Optimizating the deployment of wireless sensor networks, which is one of the key issues in wireless sensor networks research, helps improve the coverage of the networks and the system reliability. In this paper, we propose an evolutionary algorithm based on modified t-distribution for the wireless sensor by introducing a deployment optimization operator and an intelligent allocation operator. A directed perturbation operator is applied to the algorithm to guide the evolution of the node deployment and to speed up the convergence. In addition, with a new geometric sensor detection model instead of the old probability model, the computing speed is increased by 20 times. The simulation results show that when this algorithm is utilized in the actual scene, it can get the minimum number of nodes and the optimal deployment quickly and effectively.Compared with the existing mainstream swarm intelligence algorithms, this method has satisfied the need for convergence speed and better coverage, which is closer to the theoretical coverage value.

System expandability becomes a major concern for highly parallel computers and data centers, because their number of nodes gradually increases year by year. In this context we propose a low-degree topology and its floor layout in which a cabinet or node set can be newly inserted by connecting short cables to a single existing cabinet. Our graph analysis shows that the proposed topology has low diameter, low average shortest path length and short average cable length comparable to existing topologies with the same degree. When incrementally adding nodes and cabinets to the proposed topology, its diameter and average shortest path length increase modestly. Our discrete-event simulation results show that the proposed topology provides a comparable performance to 2-D Torus for some parallel applications. The network cost and power consumption of DSN-F modestly increase when compared to the counterpart non-random topologies.

Because accurate position information plays an important role in wireless sensor networks (WSNs), target localization has attracted considerable attention in recent years. In this paper, based on target spatial domain discretion, the target localization problem is formulated as a sparsity-seeking problem that can be solved by the compressed sensing (CS) technique. To satisfy the robust recovery condition called restricted isometry property (RIP) for CS theory requirement, an orthogonalization preprocessing method named LU (lower triangular matrix, unitary matrix) decomposition is utilized to ensure the observation matrix obeys the RIP. In addition, from the viewpoint of the positioning systems, taking advantage of the joint posterior distribution of model parameters that approximate the sparse prior knowledge of target, the sparse Bayesian learning (SBL) approach is utilized to improve the positioning performance. Simulation results illustrate that the proposed algorithm has higher positioning accuracy in multi-target scenarios than existing algorithms.

Cognitive radio sensor networks (CRSNs) with their dynamic spectrum access capability appear to be a promising solution to address the increasing challenge of spectrum crowding faced by the traditional WSN. In this paper, through maximizing the utility index of the CRSN, a node density-adaptive spectrum access strategy for sensor nodes is proposed that takes account of the node density in a certain event-driven region. For this purpose, considering the burst real-time data traffic, we analyze the energy efficiency (EE) and the packet failure rate (PFR) combining network disconnected rate (NDR) and packet loss rate (PLR) during the channel switching interval (CSI) for both underlay and interweave spectrum access schemes. Numerical results confirm the validity of our theoretical analyses and indicate that the adaptive node density threshold (ANDT) exists for underlay and interweave spectrum access scheme switching.

Content oriented network is expected to be one of the most promising approaches for resolving design concept difference between content oriented network services and location oriented architecture of current network infrastructure. There have been proposed several content oriented network architectures, but research efforts for content oriented networks have just started and technical issues to be resolved are still remained. Because of content oriented feature, content data transmitted in a network can be reused by content requests from other users. Pervasive cache is one of the most important benefits brought by the content oriented network architecture, which forms interconnected caching networks. Caching network is the hottest research area and lots of research activities have been published. This paper surveys recent research activities for caching networks in content oriented networks, with focusing on important factors which affect caching network performance, i.e. content request routing, caching decision, and replacement policy of cache. And this paper also discusses future direction of caching network researches.

The recently proposed distributed adaptive direct position determination (D-ADPD) algorithm provides an efficient way to locating a radio emitter using a sensor network. However, this algorithm may be suboptimal in the situation of colored emitted signals. We propose an enhanced distributed adaptive direct position determination (EDA-DPD) algorithm. Simulations validate that the proposed EDA-DPD outperforms the D-ADPD in colored emitted signals scenarios and has the similar performance with the D-ADPD in white emitted signal scenarios.

Content centric network (CCN) is conceived as a good candidate for a futuristic Internet paradigm due to its simple and robust communication mechanism. By directly applying the CCN paradigm in wireless multihop mobile ad hoc networks, we experience various kind of issues such as packet flooding, data redundancy, packet collisions, and retransmissions etc., due to the broadcast nature of the wireless channel. To cope with the problems, in this study, we propose a novel location-aware forwarding and caching scheme for CCN-based mobile ad hoc networks. Extensive simulations are performed by using simulator, named ndnSIM. Experiment results show that proposed scheme does better as compared to other schemes in terms of content retrieval time and the number of Interest retransmissions triggered in the network.

One of the main research tasks in community question answering (cQA) is finding the most relevant questions for a given new query, thereby providing useful knowledge for users. The straightforward approach is to capitalize on textual features, or a bag-of-words (BoW) representation, to conduct the matching process between queries and questions. However, these approaches have a lexical gap issue which means that, if lexicon matching fails, they cannot model the semantic meaning. In addition, latent semantic models, like latent semantic analysis (LSA), attempt to map queries to its corresponding semantically similar questions through a lower dimension representation. But alas, LSA is a shallow and linear model that cannot model highly non-linear correlations in cQA. Moreover, both BoW and semantic oriented solutions utilize a single dictionary to represent the query, question, and answer in the same feature space. However, the correlations between them, as we observe from data, imply that they lie in entirely different feature spaces. In light of these observations, this paper proposes a tri-modal deep belief network (tri-DBN) to extract a unified representation for the query, question, and answer, with the hypothesis that they locate in three different feature spaces. Besides, we compare the unified representation extracted by our model with other representations using the Yahoo! Answers queries on the dataset. Finally, Experimental results reveal that the proposed model captures semantic meaning both within and between queries, questions, and answers. In addition, the results also suggest that the joint representation extracted via the proposed method can improve the performance of cQA archives searching.

This paper empirically validates battery-less sensor activation via wireless energy transmission to release sensors from wires and batteries. To seamlessly extend the coverage and activate sensor nodes distributed in any indoor environment, we proposed multi-point wireless energy transmission with carrier shift diversity. In this scheme, multiple transmitters are employed to compensate path-loss attenuation and orthogonal frequencies are allocated to the multiple transmitters to avoid the destructive interference that occurs when the same frequency is used by all transmitters. In our previous works, the effectiveness of the proposed scheme was validated theoretically and also empirically by using just a spectrum analyzer to measure the received power. In this paper, we develop low-energy battery-less sensor nodes whose consumed power and required received power for activation are respectively 142µW and 400µW. In addition, we conduct indoor experiments in which the received power and activation of battery-less sensor node are simultaneously observed by using the developed battery-less sensor node and a spectrum analyzer. The results show that the coverage of single-point and multi-point wireless energy transmission without carrier shift diversity are, respectively, 84.4% and 83.7%, while the coverage of the proposed scheme is 100%. It can be concluded that the effectiveness of the proposed scheme can be verified by our experiments using real battery-less sensor nodes.

The alternating direction implicit (ADI) method is proposed for low-rank solution of projected generalized continuous-time algebraic Lyapunov equations. The low-rank solution is expressed by Cholesky factor that is similar to that of Cholesky factorization for linear system of equations. The Cholesky factor is represented in a real form so that it is useful for balanced truncation of sparsely connected RLC networks. Moreover, we show how to determine the shift parameters which are required for the ADI iterations, where Krylov subspace method is used for finding the shift parameters that reduce the residual error quickly. In the illustrative examples, we confirm that the real Cholesky factor certainly provides low-rank solution of projected generalized continuous-time algebraic Lyapunov equations. Effectiveness of the shift parameters determined by Krylov subspace method is also demonstrated.

The growth of the size of the routing tables limits the scalability of the conventional IP routing. As scalable routing schemes for large-scale networks are highly demanded, this paper proposes and evaluates an efficient geometric routing scheme and related low-cost node design applicable to large-scale networks. The approach guarantees that greedy forwarding on derived coordinates will result in successful packet delivery to every destination in the network by relying on coordinates deduced from a spanning tree of the network. The efficiency of the proposed scheme is measured in terms of routing quality (stretch) and size of the coordinates. The cost of the proposed router is quantified in terms of area complexity of the hardware design and all the evaluations involve comparison with a state-of-the-art approach with virtual coordinates in the hyperbolic plane. Extensive simulations assess the proposal in large topologies consisting of up to 100K nodes. Experiments show that the scheme has stretch properties comparable to geometric routing in the hyperbolic plane, while enabling a more efficient hardware design, and scaling considerably better in terms of storage requirements for coordinate representation. These attractive properties make the scheme promising for routing in large networks.

The power grid defines one of the most important technological networks of our times and has been widely studied as a kind of complex network. It has been developed for more than one century and becomes an extremely huge and seemingly robust system. But it becomes extremely fragile as well because some unexpected minimal failures may lead to sudden and massive blackouts. Many works have been carried out to investigate the structural vulnerability of power grids from the topological point of view based on the complex network theory. This Letter focuses on the structural vulnerability of the power grid under the effect of selective node removal. We propose a new kind of node centrality called overall information centrality (OIC) to guide the node removal attack. We test the effectiveness of our centrality in guiding the node removal based on several IEEE power grids. Simulation results show that, compared with other node centralities such as degree centrality (DC), betweenness centrality (BC) and closeness centrality (CC), our OIC is more effective to guide the node removal and can destroy the power grid in less steps.

This work presents the exact outage performance and throughput of two-way cognitive decode-and-forward relaying wireless sensor networks with realistic transceiver relay. The relay is a self-powered wireless node that harvests radio frequency energy from the transmitted signals. We consider four configurations of a network with formed by combining two bidirectional relaying protocols (multiple access broadcast protocol and time division broadcast protocol), and two power transfer policies (dual-source energy transfer and single-fixed-source energy transfer). Based on our analysis, we provide practical insights into the impact of transceiver hardware impairments on the network performance, such as the fundamental capacity ceiling of the network with various configurations that cannot be exceeded by increasing transmit power given a fixed transmission rate and the transceiver selection strategy for the network nodes that can optimize the implementation cost and performance tradeoff.

The widespread use and increasing popularity of broadband service has prompted a focus on the measurement and analysis of its empirical performance in recent studies. The worldwide view of broadband performance has been examined over the short term with Speedtest.net, but research in this area has not yet provided a long-term evolutionary insight on how DSL, Cable, and Fiber access technologies have influenced on user experience. In this study, we present 6 years of measurement results, from 2006 to 2011, of broadband performance with fast developing broadband networks in Korea. With 57% Fiber penetration in 2011, our data consist of a total of 29M test records and 10M subscribers. Over the 6 years, we have observed a 2.9-fold improvement in download speed (57Mbps), 2.8-fold increase in upload speed (38Mbps), and 0.7-fold decrease in latency due to the high penetration rate of Fiber broadband service and the advanced Cable modem technology. In addition, we carried out longitudinal analysis of various aspects of services, providers, regions, and cost-performance. We believe that the evolutionary Korean broadband measurement results can shed light on how high-speed access technologies are substantially enhancing on end-to-end performance.

Flexible resource utilization in terms of adaptive use of optical bandwidth with agile reconfigurability is key for future metro networks. To address this issue, we focus on optical subwavelength switched network architectures that leverage high-speed optical switching technologies and can accommodate dynamic traffic cost-effectively. Although optical subwavelength switched networks have been attracting attention, most conventional studies apply static (pre-planned) protection scenarios in the networks of limited sizes. In this paper, we discuss optical switch requirements, the use of transceivers, and protection schemes to cost-effectively create large-scale reliable metro networks. We also propose a cost-effective adaptive protection scheme appropriate for optical subwavelength switched networks using our fast time-slot allocation algorithm. The proposed scheme periodically re-optimizes the bandwidth of both working and protection paths to prevent bandwidth resources from being wasted. The numerical examples verify the feasibility of our proposed scheme and the impact on network resources.

In this letter, the problem of how to set reserve prices so as to improve the primary user's revenue in the second price-sealed auction under the incomplete information of secondary users' private value functions is investigated. Dirichlet process is used to predict the next highest bid based on historical data of the highest bids. Before the beginning of the next auction round, the primary user can obtain a reserve price by maximizing the additional expected reward. Simulation results show that the proposed scheme can achieve an improvement of the primary user's averaged revenue compared with several counterparts.

In this paper, we propose a novel censor-based cooperative spectrum sensing strategy, called adaptive energy-efficient sensing (AES), in which both sequential sensing and censoring report mechanism are employed, aiming to reduce the sensing energy consumption of secondary user relays (SRs). In AES, an anchor secondary user (SU) requires cooperative sensing only when it does not detect the presence of PU by itself, and the cooperative SR adopts decision censoring report only if the sensing result differs from its previous one. We derive the generalized-form expressions false alarm and detection probabilities over Rayleigh fading channels for AES. The sensing energy consumption is also analyzed. Then, we study sensing energy overhead minimization problem and show that the sensing time allocation can be optimized to minimize the miss detection probability and sensing energy overhead. Finally, numerical results show that the proposed strategy can remarkably reduce the sensing energy consumption while only slightly degrading the detection performance compared with traditional scheme.

Accidental falling among elderly people has become a public health concern. Thus, there is a need for systems that detect a fall when it happens. This paper presents a portable real-time remote health monitoring system that can remotely monitor patients' movements. The system is designed and implemented using ZigBee wireless technologies, and the data is analysed using Matlab. The purpose of this research is to determine the acceleration thresholds for fall detection, using tri-axial accelerometer readings at the head, waist, and knee. Seven voluntary subjects performed purposeful falls and Activities of Daily Living (ADL). The results indicated that measurements from the waist and head can accurately detect falls; the sensitivity and reliability measurements of fall detection ranged between 80% and 90%. In contrast, the measurements showed that the knee is not a useful position for the fall detection.

The new generation of telemedicine systems enables healthcare service providers to monitor patients not only in the hospital but also when they are at home. In order to efficiently exploit these systems, human information collected from end devices must be sent to the medical center through reliable data transmission. In this paper, we propose an adaptive relay transmission scheme to improve the reliability of data transmission for wireless body area networks. In our proposal, relay nodes that have successfully decoded a packet from the source node are selected as relay nodes in which the best relay with the highest channel gain is selected to forward the failed packet instead of the source node. The scheme addresses both the data collision problem and the inefficient relay selection in relay transmission. Our experimental results show that the proposed scheme provides a better performance than previous works in terms of the packet delivery ratio and end-to-end delay.

Time synchronization is of paramount importance in wireless sensor networks (WSNs) due to the inherent distributed characteristics of WSNs. Border surveillance WSNs, especially, require a highly secure and accurate time synchronization scheme to detect and track intruders. In this paper, we propose a Secure and Efficient Time synchronization scheme for Border surveillance WSNs (SETB) which meets the requirements of border surveillance WSNs while minimizing the resource usage. To accomplish this goal, we first define the performance and security requirements for time synchronization in border surveillance WSNs in detail. Then, we build our time synchronization scheme optimized for these requirements. By utilizing both heterogeneous WSNs and one-way key chains, SETB satisfies the requirements with much less overhead than existing schemes. Additionally, we introduce on-demand time synchronization, which implies that time synchronization is conducted only when an intruder enters the WSN, in order to reduce energy consumption. Finally, we propose a method of deploying time-source nodes to keep the synchronization error within the requirement. Our analysis shows that SETB not only satisfies the performance and security requirements, but also is highly efficient in terms of communication and computation overhead, thus minimizing energy consumption.