. We extend our cross-layer approach by exploiting the multi-rate link adaptation function to select the appropriate transmission rate on a frame basis, based on the channel state information. The performance of the proposed scheme is thoroughly evaluated through the simulations, which highlight the advantages of our cross-layer mechanism.
Keywords: cross layer; data rate; MANETs; priority scheduling; QoS; routing; 802.11e.
Numerical analysis of effects of tooth anteversion angle on labyrinth sealing characteristics
by Guoda Wang, Shaobin Lu, Guanbing Cheng
Abstract: Numerical analysis on effects of tooth anteversion angles was made on one straight labyrinth sealing performances. Both labyrinth physical and computational models were established by softwares Solidworks and ANSYS CFX. Five labyrinth tooth anteversion angles were considered. Variations of airflow total pressure and velocity were obtained in one labyrinth with different anteversion angles. The mass flow leakage and its discharge coefficients were calculated accordingly. The simulation results indicate that the pressure degradation becomes more important as the tooth anteversion angle increases. The airflow accelerates across the labyrinth tooth and decelerates in the cavities. The tooth number increases oscillations of flow velocity. The bigger tooth anteversion angle affects the airflow process earlier than those in smaller ones. With increases of anteversion angle, the labyrinth mass flow leakage and its discharge coefficient decrease firstly and then decrease. There is an optimal anteversion angle of the labyrinth regardless of the tooth numbers.
Keywords: aero-engine; labyrinth seal; mass flow leakage; discharge coefficient; numerical simulation.
Experimental and numerical analysis on vibration features of typical external pipe in aero-engine
by Guanbing Cheng, Xuan Wang, Guoda Wang
Abstract: The aero-engine pipe vibration phenomenon is still a serious complicated problem in engine structure design and application. In the present paper, an experimental and computational study was implemented on the aviation straight and L-shape pipe vibration characteristics. The pipe vibration shape and natural frequency were obtained by both hammering and finite element methods (FEM). Effects of fluid type, pressure and temperature were examined on pipe vibration characteristic parameters. The results show that the pipe vibrates along transverse and vertical directions. There are slight differences in pipe vibrating natural frequency in both directions. The experimental natural frequency and vibration modes agree well with those obtained in FEM computation. The fluid type, pressure and temperature can change the pipe vibrating amplitude values, but cannot influence the pipe vibration modal characteristics. Varying the fluid pressure and temperature can to some extent change the pipe natural frequencies.
Keywords: aero-engine straight pipe; vibration characteristic parameters; experimental and computational modals.
QoS-aware routing in body-to-body network for emergency medical care: issues and challenges
by Diana Olivia, Ashalatha Nayak, Mamatha Balachandra
Abstract: With the increase in frequencies, intensities, and unpredictability of disasters
worldwide, currently there is a necessity for novel ubiquitous communication systems enabling emergency medical care (EMC) at the disaster site for e-triaging of the victims. To reduce the mortality rate at EMC, the victims have to be treated in the order of their health criticality level, where the high critical victims have to be treated before the non-critical ones. Thus, it is necessary to give importance to the transmission of critical victims' data as opposed to non-critical victims' data over the deployed communication system towards the medical caretaker at the disaster site, so that the caretaker can immediately prioritise the patients and the type of treatment. This necessity the requirement of medical condition aware Quality of Service (QoS) support for the transmission of the heterogeneous type of medical data. This paper proposes the deployment of Body-to-Body network (BBN/B2B) to transmit medical data towards the healthcare professionals at EMC to perform e-triaging and thereby to reduce the mortality rate. Further, the paper focuses on the importance of medical condition aware probabilistic and differentiated flow specific and network specific QoS support at BBN to improve the quality and speediness of the e-triage by analysing design criteria required by the routing protocol for BBN at EMC. The existing QoS aware routing protocols in wireless networks, such as Wireless Body Area Network (WBAN), mobile ad-hoc network (MANET), Wireless Sensor Network (WSN) and Emergency Network (EN), are investigated, along with their merits and demerits with concern to their applicability in BBN at EMC. The study revealed that the existing routing protocols are not suitable and there is a requirement for the novel routing protocol, which focuses on both flow and network specific QoS at the same time. This paper proposes medical data priority and QoS-aware scheduling and routing framework for BBN at EMC. The proposed approach is applicable to the massive scale of applications, such as disaster management, ambient assisted living, mobile health monitoring, military uses, and sports training.
Keywords: emergency medical care; body-to-body network; wireless body area network; routing protocol; quality of service.
Node location algorithm for wireless sensor networks oriented to mountainous terrain
by Zhong Dong Hu, Tao Yi, Zhendong Wang
Abstract: Aiming at the problem of large positioning error in the non-ranging three-dimensional DV-Hop localisation algorithm for wireless sensor networks in mountainous terrain, the NLA-MT localisation algorithm is proposed in this paper. NLA-MT uses the characteristics of the mountain terrain environment effectively. Fitting the topographic surface of the mountain with local plane, the three-dimensional spatial positioning operation can be reduced to the positioning operation of the two-dimensional plane, which improves the positioning accuracy of the node effectively. When compared with the multi-angle simulation experiments, with different communication radii, different anchor nodes and different nodes, NLA-MT performs well in the mountain terrain model, and the accuracy of the non-ranging location algorithm of the wireless sensor network is improved, with the positioning error of about 35% with a high practical value.
Keywords: wireless sensor network; mountain terrain; DV-Hop; positioning algorithm.
An effective computing service provider using virtual cloud in ad-hoc network
by Abhishek Bajpai, Shivangi Nigam
Abstract: Virtual cloud is the next big thing that will aid mobile cloud computing (MCC) to overcome its shortcomings. The problems associated with public cloud include the cost of access, link failure, dependencies on a single facility provider, to name a few. Since the advent of dynamic devices into the picture, resources of these devices can be used as virtual cloud. These can access the cloud for computation on the go with several communication interfaces. In this work, we have tried to reduce response time for any computing services and save energy for dynamic devices. When there is no optimal device in the vicinity of a weak client, it computes by any local dynamic device and afterwards downloads to the client. By transferring the computation part onto a virtual device, battery level is saved in testing applications. The results proved to significantly reduce the response time and thus the energy at high load times of the system.
Keywords: ad-hoc network; virtual cloud; distributed computing; virtual machine.
A comprehensive analytical model of user influence in the social networks
by Bailing Wang, Dongjie Zhu, Junheng Huang, Zhaoqing Chen
Abstract: The user influence analysis is one of the most interesting research topics in the field of social networks (SNS). The traditional methods based on degree centrality only considered the user's local influence. In recent years, the famous web ranking method (PageRank) has been widely studied in the measurement of user influence. It has achieved good results by using the global structure information of social networks. However, there are deficiencies in the contributions among users' influence. Intuitively, users' influence is closely related to the scale, solidarity and the users' status of the community. Based on the PageRank algorithm and the label propagation algorithm, this paper proposes a new comprehensive model of evaluating users' influence. This model takes into account the user's PageRank value, the user's status in the community as well as the size and solidarity of the community, closer to the real situation of social networks. Experimental results show that the new model can evaluate user influence with higher efficiency and is more rational than traditional models.
Keywords: PageRank; label propagation; community; node degree; social networks.
Enhanced interference cancellation techniques for downlink of LTE-A heterogeneous networks
by S. Shibu, V. Saminadan
Abstract: The formation of a Heterogeneous Network (HetNet) into the cellular system improves the overall spectral efficiency and network capacity of the system. In recent times, cellular customers have found the Fourth Generation Long Term Evolution Advanced (LTE-A) fascinating because of the high data rate and the high speed transmission performance. Although the forming of the heterogeneous cellular network increases the complexity and overall interference of the system, the interference between the macro cell and smaller cells such as femto/pico reduces the overall performance of the system in the downlink. Several control channels are used in the downlink of the LTE-A system to support the data traffic and maintain the system functions. In downlink, the Common Reference Signal (CRS) is used at the UE to estimate the channel characteristics and is available during the entire frequency band. The presence of CRS of the neighboring cells creates interference to the users. It is classified into two types, namely colliding CRS and non-colliding CRS. Linear Minimum Mean Square Error (LMMSE) based equaliser is proposed to reduce the effect of the non-colliding CRS at the UE. Enhanced space alternating generalised expectation maximisation-maximum a posteriori probability (ESAGE-MAP) estimator is used at the UE to mitigate colliding CRS interference. The simulation results have proved that the proposed LMMSE and ESAGE-MAP interference cancellation techniques perform better than the existing methods.
Keywords: common reference signal; long term evolution - advanced; heterogeneous network; linear minimum mean square error; enhanced space alternating generalised expectation maximisation.
Metallurgical machinery vibration based on computational modelling analysis
by Zhigang Wang, Lei He, Changming Liu, Han Xiao, Chao Xu
Abstract: Much equipment in metallurgical industry involves mechanical vibration. The subject of mechanical vibration covers a wide range of fields. Mathematical theory and related formulas are abstract and complex. Therefore, as a mechanical student, it is difficult to learn and not feel bored. In view of the above problems, this paper introduces computational modelling into the teaching of mechanical vibration course, and reforms the teaching mode of this course. MATLAB software is used to model the fuzzy and abstract theories and mathematical formulas graphically and abstractly, which can reduce the difficulty of learning and improve the interest of learning. The problems existing in the teaching of mechanical vibration course are analysed, and two examples are modelled by using the theory of mechanical vibration. Finally, the software of MATLAB is used for analysis. Based on the relevant theories, this paper starts from improving students' comprehensive professional quality, and then discusses how to help students to master mechanical vibration and how to use it in practice. Through the teaching reform, the students have solved the vibration problem of metallurgical machinery better, improved their ability, and made great progress in all aspects.
Keywords: metallurgical machinery; mechanical vibration; computational modelling analysis.
Developing an SMS-based mobile application in the food supply chain in Zambia.
by Ariel Henry Phiri, Jackson Phiri, Selvas Mwanza
Abstract: An SMS-based mobile application can be used by cooperatives to link traders and farmers, and reduced the exposure of traders to road traffic accidents, loss of cash, lives and commodities. This will reduce the cost of doing business. A survey was conducted in Lusaka and Livingstone, where 35.25% of the total number of respondents obtained food commodities from outside their locality. The risks were associated with travel, where 30.5% of the respondents lost commodities, and 91.6% travelled with large sums of cash. Further, 50.4% of the respondents use mobile money and 75.25% use mobile phones when trading. A mobile application, called Smart Trader System, was then developed using NetBeans IDE, MySQL database and Java development kit for Windows. This system interacts with the mobile phone for the traders via SMS. It has been implemented and tested. This application will reduce the cost of doing business among the farmers and traders.
Keywords: mobile application; Smart Trader System; traders; farmers; SMS; Zambia.
Surrogate-based adaptive particle swarm optimisation
by Lei Zhang, Jing Jie, Hui Zheng, Xiaoli Wu, Shiqing Dai
Abstract: Aiming at the shortcomings of particle swarm optimisation (PSO) in solving complex problems, such as large computation cost and long computation time, the paper proposes a surrogate-based adaptive particle swarm optimisation (SAPSO). In the algorithm, PSO carries on the optimisation search through a global exploration population and a local exploitation population. At the same time, a global Gaussian process surrogate and a local one are built based on the history search data to evaluate the two populations approximately. Moreover, some adaptive optimisation strategies have been developed, including Latin hyper-cube sampling (LHS) based initial strategy, self-adapting local optimisation, EI sampling based global optimisation and cooperative searching strategy, which can ensure the balance between the global exploration and the local exploitation validly. The experimental results on benchmark problems show that the proposed algorithm not only can decrease the evaluation costs of the functions validly, but also has good convergence and robustness.
Keywords: swarm intelligence; particle swarm optimisation; surrogate; Gaussian process.
A hybrid swarm algorithm and its application in vehicle route guidance system on wireless networks
by Qi Xin, Han Chenghao
Abstract: In this paper, a hybrid optimisation algorithm for the vehicle route guidance system on wireless network is presented. Applying the wireless sensor network technology to intelligent transportation systems has become a research hotspot in recent years. Research on the shortest path algorithms and improving vehicle route guidance system has been the core of the study on the intelligent transport systems. The goal of our approach is to reduce the computing time and get better solutions. By a thorough analysis of several existing optimal routing choice algorithms, we propose an optimal routing choice algorithm based on artificial fish swarm algorithm. Our simulations show that the speed of convergence of the improved algorithm is enhanced greatly compared with other optimal choice algorithms, and the new algorithm obtained a better result. The results show that the improved algorithm can be applied to intelligent transport systems.
Keywords: vehicle route guidance system; swarm intelligence; artificial fish swarm algorithm; transportation.
BER analysis of EGC receiver over correlated Nakagami-m fading channels with phase error and asynchronous CCI
by G. Aruna
Abstract: Performance analysis of an L branch equal gain combining (EGC) receiver with phase estimation error and asynchronous co-channel interference (CCI) over correlated Nakagami-m fading channel is analysed. Both the desired and interfering signals are assumed to be Nakagami-m distributed. The average bit error probability (ABEP) of a dual branch EGC receiver is obtained for binary phase shift keying (BPSK) modulation using moment generating function (MGF) and Pade approximation approach. The output signal to noise ratio (SNR) of the EGC combiner is derived. A closed form expression for the nth moment of the output SNR is derived. Using the nth moment expression, ABEP for BPSK modulation is derived using MGF and Pade approximation method. Numerical and simulation results of ABEP for various desired and interfering signal parameters are obtained. ABEP results for various degrees of phase errors are also obtained. The results for special cases are verified with the available results.
Keywords: moment generating function; average bit error probability; EGC combiner.
Feedforward neural network based on ensemble evolutionary algorithm with self-adaptive strategy and parameter for intrusion detection
by Yu Xue, Tao Tang, Alex X. Liu
Abstract: The applications of wireless sensor networks (WSNs) have driven the development of many fields, and information security is an important issue in the WSNs. Intrusion Detection System (IDS) is an effective system for identifying network attacks and protecting data security, which has a great significance for WSNs. In this paper, we transform the intrusion detection problem into a classification problem and introduce the feedforward neural network (FNN) classifier to solve it. At the same time, we propose a novel self-adaptive parameter and strategy differential particle swarm optimisation (SPS-DPS) algorithm to find the optimal weights for the FNN. Experiments are performed on eight datasets, which are constructed based on the intrusion detection dataset KDDCUP99, and the results are compared with five evolutionary computation methods. The results show that the SPS-DPS based FNN method can solve the intrusion detection problem well compared with the other methods.
Keywords: wireless sensor network; intrusion detection; feedforward neural network; classification; evolutionary computation; particle swarm optimisation; differential evolution; self-adaptive strategy and parameter.
Lean evaluation system of manufacturing enterprises based on full lifecycle
by Le Yang, Guozhang Jiang, Zhongyuan Li, Gongfa Li, Chao Xu
Abstract: The production of manufacturing enterprises is a complex process. In lean production it is hard to achieve lean weight reduction. It is very important to propose a lean life assessment framework. This paper evaluates the lean production level of the whole lifecycle of the company by using the fuzzy theory and the neural network technology, establishes a scientific and systematic framework of the lean evaluation index of the whole lifecycle, and establishes the evaluation model of the fuzzy neural network. The example analysis shows that the actual output value of the fuzzy neural network model is not much different from the predicted output value, which indicates that the model has high prediction accuracy. The experimental results further verify the reliability and validity of the model. The system framework can well plan and evaluate the whole lean production level. Accurate assessment of lean production level is an effective way to improve lean levels.
Keywords: whole lifecycle; system architecture; fuzzy theory; neural network; evaluation system.
Colour image encryption using Nahrain chaotic map
by Hamsa Abdullah, Hikmat Abdullah
Abstract: Recently, great attention has been paid to the use of chaotic maps in image encryption applications owing their excellent randomness properties. In this paper, an efficient image encryption algorithm using a set of chaotic maps is proposed. The algorithm diffuses images by a key image generated by a recently developed chaotic map called Nahrain. To evaluate the performance, Matlab simulations are done for both the proposed algorithm and some existing algorithms while histogram, correlation, information entropy, Number of Pixel Change Rate (NPCR), and Unified Average Changing Intensity (UACI) measures are used for security analysis. The simulation results and security analysis have demonstrated that the proposed encryption system is robust and flexible. For example, the amount of entropy obtained by the proposed algorithm is 7.9758, which is very close to its ideal amount: 8, and NPCR is 100%, which is the ideal value to obtain.
Keywords: chaotic; image encryption; robust; security analysis.
An actual traffic prediction method based on particle swarm optimisation and wavelet neural network
by Ke Chen, Zhiping Peng, Wende Ke
Abstract: For the congestion phenomena of network, this paper provides a new prediction method for service flow, based on particle swarm optimisation and wavelet neural network prediction (PSOWNNP). Firstly, this method uses wavelet exchange to resolve the service flow, and uses its wavelet coefficient and metric coefficient as the sample data. Secondly, the sample data is trained using the neural network method of the particle swarm optimisation, in which the wavelet model is applied for construction, and the prediction data for service flow are obtained from this. At the same time, the prediction methods of wavelet neural network and BP neural network for particle swarm optimisation are analysed and compared through simulation experiments, and the result for indicating the performance of AWNNP method is relatively good, with a tolerance of 17.21%.
Keywords: congestion; prediction; particle swarm; neural network.
An anomaly detection technique based intrusion detection system for wireless sensor networks
by Sushant Kumar Pandey
Abstract: In wireless sensor networks (WSN), from research it has been found that to figure out a compromised node is a very difficult task. A compromised node is one that doesn't have features like other normal nodes. A compromised node can be an intruder for the network and can be harmful for the network. It can steal information or can interrupt data communication. Sometimes it can corrupt other nodes in a network. In WSN, there is limited power and very limited processing capability. Moreover, in the WSN homogeneous network nodes have similar behaviour and this is the main reason why to figure out a compromised node is a difficult task. We have used an anomaly technique for detection of compromised nodes, in which we have compared the behaviour of anonymous node with normal node. There are some certain parameters on the basis of which it is decided that behaviour will get abnormal or not. We have chosen some operators called IDS operators from all the set of normal nodes. This selection is done by internal congestion within a node. The IDS operator will be selected in such a way so that it will cover the full network architecture. Every node should be in the radio range of IDS operator. Learning will be provided to the IDS operator, so that it can figure out the compromised node from the network. This learning is based on parameters, which are related with behaviour of the normal sensor nodes. After detection of a compromised node, the IDS operator will notify the sink node about it. The IDS operator is behaving as normal nodes. If any suspicious node is in the radio range of it, then it will be tested by the IDS operator.
Keywords: anomaly technique; intrusion detection system; IDS controller node; WSN; behaviour parameters.
Evaluating the performance of asynchronous MAC protocols for wireless sensor networks
by Abdelmalek Bengheni, Fedoua Didi
Abstract: Medium Access Control (MAC) protocols for duty-cycling, in Wireless Sensor Networks (WSN), are responsible for arbitrating access to a shared medium, for coordinating the access from active nodes and conserving power energy. These types of protocol can be classified into two categories: synchronous and asynchronous MAC protocols. In synchronous MAC protocols, each node is synchronised with the neighbourhood where each transmitter node can transmit a packet to the corresponding receiver during their period of listening, through the use of the control messages. The main goal of these protocols is to reduce energy loss caused by idle-listening, collision, overhearing and control overhead. On the other hand, asynchronous MAC protocols reduce energy consumption without the use of control messages. The main objective of this paper is to evaluate the performance of an experimental WSN using two different types of asynchronous MAC protocol; the first uses the transmission of the preamble frame such as B-MAC (Berkeley MAC) and X-MAC (A Short Preamble MAC) and the subsequent based on beaconing paradigm that uses the transmission of the beacon frame as RI-MAC (Receiver Initiated MAC). In this experiment, we used OMNeT++/MiXiM network simulator to create WSN and then evaluate its performance in terms of the packet delivery ratio, mean latency and energy consumption. The simulation results show that RI-MAC performs better than X-MAC and B-MAC and that X-MAC is ranked second best before B-MAC.
Keywords: performance; wireless sensor network; asynchronous MAC protocols; OMNeT++; MiXiM.
Enhancement of the dynamic bandwidth channel access for IEEE 802.11ac WLANs
by Fadhila Halfaoui, Mohand Yazid, Louiza Bouallouche-Medjkoune
Abstract: The aim of the new IEEE 802.11ac amendment is to significantly increase the throughput within the Basic Service Set (BSS) by improving the physical data rate. IEEE 802.11ac provides a maximum Multi-Station (Multi-STA) throughput of at least 1 Gbps and a maximum single link of at least 500 Mbps. This achieved throughput is obtained by adding many enhancements for the PHY and MAC layers. One of the main features that allows 802.11ac to reach gigabit transmission rates is a static and dynamic channel bonding technique. In this paper, we first overview the static 80 MHz and the dynamic 20/40/80 MHz bandwidth channel access schemes defined in 802.11ac. We then present the proposed enhancement of the dynamic access for an 80 MHz wide channel. The simulation results show that the enhanced dynamic access offers better throughput compared with the two methods used by 802.11ac stations.
Keywords: IEEE 802.11ac; multi-channel access; simulation and performance analysis.
Transport layer dependability benchmarking: TCP congestion control with fault injection
by Maroua Belkneni, M.Taha Bennani, Samir Ben Ahmed
Abstract: Previous approaches have used fault injection to evaluate the distributed system's dependability by targeting the application and hardware layers. In this paper, we delve on the communication layer services which are located between the two previous layers. We provide the specification of the assessment components: fault injection, architectural structure of the workload, and dependability measures. We have examined in this paper, the use of fault injections to evaluate the dependability of a transport layer protocol (i.e., TCP) with a random study. We have focused on the congestion control service, then, we have defined workload, faultload and dependability measures. We have shown that the communication is interrupted after exceeding a given tolerance threshold (below this limit, the service employs a recovery time to resume execution). We conclude that congestion control is robust to port fields; however, fault injections to the window size and flag fields hang the service. The test bed is carried out through the simulator NS-3.
Keywords: wireless sensor networks; congestion control; transmission control protocol; NS-3; dependability; assessment; fault injection.
Anti-conspiracy attack threshold signature model and protocol
by Xiaoping Wang, Zhenhu Ning, Wei Wang, Yongli Yang
Abstract: Threshold signature has security and robustness, so more and more scholars pay close attention to it. Aiming at the disadvantage that threshold signature cannot prevent conspiracy attack, this paper makes full use of tracing set and other technologies, proposes a threshold signature model that can withstand the conspiracy attack, and resolves conspiracy attack problem successfully. Moreover, the model can prevent replay attack, has forward security and does not need the support of the trusted centre. Finally, this paper proves that in the standard model, the model is unforgeable under adaptive chosen message attack.
Keywords: threshold signature; conspiracy attack.
Intelligent task scheduling strategy for cloud robot based on parallel reinforcement learning
by Xue Fei, Su Qinghua
Abstract: Cloud computing is an emerging computing model that has been developed on the basis of grid computing. Its powerful computing capabilities have evoked great vigour in its integration with various industries. The integration of cloud computing and robotics has created the concept of cloud robots. This paper proposes an intelligent task scheduling strategy for cloud robot based on parallel reinforcement learning. Firstly, the cloud computing platform is used to divide the complex reinforcement learning problem into several sub-problems. Then the task-scheduling strategy is used to assign sub-tasks to the robot to learn and summarise the results. Finally, Cloudsim builds a cloud computing platform for simulation experiments to verify the effectiveness of the proposed method. The experimental results show that the proposed method reduces the time for the robot to learn the whole problem and improves the learning efficiency.
Keywords: cloud robots; reinforcement learning; parallel computing; task scheduling; Cloudsim.
Joint relay selection and power allocation protocol for two-way relaying system
by Hui Zhi, Jun Zhu, Yanjun Hu
Abstract: The joint relay selection and power allocation (JRSPA) for amplify-and-forward (AF) relaying (JRSPA-AF) combines power allocation (PA) and relay selection (RS) very well in two-way relaying (TWR) system. In order to explore the system performance of JRSPA-AF protocol, the outage probability and diversity-multiplexing tradeoff (DMT) of JRSPA-AF protocol are analysed. One upper bound, two lower bounds and approximate expressions of outage probability along with the DMT are derived. Based on this, the idea of JRSPA is introduced into decode-and-forward (DF) relaying TWR system, and the JRSPA-DF protocol is proposed. Moreover, the exact expressions of outage probability and DMT for JRSPA-DF are derived. Simulations are developed to validate the analytical results, the results show that the approximation outage probability of JRSPA-AF can be used well to evaluate system outage probability over the entire transmission SNR region, and the analysis results of outage probability of JRSPA-DF are consistent with its simulation results. In addition, the simulation results indicate that JRSPA-DF can achieve lower outage probability than JRSPA-AF and other protocols.
Keywords: joint relay selection and power allocation; two-way relaying; outage probability; diversity-multiplexing tradeoff.
Particle swarm optimisation with multi-strategy learning
by Guohan Lin, Jing Sun
Abstract: To ease the conflict between diversity and convergence rate encountered by PSO, a multi-strategy learning particle swarm optimisation algorithm (Multi-strategy Learning PSO, MSLPSO) is proposed. The proposed method can effectively preserve the heuristic information, a modified differential mutation is combined with PSO to expand the search range and to increase the diversity of the population. If the population is trapped into local optimum, the inferior particle adopts opposition-based learning, This mechanism can improve the diversity and can help the particles to move away from the local optimum. Gaussian disturbance is applied to elite particle to further improve the diversity of particle and to the proposed MLSPSO's exploration ability. Twelve benchmark function tests from CEC2005 are used to evaluate the performance of the proposed algorithm. The results show that the proposed multi-strategy learning has performed consistently well compared with other state-of-art PSO algorithms
Keywords: particle swarm optimisation; learning strategy; differential mutation; perturbation strategy; numerical optimisation.
An improved sum-of-sinusoids based Rayleigh and Rician fading channel simulation model
by Mohit Sharma, Manpreet Dhanjal
Abstract: Sum of sinusoids has been considered as a common approach to model the Rayleigh as well as the Rician fading channel in the multipath environment. A number of models have been suggested by various authors as modification of Clarke's model to best fit the theoretical results. In this paper, a modification is proposed to the angle of arrival of the signal at the receiver to address the situations where scatterers are scarcely present in the proximity of the receiver. Therefore, the probability of reception of the signal is assumed high in pi/2 to +pi/2 than the rest of the range. The proposed model is a generalised model for Rayleigh and Rician channels adaptable to wide range of scenarios. Simulation results of the proposed model in terms of autocorrelation function, probability density function, and power spectral density function are in agreement with the reference Clarke's model.
Keywords: fading channel simulator; Rayleigh fading channel; Rician fading channel; sum Of sinusoids.
Improved Bayesian inverse reinforcement learning based on demonstration and feedback
by Hengliang Tang, Anqi Wang, Xi Yang
Abstract: A major obstacle to traditional reinforcement learning is that rewards need to be artificially set to have a strong subjectivity. The inverse reinforcement learning algorithm solves this problem. Traditional inverse reinforcement learning requires an optimized demonstration, which is often not met in reality. Therefore, an interactive learning method is proposed to enhance the learned reward function by combining the feedback with the demonstration and using the improved Bayesian rule iteration of the imagery to improve the agent strategy. The proposed method was tested in experimental and simulation tasks. The results showed that the efficiency of the method was significantly improved under different degrees of non-optimal proof.
Keywords: inverse reinforcement learning; Bayesian rule; IRLDF algorithm; demonstration and feedback.
An improved DV-Hop algorithm based on distance optimisation for wireless sensor networks
by Fei Tang, Sanfeng Chen, Guangming Lin
Abstract: To improve the localisation accuracy for unknown nodes within a one-hop distance of an anchor node, this paper analyses the main reason that results in localisation error of DDV-Hop localisation algorithm, which is the estimation of the number of hops between nodes. The localisation algorithm based on distance optimisation is proposed. Jaccard coefficient is conducive to reduce the estimation error on the number of hops to an unknown node at a one-hop distance，and the difference error coefficient of the DDV-Hop algorithm is used to reduce the error accumulated when calculating the average hop distance to correct the average hop distance between nodes. A credibility factor is introduced to select the anchor node for localisation, which can calculate the locations of nodes. The node with the highest localisation accuracy is used as a new anchor node. Simulation results show that under the same conditions, the improved algorithm has a higher localisation accuracy than both the DDV-Hop algorithm and DV-Hop algorithm. The algorithm proposed in this paper is of great significance to the localisation performance of wireless sensor networks.
Keywords: node localisation; Jaccard coefficient; DDV-Hop; credibility factor.
Performance analysis of the IEEE 802.15.4e TSCH-CA algorithm under a non-ideal channel
by Soraya Touloum, Louiza Bouallouche-Medjkoune, Djamil Aissani, Celia Ouanteur
Abstract: Recently, the IEEE 802.15.4e amendment has developed a new MAC behaviour mode named Time Slotted and Channel Hopping (TSCH) to support the Industrial Wireless Sensor Networks (IWSNs) requirements. TSCH combines time slots with channel hopping and defines shared and dedicated links. A shared link is attributed to more than one sender which leads to collisions. To decrease the probability of repeated collisions in the packet retransmission, the TSCH Collision Avoidance (TSCH-CA) algorithm has been implemented by the 802.15.4e amendment. This paper proposes a two-dimensional Markov chain model to evaluate the performances of the TSCH-CA algorithm when only shared links are used under non-ideal channel conditions. The accuracy of this model has been verified through Monte Carlo simulations. Based on the proposed model, the expressions of different performance metrics that include retransmission probability, data packet loss rate, reliability, energy consumption, normalised throughput and average access delay have been obtained. Furthermore, a comparative study between TSCH-CA and the unslotted CSMA-CA of IEEE 802.15.4 under a non-ideal channel has been provided. Numerical results reveal that the TSCH-CA performances are clearly affected by channel errors when using only shared links under a noisy environment.
Keywords: IWSNs; IEEE 802.15.4e; TSCH-CA; non-ideal channel; modelling; Markov chains; performance analysis.
Performance of UWB communication systems in the presence of perfect/imperfect power control MAI and IEEE802.11a interference
by Ehab Moustafa Shaheen
Abstract: This paper evaluates the bit error rate performance of ultra-wideband (UWB) communication system under the impact of both multiple access and narrowband interferences operating. The narrowband interference (NBI) signal is modelled as the IEEE802.11a orthogonal frequency division multiplexing based wireless local area network signal, which can be approximated by the sum of independent asynchronous tone interferers with arbitrary frequencies. Multiple access interference (MAI) is assumed a zero mean Gaussian process, where it has been investigated in both perfect and imperfect power control scenarios. The bit error rate performance is evaluated in three different channel models: ideal channel model (additive white Gaussian noise channel), Nakagami-m multipath fading channel model and the IEEE802.15.3a UWB channel model. It is shown that the performance of a UWB system is severely degraded owing to the presence of both types of interference, yet the NBI has more impact on the performance of UWB communication systems compared with the multiple access one.
Keywords: impulse radio ultra-wideband; narrow band interference; IEEE802.11a; multiple access interference; Nakagami-m multipath fading channel; IEEE802.15.3a UWB channel model.
An efficient software/hardware architecture for cooperative transmission in wireless sensor networks
by Nesrine Atitallah, Kais Loukil, Hela Hakim, Mohammed Bensalah, Mohamed Abid
Abstract: Energy-efficient communication has gained increasing attention in the last few years owing to the limited-energetic resources in Wireless Sensor Networks (WSNs). Most existing works use limited-resource Sensor Nodes (SN) with a software implementation. This is often not efficient enough for intensive computing tasks such as relaying algorithms. Consequently, the Software/Hardware (Sw/Hw) co-design reaches a good compromise between energy efficiency and performances (workload and real-time). This paper investigates the design and implementation of a Cooperative Transmission Technique (CTT) for low power communication in WSN using two architectures. The first one is a pure software implementation based on an embedded soft-core processor. The validation of the technique mentioned above in real design is performed. Despite the use of a software core to optimise the processor, performances were limited. The identification of the most critical time and energy consuming tasks are performed using the profiling technique. An efficient Sw/Hw architecture (second architecture) based on soft-core processor with accelerator modules is deduced. Indeed, hardware acceleration of the CTT is implemented on a System on Chip (SoC) to achieve low power consumption level, reduced execution time as well as low resource occupancy. Experimental results of the Sw/Hw implementation demonstrate significant improvements in terms of performance metrics comparing with the software implementation.
Keywords: cooperative transmission technique; power efficiency; sensor node design; software/hardware co-design.
Research on the evaluation method of surface roughness in carbon fibre-reinforced plastic grinding based on mobile computing
by Penghua Xie, Ming Lv
Abstract: With the rapid development of mobile computing techniques, mobile users can share the service of the computing capability and resources provided by their mobile devices and other surrounding devices. However, privatisation, resource-constrained and mobility of mobile devices are challenges for data extraction and processing. As a kind of new material, Carbon Fibre-Reinforced Plastic (CFRP) has excellent properties such as light weight, high strength, good toughness, excellent corrosion resistance and design ability. Nevertheless, owing to the anisotropy of CFRP, it is difficult to follow the traditional evaluation method of the surface quality of single-phase materials after machining. In order to take full advantage of computing image processing technology in a mobile computing environment, this paper focuses on analysing the surface topography of CFRP after grinding and proposes a novel method for the surface roughness evaluation based on micro-vision using texture features value extracted by Gabor transform. By analysing the relationship between texture features value and surface roughness three-dimensional evaluation parameter Sq, the paper comes to a conclusion that the surface roughness can be evaluated by the texture features value entropy value (H). The experiments show that the method is superior to the evaluation of surface roughness in CFRP grinding with slight difference, and the convenience of image processing is improved by using mobile equipment and wireless network.
Keywords: carbon fibre-reinforced plastic; surface roughness; Gabor transform; micro-vision; evaluation; mobile computing.