This paper presents an experimental study of on-body ultra-wideband (UWB) radio propagation channels within an enclosed space. To facilitate high-speed wireless body area networks, UWB is a promising technology because of its low power consumption and anti-multipath capabilities. The motivation of this study is to examine the effects of nearby humans on the UWB channels by varying the population within an elevator cabin from one (subject alone) to 20 (full capacity of the elevator). The first domain (0 < delay, t ≤ 4ns) in the measured delay profiles was either a direct (for line-of-sight) or diffracted (for non-line-of-sight) wave, which was found almost unrelated to the population; whereas the second domain (t > 4ns) highly depended on it. Total received power and delay spreads decreased with increasing the population. In addition, by varying human population, average power delay profiles were modeled based on measurements.

Software-Defined Networking currently appears to be a major evolution towards network programmability. In this paper, we first analyze the network management capabilities of OpenFlow in order to identify the main challenges that are raised for SDN management. We address current deficiencies of SDN management and suggest solutions that incur research directions to be carried out for the management of enhanced SDN.

TSV-interconnected 3D chips face problems such as high cost, low yield and large power dissipation. We propose a wireless 3D on-chip-network architecture for application-specific SoC design, using inductive-coupling interconnect instead of TSV for inter-layer communication. Primary design challenge of inductive-coupling 3D SoC is allocating wireless links in the 3D on-chip network effectively. We develop a design flow fully exploiting the design space brought by wireless links while providing flexible tradeoff for user's choice. Experimental results show that our design brings great improvement over uniform design and Sunfloor algorithm on latency (5% to 20%) and power consumption (10% to 45%).

To solve the problems of the existing trusted network access protocols for Wireless Local Area Network (WLAN) mesh networks, we propose a new trusted network access protocol for WLAN mesh networks, which is abbreviated as WMN-TNAP. This protocol implements mutual user authentication and Platform-Authentication between the supplicant and Mesh Authenticator (MA), and between the supplicant and Authentication Server (AS) of a WLAN mesh network, establishes the key management system for the WLAN mesh network, and effectively prevents the platform configuration information of the supplicant, MA and AS from leaking out. Moreover, this protocol is proved secure based on the extended Strand Space Model (SSM) for trusted network access protocols.

In P2P applications, networks are formed by devices belonging to independent users. Therefore, routing hotspots or routing congestions are typically created by an unanticipated new event that triggers an unanticipated surge of users to request streaming service from some particular nodes; and a challenging problem is how to provide incentive mechanisms to allocation bandwidth more fairly in order to avoid congestion and other short backs for P2P QoS. In this paper, we study P2P bandwidth game — the bandwidth allocation in P2P networks. Unlike previous works which focus either on routing or on forwarding, this paper investigates the game theoretic mechanism to incentivize node's real bandwidth demands and propose novel method that avoid congestion proactively, that is, prior to a congestion event. More specifically, we define an incentive-compatible pricing vector explicitly and give theoretical proofs to demonstrate that our mechanism can provide incentives for nodes to tell the true bandwidth demand. In order to apply this mechanism to the P2P distribution applications, we evaluate our mechanism by NS-2 simulations. The simulation results show that the incentive pricing mechanism can distribute the bandwidth fairly and effectively and can also avoid the routing hotspot and congestion effectively.

As a promising wireless access standard for machine-to-machine (M2M) networks, the IEEE 802.11 task group ah has been discussing a new standard which is based on the wireless local area network (WLAN) standard. This new standard will support an enormous number of stations (STAs) such as 6,000 STAs. To mitigate degradation of the throughput and delay performance in WLANs that employ a carrier sense multiple access with collision avoidance (CSMA/CA) protocol, this paper proposes a virtual grouping method which exploits the random arbitration interframe space number scheme. This method complies with the CSMA/CA protocol, which employs distributed medium access control. Moreover, power saving is another important issue for M2M networks, where most STAs are operated by primary or secondary batteries. This paper proposes a new power saving method for the IEEE 802.11ah based M2M network employing the proposed virtual grouping method. With the proposed virtual grouping and power saving methods, the STAs can save their power by as much as 90% and maintain good throughput and delay performance.

Recently, the border security systems attract attention as large-scale monitoring system in wireless sensor networks (WSNs). In the border security systems whose aim is the monitoring of illegal immigrants and the information management in long-period, it deploys a lot of sensor nodes that have the communication and sensing functions in the detection area. Hence, the border security systems are necessary to reduce the power consumption of the whole system in order to extend the system lifetime and accurately monitor the track of illegal immigrants. In this paper, we propose two effective barrier coverage construction methods by switch dynamically operation modes of sensor nodes to reduce the operating time of the sensing function that wastes a lot of power consumption. We carry out performance evaluations by computer simulations to show the effectiveness of two proposed methods and show that the proposed methods are suitable for the border security systems.

Computing the level of trust between two indirectly connected users in an online social network (OSN) is a problem that has received considerable attention of researchers in recent years. Most algorithms focus on finding the most accurate prediction of trust; however, little work has been done to make them fast enough to be applied on today's very large OSNs. To address this need we propose a method for fast trust computation that is suitable for very large social networks. Our method uses min-max trust propagation strategies along with the landmark based method. Path strength of every node is pre-computed to and from a small set of reference users or landmarks. Using these pre-computed values, we estimate the strength of trust paths from the source user to in-neighbors of the target user. The final trust estimate is obtained by aggregating information from most reliable in-neighbors of the target user. We also describe how the landmark based method can be used for fast trust computation according to other trust propagation models. Experiments on a variety of real social network datasets verify the efficiency and accuracy of our method.

The link structure of the Web is generally viewed as a webgraph. One of the main objectives of web structure mining is to find hidden communities on the Web based on the webgraph, and one of its approaches tries to enumerate substructures, each of which corresponds to a set of web pages of a community or its core. Research has shown that certain substructures can find sets of pages that are inherently irrelevant to communities. In this paper, we propose a model, which we call contracted webgraphs, where such substructures are contracted into single nodes to hide useless information. We then try structure mining iteratively on those contracted webgraphs since we can expect to find further hidden information once irrelevant information is eliminated. We also explore the structural properties of contracted webgraphs from the viewpoint of scale-freeness, and we observe that they exhibit novel and extreme self-similarities.

Relay has been incorporated into standards of wireless access networks to improve the system capacity and coverage. However, the resource allocation problem to support scalable video coding (SVC) multicast for wireless relay networks is challenging due to the existence of relay stations (RSs). In this paper, we study the resource allocation problem for SVC multicast over multi-hop wireless relay networks to maximize the total utility of all users with a general non-negative, non-decreasing utility function. Since the problem is NP-hard, we simplify it with RS specification functions which specialize the relay station to receive data for each user, and convert the resource allocation problem with one RS specification function as finding a maximum spanning sub-tree of a directed graph under budget constraint. A heuristic algorithm is proposed to solve the problem with polynomial time complexity. The simulation results reveal that the proposed algorithm outperforms other algorithms under assumptions of two-hop wireless relay networks or separated transmission for relay and access links, and it keeps good approximation to the optimal results.

Machine-to-Machine (M2M) communication is expected to grow in networks of the future, where massive numbers of low cost, low function M2M terminals communicate in many-to-many manner in an extremely mobile and dynamic environment. We propose a network architecture called Data-centric Network (DCN) where communication is done using a data identifier (ID) and the dynamic data registered by mobile terminals can be retrieved by specifying the data ID. DCN mitigates the problems of prior arts, which are large size of routing table and transaction load of name resolution service. DCN introduces concept of route attraction and aggregation in which the related routes are attracted to an aggregation point and aggregated to reduce routing table size, and route optimization in which optimized routes are established routes to reduce access transaction load to the aggregation points. These allow the proposed architecture to deal with ever increasing number of data and terminals with frequent mobility and changes in data.

We propose a natural synchronization scheme for wireless uncoupled devices, without any signal exchange among them. Our proposed scheme only uses natural environmental fluctuations, such as the temperature or humidity of the air, the environmental sounds, and so on, for the synchronization of the uncoupled devices. This proposed synchronization is realized based on the noise-induced synchronization phenomenon, uncoupled nonlinear oscillators synchronize with each other only by adding identical common noises to each of them. Based on the theory of this phenomenon, the oscillators can also be synchronized by noise sequences, which are not perfectly identical signals. Since the environmental natural fluctuations collected at neighboring locations are similar to each other and cross-correlation becomes high, our proposed scheme enabling synchronization only by natural environmental fluctuations can be realized. As an application of this proposed synchronization, we introduce wireless sensor networks, for which synchronization is important for reducing power consumption by intermittent data transmission. We collect environmental fluctuations using the wireless sensor network devices. Our results show that the wireless sensor network devices can be synchronized only by the independently collected natural signals, such as temperature and humidity, at each wireless sensor device.

Due to vehicle movement and lossy wireless channels, providing a reliable and efficient multi-hop broadcast service in vehicular ad hoc networks (VANETs) is a well-known challenging problem. In this paper, we propose BR-NB (broadcast with neighbor information), a fuzzy logic based multi-hop broadcast protocol for VANETs. BR-NB achieves a low overhead by using only a subset of neighbor nodes to relay data packets. For the relay node selection, BR-NB jointly considers multiple metrics of the inter-vehicle distance, vehicle mobility and link quality by employing fuzzy logic. Since the expected coverage and vehicle mobility are inferred from the two-hop neighbor information which can be acquired from the hello message exchange, BR-NB is independent of position information. BR-NB provides a practical and portable solution for broadcast services in VANETs. We use computer simulations and real-world experiments to evaluate the performance of BR-NB.

Broadcasting is an essential function in almost all wireless networks. Because of the dynamic nature of environment, broadcasting in cognitive radio ad hoc networks is a great challenge. Cognitive radio network technology has been well studied for more than a decade as a new way to improve the spectral efficiency of wireless networks and numerous precious works have been proposed. However, very few existing works consider how to broadcast messages in cognitive radio networks that operate in multichannel environments and none of these provides a full broadcast mechanism. Therefore, in this paper, we propose a broadcasting mechanism for multichannel cognitive radio ad hoc networks. Then, we analyze the mechanism regarding the speed of message dissemination, number of transmissions, fraction of the users that receive the broadcast message and so forth.

The relationship between different brain areas is characterized by functional networks through correlations of time series obtained from neuroimaging experiments. Due to its high spatial resolution, functional MRI data is commonly used for generating functional networks of the entire brain. These networks are comprised of the measurement points/channels as nodes and links are established if there is a correlation in the measured time series of these nodes. However, since the evaluation of correlation becomes more accurate with the length of the underlying time series, we construct in this paper functional networks from MEG data, which has a much higher time resolution than fMRI. We study in particular how the network topologies change in an experiment on ambiguity of words, where the subject first receives a priming word before being presented with an ambiguous or unambiguous target word.

This paper presents a Complex-Valued Neural Network-based sound localization method. The proposed approach uses two microphones to localize sound sources in the whole horizontal plane. The method uses time delay and amplitude difference to generate a set of features which are then classified by a Complex-Valued Multi-Layer Perceptron. The advantage of using complex values is that the amplitude information can naturally masks the phase information. The proposed method is analyzed experimentally with regard to the spectral characteristics of the target sounds and its tolerance to noise. The obtained results emphasize and confirm the advantages of using Complex-Valued Neural Networks for the sound localization problem in comparison to the traditional Real-Valued Neural Network model.

In this letter, a distributed TDMA-based data gathering scheme for wireless sensor networks, called DTDGS, is proposed in order to avoid transmission collisions, achieve high levels of power conservation and improve network lifetime. Our study is based on corona-based network division and a distributed TDMA-based scheduling mechanism. Different from a centralized algorithm, DTDGS does not need a centralized gateway to assign the transmission time slots and compute the route for each node. In DTDGS, each node selects its transmission slots and next-hop forwarding node according to the information gathered from neighbor nodes. It aims at avoiding transmission collisions and balancing energy consumption among nodes in the same corona. Compared with previous data gathering schemes, DTDGS is highly scalable and energy efficient. Simulation results show high the energy efficiency of DTDGS.

This paper proposes T-CROM (Time-delayed Collaborative ROuting and MAC) protocol, that allows collaboration between network and MAC layers in order to extend the lifetime of MANETs in a resources-limited environment. T-CROM increases the probability of preventing energy-poor nodes from joining routes by using a time delay function that is inversely proportional to the residual battery capacity of intermediate nodes, making a delay in the route request (RREQ) packets transmission. The route along which the first-arrived RREQ packet traveled has the smallest time delay, and thus the destination node identifies the route with the maximum residual battery capacity. This protocol leads to a high probability of avoiding energy-poor nodes and promotes energy-rich nodes to join routes in the route establishment phase. In addition, T-CROM controls the congestion between neighbors and reduces the energy dissipation by providing an energy-efficient backoff time by considering both the residual battery capacity of the host itself and the total number of neighbor nodes. The energy-rich node with few neighbors has a short backoff time, and the energy-poor node with many neighbors gets assigned a large backoff time. Thus, T-CROM controls the channel access priority of each node in order to prohibit the energy-poor nodes from contending with the energy-rich nodes. T-CROM fairly distributes the energy consumption of each node, and thus extends the network lifetime collaboratively. Simulation results show that T-CROM reduces the number of total collisions, extends the network lifetime, decreases the energy consumption, and increases the packet delivery ratio, compared with AOMDV with IEEE 802.11 DCF and BLAM, a battery-aware energy efficient MAC protocol.

Many applications of wireless sensor networks (WSNs) require secure communication. The tree-based key management scheme, which is a symmetric key scheme, provides backward and forward secrecy. The sensor nodes in the communication group share a secret key for encrypting messages. When the sensor nodes are added to or evicted from the group, the group key has to be updated by sending rekeying messages. In this paper, we propose a method of key tree structure (KTS) generation by considering the addition and eviction ratio of sensor nodes to reduce the number of rekeying messages, which is influenced by the structure of the tree. For this, we define an extension of an existing tree structure such as a binary or ternary tree and generate KTS using an A* algorithm. To reduce the energy consumed by the message transmission, we also exploit genetic algorithm (GA) to build a secure communication group by considering the KTS. In the paper, we show the effectiveness of the proposed method compared with the existing structure via the simulation in terms of memory usage, the number of rekeying messages and energy consumption.

This paper studies the simple dynamic binary neural network characterized by the signum activation function, ternary weighting parameters and integer threshold parameters. The network can be regarded as a digital version of the recurrent neural network and can output a variety of binary periodic orbits. The network dynamics can be simplified into a return map, from a set of lattice points, to itself. In order to store a desired periodic orbit, we present two learning algorithms based on the correlation learning and the genetic algorithm. The algorithms are applied to three examples: a periodic orbit corresponding to the switching signal of the dc-ac inverter and artificial periodic orbit. Using the return map, we have investigated the storage of the periodic orbits and stability of the stored periodic orbits.