The fault-tolerance routing problem is one of the most important issues in the application of the Internet of Things, and has been attracting growing research interests. In order to maintain the communication paths from source sensors to the macronodes, we present a hybrid routing scheme and model, in which alternate paths are created once the previous routing is broken. Then, we propose an improved efficient and intelligent fault-tolerance algorithm (IEIFTA) to provide the fast routing recovery and reconstruct the network topology for path failure in the Internet of Things. In the IEIFTA, mutation direction of the particle is determined by multi-swarm evolution equation, and its diversity is improved by the immune mechanism, which can improve the ability of global search and improve the converging rate of the algorithm. The simulation results indicate that the IEIFTA-based fault-tolerance algorithm outperforms the EARQ algorithm and the SPSOA algorithm due to its ability of fast routing recovery mechanism and prolonging the lifetime of the Internet of Things.

Dynamic spectrum sharing is a key technology to improve spectrum utilization in wireless networks. The elastic spectrum management provides a new opportunity for licensed primary users and unlicensed secondary users to efficiently utilize the scarce wireless resource. In this paper, we present a game-theoretic framework for dynamic spectrum allocation where the primary users rent the unutilized spectrum to the secondary users for a monetary profit. In reality, due to the ON-OFF behavior of the primary user, the quantity of spectrum that can be opportunistically shared by the secondary users is limited. We model this situation with the renewal theory and formulate the spectrum pricing scheme with the Bertrand game, taking into account the scarcity of the spectrum. By the Nash-equilibrium pricing scheme, each player in the game continually converges to a strategy that maximizes its own profit. We also investigate the impact of several properties, including channel quality and spectrum substitutability. Based on the equilibrium analysis, we finally propose a decentralized algorithm that leads the primary users to the Nash-equilibrium, called DST. The stability of the proposed algorithm in terms of convergence to the Nash equilibrium is also studied.

Due to the low utilization and scarcity of frequency spectrum in current spectrum allocation methodology, cognitive radio networks (CRNs) have been proposed as a promising method to solve the problem, of which spectrum sensing is an important technology to utilize the precious spectrum resources. In order to protect the primary user from being interfered, most of the related works focus only on the restriction of the missed detection probability, which may causes over-protection of the primary user. Thus the interference probability is defined and the interference-aware sensing model is introduced in this paper. The interference-aware sensing model takes the spatial conditions into consideration, and can further improve the network performance with good spectrum reuse opportunity. Meanwhile, as so many fading factors affect the spectrum channel, errors are inevitably exist in the reporting channel in cooperative sensing, which is improper to be ignored. Motivated by the above, in this paper, we study the throughput tradeoff for interference-aware cognitive radio networks over imperfect reporting channel. For the cooperative spectrum sensing, the K-out-of-N fusion rule is used. By jointly optimizing the sensing time and the parameter K value, the maximum throughput can be achieved. Theoretical analysis is given to prove the feasibility of the optimization and computer simulations also shows that the maximum throughput can be achieved when the sensing time and the parameter of K value are both optimized.

With the extension of wireless technology, vehicular ad hoc networks provide important services for the dissemination of general data and emergency warnings. However, since, the vehicle topology frequently changes from a dense to a sparse network depending on the speed of the moving vehicles and the time of day, vehicular ad hoc networks require a protocol that can facilitate the efficient and reliable dissemination of emergency messages in a highly mobile environment under dense or intermittent vehicular connectivity. Therefore, this paper proposes a new vehicular broadcast protocol, called BL-CAST, that can operate effectively in both dense and sparse network scenarios. As a low overhead multi-hop broadcast protocol, BL-CAST does not rely on the periodic exchange of beacons for updating location information. Instead, the location information of a vehicle is included in a broadcast message to identify the last rebroadcasting vehicle in an intermittently connected network. Simulation results show that BL-CAST outperforms the DV-CAST protocol in terms of the end-to-end delay, message delivery ratio and network overhead.

In wireless sensor networks (WSNs), hierarchical clustering is an efficient approach for lower energy consumption and extended network lifetime. In cluster-based multi-hop communications, a cluster head (CH) closer to the sink is loaded heavier than those CHs farther away from the sink. In order to balance the energy consumption among CHs, we development a novel cluster-based routing protocol for corona-structured wireless sensor networks. Based on the relaying traffic of each CH conveys, adequate radius for each corona can be determined through nearly balanced energy depletion analysis, which leads to balanced energy consumption among CHs. Simulation results demonstrate that our clustering approach effectively improves the network lifetime, residual energy and reduces the number of CH rotations in comparison with the MLCRA protocols.

As one of the new self-organizing and self-configuration broadband networks, wireless mesh networks are being increasingly attractive. In order to solve the load balancing problem in wireless mesh networks, this paper proposes a novel multi-path routing algorithm based on clustering (Cluster_MMesh) for wireless mesh networks. In the clustering stage, on the basis of the maximum connectivity clustering algorithm and k-hop clustering algorithm, according to the idea of maximum connectivity, a new concept of node connectivity degree is proposed in this paper, which can make the selection of cluster head more simple and reasonable. While clustering, the node which has less expected load in the candidate border gateway node set will be selected as the border gateway node. In the multi-path routing establishment stage, we use the intra-clustering multi-path routing algorithm and inter-clustering multi-path routing algorithm to establish multi-path routing from the source node to the destination node. At last, in the traffic allocation stage, we will use the virtual disjoint multi-path model (Vdmp) to allocate the network traffic. Simulation results show that the Cluster_MMesh routing algorithm can help increase the packet delivery rate, reduce the average end to end delay, and improve the network performance.

In the field of visible light communication (VLC), light-emitting diodes (LEDs) are used for transmitting data via visible light. In this study, we analyze pulse dual slope modulation (PDSM) as a means of delivering information in VLC. PDSM involves the modulation of symmetrical slope pulses to encode binary 0s and 1s, and owing to the moderately increasing and decreasing pulse shapes that are created, this method enables more spectral efficiency than the variable pulse position modulation (VPPM) technique currently adopted in IEEE 802.15.7. In particular, PDSM allows for the avoidance of intra-frame flicker by providing idle pulses in a spectrum-efficient way. A simple detection scheme is proposed for PDSMsignals, and its bit error rate (BER) is analyzed mathematically at varying slopes to validate the process through simulation. The BER performance of PDSM detection using dual sampling is compared to the performances of PDSM and VPPM using correlation detection. It is found that, when the probability of idle pulse transmission is less than 0.08 and higher than 0, the BER of dual sampling PDSM is lower than that of PDSM using correlation detection over the entire light intensity range.

This paper proposes a space-polarization division multiple access (SPDMA) system that has limited feedback channels. The system simultaneously serves data streams to multiple mobile users through dual-polarized antenna arrays, by using pre-determined sets of precoding vectors that are orthogonal in both space and polarization domains. To this end, a codebook whose elements are sets of the precoding vectors is systematically designed based on the discrete Fourier transform (DFT) matrix and considering the power imbalance of polarized channels. Throughput of the SPDMA system is evaluated and compared to that of space division multiple access (SDMA) system, according to the various parameters including cross polarization discrimination (XPD). The results show that the throughput of SPDMA system outperforms that of SDMA in the environments of high XPD with many mobile users.

With the exhaustion of global IPv4 addresses, IPv6 technologies have attracted increasing attentions, and have been deployed widely. Meanwhile, new applications running over IPv6 networks will change the traditional traffic characteristics obtained from IPv4 networks. Traditional models obtained from IPv4 cannot be used for IPv6 network monitoring directly and there is a need to investigate those changes. In this paper, we explore the flow features of IPv6 traffic and compare its difference with that of IPv4 traffic from flow level. Firstly, we analyze the differences of the general flow statistical characteristics and users' behavior between IPv4 and IPv6 networks. We find that there are more elephant flows in IPv6, which is critical for traffic engineering. Secondly, we find that there exist many one-way flows both in the IPv4 and IPv6 traffic, which are important information sources for abnormal behavior detection. Finally, in light of the challenges of analyzing massive data of large-scale network monitoring, we propose a group flow model which can greatly reduce the number of flows while capturing the primary traffic features, and perform a comparative measurement analysis of group users' behavior dynamic characteristics. We find there are less sharp changes caused by abnormity compared with IPv4, which shows there are less large-scale malicious activities in IPv6 currently. All the evaluation experiments are carried out based on the traffic traces collected from the Northwest Regional Center of CERNET (China Education and Research Network), and the results reveal the detailed flow characteristics of IPv6, which are useful for traffic management and anomaly detection in IPv6.

In recent years, the problem of spectrum mobility in Cognitive Radio (CR) Networks has been widely investigated. In order to utilize spectrum resources completely, many spectrum handoff techniques based on game theory have been proposed, but most studies only concern that users how to achieve better payoffs, without much attention to the diverse needs of users. In this paper, we propose a new channel-switching model based on game theory, using a prioritized approach to meet the diverse needs of users in two different modes (CQ and PS). At the same time, this paper proposes some acceleration techniques to reach the Nash equilibrium more efficiently. We evaluate the performance of the proposed schemes depending on priority using real channel availability measurements, and conclude that the channel quality function (CQ) mode provide better service for priority user but the plan-sorting (PS) mode can be more suitable in multiple priority users exist scene.

Mobile traffic is increasing a masse because of the propagation of the Internet and the development of wireless mobile technology. Accordingly, the Network Local Mobility Management (NETLMM) working group [1] of the Internet Engineering Task Force (IETF) has standardized Proxy Mobile IPv6 (PMIPv6) [2] as a protocol for accomplishing the transmissibility of mobile terminals. PMIPv6 is a network-led IP-based mobility management protocol, which can control terminal mobility without depending on the type of access system or the capability of the terminal. By combining PMIPv6 and the mobility of Session Initiation Protocol (SIP), we can establish terminal mobility and session mobility through a more effective route. The mobility function can be improved and the overlap of function reduced as compared to that in the case of independent operation. PMIPv6 is appropriate for a non-real-time service using TCP, and SIP is appropriate for a real-time service using RTP/UDP. Thus, in the case of a terminal using both services, an effective mobility management is possible only by using PMIPv6 together with SIP. In order to manage mobility in this manner, researches on PMIPv6-SIP are in progress. In line with this trend, this paper suggests a new PMIPv6-SIP architecture where when a mobile terminal conducts a handover, a network-led handover while maintaining the session without the addition of a special function or middleware is possible along with effective performance evaluation through mathematical modeling by comparing the delay and the packet loss that occur during the handover to the Pure-SIP.

Three-dimensional multiple-input multiple-output (3D MIMO) and large-scale MIMO are two promising technologies for upcoming high data rate wireless communications, since the inter-user interference can be reduced by exploiting antenna vertical gain and degree of freedom, respectively. In this paper, we derive the achievable sum rate of 3D MIMO systems employing zero-forcing (ZF) receivers, accounting for log-normal shadowing fading, path-loss and antenna gain. In particular, we consider the prevalent log-normal model and propose a novel closed-form lower bound on the achievable sum rate exploiting elevation features. Using the lower bound as a starting point, we pursue the "large-system" analysis and derive a closed-form expression when the number of antennas grows large for fixed average transmit power and fixed total transmit power schemes. We further model a high-building with several floors. Due to the floor height, different floors correspond to different elevation angles. Therefore, the asymptotic achievable sum rate performances for each floor and the whole building considering the elevation features are analyzed and the effects of tilt angle and user distribution for both horizontal and vertical dimensions are discussed. Finally, the relationship between the achievable sum rate and the number of users is investigated and the optimal number of users to maximize the sum rate performance is determined.

This paper investigates optimal relay selection and power allocation under an aggregate power constraint for cooperative wireless sensor networks assisted by amplify-and-forward relay nodes. By considering both transmission power and circuit power consumptions, the received signal-to-noise ratio (SNR) at the destination node is calculated, based on which, a relay selection and power allocation scheme is developed. The core idea is to adaptively adjust the selected relays and their transmission power to maximize the received SNR according to the channel state information. The proposed scheme is derived by recasting the optimization problem into a three-layered problem-determining the number of relays to be activated, selecting the active relays, and performing power allocation among the selected relays. Monte Carlo simulation results demonstrate that the proposed scheme provides a higher received SNR and a lower bit error rate as compared to the average power allocation scheme.

Multi-mode device which combines multiple access technologies into a device will offer more cost-effective solution than a sole access implementation. Its concurrent multipath transfer (CMT) technology can transmit media flows over multiple end-to-end paths simultaneously, which is essential to select at least two paths from all available paths. At real networks, different paths are likely to overlap each other and even share bottleneck, which can weaken the path diversity gained through CMT. Spurred by this observation, it is necessary to select multiple independent paths as much as possible to avoid underlying shared bottleneck between topologically joint paths. Recent research in this context has shown that different paths with shared bottleneck can weaken the path diversity gained through CMT. In our earlier work, a grouping-based multipath selection (GMS) mechanism is introduced and developed. However, how to estimating the selection is still to be resolved. In this paper, we firstly introduce a Selection Correctness Index (SCI) to evaluate the correctness of selection results in actual CMT experiment. Therefore, this metric is helpful to discuss and validate the accuracy of the output paths. From extensive experiments with a realized prototype, the proposed scheme provides better evaluation tool and criterion in various network conditions.

Two-tier femtocell networks, consisting of a conventional cellular network underlaid with femtocell hotspots, play an important role in the indoor coverage and capacity of cellular networks. However, the cross- and co-tier interference will cause an unacceptable quality of service (QoS) for users with universal frequency reuse. In this paper, we propose a novel downlink interference mitigation strategy for spectrum-shared two-tier femtocell networks. The proposed solution is composed of three parts. The first is femtocells clustering, which maximizes the distance between femtocells using the same slot resource to mitigate co-tier interference. The second is to assign macrocell users (MUEs) to clusters by max-min criterion, by which each MUE can avoid using the same resource as the nearest femtocell. The third is a novel adaptive power control scheme with femtocells downlink transmit power adjusted adaptively based on the signal to interference plus noise ratio (SINR) level of neighboring users. Simulation results show that the proposed scheme can effectively increase the successful transmission ratio and ergodic capacity of femtocells, while guaranteeing QoS of the macrocell.

Packet classification is a key technology of the Internet for routers to classify the arriving packets into different flows according to the predefined rulesets. Previous packet classification algorithms have mainly focused on search speed and memory usage, while overlooking update performance. In this paper, we propose PreCuts, which can drastically improve the update speed. According to the characteristics of IP field, we implement three heuristics to build a 3-layer decision tree. In the first layer, we group the rules with the same highest byte of source and destination IP addresses. For the second layer, we cluster the rules which share the same IP prefix length. Finally, we use the heuristic of information entropy-based bit partition to choose some specific bits of IP prefix to split the ruleset into subsets. The heuristics of PreCuts will not introduce rule duplication and incremental update will not reduce the time and space performance. Using ClassBench, it is shown that compared with BRPS and EffiCuts, the proposed algorithm not only improves the time and space performance, but also greatly increases the update speed.

It is well known that sparse code is effective for feature extraction of face recognition, especially sparse mode can be learned in the kernel space, and obtain better performance. Some recent algorithms made use of single kernel in the sparse mode, but this didn't make full use of the kernel information. The key issue is how to select the suitable kernel weights, and combine the selected kernels. In this paper, we propose a novel multiple kernel sparse representation based classification for face recognition (MKSRC), which performs sparse code and dictionary learning in the multiple kernel space. Initially, several possible kernels are combined and the sparse coefficient is computed, then the kernel weights can be obtained by the sparse coefficient. Finally convergence makes the kernel weights optimal. The experiments results show that our algorithm outperforms other state-of-the-art algorithms and demonstrate the promising performance of the proposed algorithms.

Automated activity monitoring has become important in many applications. In particular, automated monitoring is an important issue in large-scale management of group-housed livestock because it can save a significant part of farm workers' time or minimize the damage caused by livestock problems. In this paper, we propose an automated solution for measuring the daily-life activities of pigs by using video data in order to manage the group-housed pigs. Especially, we focus on the circadian rhythm of group-housed pigs under windowless and 24-hour light-on conditions. Also, we derive a cost-effective solution within the acceptable range of quality for the activity monitoring application. From the experimental results with the video monitoring data obtained from two pig farms, we believe our method based on circadian rhythm can be applied for detecting management problems of group-housed pigs in a cost-effective way.

This paper proposes a novel blind image watermarking scheme exploiting Block Truncation Coding (BTC). Most of existing BTC-based watermarking or data hiding methods embed information in BTC compressed images by modifying the BTC encoding stage or BTC-compressed data, resulting in watermarked images with bad quality. Other than existing BTC-based watermarking schemes, our scheme does not really perform the BTC compression on images during the embedding process but uses the parity of BTC quantization data to guide the watermark embedding and extraction processes. In our scheme, we use a binary image as the original watermark. During the embedding process, the original cover image is first partitioned into non-overlapping $4{\times}4$ blocks. Then, BTC is performed on each block to obtain its BTC quantized high mean and low mean. According to the parity of high mean and the parity of low mean, two watermark bits are embedded in each block by modifying the pixel values in the block to make sure that the parity of high mean and the parity of low mean in the modified block are equal to the two watermark bits. During the extraction process, BTC is first performed on each block to obtain its high mean and low mean. By checking the parity of high mean and the parity of low mean, we can extract the two watermark bits in each block. The experimental results show that the proposed watermarking method is fragile to most image processing operations and various kinds of attacks while preserving the invisibility very well, thus the proposed scheme can be used for image authentication.