A dynamic CSFICA and feature‐based collision detection method in multichannel space‐based AIS

To detect message collisions in multichannel spaced‐based automatic identification system (AIS), a dynamic complex symmetric fast independent component analysis (CSFICA) and feature‐based collision detection method is proposed in this paper. A fast and stable blind source separation algorithm, dynamic CSFICA, is utilized to separate signals dynamically and improve the signal‐to‐interference ratio (SIR) in each channel. A frequency and phase offset insensitive feature detection algorithm is used to calculate the test statistics in each channel. The false alarm is suppressed by applying the arithmetic to geometric mean (AGM) method, and test statistics of channels with sufficient signal quality are extracted to detect the preamble. Simulation results show that the proposed algorithm outperforms the reference feature detection algorithm under collision conditions and is insensitive to the SIR. The proposed algorithm is more resistant to false alarm caused by signal (FAS) than the differential correlation (DC) algorithm.     

Collision‐interference cancellation for space‐based AIS using beam synthesis technology with optimal sparse linear array

A basic problem in the space‐based automatic identification system (AIS) is the low probability of detecting messages because ships' messages arrive at the receiver in the same time slot. In this study, sparse linear array optimal beam synthesis (SLA–OBS) technology is proposed to improve the capture ability of AIS messages by forming a narrow beam pattern that points in the direction of the desired AIS messages. To capture the desired signal within the narrow beam pattern, the directions of arrival (DOA) and the number of sources from ships are first estimated. Then, the ideal narrow beam pattern and minimal number of array elements are achieved synchronously with the CPLEX optimal tool. The simulations show that the message detection probability with the proposed method is greater than 95%, even when the situations are very serious, whereas the number of sparse linear antennas is small (no more than six). Copyright © 2015 John Wiley & Sons, Ltd.     

A constant false alarm rate frame detector for satellite‐based automatic identification system

Frame detection is an important step in satellite‐based automatic identification system for its contributions in verifying the presence of automatic identification system signal before frame synchronization. In this paper, a constant false alarm rate frame detector is proposed, which exploits the feature implied in the training sequence, to realize frame detection in the presence of additive white Gaussian noise and frequency offset. False alarm probability is related with a threshold, which is independent of the signal and noise. For fixed false alarm probability, the relationship between detection performance and E_b/N₀ is analyzed. Simulations prove that the proposed detector outperforms the detector based on cyclic autocorrelation when message collisions exist. Copyright © 2016 John Wiley & Sons, Ltd.     

An improved anti‐collision protocol for radio frequency identification tag

Many anti‐collision protocols have been proposed at present. Almost all known protocols exhibit an overall identification efficiency smaller than 50%. And all of them are proposed for general purpose applications and do not consider the distribution characteristic of tag IDs in different radio frequency identification (RFID) systems. In real world, there are many RFID systems, in which the tag IDs are mostly distributed continuously, such as in container terminals, warehouse management, supply chain management, and so on. This paper presents an efficient anti‐collision protocol, named improved collision tree protocol (ICT), to identify RFID tags simultaneously. The main novelties of this paper include that the duality and certainty principle is introduced and used in ICT to improve the tag identification efficiency, and the continuous and partially continuous distributions of tag IDs are taken into account in this paper. Both the theoretical and experimental results indicate that ICT improves the tag identification efficiency up to 100% when the tag IDs are distributed continuously, and always above 50% even when the tag IDs are distributed uniformly. For straightforward and efficient, ICT can be used in various RFID tag identification conditions, especially when the tag IDs are distributed continuously or partially continuously. Copyright © 2013 John Wiley & Sons, Ltd.     

A cross‐layer optimization for maximum‐revenue‐based multicast in multichannel multiradio wireless mesh networks

Given a video/audio streaming system installed on a multichannel multiradio wireless mesh network, we are interested in a problem concerning about how to construct a delay‐constrained multicast tree to support concurrent interference‐free transmissions so that the number of serviced mesh clients is maximized. In this paper, we propose a heuristic approach called cross‐layer and load‐oriented (CLLO) algorithm for the problem. On the basis of the cross‐layer design paradigm, our CLLO algorithm can consider application demands, multicast routing, and channel assignment jointly during the formation of a channel‐allocated multicast tree. The experimental results show that the proposed CLLO outperforms the layered approaches in terms of the number of serviced mesh clients and throughputs. This superiority is due to information from higher layers can be used to guide routing selection and channel allocation at the same time. As a result, the CLLO algorithm can explore more solution spaces than the traditional layered approaches. In addition to that, we also propose a channel adjusting procedure to enhance the quality of channel‐allocated multicast trees. According to our simulations, it is proved to be an effective method for improving the performance of the proposed CLLO algorithm. Copyright © 2013 John Wiley & Sons, Ltd.     

Frequency offset insensitive demodulation algorithm for satellite‐based automatic identification system

The frequency offset caused by the Doppler shift and the oscillators instability degrades the performance of satellite‐based demodulators for automatic identification system (AIS) signals unless proper synchronization algorithms are used. A noncoherent demodulation algorithm (NDA) based on cyclic redundancy check (CRC) error correction is proposed in this paper, which is able to tolerate large frequency offsets, thus avoiding the use of an explicit frequency synchronizer. To reduce the complexity, the number of CRC register states for error correction can be limited. Simulation results of the proposed algorithm are presented and compared with other demodulation algorithms in the literature in terms of bit error rate (BER) and packet error rate (PER).     

Electromagnetism‐like method tuned constant modulus algorithm for blind detector in multicarrier CDMA system

This paper presents an efficient meta‐heuristic algorithm based on electromagnetism‐like method, which has been successfully implemented in multiuser detection problems. The contribution revisits blind multiuser detection for multicarrier code division multiple access systems using a novel combined adaptive step‐size constant modulus algorithm (CMA) and electromagnetism‐like method scheme. To work around potentially computational intractability and improved the capability of suppressing multiple access interference (MAI) for Multicarrier CDMA System, the proposed scheme exploits heuristics in consideration of both global and local exploration of the step size of the CMA. Simulation results obtained confirm that faster convergence and desirable BER performance with low computational complexity can be achieved with electromagnetism‐like method based CMA scheme, compared with the previous step‐size CMA scheme, genetic algorithm, and particle swarm optimization with CMA scheme. Copyright © 2012 John Wiley & Sons, Ltd.     

Fuzzy step size least mean square algorithm tuned linearly constrained constant modulus algorithm for multi‐carrier code division multiple access blind multiuser detector

Adaptive fuzzy logic step size least mean square algorithm (FLCLMS) tuning unit is designed to adjust the step size of the linear constrained constant modulus algorithm for blind multiuser detection (MUD) in multi‐carrier code division multiple access (MC‐CDMA) systems is presented. In wireless communications system, the conventional constant modulus algorithm for blind MUD has some disadvantages such as slow convergence speed and phase rotation. To overcome these shortages, a modified constant modulus algorithm was developed for blind multiuser detector. On the basis of the deterministic behavior of the FLCLMS algorithm, it has also proposed simplification over the cost function calculation, obtaining more efficient algorithm and creating new perspective for the MUD implementation. The proposed algorithm ensures the algorithm convergence to the desired user and suppresses the multiple access interference in this cost function. Thus, the performance of the system is improved. The computational experiments show that the proposed FLCLMS not only can find optimal or closed‐to‐optimal solutions but also can obtain the low computation complexity both better and more robust results than existing algorithm reported recently in the literature. Copyright © 2013 John Wiley & Sons, Ltd.     

An improved distance‐based ant colony optimization routing for vehicular ad hoc networks

Vehicular ad hoc network (VANET) has earned tremendous attraction in the recent period due to its usage in a wireless intelligent transportation system. VANET is a unique form of mobile ad hoc network (MANET). Routing issues such as high mobility of nodes, frequent path breaks, the blind broadcasting of messages, and bandwidth constraints in VANET increase communication cost, frequent path failure, and overhead and decrease efficiency in routing, and shortest path in routing provides solutions to overcome all these problems. Finding the shortest path between source and destination in the VANET road scenario is a challenging task. Long path increases network overhead, communication cost, and frequent path failure and decreases routing efficiency. To increase efficiency in routing a novel, improved distance‐based ant colony optimization routing (IDBACOR) is proposed. The proposed IDBACOR determines intervehicular distance, and it is triggered by modified ant colony optimization (modified ACO). The modified ACO method is a metaheuristic approach, motivated by the natural behavior of ants. The simulation result indicates that the overall performance of our proposed scheme is better than ant colony optimization (ACO), opposition‐based ant colony optimization (OACO), and greedy routing with ant colony optimization (GRACO) in terms of throughput, average communication cost, average propagation delay, average routing overhead, and average packet delivery ratio.     

An improved teaching‐learning–based optimization for design of frequency reconfigurable antennas

This paper proposes an improved teaching‐learning–based optimization (ITLBO) for the electromagnetics and antenna community. The basic TLBO was applied to many different problems with consistent success. For improving the algorithm performance, in the learner phase, each group of two learners is replaced by three‐member groups. Furthermore, two new phases are added to the algorithm. The first phase involves selection of several better learners for teaching subjects to randomly selected weaker learners. The second phase is a mutation operation. The presented algorithm with these changes simulates a classroom more realistically and avoids being trapped in local optima. First, the ITLBO is evaluated to optimize seven benchmark functions and is shown to be faster and better. In addition, a frequency reconfigurable antenna design is considered as a practical problem and Taguchi's method is applied for adjusting the control parameters of the algorithm. Comparisons of the performance of this algorithm with those of the TLBO, two other improved versions of TLBO (I‐TLBO and improved TLBO with learning experience of other learners [LETLBO]) and genetic algorithms demonstrate the higher efficiency for this algorithm in electromagnetic problems. A prototype of the proposed antenna is fabricated, and the simulation and measurement results agree well.     

An improved password‐based authentication scheme for session initiation protocol using smart cards without verification table

Authentication schemes have been widely deployed access control and mobility management in various communication networks. Especially, the schemes that are based on multifactor authentication such as on password and smart card come to be more practical. One of the standard authentication schemes that have been widely used for secure communication over the Internet is session initiation protocol (SIP). The original authentication scheme proposed for SIP was vulnerable to some crucial security weaknesses. To overcome the security problems, various improved authentication schemes have been developed, especially based on elliptic curve cryptography (ECC). Very recently, Zhang et al . proposed an improved authentication scheme for SIP based on ECC using smart cards to overcome the security flaws of the related protocols. Zhang et al . claimed that their protocol is secure against all known security attacks. However, this paper indicates that Zhang et al . protocol is still insecure against impersonation attack. We show that an active attacker can easily masquerade as a legal server to fool users. As a remedy, we also improve Zhang et al . protocol by imposing a little extra computation cost. Copyright © 2014 John Wiley & Sons, Ltd.     

Frame‐based adaptive uplink scheduling algorithm in orthogonal frequency division multiple access‐based Worldwide Interoperability for Microwave Access networks

Because the orthogonal frequency division multiple access physical resource available for scheduling in Worldwide Interoperability for Microwave Access networks is frame by frame, an uplink scheduler located at the base station must efficiently allocate available resources to the subscriber stations in response to constant or bursty data traffic on a per‐frame basis. Available resources for real‐time and nonreal‐time traffics, called frame‐based adaptive bandwidth allocation and minimum guarantee and weight‐based bandwidth allocation, respectively, are proposed in this paper. Moreover, both short‐term and long‐term bandwidth predictions for traffic are incorporated so that the long‐term bandwidth prediction can have sustainable throughput requirement, and the short‐term bandwidth prediction can meet the objectives of low delay and jitter. For the scenarios studied, it shows that system performance of the proposed algorithm is better than the hybrid (earliest deadline first + weighted fair queuing + FIFO) algorithm in terms of packet delay, jitter, throughput, and fairness. Copyright © 2011 John Wiley & Sons, Ltd.     

A time‐efficient shrinkage algorithm for the Fourier‐based prediction enabling proactive optimisation in software‐defined networks

This paper focuses on the problem of time‐efficient traffic prediction. The prediction enables the proactive and globally scoped optimisation in software‐defined networks (SDNs). We propose the shrinkage and selection heuristic method for the trigonometric Fourier‐based traffic models in SDNs. The proposed solution allows us to optimise the network for an upcoming time window by installing flow entries in SDN nodes before the first packet of a new flow arrives. As the mechanism is designed to be a part of a sophisticated routing‐support system, several critical constraints are considered and taken into account. Specifically, the system is traffic‐ and topology‐agnostic, thus the prediction mechanism must be applicable to the networks with highly variable traffic loads (e.g., observed inside intra‐DCNs: datacentre networks). Furthermore, the system must effectively optimise routing in large‐scale SDNs comprised of numerous nodes and handling millions of flows of a dynamic nature. Therefore, the prediction must be simultaneously accurate as well as being time efficient and scalable. These requirements are met by our Fourier‐based solution, which subtracts consecutive harmonics from the original signal and compares the result with an adaptive threshold adjusted to the signal's standard deviation. The evaluation is performed by comparing the proposed heuristic with the well‐known Lasso method of proven accuracy. The results show that our solution is able to retain prediction accuracy at a comparable level. Moreover, in accordance with our main aim, we operate in a manner which is always significantly faster. In some cases, computation times are reduced by as much as 50 times.     

A new fuzzy‐based method for load balancing in the cloud‐based Internet of things using a grey wolf optimization algorithm

Cloud computing provides high accessibility, scalability, and flexibility in the era of computing for different practical applications. Internet of things (IoT) is a new technology that connects the devices and things to provide user required services. Due to data and information upsurge on IoT, cloud computing is usually used for managing these data, which is known as cloud‐based IoT. Due to the high volume of requirements, service diversity is one of the critical challenges in cloud‐based IoT. Since the load balancing issue is one of the NP‐hard problems in heterogeneous environments, this article provides a new method for response time reduction using a well‐known grey wolf optimization algorithm. In this paper, we supposed that the response time is the same as the execution time of all the tasks that this parameter must be minimized. The way is determining the status of virtual machines based on the current load. Then the tasks will be removed from the machine with the additional load depending on the condition of the virtual machine and will be transferred to the appropriate virtual machine, which is the criterion for assigning the task to the virtual machine based on the least distance. The results of the CloudSim simulation environment showed that the response time is developed in compared to the HBB‐LB and EBCA‐LB algorithm. Also, the load imbalancing degree is improved in comparison to TSLBACO and HJSA.     

Beamforming‐based feature extraction and RVM‐based method for attacker node classification in CRN

Cognitive radio is a promising technology for the future wireless spectrum allocation to improve the utilization rate of the licensed bands. However, the cognitive radio network is susceptible to various attacks. Hence, there arises a need to develop a highly efficient security measure against the attacks. This paper presents a beamforming‐based feature extraction and relevance vector machine (RVM)‐based method for the classification of the attacker nodes in the cognitive radio network. Initially, the allocation of the Rayleigh channel is performed for the communication. The quaternary phase shift keying method is used for modulating the signals. After obtaining the modulated signal, the extraction of the beamforming‐based features is performed. The RVM classifier is used for predicting the normal nodes and attacker nodes. If the node is detected as an attacker node, then communication with that node is neglected. Particle swarm optimization is applied for predicting the optimal channel, based on the beamforming feature values. Then, signal communication with the normal nodes is started. Finally, the signal is demodulated. The signal‐to‐noise ratio and bit‐error rate values are computed to evaluate the performance of the proposed approach. The accuracy, sensitivity, and specificity of the RVM classifier method are higher than the support vector machine classifier. The proposed method achieves better performance in terms of throughput, channel sensing/probing rate, and channel access delay. Copyright © 2016 John Wiley & Sons, Ltd.