Cooperative diversity is a technique with which a virtual multiple antenna array is established among the single antenna users of the wireless network to realize space diversity. Signal space diversity (SSD) is a bandwidth-efficient diversity technique, which uses constellation rotation and interleaving techniques to achieve diversity gain. A new cooperative diversity scheme with rotated constellations (RCCD) is proposed in this paper. In this scheme, data are modulated by using a rotated constellation, and the source and the relays transmit different components of the modulated symbols. Since any one of the components contains full information of the symbols, the destination can obtain multiple signals conveying the same information from different users. In this way, space diversity is achieved. The RCCD scheme inherits the advantage of SSD - being bandwidth-efficient but without the delay problem of SSD brought by interleaving. The symbol error rate of the RCCD scheme is analyzed and simulated. The analysis and simulation results show that the RCCD scheme can achieve full diversity order of two when the inter-user channel is good enough, and, with the same bandwidth efficiency, has a better performance than amplify-and-forward and detect-and-forward methods.

In this paper, a cross-layer resource allocation mechanism is proposed for wireless multimedia service. In particular, a game theory based on quality of service (QoS) for multimedia users is introduced to deal with the fairness of network resource allocation in wireless networks. Moreover, the channel states of wireless users are additionally regarded under the cross-layer design in WiMAX environment. In details, the bargaining solution is adopted to discover the efficient and fair resource allocation strategy for multimedia service in considering QoS in the peak signal-to-noise ratio (PSNR) and the channel states in the carrier-to-interface ratio (CINR). The proposed mechanism is illustrated and evaluated by simulation results of transmitting video sequences in WiMAX environment.

In cognitive radio networks, cooperative spectrum sensing schemes are proposed to improve the performance of detecting licensees by secondary users. Commonly, the cooperative sensing can be realized by means of hard decision fusion (HDF) or soft decision fusion (SDF) schemes. The SDF schemes are superior to the HDF ones in terms of the detection performance whereas the HDF schemes are outperforming the SDF ones when the traffic overhead is taken into account. In this paper, a hybrid SFD-HDF cluster-based approach is developed to jointly exploit the advantages of SFD and HDF schemes. Different SDF schemes have been proposed and compared within a given cluster whereas the OR-rule base HDF scheme is applied to combine the decisions reported by cluster headers to a common receiver or base station. The computer simulations show promising results as the performance of the proposed scenario of hybridizing soft and hard fusion schemes is significantly outperforming other different combinations of conventional SDF and HDF schemes while it noticeably reduces the network traffic overhead.

Cooperative spectrum sensing (CSS) is an effective technology for alleviating the unreliability of local spectrum sensing due to fading/shadowing effects. Unlike most existing solutions, this paper considers the use of CSS technology in decentralized networks where a fusion center is not available. In such a decentralized network, some attackers may sneak into the ranks of cooperative users. On the basis of recent advances in bio-inspired consensus algorithms, an attack-proof, decentralized CSS scheme is proposed in which all secondary users can maintain cooperative sensing by exchanging information locally instead of requiring centralized control or data fusion. Users no longer need any prior knowledge of the network. To counter three potential categories of spectrum sensing data falsification (SSDF) attacks, some anti-attack strategies are applied to the iterative process of information exchange. This enables most authentic users to exclude potentially malicious users from their neighborhood. As represented by simulation results, the proposed scheme can generally ensure that most authentic users reach a consensus within the given number of iterations, and it also demonstrates much better robustness against different SSDF attacks than several existing schemes.

Vehicle ad hoc networks (VANET) are one of the most important technologies to provide various ITS services. While VANET requires rapid and reliable transmission, packet transmission in VANET is unstable because of high mobility. Many routing protocols have been proposed and assessed to improve the efficiency of VANET. However, topology-based routing protocols generate heavy overhead and long delay, and position-based routing protocols have frequent packet loss due to inaccurate node position. In this paper, we propose a position-based routing repair algorithm to improve the efficiency of VANET. This algorithm is proposed based on the premise that AODV (-PGB) can be used effectively in VANET, if the discovery, maintenance and repair mechanism of AODV is optimized for the features of VANET. The main focus of this algorithm is that the relay node can determine whether its alternative node exits and judge whether the routing path is disconnected. If the relay node is about to swerve from the routing path in a multi-hop network, the node recognizes the possibility of path loss based on a defined critical domain. The node then transmits a handover packet to the next hop node, alternative nodes and previous node. The next node repairs the alternative path before path loss occurs to maintain connectivity and provide seamless service. We simulated protocols using both the ideal traffic model and the realistic traffic model to assess the proposed algorithm. The result shows that the protocols that include the proposed algorithm have fewer path losses, lower overhead, shorter delay and higher data throughput compared with other protocols in VANET.

Well organized and easy usable Grid management system is very important for executing various Grid applications and managing Grid computing environment. Moreover, information system which can support Grid management system by providing various Grid environment related information is also one of the most interesting issue in the Grid middleware system area. Effective cooperation between Grid management system and information system can make a novel Grid middleware system. Especially, service oriented architecture based Grid management system is flexible and extensible for providing various type of Grid services. Also, information system based on data mining process which comprises various different kinds of domains such as users, resources and applications can make Grid management system more precise and efficient. In this paper, we propose semantic Grid middleware system which is a combination of Grid management system and semantic information system.

An inseparable challenge associated with every random access network is the design of an efficient Collision Resolution Algorithm (CRA), since collisions cannot be completely avoided in such network. To maximize the collision resolution efficiency of a popular CRA, namely Binary Exponential Backoff (BEB), we propose a reactive backoff algorithm. The proposed backoff algorithm is reactive in the sense that it updates the contention window based on the previously selected backoff value in the failed contention stage to avoid a typical type of collision, referred as cross-collision. Cross-collision would occur if the contention slot pointed by the currently selected backoff value appeared to be present in the overlapped portion of the adjacent (the previous and the current) windows. The proposed reactive algorithm contributes to significant performance improvements in the network since it offers a supplementary feature of Cross Collision Exclusion (XCE) and also retains the legacy collision mitigation features. We formulate a Markovian model to emulate the characteristics of the proposed algorithm. Based on the solution of the model, we then estimate the throughput and delay performances of WLAN following the signaling mechanisms of the Distributed Coordination Function (DCF) considering IEEE 802.11b system parameters. We validate the accuracy of the analytical performance estimation framework by comparing the analytically obtained results with the results that we obtain from the simulation experiments performed in ns-2. Through the rigorous analysis, based on the validated model, we show that the proposed reactive cross collision exclusionary backoff algorithm significantly enhances the throughput and reduces the average packet delay in the network.

In this paper, a new forward error correction (FEC) protocol is proposed for point-to-multipoint satellite links. Link-layer error control protocols in point-to-multipoint satellite links impose several problems such as unreliability and receiver-heterogeneity. To resolve the problem of heterogeneous error rates at different receivers, the proposed scheme exploits multiple multicast channels to which each receiver tunes. The more channels a receiver tunes to, the more powerful error correcting capability it achieves. Based on its own channel condition, each receiver tunes to as many channels as it needs, which prevents from receiving unwanted parities. Furthermore, each receiver saves the decoding time, processing overhead, and processing energy. Performance evaluation shows that the proposed scheme guarantees the target PER while saving energy. The proposed technique is highly adaptive to the channel variation with respect to the throughput efficiency, and provides scalable PER and throughput efficiency.

Energy balanced consumption routing is based on assumption that the nodes consume energy both in transmitting and receiving. Lopsided energy consumption is an intrinsic problem in low-cost sensor networks characterized by multihop routing and in many traffic overhead pattern networks, and this irregular energy dissipation can significantly reduce network lifetime. In this paper, we study the problem of maximizing network lifetime through balancing energy consumption for uniformly deployed low-cost sensor networks. We formulate the energy consumption balancing problem as an optimal balancing data transmitting problem by combining the ideas of corona cluster based network division and optimized transmitting state routing strategy together with data transmission. We propose a localized cluster based routing scheme that guarantees balanced energy consumption among clusters within each corona. We develop a new energy cluster based routing protocol called "OECR". We design an offline centralized algorithm with time complexity O (log n) (n is the number of clusters) to solve the transmitting data distribution problem aimed at energy balancing consumption among nodes in different cluster. An approach for computing the optimal number of clusters to maximize the network lifetime is also presented. Based on the mathematical model, an optimized energy cluster routing (OECR) is designed and the solution for extending OEDR to low-cost sensor networks is also presented. Simulation results demonstrate that the proposed routing scheme significantly outperforms conventional energy routing schemes in terms of network lifetime.

Recently, due to the prevalence of various mobile devices and wireless broadband networks, there has been a significant increase in interest and demand for multimedia streaming services such as the mobile IPTV. In such a wireless broadband network, transmitting a continuous stream of multimedia data is difficult to achieve due to mobile stations (MSs) movement. Providing Quality of Service (QoS) for multimedia video streaming applications requires the server and/or client to be network-aware and adaptive. Therefore, in order to deploy a mobile IPTV service in wireless broadband networks, offering users efficient wireless resource utilization and seamlessly offering user perceived QoS are important issues. In this paper, we propose a new adaptive streaming scheme, called MARC (Mobile-aware Adaptive Rate Control), which adjusts the quality of bit-stream and transmission rate of video streaming based on the wireless channel status and network status. The proposed scheme can control the rate of multimedia streaming to be suitable for the wireless channel status by using awareness information of the wireless channel quality and the mobile station location. The proposed scheme can provide a seamless multimedia playback service in wireless broadband networks in addition to improving the QoS of multimedia streaming services. The proposed MARC scheme alleviates the discontinuity of multimedia playback and allocates a suitable client buffer to the wireless broadband network. The simulation results demonstrate the effectiveness of our proposed scheme.

In this paper, we present and compare two different multiple camera collaboration strategies to reduce false association in finding the correspondence of objects. Collaboration matrices are defined with the required minimum separation for an effective collaboration because homographic lines for objects association are ineffective with the insufficient separation. The first strategy uses the collaboration matrices to select the best pair out of many cameras having the maximum separation to efficiently collaborate on the object association. The association information in selected cameras is propagated to unselected cameras by the global information constructed from the associated targets. While the first strategy requires the long operation time to achieve the high association rate due to the limited view by the best pair, it reduces the computational cost using homographic lines. The second strategy initiates the collaboration process of objects association for all the pairing cases of cameras regardless of the separation. In each collaboration process, only crossed targets by a transformed homographic line from the other collaborating camera generate homographic lines. While the repetitive association processes improve the association performance, the transformation processes of homographic lines increase exponentially. The proposed methods are evaluated with real video sequences and compared in terms of the computational cost and the association performance. The simulation results demonstrate that the proposed methods effectively reduce the false association rate as compared with basic pair-wise collaboration.

As visual surveillance systems gain wider usage in a variety of fields, it is important that they are capable of interpreting scenes automatically, also known as "human motion analysis" (HMA). However, existing HMA methods are too domain specific and computationally expensive. This paper proposes a general purpose HMA method that is based on the idea that human beings tend to exhibit erratic motion patterns during abnormal situations. Limb movements are characterized using the statistics of angular and linear displacements. In addition, the method is enhanced via the use of the entropy of the Fourier spectrum to measure the randomness of subject's motions. Various experiments have been conducted and the results indicate that the proposed method has very high classification accuracy in identifying anomalous behavior.

Three dimensional (3D) video is expected to be an important application for broadcast and IP streaming services. One of the main limitations for the transmission of 3D video over IP networks is network bandwidth mismatch due to the large size of 3D data, which causes fatal decoding errors and mosaic-like damage. This paper presents a novel selective frame discard method to address the problem. The main idea of the proposed method is the symmetrical discard of the two dimensional (2D) video frame and the depth map frame. Also, the frames to be discarded are selected after additional consideration of the playback deadline, the network bandwidth, and the inter-frame dependency relationship within a group of pictures (GOP). It enables the efficient utilization of the network bandwidth and high quality 3D IPTV service. The simulation results demonstrate that the proposed method enhances the media quality of 3D video streaming even in the case of bad network conditions.

In this paper, we propose an improved distributed multi-view video coding method that is robust to illumination changes among different views. The use of view dependency is not effective for multi-view video because each view has different intrinsic and extrinsic camera parameters. In this paper, a modified distributed multi-view coding method is presented that applies illumination compensation when generating side information. The proposed encoder codes DC values of discrete cosine transform (DCT) coefficients separately by entropy coding. The proposed decoder can generate more accurate side information by using the transmitted DC coefficients to compensate for illumination changes. Furthermore, AC coefficients are coded with conventional entropy or channel coders depending on the frequency band. We found that the proposed algorithm is about 0.1~0.5 dB better than conventional algorithms.

This paper proposes an intelligent technique for data sharing and event transition among personal devices including smart phones, laptops, and desktops. We implemented the PES (Personal Event Service) system that proactively executes appropriate tasks across multiple devices without explicit user requests by sharing the data used by the user and recognizing user intention based on the observed actions of the user for specific devices. The client module of PES installed on each device monitors the user actions and recognizes the intention of the user. The server provides data sharing and maintenance for clients. The connection between client and server is established by Java RMI (Remote Method Invocation). A series of experiments were performed to evaluate user satisfaction and system accuracy, and the results showed that the PES system can proactively provide appropriate, personalized services with a high degree of satisfaction to the user in an effective and efficient manner.

In this paper, we propose a new affine shape adaptation scheme for the affine invariant feature detector, in which the convergence stability is still an opening problem. This paper examines the relation between the integration scale matrix of next iteration and the current second moment matrix and finds that the convergence stability of the method can be improved by adjusting the relation between the two matrices instead of keeping them always proportional as proposed by previous methods. By estimating and updating the shape of the integration kernel and differentiation kernel in each iteration based on the anisotropy of the current second moment matrix, we propose a coarse-to-fine affine shape adaptation scheme which is able to adjust the pace of convergence and enable the process to converge smoothly. The feature matching experiments demonstrate that the proposed approach obtains an improvement in convergence ratio and repeatability compared with the current schemes with relatively fixed integration kernel.

Immune-inspired intrusion detection is a promising technology for network security, and well known for its diversity, adaptation, self-tolerance, etc. However, scalability and coverage are two major drawbacks of the immune-inspired intrusion detection systems (IIDSes). In this paper, we propose an IIDS framework, named GEP-IIDS, with improved basic system elements to address these two problems. First, an additional bio-inspired technique, gene expression programming (GEP), is introduced in detector (corresponding to detection rules) representation. In addition, inspired by the avidity model of immunology, new avidity/affinity functions taking the priority of attributes into account are given. Based on the above two improved elements, we also propose a novel immune algorithm that is capable of integrating two bio-inspired mechanisms (i.e., negative selection and positive selection) by using a balance factor. Finally, a pruning algorithm is given to reduce redundant detectors that consume footprint and detection time but do not contribute to improving performance. Our experimental results show the feasibility and effectiveness of our solution to handle the scalability and coverage problems of IIDS.

User authentication using fingerprint information provides convenience as well as strong security. However, serious problems may occur if fingerprint information stored for user authentication is used illegally by a different person since it cannot be changed freely as a password due to a limited number of fingers. Recently, research in fuzzy fingerprint vault system has been carried out actively to safely protect fingerprint information in a fingerprint authentication system. In addition, research to solve the fingerprint alignment problem by applying a geometric hashing technique has also been carried out. In this paper, we propose the hardware architecture for a geometric hashing based fuzzy fingerprint vault system that consists of the software module and hardware module. The hardware module performs the matching for the transformed minutiae in the enrollment hash table and verification hash table. On the other hand, the software module is responsible for hardware feature extraction. We also propose the hardware architecture which parallel processing technique is applied for high speed processing. Based on the experimental results, we confirmed that execution time for the proposed hardware architecture was 0.24 second when number of real minutiae was 36 and number of chaff minutiae was 200, whereas that of the software solution was 1.13 second. For the same condition, execution time of the hardware architecture which parallel processing technique was applied was 0.01 second. Note that the proposed hardware architecture can achieve a speed-up of close to 100 times compared to a software based solution.

Peer-to-peer (P2P) networks consume the most bandwidth in the current Internet and file sharing accounts for the majority of the P2P traffic. Thus it is important for a P2P file sharing application to be efficient in bandwidth consumption. Bandwidth consumption as much as downloaded file sizes is inevitable, but those in file search and bad downloads, e.g. wrong, corrupted, or malicious file downloads, are overheads. In this paper, we target to reduce these overheads even in the presence of high volume of malicious users and their bad files. Sybil attacks are the example of such hostile environment. Sybil attacker creates a large number of identities (Sybil nodes) and unfairly influences the system. When a large portion of the system is subverted, either in terms of the number of users or the number of files shared in the system, the overheads due to the bad downloads rapidly increase. We propose ELiSyR, a file search protocol that can tolerate such a hostile environment. ELiSyR uses social networks for P2P file search and finds benign files in 71% of searches even when more than half of the users are malicious. Furthermore, ELiSyR provides similar success with less bandwidth than other general efforts against Sybil attacks. We compare our algorithm to SybilGuard, SybilLimit and EigenTrust in terms of bandwidth consumption and the likelihood of bad downloads. Our algorithm shows lower bandwidth consumption, similar chances of bad downloads and fairer distribution of computation loads than these general efforts. In return, our algorithm takes more rounds of search than them. However the time required for search is usually much less than the time required for downloads, so the delay in search is justifiable compared to the cost of bad downloads and subsequent re-search and downloads.

With the wide deployment of biometric authentication systems, several issues pertaining security and privacy of the biometric template have gained great attention from the research community. To resolve these issues, a number of biometric template protection methods have been proposed. However, the design of a template protection method to satisfy four criteria, namely diversity, revocability and non-invertibility is still a challenging task, especially performance degradation when template protection method is employed. In this paper, we propose a novel method to generate a revocable minutiae-based fingerprint template. The proposed method consists of feature extraction from fingerprint minutiae pairs, quantization, histogram binning, binarization and eventually binary bit-string generation. The contributions of our method are two fold: alignment-free and good performance. Various experiments on FVC2004 DB1 demonstrated the effectiveness of the proposed methods.