In this paper, the average bit error probability (ABEP) performance of the incremental-selective decode-and-forward (ISDF) relaying mobile-to-mobile (M2M) cooperative networks over N-Nakagami fading channels is investigated. The exact ABEP expressions are derived, and the power allocation problem is formulated.The derived ABEP expressions are verified by Monte Carlo simulations. The simulation results showed that the propagation parameters, such as the fading coefficient, and the power-allocation parameter, have a significant influence on the ABEP performance.

Cooperative forwarding has shown a substantial network performance improvement compared to traditional routing in multi-hop wireless network. To further enhance the system throughput, especially in the presence of highly congested multiple cross traffic flows, a promising way is to incorporate the multi-radio multi-channel (MRMC) capability into cooperative forwarding. However, it requires to jointly address multiple issues. These include radio-channel assignment, routing metric computation, candidate relay set selection, candidate relay prioritization, data broadcasting over multi-radio multi-channel, and best relay selection using a coordination scheme. In this paper, we propose a simple and efficient cluster-based cooperative data forwarding (CCDF) which jointly addresses all these issues. We study the performance impact when the same candidate relay set is being used for multiple cross traffic flows in the network. The network simulation shows that the CCDF with MRMC not only retains the advantage of receiver diversity in cooperative forwarding but also minimizes the interference, which therefore further enhances the system throughput for the network with multiple cross traffic flows.

Recent years have witnessed an explosive growth of mobile devices, mobile cloud computing services offered by these devices and the remote clouds behind them. In this paper, we noticed ultra-low latency service, as a type of mobile cloud computing service, requires extremely short delay constraints. Hence, such delay-sensitive applications should be satisfied with strong QoS guarantee. Existing solutions regarding this problem have poor performance in terms of throughput. In this paper, we propose an end-to-end bandwidth resource reservation via software defined scheduling inspired by the famous SDN framework. The main contribution of this paper is the end-to-end resource reservation and flow scheduling algorithm, which always gives priority to delay sensitive flows. Simulation results confirm the advantage of the proposed solution, which improves the average throughput of ultra-low latency flows.

It is essential to satisfy class-specific QoS constraints to provide broadband services for new generation networks. The present study proposes a QoS-driven multicast scheme for wireless networks in which the transmission rate and end-to-end delay are assumed to be bounded during a multiple multicast session. A distributed algorithm was used to identify a cost-efficient sub-graph between the source and destination which can satisfy QoS constraints of a multicast session. The model was then modified as to be applied for wireless networks in which satisfying interference constraints is the main challenge. A discrete power control scheme was also applied for the QoS-aware multicast model to accommodate the effect of transmission power level based on link capacity requirements. We also proposed random power allocation (RPA) and gradient power allocation (GPA) algorithms to efficient resource distribution each of which has different time complexity and optimality levels. Experimental results confirm that the proposed power allocation techniques decrease the number of unavailable links between intermediate nodes in the sub-graph and considerably increase the chance of finding an optimal solution.

How to determine the right number of small base stations to activate in multi-cell uplinks to match traffic from a fixed quantity of K users is an open question. This paper analyses the uplink cooperative that jointly receives base stations activation to explore this question. This paper is different from existing works only consider transmitting power as optimization objective function. The global objective function is formulated as a summation of two terms: transmitting power for data and coordinated overhead for control. Then, the joint base stations activation and beamforming problem is formulated as a mixed integer second order cone optimization. To solve this problem, we develop two polynomial-time distributed methods. Method one is a two-stage solution which activates no more than K small base stations (SBSs). Method two is a heuristic algorithm by dual decomposition to MI-SOCP that activates more SBSs to obtain multiple-antennae diversity gains. Thanks to the parallel computation for each node, our methods are more computationally efficient. The strengths and weaknesses of these two proposed two algorithms are also compared using numerical results.

As a service-oriented paradigm, web service composition has obtained great attention from both academia and industry, especially in the area of cloud service. Nowadays more and more web services providing the same function but different in QoS are available in cloud, so an important mission of service composition strategy is to select the optimal composition solution according to QoS. Furthermore, the selected composition solution should satisfy the service level agreement (SLA) which defines users' request for the performance of composite service, such as price and response time. A composite service is feasible only if its QoS satisfies user's request. In order to obtain composite service with the optimal QoS and avoid SLA violations simultaneously, in this paper we first propose a QoS evaluation method which takes the SLA satisfaction into account. Then we design a service selection algorithm based on our QoS evaluation method. At last, we put forward a parallel running strategy for the proposed selection algorithm. The simulation results show that our approach outperforms existing approaches in terms of solutions' optimality and feasibility. Through our running strategy, the computation time can be reduced to a large extent.

Cognitive radio is an efficient technique to improve spectrum efficiency and relieve the pressure of spectrum resources. In this paper, we investigate the spectrum sensing period in cooperative relay cognitive radio networks; analyze the relationship between the available capacity and the signal-to-noise ratio of the received signal of second users, the target probability of detection and the active probability of primary users. Finally, we derive the closed form expression of the optimal spectrum sensing period in terms of maximum throughput. We simulate the probability of false alarm and available capacity of cognitive radio networks and compare optimal spectrum sensing period scheme with fixed sensing period one in these performance. Simulation results show that the optimal sensing period makes the cognitive networks achieve the higher throughput and better spectrum sensing performance than the fixed sensing period does. Cooperative relay cognitive radio networks with optimal spectrum sensing period can achieve the high capacity and steady probability of false alarm in different target probability of detection. It provides a valuable reference for choosing the optimal spectrum sensing period in cooperative relay cognitive radio networks.

Digital watermarking techniques are widely applied to protect the integrity and copyright of digital content. In a majority of the literature for watermarking techniques, the watermarked image often causes some distortions after embedding a watermark. For image-quality-concerned users, the distortions from a watermarked image are unacceptable. In this article, we propose a removable watermarking scheme that can restore an original-like image and resist signal-processing attacks to protect the ownership of an image by utilizing the property of singular value decomposition (SVD). The experimental results reveal that the proposed scheme meets the requirements of watermarking robustness, and also reestablishes an image like the original with average PSNR values of 59.07 dB for reconstructed images.

Emerging applications in automation, medical imaging, traffic monitoring and surveillance need real-time data transmission over Wireless Sensor Networks (WSNs). Guaranteeing Quality of Service (QoS) for real-time traffic over WSNs creates new challenges. Rapid penetration of smart devices, standardization of Machine Type Communications (MTC) in next generation 5G wireless networks have added new dimensions in these challenges. In order to satisfy such precise QoS constraints, in this paper, we propose a new cross-layer QoS-provisioning strategy in Wireless Multimedia Sensor Networks (WMSNs). The network layer performs statistical estimation of sensory QoS parameters. Identifying QoS-routing problem with multiple objectives as NP-complete, it discovers near-optimal QoS-routes by using evolutionary genetic algorithms. Subsequently, the Medium Access Control (MAC) layer classifies the packets, automatically adapts the contention window, based on QoS requirements and transmits the data by using routing information obtained by the network layer. Performance analysis is carried out to get an estimate of the overall system. Through the simulation results, it is manifested that the proposed strategy is able to achieve better throughput and significant lower delay, at the expense of negligible energy consumption, in comparison to existing WMSN QoS protocols.

Restricted by finite battery energy, traditional wireless sensor networks (WSNs) can only maintain for a limited period of time, resulting in serious performance bottleneck in long-term deployment of WSN. Fortunately, the advancement in the wireless energy transfer technology provides a potential to free WSNs from limited energy supply and remain perpetual operational. A mobile charger called wireless charging vehicle (WCV) is employed to periodically charge each sensor node and keep its energy level above the minimum threshold. Aiming at maximizing the ratio of the WCV's vocation time over the cycle time as well as guaranteeing the perpetual operation of networks, we propose a feasible and optimal solution to this issue within the context of a real-time large-scale deployed WSN. First, we develop two different types of charging cycles: initialization cycles and renewable cycles and give relevant algorithms to construct these two cycles for each sensor node. We then formulate the optimization problem into an optimal construction algorithm and prove its correctness through theoretical analysis. Finally, we conduct extensive simulations to demonstrate the effectiveness of our proposed algorithms.

An optimal power control algorithm based on convex optimization is proposed for base stations in long term evolution networks. An objective function was formulated to maximize the proportional fairness of the networks. The optimal value of the objective function was obtained using convex optimization and distributed methods based on the path loss model between the base station and users. Field tests on live networks were conducted to evaluate the performance of the proposed algorithm. The experimental results verified that, in a multi-cell multi-user scenario, the proposed algorithm increases system throughputs, proportional fairness, and energy efficiency by 9, 1.31 and 20.2 %, respectively, compared to the conventional fixed power allocation method.

In decode and forward relay systems, choosing the duplex mode is an important factor to the performance. To satisfy the performance requirement, self-interference must be mitigated for the full-duplex relay (FDR), and the resource efficiency must be increased for the half-duplex ratio (HDR). Therefore, if a wise scheme to consider these two factors exists, decode and forward relay systems are used more effectively. This study proposes a new duplex selection scheme for decode and forward relay systems. The proposed duplex selection scheme chooses the better duplex mode according to the channel statistical conditions with optimal power allocation. The simulation results show that the proposed duplex scheme with optimal power allocation has lower outage probability than the FDR and the HDR.

Combining channel coding and network coding in a physical layer in a fading channel, generalized joint channel-network coding (G-JCNC) is proved to highly perform in a two-way relay channel (TWRC). However, most relevant discussions are restricted to symmetric networks. This paper investigates the G-JCNC protocols in an asymmetric TWRC (A-TWRC). A newly designed encoder used by source nodes that is dedicated to correlate codewords with different orders is presented. Moreover, the capability of a simple common non-binary decoder at a relay node is verified. The effects of a power match under various numbers of iteration and code lengths are also analyzed. The simulation results give the optimum power match ratio and demonstrate that the designed scheme based on G-JCNC in an A-TWRC has excellent bit error rate performance under an appropriate power match ratio.

IOMMU is a hardware unit that is indispensable for DMA. Besides address translation and remapping, it also provides I/O virtual address space isolation among devices and memory access control on DMA transactions. However, currently commodity virtualization platforms lack of IOMMU virtualization, so that the virtual machines are vulnerable to DMA security threats. Previous works focus only on DMA security problem of directly assigned devices. Moreover, these solutions either introduce significant overhead or require modifications on the guest OS to optimize performance, and none can achieve high I/O efficiency and good compatibility with the guest OS simultaneously, which are both necessary for production environments. However, for simulated virtual devices the DMA security problem also exists, and previous works cannot solve this problem. The reason behind that is IOMMU circuits on the host do not work for this kind of devices as DMA operations of which are simulated by memory copy of CPU. Motivated by the above observations, we propose an IOMMU para-virtualization solution called PVIOMMU, which provides general functionalities especially DMA security guarantees for both directly assigned devices and simulated devices. The prototype of PVIOMMU is implemented in Qemu/KVM based on the virtio framework and can be dynamically loaded into guest kernel as a module, As a result, modifying and rebuilding guest kernel are not required. In addition, the device model of Qemu is revised to implement DMA access control by separating the device simulator from the address space of the guest virtual machine. Experimental evaluations on three kinds of network devices including Intel I210 (1Gbps), simulated E1000 (1Gbps) and IB ConnectX-3 (40Gbps) show that, PVIOMMU introduces little overhead on DMA transactions, and in general the network I/O performance is close to that in the native KVM implementation without IOMMU virtualization.

Both low-density parity-check (LDPC) codes and the multiple access technique of spatially coupling data transmission (SCDT) can be expressed in bipartite graphs. To improve the performance of iterative demodulation and decoding for SCDT, a novel joint sparse graph (JSG) with SCDT and LDPC codes is constructed. Based on the JSG, an approach for iterative joint demodulation and decoding by belief propagation (BP) is presented as an exploration of the flooding schedule, and based on BP, density evolution equations are derived to analyze the performance of the iterative receiver. To accelerate the convergence speed and reduce the complexity of joint demodulation and decoding, a novel serial schedule is proposed. Numerical results show that the joint demodulation and decoding for SCDT based on JSG can significantly improve the system's performance, while roughly half of the iterations can be saved by using the proposed serial schedule.

Despite the abundant literature in the field, there is still the need to find a time-efficient, highly accurate, easy to deploy and robust localization algorithm for real use. The algorithm only involves minimal human intervention. We propose an enhanced Received Signal Strength Indicator (RSSI) based positioning algorithm for Wi-Fi capable devices, called the Dynamic Weighted Evolution for Location Tracking (DWELT). Due to the multiple phenomena affecting the propagation of radio signals, RSSI measurements show fluctuations that hinder the utilization of straightforward positioning mechanisms from widely known propagation loss models. Instead, DWELT uses data processing of raw RSSI values and applies a weighted posterior-probabilistic evolution for quick convergence of localization and tracking. In this paper, we present the first implementation of DWELT, intended for 1D location (applicable to tunnels or corridors), and the first step towards a more generic implementation. Simulations and experiments show an accuracy of 1m in more than 81% of the cases, and less than 2m in the 95%.

Designing efficient routing protocols for a wireless sensor network with mobile sinks (mWSN) is a challenging task since the network topology and data paths change frequently as sink nodes move. In this paper, we design a novel lightweight reactive ring based routing protocol called R3, which removes the need of proactively maintaining data paths to mobile sinks as they move in the network. To achieve high packet delivery ratio and low transmission cost, R3 combines ring based forwarding and trail based forwarding together. To support efficient ring based forwarding, we build a ring based structure for a network in a way such that each node in the network can easily obtain its ring ID and virtual angle information. For this purpose, we artificially create a virtual hole in the central area of the network and accordingly find a shortest cycled path enclosing the hole, which serves as base ring and is used for generating the remaining ring based structure. We accordingly present the detailed design description for R3, which only requires each node to keep very limited routing information. We derive the communication overhead by ring based forwarding. Extensive simulation results show that R3 can achieve high routing performance as compared with existing work.

Few samples face recognition has become a highly challenging task due to the limitation of available labeled samples. As two popular paradigms in face image representation, sparse component analysis is highly robust while parts-based paradigm is particularly flexible. In this paper, we propose a probabilistic generative model to incorporate the strengths of the two paradigms for face representation. This model finds a common spatial partition for given images and simultaneously learns a sparse component analysis model for each part of the partition. The two procedures are built into a probabilistic generative model. Then we derive the score function (i.e. feature mapping) from the generative score space. A similarity measure is defined over the derived score function for few samples face recognition. This model is driven by data and specifically good at representing face images. The derived generative score function and similarity measure encode information hidden in the data distribution. To validate the effectiveness of the proposed method, we perform few samples face recognition on two face datasets. The results show its advantages.

In this article, a video based fire detection framework for CCTV surveillancesystems is presented. Two novel features and a novel image type with their corresponding algorithmsareproposed for this purpose. One is for the slow-smoke detection and another one is for fast-smoke/flame detection. The basic idea is slow-smoke has a highly varying chrominance/luminance texture in long periods and fast-smoke/flame has a highly varying texture waiting at the same location for long consecutive periods. Experiments with a large number of smoke/flame and non-smoke/flame video sequences outputs promising results in terms of algorithmic accuracy and speed.

In computer vision, salient object is important to extract the useful information of foreground. With active contour analysis acting as the core in this paper, we propose a bottom-up saliency detection algorithm combining with the Bayesian model and the global color distribution. Under the supports of active contour model, a more accurate foreground can be obtained as a foundation for the Bayesian model and the global color distribution. Furthermore, we establish a contour-based selection mechanism to optimize the global-color distribution, which is an effective revising approach for the Bayesian model as well. To obtain an excellent object contour, we firstly intensify the object region in the source gray-scale image by a seed-based method. The final saliency map can be detected after weighting the color distribution to the Bayesian saliency map, after both of the two components are available. The contribution of this paper is that, comparing the Harris-based convex hull algorithm, the active contour can extract a more accurate and non-convex foreground. Moreover, the global color distribution can solve the saliency-scattered drawback of Bayesian model, by the mutual complementation. According to the detected results, the final saliency maps generated with considering the global color distribution and active contour are much-improved.

Mobile cloud computing (MCC) has revolutionized the way in which the services can be obtained from the cloud service providers. Manifold increase in the number of mobile devices and subscribers in MCC has further enhanced the need of an efficient and robust authentication solution. Earlier, the subscribers could get cloud-computing services from the cloud service providers only after having consulted the trusted third party. Recently, Tsai and Lo has proposed a multi-server authenticated key agreement solution for MCC based on bilinear pairing, to eliminate the trusted third party for mutual authentication. The scheme has been novel as far as the minimization of trusted party involvement in authenticating the user and service provider, is concerned. However, the Tsai and Lo scheme has been found vulnerable to server spoofing attack (misrepresentation attack), de-synchronization attack and denial-of-service attack, which renders the scheme unsuitable for practical deployment in different wireless mobile access networks. Therefore, we have proposed an improved model based on bilinear pairing, countering the identified threats posed to Tsai and Lo scheme. Besides, the proposed work also demonstrates performance evaluation and formal security analysis.

In this paper, we introduce a new concept called generalized ring signcryption (GRSC), which can achieve ring signature and ring signcryption functions with only one key pair and one algorithm. It is very useful for a system which has a large number of users, or has limited storage space, or whose function requirements may be changed later. We give a formal definition and a security model of GRSC and propose a concrete scheme based on bilinear pairings. In the random oracle model, the scheme's confidentiality can be proved under the GBDH assumption, and its unforgeability can be proved under GDH' assumption, and what is more, this scheme also allows unconditional anonymity. Compared with other identity-based ring signcryption schemes that use bilinear pairings as well, our scheme is a highly efficient one.

Multi-server authentication enables the subscribers to enjoy an assortment of services from various service providers based on a single registration from any registration centre. Previously, a subscriber had to register from each service provider individually to avail respective services relying on single server authentication. In the past, a number of multi-server authentication techniques can be witnessed that employed lightweight and even computationally intensive cryptographic operations. In line with this, Zhu has presented a chaotic map based multi-server authentication scheme recently, which is not only vulnerable to denial-of-service attack, stolen-verifier attack, but also lacks anonymity. This research aims at improving the Zhu's protocol in terms of cost and efficiency. Moreover, the comparative study is presented for the performance of improved model against the existing scheme, and the security of proposed model is formally proved using BAN Logic.

Security is one of the major challenges in the Wireless Sensor Networks (WSNs). WSNs are more vulnerable to adversarial activities. All cryptographic security services indirectly depend on key management. Symmetric key management is the best key establishment process for WSNs due to the resource constraints of the sensors. In this paper, we proposed dynamic session key establishment scheme based on randomly generated nonce value and sensor node identity, in which each sensor node is equipped with session key on expire basis. The proposed scheme is compare with five popular existing key management systems. Our scheme is simulated in OMNET++ with MixiM and presented experimental results. The analytical study and experimental results show the superiority of the proposed scheme over the existing schemes in terms of energy, storage, resilience and communication overhead.

Different from traditional auctions, electronic auctions provide a platform to allow bidders and auctioneers merchandise to each other over network anytime and anywhere. Auctioneers can publish information of goods, and bidders can choose the interested targets through this bidding platform. To ensure the fairness and security of electronic auctions, Li et al. have proposed a practical electronic auction scheme which can confirm the requirement of strong anonymity, bidding privacy, and secret bidding price. However, we have found out that Li et al.'s scheme may lurk the risk of the denial-of-service attack during the bidding phase in a sealed-bid auction. Thus, we propose a brand-new sealed-bid auction mechanism, in which the essentials of e-auction can be firmly preserved. In particular, each bidder only needs to register at the center once and then can join to multiple plays launched by different auctioneers. Moreover, the correctness of mutual authentication is confirmed according to the BAN logic model.

The detection accuracy of steganalysis depends on many factors, including the embedding algorithm, the payload size, the steganalysis feature space and the properties of the cover source. In practice, the cover source mismatch (CSM) problem has been recognized as the single most important factor negatively affecting the performance. To address this problem, we propose a new framework for blind, universal steganalysis which uses traditional steganalyst features. Firstly, cover images with the same statistical properties are searched from a reference image database as aided samples. The test image and its aided samples form a whole test set. Then, by assuming that most of the aided samples are innocent, we conduct outlier detection on the test set to judge the test image as cover or stego. In this way, the framework has removed the need for training. Hence, it does not suffer from cover source mismatch. Because it performs anomaly detection rather than classification, this method is totally unsupervised. The results in our study show that this framework works superior than one-class support vector machine and the outlier detector without considering the image retrieval process.