Clustering provides an effective way to prolong the lifetime of wireless sensor networks. One of the major issues of a clustering protocol is selecting an optimal group of sensor nodes as the cluster heads to divide the network. Another is the mode of inter-cluster communication. In this paper, an energy-balanced unequal clustering (EBUC) protocol is proposed and evaluated. By using the particle swarm optimization (PSO) algorithm, EBUC partitions all nodes into clusters of unequal size, in which the clusters closer to the base station have smaller size. The cluster heads of these clusters can preserve some more energy for the inter-cluster relay traffic and the ‘hot-spots’ problem can be avoided. For inter-cluster communication, EBUC adopts an energy-aware multihop routing to reduce the energy consumption of the cluster heads. Simulation results demonstrate that the protocol can efficiently decrease the dead speed of the nodes and prolong the network lifetime.

The non-uniform transmission and network topological structure are combined to investigate the spreading behavior of susceptible-infected-susceptible (SIS) epidemic model. Based on the mean-field theory, the analytical and numerical results indicate that the epidemic threshold is correlated with the topology of underlying networks, as well as the disease transmission mechanism. These discoveries can greatly help us to further understand the virus propagation on communication networks.

This paper reviews multi-channel media access control (MAC) protocols based on IEEE 802.11 in wireless Mesh networks (WMNs). Several key issues in multi-channel IEEE 802.11-based WMNs are introduced and typical solutions proposed in recent years are classified and discussed in detail. The experiments are performed by network simulator version 2 (NS2) to evaluate four representative algorithms compared with traditional IEEE 802.11. Simulation results indicate that using multiple channels can substantially improve the performance of WMNs in single-hop scenario and each node equipped with multiple interfaces can substantially improve the performance of WMNs in multi-hop scenario.

It is of great importance to take various factors into account when evaluating the network security performance. Multilevel fuzzy comprehensive evaluation is a relatively valid method. However, the traditional multilevel fuzzy comprehensive evaluation algorithm relies on the expert’s knowledge and experiences excessively, and the result of the evaluation is usually less accurate. In this article, an improved multilevel fuzzy comprehensive evaluation algorithm, based on fuzzy sets core and entropy weight is presented. Furthermore, a multilevel fuzzy comprehensive evaluation model of P2P network security performance has also been designed, and the improved algorithm is used to make an instant computation based on the model. The advantages of the improved algorithm can be embodied in comparison with the traditional evaluation algorithm.

Energy-efficient communication is an important requirement for mobile relay networks due to the limited battery power of user terminals. This paper considers energy-efficient relaying schemes through selection of mobile relays in cooperative cellular systems with asymmetric traffic. The total energy consumption per information bit of the battery-powered terminals, i.e., the mobile station (MS) and the relay, is derived in theory. In the joint uplink and downlink relay selection (JUDRS) scheme we proposed, the relay which minimizes the total energy consumption is selected. Additionally, the energy-efficient cooperation regions are investigated, and the optimal relay location is found for cooperative cellular systems with asymmetric traffic. The results reveal that the MS-relay and the relay-base station (BS) channels have different influence over relay selection decisions for optimal energy-efficiency. Information theoretic analysis of the diversity-multiplexing tradeoff (DMT) demonstrates that the proposed scheme achieves full spatial diversity in the quantity of cooperating terminals in this network. Finally, numerical results further confirm a significant energy efficiency gain of the proposed algorithm comparing to the previous best worse channel selection and best harmonic mean selection algorithms.

Considering severe resources constraints and security threat of wireless sensor networks (WSN), the article proposed a novel hierarchical routing protocol algorithm. The proposed routing protocol algorithm can adopt suitable routing technology for the nodes according to the distance of nodes to the base station, density of nodes distribution, and residual energy of nodes. Comparing the proposed routing protocol algorithm with simple direction diffusion routing technology, cluster-based routing mechanisms, and simple hierarchical routing protocol algorithm through comprehensive analysis and simulation in terms of the energy usage, packet latency, and security in the presence of node compromise attacks, the results show that the proposed routing protocol algorithm is more efficient for wireless sensor networks.

This paper proposes rate-maximized (MR) joint subcarrier pairing (SP) and power allocation (PA) (MR-SP&PA), a novel scheme for maximizing the weighted sum rate of the orthogonal-frequency-division multiplexing (OFDM) relaying system with a decode-and-forward (DF) relay. MR-SP&PA is based on the joint optimization of both SP and power allocation with total power constraint, and formulated as a mixed integer programming problem in the paper. The programming problem is then transformed to a convex optimization problem by using continuous relaxation, and solved in the Lagrangian dual domain. Simulation results show that MR-SP&PA can maximize the weighted sum rate under total power constraint and outperform equal power allocation (EPA) and proportion power allocation (PCG).

In radio frequency identification (RFID) systems, tag collision arbitration is a significant issue for fast tag identification. This article proposes a novel tag anti-collision algorithm called framed slotted ALOHA with grouping tactic and binary selection (GB-FSA). The novelty of GB-FSA algorithm is that the reader uses binary tree algorithm to identify the tags according to the collided slot counters information. Furthermore, to save slots, tags are randomly divided into several groups based on the number of collided binary bits in the identification codes (IDs) of tags, and then only the number of the first group of tags is estimated. Performance analysis and simulation results show that the GB-FSA algorithm improves the identification efficiency by 9.9%–16.3% compared to other ALOHA-based tag anti-collision algorithms when the number of tags is 1 000.

Recently, echo state networks (ESN) have aroused a lot of interest in their nonlinear dynamic system modeling capabilities. In a classical ESN, its dynamic reservoir (DR) has a sparse and random topology, but the performance of ESN with its DR taking another kind of topology is still unknown. So based on complex network theory, three new ESNs are proposed and investigated in this paper. The small-world topology, scale-free topology and the mixed topology of small-world effect and scale-free feature are considered in these new ESNs. We studied the relationship between DR architecture and prediction capability. In our simulation experiments, we used two widely used time series to test the prediction performance among the new ESNs and classical ESN, and used the independent identically distributed (i.i.d) time series to analyze the short-term memory (STM) capability. We answer the following questions: What are the differences of these ESNs in the prediction performance? Can the spectral radius of the internal weights matrix be wider? What is the short-term memory capability? The experimental results show that the proposed new ESNs have better prediction performance, wider spectral radius and almost the same STM capacity as classical ESN’s.

A novel methodology for prediction of network traffic, WPANFIS, which relies on wavelet packet transform (WPT) for multi-resolution analysis and adaptive neuro-fuzzy inference system (ANFIS) is proposed in this article. The widespread existence of self-similarity in network traffic has been demonstrated in earlier studies, which exhibits both long range dependence (LRD) and short range dependence (SRD). Also, it has been shown that wavelet decomposition is an effective tool for LRD decorrelation. The new method uses WPT as extension of wavelet transform which can decoorrelate LRD and make more precisely partition in the high-frequency section of the original traffic. Then ANFIS which can extract useful information from the original traffic is implemented in this study for better prediction performance of each decomposed non-stationary wavelet coefficients. Simulation results show that the proposed WPANFIS can achieve high prediction accuracy in real network traffic environment.

Threshold signature plays an important role to distribute the power of a single authority in modern electronic society. In order to add functions and improve efficiency of threshold signatures, a multi-policy threshold signature scheme with distinguished signing authorities is proposed. In the scheme two groups can sign and verify each other, so the scheme is two-way signing and verifying. Moreover, the threshold values of the two groups can change with the security classification of the signing document, every discretionary signatory only signs a small part of the document instead of the whole one, so the bandwidth of data transmission for group signature construction can be reduced and the size of group signature is equivalent to that of any individual signature.

The problem of Gray image of constacyclic code over finite chain ring is studied. A Gray map between codes over a finite chain ring and a finite field is defined. The Gray image of a linear constacyclic code over the finite chain ring is proved to be a distance invariant quasi-cyclic code over the finite field. It is shown that every code over the finite field, which is the Gray image of a cyclic code over the finite chain ring, is equivalent to a quasi-cyclic code.

In this paper, we focus on the resource scheduling in the downlink of long term evolution advanced (LTE-A) assuming equal power allocation among subcarriers. Considering the backward compatibility, the LTE-A system serves LTE-A and long term evolution (LTE) users together with carrier aggregation (CA) technology. When CA is applied, a well-designed resource scheduling scheme is essential to the LTE-A system. Joint scheduling (JS) and independent scheduling (INS) are two resource scheduling schemes. JS is optimal in performance but with high complexity. Whereas INS is applied, the LTE users will acquire few resources because they can not support CA technology. And the system fairness is disappointing. In order to improve the system fairness without bringing high complexity to the system, an improved proportional fair (PF) scheduling algorithm base on INS is proposed. In this algorithm, we design a weigh factor which is related with the number of the carriers and the percentage of LTE users. Simulation result shows that the proposed algorithm can effectively enhance the throughput of LTE users and improve the system fairness.

In order to solve particle degeneracy phenomenon and simultaneously avoid sample impoverishment, this paper proposed an improved particle filter based on fine resampling algorithm for general case, called as particle filter with fine resampling (PF-FR). By introducing distance-comparing process and generating new particle based on optimized combination scheme, PF-FR filter performs better than generic sampling importance resampling particle filter (PF-SIR) both in terms of effectiveness and diversity of the particle system, hence, evidently improving estimation accuracy of the state in the nonlinear/non-Gaussian models. Simulations indicate that the proposed PF-FR algorithm can maintain the diversity of particles and thus achieve the same estimation accuracy with less number of particles. Consequently, PF-FR filter is a competitive choice in the applications of nonlinear state estimation.

By analysis and comparison of several chaotic systems that are applied to generate pseudo-random sequence, the generalized Henon map is proposed as a pseudo-random sequence generator. A new algorithm is created to solve the problem of non-uniform distribution of the sequence generated by the generalized Henon map. First, move the decimal point of elements in the sequence to the right; then, cut off the integer; and finally, quantify it into a binary sequence. Statistical test, security analysis, and the application of image encryption have strongly supported the good random statistical characteristics, high linear complexity, large key space, and great sensitivity of the binary sequence.

In this paper, a network scenario of two-way relaying over orthogonal frequency division multiplexing (OFDM) is considered, in which two nodes intend to exchange the information via a relay using physical-layer network coding (PLNC). Assuming that the full channel knowledge is available, an optimization problem, which maximizes the achievable sum rate under a sum-power constraint, is investigated. It is shown that the optimization problem is non-convex, which is difficult to find the global optimum solution in terms of the computational complexity. In consequence, a low-complexity optimal power allocation scheme is proposed for practice implementation. A link capacity diagram is first employed for power allocation on each subcarrier. Subsequently, an equivalent relaxed optimization problem and Karush-Kuhn-Tucker (KKT) conditions are developed for power allocation among each subcarrier. Simulation results demonstrate that the substantial capacity gains are achieved by implementing the proposed schemes efficiently with a low-complexity computational effort.

The problem to improve the performance of resisting geometric attacks in digital watermarking is addressed in this paper. Based on the optimized support vector regression (SVR), a zero-bit watermarking algorithm is presented. The proposed algorithm encrypts the watermarking image by using composite chaos with large key space and capacity against prediction, which can strengthen the safety of the proposed algorithm. By using the relationship between Tchebichef moment invariants of detected image and watermarking characteristics, the SVR training model optimized by composite chaos enhances the ability of resisting geometric attacks. Performance analysis and simulations demonstrate that the proposed algorithm herein possesses better security and stronger robustness than some similar methods.

This paper proposes a novel energy efficient unequal clustering algorithm for large scale wireless sensor network (WSN) which aims to balance the node power consumption and prolong the network lifetime as long as possible. Our approach focuses on energy efficient unequal clustering scheme and inter-cluster routing protocol. On the one hand, considering each node’s local information such as energy level, distance to base station and local density, we use fuzzy logic system to determine one node’s chance of becoming cluster head and estimate the corresponding competence radius. On the other hand, adaptive max-min ant colony optimization is used to construct energy-aware inter-cluster routing between cluster heads and base station (BS), which balances the energy consumption of cluster heads and alleviates the hot spots problem that occurs in multi-hop WSN routing protocol to a large extent. The confirmation experiment results have indicated the proposed clustering algorithm has more superior performance than other methods such as low energy adaptive clustering hierarchy (LEACH) and energy efficient unequal clustering (EEUC).

Privacy is an important issue in electronic voting. The concept of ‘full privacy’ in electronic voting was firstly proposed, not only the privacy of voters is concerned, but also the candidates’. Privacy preserving electronic election architecture without any trusted third party is presented and a general technique for k¬-out-of-m election based on distributed ElGamal encryption and mix-match is also provided. The voters can compute the result by themselves without disclosing their will and the vote of the losing candidates. Moreover, whether the vote of winner candidate is more than a half can be verified directly. This scheme satisfies ‘vote and go’ pattern and achieves full privacy. The correctness and security are also analyzed.

In teleportation, it can be seen that the probability of success is determined by Alice’s measurement and quantum channel. If the Alice’s measurement is appropriate, the teleportation can be successfully realized with the maximal probability. In accordance with transformation operator, two schemes are proposed for teleportation of an unknown one-particle state via a general W state, through which the successful probability and the fidelity of both schemes reach 1. Furthermore, two optimal matches of orthogonal complete measurement bases are given for teleporting an unknown one-particle state.