Opportunistic Data Aggregation in Low-Duty-Cycle Wireless Sensor Networks with Unreliable Links

This paper proposes an opportunistic data aggregation algorithm to support the data collection in low-duty-cycle Wireless sensor networks （WSNs） with unreliable links. In this algorithm, each sensor selectively waits for some certain time to maximize the number of packets that it can aggregate from its downstream nodes, then transmits the aggregated result to an adaptively selected upstream node following an optimal forwarding sequence. Simulation results show that the algorithm can significantly increase the data aggregation efficiency, and reduce energy consumption and message overhead.     

Jitter Detection for Synchronization Control in Wireless Multimedia Sensor Networks

Collaborative in-network processing operations in Wireless multimedia sensor networks （WMSNs） often require effective synchronization control. Extensive researches in the traditional networks mainly focus on the synchronization control with the buffer management in the receiver. However, for WMSNs, the chaotic transport channel and low bandwidth introduce serious jitter. Jitter degrades the timing relationship among packets in a single media stream and between packets from different media streams and, hence, creates multimedia synchronization problems. Moreover, too much jitter will also degrade the performance of the streaming buffer. By only employing the buffer management scheme in the receiver, we can hardly satisfy the synchronization requirement of the in-network processing. In this study, we propose an active jitter detection mechanism for the synchronization control in WMSNs. This mechanism will improve the quality of service in multimedia networking by discarding the jitter-corrupted packets immediately and balancing the delay and jitter actively. We implement the proposed scheme in the practical WMSNs platform. The experiment results show that our scheme can reduce the average packet jitter effectively and improve the synchronization controlling performance significantly.     

Relay Node Placement with Base Stations in Wireless Sensor Networks Fault-Tolerant

It has been proposed to deploy relay nodes for the sake of prolonging Wireless sensor networks （WSN） lifetime, such that sensors transmit the sensed data to them which in turn delivers the data to base stations. For survivability requirements, relay placements which considers fault tolerant ability have been noticed and studied. While related works are limited or most existing works don＇t take factors such as fault tolerance, or base stations into account comprehensively in two tired WSN. We focus on fault tolerant relay node placement in two-tiered het- erogeneous WSN with base stations. As far as we know, fault tolerance contains two fundamental aspects, for one is multi-coverage and the second is multi-path. It is a NP- hard problem and figure out an approximation, whose approximation ratio is enhanced to be （18＋ε）. While a sub-problem approximation is also described as supplementary. Experimental results verify that the number of relay nodes deployed by our algorithm is somewhat superior to existed relay node placement solutions.     

QoS Routing in Wireless Mesh Networks

An H-hop interference model is proposed, where the transmission is successfully received if no other nodes that are within H hops from the receiver are transmitting on the same channel simultaneously. Based on this model. the interference-free property in the Time division multiple access Wireless mesh networks is analyzed. A heuristic algorithm with max-rain time slots reservation strategy is developed to get the maximum bandwidth of a given path. And it is used in the bandwidth guaranteed routing protocol to find a path for a connection with bidirectional bandwidth requirement. Extensive simulations show that our routing protocol decreases the blocking ratios significantly compared with the shortest path routing.     

P-Zone： Connectivity-based Packet Path Tracing in Wireless Sensor Networks

In large-scale Wireless sensor networks （WSNs）, the network status is complex and unpredictable, which brings great challenges to practical network design and management. Tracing the route path of each data packet in the network is an important way to observe network behaviors and understand network dynamics. However, tracing the full route path of each packet could be highly challenging, due to the hard resource con- straint in WSNs. Our previous work proposes a hash-based path tracing mechanism, and leverages network connectivity and node locations to reduce the computational complexity. However, the node locations may be unavailable in some scenarios. In this work, we further propose a location-free enhancement to the hash-based path tracing mechanism, called P-Zone. P-Zone requires only network connectivity information to reduce the computational complexity. Theoretical analysis and practical simulations are conducted to evaluate the effectiveness and performance of our design. The results indicate that P-Zone can significantly reduce the computational complexity of the hashbased path tracing mechanism, while effectively tracing the full route path of each packet in the network in a real-time manner, and outperforms the state-of-the-art methods.     

CL-TAP： An Efficient Certificateless Based Trusted Access Protocol for WLAN

Based on the certificateless public key cryptography and the trusted computing technologies~ a certificateless based trusted access protocol for WLAN （Wireless local area networks） is proposed. Such proto- col realizes the mutual authentication and unicast session key agreement between STA and AP within 3 protocol rounds. In particular, the platform authentication and in- tegrity verification are achieved during the authentication procedure. The security properties of the new protocol are examined using the Extended Canetti-Krawczyk secu- rity model. The analytic comparisons show that the new protocol is very ei~icient in both computing and communi- cations.     

Defending Against Sybil Attacks Based on Received Signal Strength in Wireless Sensor Networks

Sybil attacks is a particularly harmful attack against Wireless sensor networks （WSN）, in which a malicious node illegitimately claims multiple identities, and forges an unbounded number of identities to defeat redundancy mechanisms. This paper proposes using received signal strength of the nodes to defend against Sybil attacks when the Jakes channel was established. Aiming at improving the detection accuracy and reducing power consumption, we put forward the mutual supervision between head nodes and member nodes to detect Sybil attacks together, and compared the related detection scheme for Sybil attacks. The simulation results show that our scheme consumes lower power, and the detection accuracy is over 90%.     

A Key Pre-distribution Scheme for Wireless Sensor Networks Using Hexagonal Deployment knowledge

To insure security for the messages sent among sensor nodes, it is important to establish keys for encryption to nodes which have had no prior direct contact with each other in wireless sensor networks. To solve the problem above, several key pre-distribution schemes have been proposed. In this paper, we present a novel key pre-distribution scheme using hexagonal deployment knowledge, in which the q-composite keys scheme has been improved. By using hexagonal division over the deploy- ment region, the probability of sharing common keys be- tween each sub-region and its neighboring sub-regions are equal, so the keys for encryption can be generated efficiently. The analytic results show that the scheme we pre-sented can achieve a higher connection probability of any two neighboring nodes than previous schemes, and net- work resilience against node capture can be substantially improved.     

An Intra-PAN Mobility Management Scheme for IPv6 over Low-Power Wireless Personal Area Networks

This paper proposes an intra-PAN mobility management scheme for IPv6 over Low-power wireless personal area networks （6LoWPAN） on the basis of ＂networkbased＂ idea. We developed a tree-like network architecture which includes coordinate nodes for packet routing. All of the control messages are designed to transmit in link layer, and the sensor nodes are free to consider care-of address and the mobile nodes are unnecessary to deal with any mobility handoff messages. The simulation results show that this scheme efficiently cuts down the signaling cost and reduces the energy consumed by fixed nodes which can extend the life time of the whole Personal area networks （PAN）.     

PFQ-OS： A Packet Fair Queueing Based Opportunistic Scheduler in Wireless Networks

In this paper, we investigate the issues of extending the Packet fair queueing （PFQ） algorithms into continuous channel model. We present a PFQ-based Opportunistic scheduler （PFQ-OS）, which can improve user throughput while satisfying strict short-term fairness. We decouple the conflicting design objectives of fairness and user throughput improvement by introducing a Search radius （SR） into the framework of PFQ. We develop an analytical model and derive the fairness properties of PFQ-OS, which are related to the SR. Thereby system operators can focus on opportunistic scheduling for the users within the SR without violating the fairness guarantee. We further investigate the designing of scheduling policy under the strict fairness constraints, and propose that in order to utilize the opportunistic scheduling all the time, the selection rule should provide all the users with equal chance in being scheduled at each selection. Accordingly, we present Maximum relative SNR （Max-rSNR） selection rule for PFQ-OS. We derive the bounds in terms of user throughput under Rayleigh fading channel. An extensive set of simulations testifies our derived theoretical properties that PFQ-OS can significantly improve user throughput while providing excellent short-term fairness guarantee.     

Enhanced MAC Protocol and Scheduling Algorithm for High Rate WPANs

The demands for higher data rate in Wireless personal area network （WPAN） than one in Bluetooth has been completed with IEEE 802.15.3 standard. The standard, named High-rate WPAN （HR-WPAN）, adopts TDMA-based Medium access control （MAC） protocol. In this paper, we propose novel MAC protocol and scheduling algorithm to achieve efficient time-slots allocation. Time slots for data transmissions are allocated by two steps. In the first step, the time slots are initially allocated using a proposed allocation algorithm based on statistical packet inter-arrival time. Then, the initial allocation is dynamically adjusted by utilizing feedback information coming from each device. Performance evaluations are carried out through extensive simulations and significant performance enhancements are observed.     

Single Beacon Cruise Positioning Algorithm in Wireless Sensor Networks

Node localization is important in WSNs （Wireless sensor networks） applications. We present a new cruise positioning algorithm, where a single beacon node cruises an entire network, broadcasting its position periodically with fixed signal strength. Meawhile, an unknown node obtains the location and the corresponding distance of the beacon node. Two possible position coordinate sets for the unknown node can then be calculated, and the coordinate mean of the point set with a small variance is an unbiased estimator of the unknown node＇s coordinate. The positioning algorithm＇s computation is simple, positioning accuracy is not limited by a physical distance measuring tool, and there are no restrictions on the path of motion, which makes it more realistic. An algorithm simulation is presented to compare the original and cruise location algorithm. Numerical results show that the cruise localization algorithm can achieve good positioning accuracy.     

Dynamic Collaborative Support Vector Machine for Target Classification in Wireless Sensor Networks

Target classification is a significant topic addressed in Wireless sensor networks （WSNs）. The distributed learning for target classification is desired for highly-constrained WSN since the processing ability, energy and bandwidth are strictly limited. This paper presents a dynamic data fusion based collaborative Support vector machine （SVM） for target classification in WSN. With the collaboration of multiple sensor nodes, the dynamic collaborative SVM can independently select the optimal set of sensor nodes according to the estimated energy consumption and information contribution. Then the training process of SVM is incrementally carried out in the dynamic data fusion framework with the consideration of tradeoff between energy consumption and information contribution. Because of the purposeful sensor nodes selection strategy, the dynamic collaborative SVM can conquer the inevitable missing rate and false rate of samples in WSN and save the energy for prolonging the lifetime of WSN. Furthermore, the dynamic collaborative SVM can also improve the robustness in target classification, and achieve the tradeoff between the performance and the cost. The experimental results demonstrate that the proposed dynamic collaborative SVM can effectively implement target classification in WSN. It is also verified that the proposed dynamic collaborative SVM has outstanding performance in energy efficiency and time delay.     

A New Positioning Method for Location-Based Services in Wireless LANs

Positioning techniques are crucial to achieve location-based services. Location estimation systems using received signal strength in wireless LANs （Local area network） have attracted great attention for the advantages of low cost, ubiquitous coverage and ease of deployment. Existing methods neglect the difference between contributions of access points to location estimation results. Signals from far access points travel long distance and thus more uncertainty is added to the receive signal strength. This paper proposed a positioning method based on the Dempster-Shafer evidence theory. Different belief was assigned to signal strength from different access points according to its importance to location estimation. We carry out a series of experiments to evaluate the method and compare with other related work. Experimental results show that the approach gives a higher degree of positioning accuracy.     

Hybrid System for Robust Faces Detection

The automatic detection of faces is a very important problem. The effectiveness of biometric authentication based on face mainly depends on the method used to locate the face in the image. This paper presents a hybrid system for faces detection in unconstrained cases in which the illumination, pose, occlusion, and size of the face are uncontrolled. To do this, the new method of detection proposed in this paper is based primarily on a technique of automatic learning by using the decision of three neural networks, a technique of energy compaction by using the discrete cosine transform, and a technique of segmentation by the color of human skin. A whole of pictures （faces and no faces） are transformed to vectors of data which will be used for learning the neural networks to separate between the two classes. Discrete cosine transform is used to reduce the dimension of the vectors, to eliminate the redundancies of information, and to store only the useful information in a minimum number of coefficients while the segmentation is used to reduce the space of research in the image. The experimental results have shown that this hybridization of methods will give a very significant improvement of the rate of the recognition, quality of detection, and the time of execution.     

Secure Data Sharing and Retrieval Using Attribute-Based Encryption in Cloud-Based OSNs

The Online social networks （OSNs） offer attractive means for social interactions and data sharing, but also raise a number of security and privacy issues. Since the OSNs service provider is always semi-trusted, current solutions propose to encrypt data before sharing. However, data encryption causes a lot of inconveniences and large overheads for data dissemination and data retrieval. In this paper, we propose a secure data sharing and retrieval scheme in cloud-based OSNs. Based on ciphertext-policy attribute-based encryption, our scheme achieves multi- party access control, which allows data owners to outsource encrypted data to the OSNs service provider for sharing, and enables data disseminators to disseminate the data owners＇ data by customizing new access policy. Our scheme also provides searchable encryptlon scheme to support fast searches in massive amount of encrypted data from both data owners and data disseminators. Further, our scheme preserves the privacy of data owners and data retrievers during the data sharing and retrieval processes. In addition, the computation overhead of data retrievers is reduced by delegating most of the decryption operations to the OSNs service provider. The security and performance analysis results indicate that our scheme is secure and privacy-preserving.     

Learning Bayesian Networks with the Combination of Evolutionary Algorithm and EMI Method

Most Bayesian network （BN） learning algorithms use EMI algorithm to deal with incomplete data. But EMI algorithm is of low efficiency due to its iterative parameter refinement, and the problem will become even worse when multiple runs of EMI algorithm are needed. Besides, EMI algorithm usually converges to local maxima, which also degrades the accuracy of EMI based BN learning algorithms. In this paper, we replace EMI algorithm used in BN learning tasks with EMI method to deal with incomplete data. EMI is a very efficient method, which estimates probability distributions directly from incomplete data rather than performs iterative refinement of parameters. Base on EMI method, we propose an effec- tive algorithm, namely EMI-EA. EMI-EA algorithm uses EMI method to estimate probability distribution over local structures in BNs, and evaluates BN structures with a variant of MDL scoring function. To avoid getting into local maxima of the search process, EMI-EA evolves BN struc- tures with an Evolutionary algorithm （EA）. The experi- mental results on Alarm, Asia and an examplar network show that EMI-EA algorithm outperforms EMI-EA for all samples and E-TPDA algorithms for small and middle size of samples in terms of accuracy. In terms of efficiency, EMI-EA is comparable with E-TPDA algorithm and much more efficient than EMI-EA algorithm. EMI-EA also out- performs EMI-EA and M-V algorithm when learning BNs with hidden variables.     

Secure Digital Contents Distributing System on P2P Networks

In recent years, the file-sharing applications of peer-to-peer （P2P） systems, such as Napster, Bit-Torrent （BT）, Gnutella, have become very popular, with BT offering particularly high sealability and efficiency service to transmit files. But BT does not enforce the access control process, so a lot of unauthorized files are freely shared. In this paper, we proposed a digital rights management （DRM） system for BT environment to solve the serious piracy issue by using lightweight encryption methods in order to he adopted by small mobile devices in wireless environment.     

5G应用场景与可能的技术

Fast growth of mobile internet and internet-of-things has propelled the concept formation and research on 5G wireless communications systems which are to be standardized around 2020 （IMT-2020）. There will be diverse application scenarios expected for 5G networks. Hence, key performance indicators （KPIs） of 5G systems would be very diverse, not just the peak data rate and average/edge spectral efficiency requirements as in previous generations. For each typical scenario, multiple technologies may be used independently or jointly to improve the transmission efficiency, to lower the cost, and to increase the number of connections, etc. Key enabling technologies are discussed which include massive MIMO, ultradense deployment specific techniques, nonorthogonal transmission, high frequency communications, etc.