The outage probability (OP) performance of multiple-relay-based incremental hybrid decode-amplify-forward (IHDAF) relaying mobile-to-mobile (M2M) networks with transmit antenna selection (TAS) over N-Nakagami fading channels is investigated in this paper. The closed-form expressions for approximate OP of the optimal and suboptimal TAS schemes are derived. The power allocation problem is formulated for performance optimization. Then the OP performance under different conditions is evaluated through numerical simulations to verify the analysis. The simulation results showed that optimal TAS scheme has a better OP performance than suboptimal TAS scheme; the power-allocation parameter has an important influence on the OP performance.

This paper investigates the problem of co-tier interference mitigation for dynamic small- cell networks, in which the load of each small-cell varies with the number of active associated small-cell users (SUs). Due to the fact that most small-cell base stations (SBSs) are deployed in an ad-hoc manner, the problem of reducing co-tier interference caused by dynamic loads in a distributed fashion is quite challenging. First, we propose a new distributed channel allocation method for small-cells with dynamic loads and define a dynamic interference graph. Based on this approach, we formulate the problem as a dynamic interference graph game and prove that the game is a potential game and has at least one pure strategy Nash equilibrium (NE) point. Moreover, we show that the best pure strategy NE point minimizes the expectation of the aggregate dynamic co-tier interference in the small-cell network. A distributed dynamic learning algorithm is then designed to achieve NE of the game, in which each SBS is unaware of the probability distributions of its own and other SBSs' dynamic loads. Simulation results show that the proposed approach can mitigate dynamic co-tier interference effectively and significantly outperform random channel selection.

In recent years, cloud computing services based on smart phones and other mobile terminals have been a rapid development. Cloud computing has the advantages of mass storage capacity and high-speed computing power, and it can meet the needs of different types of users, and under the background, mobile cloud computing (MCC) is now booming. In this paper, we have put forward a new classification-based virtual machine placement (CBVMP) algorithm for MCC, and it aims at improving the efficiency of virtual machine (VM) allocation and the disequilibrium utilization of underlying physical resources in large cloud data center. By simulation experiments based on CloudSim cloud platform, the experimental results show that the new algorithm can improve the efficiency of the VM placement and the utilization rate of underlying physical resources.

In this paper, we propose a sum transmission rate maximization based cooperative spectrum sharing protocol with quality-of-service (QoS) support for both of the primary and secondary systems, which exploits the situation when the primary system experiences a weak channel. The secondary transmitter ST_b which provides the best performance for the primary and secondary systems is selected to forward the primary signal. Specifically, ST_b helps the primary system achieve the target rate by using a fraction of its power to forward the primary signal. As a reward, it can gain spectrum access by using the remaining power to transmit its own signal. We study the secondary user selection and optimal power allocation such that the sum transmission rate of primary and secondary systems is maximized, while the QoS of both primary and secondary systems can be guaranteed. Simulation results demonstrate the efficiency of the proposed spectrum sharing protocol and its benefit to both primary and secondary systems.

Energy consumption is an important index in mobile ad hoc networks. Data packet transmission increases among nodes, particularly in big data communication. However, nodes may be unable to transmit data packets because of energy over-consumption. Consequently, information may be lost and network communication may block. While opportunistic network is a kind of mobile ad hoc networks, researchers do not focus on energy consumption in opportunistic network communication. This study proposed an effective sensor energy supply scheme that can be applied in opportunistic networks. This scheme considers nodes sensor requests and communication model. In this scheme, nodes do not only accomplish energy supply in communication, but also extend communication time in opportunistic networks. Compared with the Spray and Wait algorithm and the Binary Spray and Wait algorithm in simulations, the proposed scheme extends communication time, increases data packet transmission, and accomplishes energy supply among nodes.

In this paper, we investigate joint power allocation and relay selection (PARS) schemes in non-orthogonal cooperative protocol (NOCP) based cognitive relay networks. Generally, NOCP outperforms the orthogonal cooperative protocol (OCP), since it can provide more transmit diversity. However, most existing PARS schemes in cognitive relay networks focus on OCP, which are not suitable for NOCP. In the context of NOCP, we first derive the joint constraints of transmit power limit for secondary user (SU) and interference constraint for primary user (PU). Then we formulate optimization problems under the aforementioned constraints to maximize the capacity of SU in amplify-and-forward (AF) and decode-and-forward (DF) modes, respectively. Correspondingly, we derive the closed form solutions with respect to different parameters. Numerical results are provided to verify the performance improvement of the proposed PARS schemes.

Cooperative spectrum sensing (CSS) for vacant licensed bands is one of the key techniques in cognitive radio networks. Currently, sequential probability ratio test scheme (SPRT) is considered as a powerful soft decision approach to improve the sensing result for CSS. However, SPRT assumes all secondary users (SU) are honest, and thus offering opportunities for malicious SUs to launch the spectrum sensing data falsification attack (SSDF attack). To combat such misbehaved behaviors, recent efforts have been made to trust mechanism. In this paper, we argue that powering SPRT with traditional trust mechanism is not enough. Dynamic SSDF attackers can maintain high trust in an alternant process of submitting honest or false sensing data, resulting in difficultly detecting them. Noting that the trust value of dymamic SSDF attackers behave highly volatile, a novel trusted SPRT scheme (VSPRT) based on volatility decay analysis is proposed in this paper to mitigate the harmful effect of dynamic SSDF attackers in the process of the soft-decision data fusion, and thus improving the accuracy of the final sensing result. Simulation results show that the VSPRT scheme outperforms the conventional SPRT schemes.

Successive interference cancellation (SIC) is considered to be a promising technique to mitigate multi-user interference and achieve concurrent uplink transmissions, but the optimal power allocation (PA) issue for SIC users is not well addressed. In this article, we focus on the optimization of the PA ratio of users on an SIC channel and analytically obtain the optimal PA ratio with regard to the signal-to-interference-plus-noise ratio (SINR) threshold for successful demodulation and the sustainable demodulation error rate. Then, we design an efficient resource allocation (RA) scheme using the obtained optimal PA ratio. Finally, we compare the proposal with the near-optimum RA obtained by a simulated annealing search and the RA scheme with random PA. Simulation results show that our proposal achieves a performance close to the near-optimum and much higher performance than the random scheme in terms of total utility and Jain's fairness index. To demonstrate the applicability of our proposal, we also simulate the proposal in various network paradigms, including wireless local area network, body area network, and vehicular ad hoc network.

This paper considers a channel estimation scheme for millimeter-wave multiuser multiple-input multiple-output systems. According to the proposed method, parts of the beams are selected and the channel parameters are estimated according to the sparsity of channels and the orthogonality of the beams. Since the beams for each channel become distinct and the signal power increases with the increased number of antennas, the proposed approach is able to achieve good estimation performance. As a result, the sum rate can be increased in comparison with traditional approaches, and channels can be estimated with fewer pilot symbols. Numerical results verify that the proposed approach outperforms traditional approaches in cases with large numbers of antennas.

In Long Term Evolution-Advanced (LTE-A) systems, Inter-cell Interference (ICI) is a prominent limiting factor that affects the performance of the systems, especially at the cell edges. Based on the literature, Fractional Frequency Reuse (FFR) methods are known as efficient interference management techniques. In this report, the proposed Dynamic Fractional Frequency Reuse (DFFR) technique improved the capacity and cell edge coverage performance by 70% compared to the Fractional Frequency Reuse (FFR) technique. In this study, an improved power allocation method was adopted into the DFFR technique to reach the goal of not only reducing the ICI mitigation at the cell edges, but also improving the overall capacity of the LTE-A systems. Hence, an improved water-filling algorithm was proposed, and its performance was compared with that of other methods that were considered. Through the simulation results and comparisons with other frequency reuse techniques, it was shown that the proposed method significantly improved the performance of the cell edge throughput by 42%, the capacity by 75%, and the coverage by 80%. Based on the analysis and numerical expressions, it was concluded that the proposed DFFR method provides significant performance improvements, especially for cell edge users.

In a vehicular ad hoc network, the communication links are unsteady due to the rapidly changing topology, high mobility and traffic density in the urban environment. Most of the existing geographical routing protocols rely on the continuous transmission of beacon messages to update the neighbors' presence, leading to network congestion. Source-based approaches have been proven to be inefficient in the inherently unstable network. To this end, we propose an opportunistic beaconless packet forwarding approach based on a modified handshake mechanism for the urban vehicular environment. The protocol acts differently between intersections and at the intersection to find the next forwarder node toward the destination. The modified handshake mechanism contains link quality, forward progress and directional greedy metrics to determine the best relay node in the network. After designing the protocol, we compared its performance with existing routing protocols. The simulation results show the superior performance of the proposed protocol in terms of packet delay and data delivery ratio in realistic wireless channel conditions.

We investigate the opposite of artificial noise (AN)-assisted communication in multiple-input-multiple-output (MIMO) wiretap channels for the multiuser case by taking the side of the eavesdropper. We first define a framework for an AN-assisted multiuser multiple-input-multiple-output (MU-MIMO) system, for which eavesdropping methods are proposed with and without knowledge of legitimate users' channel state information (CSI). The proposed method without CSI is based on a modified joint approximate diagonalization of eigen-matrices algorithm, which eliminates permutation indetermination and phase ambiguity, as well as the minimum description length algorithm, which blindly estimates the number of secret data sources. Simulation results show that both proposed methods can intercept information effectively. In addition, the proposed method without legitimate users' CSI performs well in terms of robustness and computational complexity.

In Wireless Sensor Networks (WSNs) and even in the Internet of Things (IoT) ecosystem, the reconfiguration of sensor variables is an important problem when the role of a system (or application) program's sensor nodes needs to be adjusted in a particular situation. For example, the outdoor temperature in a volcanic zone, which is usually updated in a system every 10 s, should be updated every 1 s during an emergency situation. To solve this problem, this paper proposes a novel approach based on changing only a set of sensor variables in a part of a program, rather than modifying the entire program, in order to reduce both network congestion and the sensor nodes' battery consumption. To validate our approach, we demonstrate an implementation of a proof-of-concept prototype system and also present results of comparative studies showing the performance and effectiveness of our proposed method.

To prevent structured peer to peer (P2P) overlay networksfrom being attacked by malicious nodes, a symmetric lookup-based routing algorithm referred to as Symmetric-Chord is proposed in this paper. The proposed algorithm determines the precision of routing lookup by constructing multiple paths to the destination. The selective routing algorithm is used to acquire information on the neighbors of the root. Authenticity of the root is validated via consistency shown between the information ascertained from the neighbors and information from the yet-to-be-verified root, resulting in greater efficiency of resource lookup. Simulation results demonstrate that Symmetric-Chordhas the capability of detecting malicious nodes both accurately and efficiently, so as to identify which root holds the correct key, and provides an effective approach to the routing security for the P2P overlay network.

In this paper, we propose a hybrid routing scheme that utilizes location information to support reliable data transmission in mobile ad hoc networks. The proposed scheme determines and maintains routing path by considering the directionality and connectivity of nodes using grid zones and information on neighbor nodes. In addition, it generates alternative paths with consideration for node distance and reliability. To show the superiority of the proposed routing scheme, a performance evaluation was conducted using simulations. The performance evaluation results show that the proposed scheme offers faster and more reliable data transmission than the existing routing schemes, and the number of messages decreases by approximately 31% compared to the existing schemes on average.

The hop count routing metric is widely used in routing protocols of Wireless Sensor Networks (WSNs) due to its simplicity and effectiveness. With a lower hop count route, fewer transmissions are required to send a packet from the source to the destination. This can improve the throughput of a network because fewer transmissions results in less channel contention and interference. Despite this, the hop count routing metric may not be ideal for mobile scenarios where the topology of a network changes constantly and rapidly. In this paper, we propose to increase route stability in mobile WSNs by discovering paths that are more stable during route discoveries using routing metrics. Two routing metrics were proposed, the true beauty of these routing metrics lies in the fact that they can even be used even without specialized hardware such as GPS and other sensors. We implemented the proposed routing metrics in the AODV routing protocol and found that they are highly effective and outperform other stability-based routing metrics and the hop count routing metric.

Information Centric Networking that uses content name instead of IP address as routing identifier can handle challenges such as traffic explosion and user mobility, but it also suffers from scalability and incompatibility problems. In this paper by combining the concept of software defined networking and Internet end to end arguments, we propose a wide area deployable software defined information centric networking service model named SD-ICN. SD-ICN employs a dual space structure that separates edge service network and core transmission network. The enhanced SDN techniques are used in edge service network in order to implement intelligent data routing and caching, while traditional IP technique is reserved in core transmission network so as to provide wide area high speed data transmission. Besides, a distributed name resolution system based on the cooperation of different controllers is also presented. The prototype experiments in our campus network show that SD-ICN can be deployed in a scalable and incremental way with no modification of the core network, and can support typical communication modes such as multicast, mobility, multihoming, load balancing, and multipath data transmission effectively.

Overlay networks have been widely deployed upon the Internet by Service Providers (SPs) to provide improved network services. However, the interaction between each overlay and traffic engineering (TE) as well as the interaction among co-existing overlays may occur. In this paper, we adopt both non-cooperative and cooperative game theory to analyze these interactions, which are collectively called hybrid interaction. Firstly, we model a situation of the hybrid interaction as an n+1-player non-cooperative game, in which overlays and TE are of equal status, and prove the existence of Nash equilibrium (NE) for this game. Secondly, we model another situation of the hybrid interaction as a 1-leader-n-follower Stackelberg-Nash game, in which TE is the leader and co-existing overlays are followers, and prove that the cost at Stackelberg-Nash equilibrium (SNE) is at least as good as that at NE for TE. Thirdly, we propose a cooperative coalition mechanism based on Shapley value to overcome the inherent inefficiency of NE and SNE, in which players can improve their performance and form stable coalitions. Finally, we apply distinct genetic algorithms (GA) to calculate the values for NE, SNE and the assigned cost for each player in each coalition, respectively. Analytical results are confirmed by the simulation on complex network topologies.

In this paper, we provide a trajectory-generation algorithm that can identify pedestrians in real time. Typically, the contours for the extraction of pedestrians from the foreground of images are not clear due to factors including brightness and shade; furthermore, pedestrians move in different directions and interact with each other. These issues mean that the identification of pedestrians and the generation of trajectories are somewhat difficult. We propose a new method for trajectory generation regarding multiple pedestrians. The first stage of the method distinguishes between those pedestrian-blob situations that need to be merged and those that require splitting, followed by the use of trained decision trees to separate the pedestrians. The second stage generates the trajectories of each pedestrian by using the point-correspondence method; however, we introduce a new point-correspondence algorithm for which the A* search method has been modified. By using fuzzy membership functions, a heuristic evaluation of the correspondence between the blobs was also conducted. The proposed method was implemented and tested with the PETS 2009 dataset to show an effective multiple-pedestrian-tracking capability in a pedestrian-interaction environment.

For the compression of color images, a common bitmap usually is generated to replace the three individual bitmaps that originate from block truncation coding (BTC) of the R, G and B channels. However, common bitmaps generated by some traditional schemes are not the best possible because they do not consider the minimized distortion of the entire color image. In this paper, we propose a near-optimized common bitmap scheme for BTC using Binary Ant Colony Optimization (BACO), producing a BACO-BTC scheme. First, the color image is compressed by the BTC algorithm to get three individual bitmaps, and three pairs of quantization values for the R, G, and B channels. Second, a near-optimized common bitmap is generated with minimized distortion of the entire color image based on the idea of BACO. Finally, the color image is reconstructed easily by the corresponding quantization values according to the common bitmap. The experimental results confirmed that reconstructed image of the proposed scheme has better visual quality and less computational complexity than the referenced schemes.

As one of the most important issues in computer vision and image processing, online object tracking plays a key role in numerous areas of research and in many real applications. In this study, we present a novel tracking method based on the proposed structured sparse representation model, in which the tracked object is assumed to be sparsely represented by a set of object and background templates. The contributions of this work are threefold. First, the structure information of all the candidate samples is utilized by a joint sparse representation model, where the representation coefficients of these candidates are promoted to share the same sparse patterns. This representation model can be effectively solved by the simultaneous orthogonal matching pursuit method. In addition, we develop a tracking algorithm based on the proposed representation model, a discriminative candidate selection scheme, and a simple model updating method. Finally, we conduct numerous experiments on several challenging video clips to evaluate the proposed tracker in comparison with various state-of-the-art tracking algorithms. Both qualitative and quantitative evaluations on a number of challenging video clips show that our tracker achieves better performance than the other state-of-the-art methods.

Communication occurs through verbal elements, which usually involve language, as well as non-verbal elements such as facial expressions, eye contact, and gestures. In particular, among these non-verbal elements, gestures are symbolic representations of physical, vocal, and emotional behaviors. This means that gestures can be signals toward a target or expressions of internal psychological processes, rather than simply movements of the body or hands. Moreover, gestures with such properties have been the focus of much research for a new interface in the NUI/NUX field. In this paper, we propose a method for recognizing the number of fingers and detecting the hand region based on the depth information and geometric features of the hand for application to an NUI/NUX. The hand region is detected by using depth information provided by the Kinect system, and the number of fingers is identified by comparing the distance between the contour and the center of the hand region. The contour is detected using the Suzuki85 algorithm, and the number of fingers is calculated by detecting the finger tips in a location at the maximum distance to compare the distances between three consecutive dots in the contour and the center point of the hand. The average recognition rate for the number of fingers is 98.6%, and the execution time is 0.065 ms for the algorithm used in the proposed method. Although this method is fast and its complexity is low, it shows a higher recognition rate and faster recognition speed than other methods. As an application example of the proposed method, this paper explains a Secret Door that recognizes a password by recognizing the number of fingers held up by a user.

Key agreement is paramount in secure wireless communications. A promising approach to address key agreement schemes is to extract secure keys from channel characteristics. However, because channels lack randomness, it is difficult for wireless networks with stationary communicating terminals to generate robust keys. In this paper, we propose a Robust Secure Key Agreement (RSKA) scheme from Received Signal Strength (RSS) in stationary wireless networks. In order to mitigate the asymmetry in RSS measurements for communicating parties, the sender and receiver normalize RSS measurements and quantize them into q-bit sequences. They then reshape bit sequences into new l-bit sequences. These bit sequences work as key sources. Rather than extracting the key from the key sources directly, the sender randomly generates a bit sequence as a key and hides it in a promise. This is created from a polynomial constructed on the sender's key source and key. The receiver recovers the key by reconstructing a polynomial from its key source and the promise. Our analysis shows that the shared key generated by our proposed RSKA scheme has features of high randomness and a high bit rate compared to traditional RSS-based key agreement schemes.

ABE has become an effective tool for data protection in cloud computing. However, since users possessing the same attributes share the same private keys, there exist some malicious users exposing their private keys deliberately for illegal data sharing without being detected, which will threaten the security of the cloud system. Such issues remain in many current ABE schemes since the private keys are rarely associated with any user specific identifiers. In order to achieve user accountability as well as provide key exposure protection, in this paper, we propose a key-insulated ciphertext policy attribute based encryption with key exposure accountability (KI-CPABE-KEA). In our scheme, data receiver can decrypt the ciphertext if the attributes he owns match with the self-centric policy which is set by the data owner. Besides, a unique identifier is embedded into each user's private key. If a malicious user exposes his private key for illegal data sharing, his identity can be exactly pinpointed by system manager. The key-insulation mechanism guarantees forward and backward security when key exposure happens as well as provides efficient key updating for users in the cloud system. The higher efficiency with proved security make our KI-CPABE-KEA more appropriate for secure data sharing in cloud computing.

A group signature scheme allows any member to sign on behalf of a group. It is applied to practical distributed security communication environments, such as privacy-preserving, data mining. In particular, the excellent features of group signatures, including membership joining and revocation, anonymity, traceability, non-frameability and controllable linkability, make group signature scheme more attractive. Among these features, non-frameability can guarantee that a member's signature cannot be forged by any other (including issuer), and controllable linkability supports to confirm whether or not two group signatures are created by the same signer while preserving anonymity. Until now, only Hwang et al.'s group schemes (proposed in 2013 and 2015) can support all of these features. In this paper, we present a new dynamic group signature scheme which can achieve all of the above excellent features. Compared with their schemes, our scheme has the following advantages. Firstly, our scheme achieves more efficient membership revocation, signing and verifying. The cost of update key in our scheme is two-thirds of them. Secondly, the tracing algorithm is simpler, since the signer can be determined without the judging step. Furthermore, in our scheme, the size of group public key and member's private key are shorter. Lastly, we also prove security features of our scheme, such as anonymity, traceability, non-frameability, under a random oracle model.

In contrast to traditional "store-and-forward" routing mechanisms, network coding offers an elegant solution for achieving maximum network throughput. The core idea is that intermediate network nodes linearly combine received data packets so that the destination nodes can decode original files from some authenticated packets. Although network coding has many advantages, especially in wireless sensor network and peer-to-peer network, the encoding mechanism of intermediate nodes also results in some additional security issues. For a powerful adversary who can control arbitrary number of malicious network nodes and can eavesdrop on the entire network, cryptographic signature schemes provide undeniable authentication mechanisms for network nodes. However, with the development of quantum technologies, some existing network coding signature schemes based on some traditional number-theoretic primitives vulnerable to quantum cryptanalysis. In this paper we first present an efficient network coding signature scheme in the standard model using lattice theory, which can be viewed as the most promising tool for designing post-quantum cryptographic protocols. In the security proof, we propose a new method for generating a random lattice and the corresponding trapdoor, which may be used in other cryptographic protocols. Our scheme has many advantages, such as supporting multi-source networks, low computational complexity and low communication overhead.