This paper presents an inter-satellite link (ISL) reassignment method to optimize the snapshot routing performance for polar-orbit LEO satellite networks. When the snapshot routing tables are switching simultaneously in all satellites, we propose to reassign the inter-plane ISLs with regularity to improve the quality of the next snapshot, such as snapshot duration, on-board transceiver utilization ratio and end to end delay. Evaluations indicate that our method can attain equal-length snapshots regardless of the latitude of the polar area border, and so is superior to the natural partition method. Meanwhile, compared with the equal partition method which is used in the Iridium system, our method can prolong 82.87% snapshot duration, increase 8.68% on-board transceiver utilization ratio and reduce 5.30% average end to end delay of the whole network. Therefore, we believe that the ISL reassignment method can be efficiently applied in all practical polar-orbit LEO satellite networks.

Several models of feed-forward complex-valued neural networks have been proposed, and those with split and polar-represented activation functions have been mainly studied. Neural networks with split activation functions are relatively easy to analyze, but complex-valued neural networks with polar-represented functions have many applications but are difficult to analyze. In previous research, Nitta proved the uniqueness theorem of complex-valued neural networks with split activation functions. Subsequently, he studied their critical points, which caused plateaus and local minima in their learning processes. Thus, the uniqueness theorem is closely related to the learning process. In the present work, we first define three types of reducibility for feed-forward complex-valued neural networks with polar-represented activation functions and prove that we can easily transform reducible complex-valued neural networks into irreducible ones. We then prove the uniqueness theorem of complex-valued neural networks with polar-represented activation functions.

Wireless sensor networks play an important role in several industries. Ad-hoc networks with multi-hop transmissions are considered suitable for wireless sensor networks because of their high scalability and low construction cost. However, a lack of centralized control makes it difficult to respond to congestion when system capacity is exceeded. Therefore, the analysis of system capacity is a critical issue for system design. In this paper, we propose a novel zone division model to analyze the capacity of multi-hop wireless sensor networks using carrier sense multiple access with collision avoidance protocols. We divide the one-hop area to a gateway (GW) into two zones: an outer zone, where access nodes (ANs) can relay packets from multi-hop ANs, and an inner zone where ANs cannot relay packets. Using this approach, we calculate the packet loss for each zone to estimate the capacity, considering the difference in the communication range of the GW and ANs, as well as the collision with hidden nodes. Comparisons with simulation results and the conventional method show that our model achieves higher estimation accuracy.

This paper investigates active period selection for cluster-based WSNs employing traffic adaptive IEEE 802.15.4 beacon enabled medium access control (MAC) under spatial non-uniform traffic and cluster mobility environments, and proposes a simple autonomous distributed superframe duration (SD) selection scheme to enhance network performance under such environments. The proposed scheme autonomously selects an active SD at each cluster head (CH) by using beacon reception power monitoring (conducted in distributed control manner) and also introduces a beacon status notice from sensor nodes (SNs) to their parent CHs in order to prevent unnecessary SD selection at CHs. Moreover, SD reuse mechanism and joint operation with previously proposed distributed backoff mechanism are proposed for the proposed SD selection scheme to further enhance the network performance. The results of computer simulation show that the proposed scheme can improve both the transmission and power efficiency performance of cluster-based WSNs under spatial non-uniform traffic and cluster mobility environments.

With shortest path bridging MAC (SPBM), shortest path trees are computed based on link metrics from each node to all other participating nodes. When an edge bridge receives a frame, it selects a path along which to forward the frame to its destination node from multiple shortest paths. Blocking ports are eliminated to allow full use of the network links. This approach is expected to use network resources efficiently and to simplify the operating procedure. However, there is only one multipath distribution point in the SPBM network. This type of network can be defined as an end-to-end multipath network. Edge bridges need to split flows to achieve the load balancing of the entire network. This paper proposes a rate-based path selection scheme that can be employed for end-to-end multipath networks including SPBM. The proposed scheme assumes that a path with a low average rate will be congested because the TCP flow rates decrease on a congested path. When a new flow arrives at an edge bridge, it selects the path with the highest average rate since this should provide the new flow with the highest rate. The performance of the proposed scheme is confirmed by computer simulations. The appropriate timeout value is estimated from the expected round trip time (RTT). If an appropriate timeout value is used, the proposed scheme can realize good load balancing. The proposed scheme improves the efficiency of link utilization and throughput fairness. The performance is not affected by differences in the RTT or traffic congestion outside the SPBM network.

Multi-hop networks have been proposed to increase the data transmission rate in wireless mobile networks, and consequently improve the quality of experience of cell-edge users. A successive resource allocation scheme (SAS) has been proposed for a 2-hop virtual cellular network (VCN). In a multi-cell environment, the performance of SAS degrades because of intra-cell and inter-cell interference. In order to alleviate the effect of intra-cell and inter-cell interference and consequently increase the channel capacity of the VCN, this paper proposes the sequential iterative allocation scheme (SIS). Computer simulation results show that, compared to SAS, SIS can improve the fairness, the ergodic, and the outage channel capacity per mobile terminal (MT) of the VCN in a multi-cell environment. This paper also analyzes the performance of the VCN compared to that of the single hop network (SHN) when SIS is applied in a multi-cell environment. Using SIS, VCN can provide higher ergodic channel capacity, and better degree of fairness than SHN in a multi-cell environment. The effect of the number of wireless ports (WPs) in the VCN is also investigated, and the results suggest that adding more WPs per virtual cell in the VCN can enhance the outage channel capacity per MT and the degree of fairness of the VCN.

Throughput capacity is of great importance for the design and performance optimization of mobile ad hoc networks (MANETs). We study the exact per node throughput capacity of MANETs under a general 2HR-(g, x, f) routing scheme which combines erasure coding and packet replication techniques. Under this scheme, a source node first encodes a group of g packets into x (x ≥ g) distinct coded packets, and then replicates each of the coded packets to at most f relay nodes which help to forward them to the destination node. All original packets can be recovered once the destination node receives any g distinct coded packets of the group. To study the throughput capacity, we first construct two absorbing Markov chain models to depict the complicated packet delivery process under the routing scheme. Based on these Markov models, an analytical expression of the throughput capacity is derived. Extensive simulation and numerical results are provided to verify the accuracy of theoretical results on throughput capacity and to illustrate how system parameters will affect the throughput capacity in MANETs. Interestingly, we find that the replication of coded packets can improve the throughput capacity when the parameter x is relatively small.

In this paper, we analyze the rollback traffic in polar-orbit satellite networks that use the snapshot routing algorithm. The concept of diamond rollback links and polar rollback links are presented for the first time, and the numbers of diamond and polar rollback links in polar-orbit satellite networks are concisely formulated. Simulations are performed based on the Iridium and Teledesic system in NS2, and the results finally confirm our analysis. With this work, we can not only simplify the rollback loops avoidance scheme, but also provide guidance for future satellite network routing optimization and topology design.

In wireless LANs, wireless clients are associated with one of access points (APs) to obtain network connectivity, and the AP performs network traffic relay between the wired infrastructure and wireless clients. If a client with a low transmission rate is associated with an AP, the throughput performance of all the clients that are associated with the AP is significantly degraded because of the long channel usage time of the low-rate client. Therefore, it is important to select an appropriate AP when a new client joins the wireless LAN to prevent the performance degradation. In this paper, we propose a traffic control that determines the feasible data traffic from an AP to the clients on the basis of the trade-off relationship between the equal-throughput and equal-airtime traffic allocation policies. We then propose a network-wide association algorithm that allows a client to be associated with the AP that can provide the highest throughput improvement. Simulation results indicate that the proposed algorithm achieves the better aggregate throughput and throughput fairness performances in IEEE 802.11 WLANs.

Breast cancer is a serious disease across the world, and it is one of the largest causes of cancer death for women. The traditional diagnosis is not only time consuming but also easily affected. Hence, artificial intelligence (AI), especially neural networks, has been widely used to assist to detect cancer. However, in recent years, the computational ability of a neuron has attracted more and more attention. The main computational capacity of a neuron is located in the dendrites. In this paper, a novel neuron model with dendritic nonlinearity (NMDN) is proposed to classify breast cancer in the Wisconsin Breast Cancer Database (WBCD). In NMDN, the dendrites possess nonlinearity when realizing the excitatory synapses, inhibitory synapses, constant-1 synapses and constant-0 synapses instead of being simply weighted. Furthermore, the nonlinear interaction among the synapses on a dendrite is defined as a product of the synaptic inputs. The soma adds all of the products of the branches to produce an output. A back-propagation-based learning algorithm is introduced to train the NMDN. The performance of the NMDN is compared with classic back propagation neural networks (BPNNs). Simulation results indicate that NMDN possesses superior capability in terms of the accuracy, convergence rate, stability and area under the ROC curve (AUC). Moreover, regarding ROC, for continuum values, the existing 0-connections branches after evolving can be eliminated from the dendrite morphology to release computational load, but with no influence on the performance of classification. The results disclose that the computational ability of the neuron has been undervalued, and the proposed NMDN can be an interesting choice for medical researchers in further research.

String-topology multi-hop network is often selected as an analysis object because it is one of the fundamental network topologies. The purpose of this paper is to establish expression for end-to-end delay for IEEE 802.11 string-topology multi-hop networks. For obtaining the analytical expression, the effects of frame collisions and carrier-sensing effect from other nodes under the non-saturated condition are obtained for each node in the network. For expressing the properties in non-saturated condition, a new parameter, which is frame-existence probability, is defined. The end-to-end delay of a string-topology multi-hop network can be derived as the sum of the transmission delays in the network flow. The analytical predictions agree with simulation results well, which show validity of the obtained analytical expressions.

In recent years, applications of complex-valued neural networks have become wide spread. Quaternions are an extension of complex numbers, and neural networks with quaternions have been proposed. Because quaternion algebra is non-commutative algebra, we can consider two orders of multiplication to calculate weighted input. However, both orders provide almost the same performance. We propose hybrid quaternionic Hopfield neural networks, which have both orders of multiplication. Using computer simulations, we show that these networks outperformed conventional quaternionic Hopfield neural networks in noise tolerance. We discuss why hybrid quaternionic Hopfield neural networks improve noise tolerance from the standpoint of rotational invariance.

Recently, the growing concepts that information communication technologies apply to social infrastructures have caused deep interests with wireless sensor networks (WSNs). WSNs can be used for various application areas such as home, health, factory and so on. For the different application areas, there are different technical issues (e.g., security, reliability, real time gathering, long life time, scalability). Efficient information gathering can be potentially obtained if we take a suitable information gathering method with considering the requirements of each WSN application. Thus, we have not persisted all information gathering perfectly and have proposed one of simple information gathering methods in response to the requirements of WSN applications in this paper. In the proposed method, the information is converted to physical-layer parameters of wireless communications, such as frequency and time. Also, simulations are performed to validate the effectiveness of the proposed method in real time gathering and estimating with high precision.

Small cell networks have been promoted as an enabling solution to enhance indoor coverage and improve spectral efficiency. Users usually deploy small cells on-demand and pay no attention to global profile in residential areas or offices. The reduction of cell radius leads to dense deployment which brings intractable computation complexity for resource allocation. In this paper, we develop a semi-distributed resource allocation algorithm by dividing small cell networks into clusters with limited inter-cluster interference and selecting a reference cluster for interference estimation to reduce the coordination degree. Numerical results show that the proposed algorithm can maintain similar system performance while having low complexity and reduced information exchange overheads.

In wireless networks, interference from adjacent nodes that are concurrently transmitting can cause packet reception failures and thus a significant throughput degradation. The interference can be simply avoided by assigning different orthogonal channels to each interfering node. However, if the number of orthogonal channels is smaller than that of interfering nodes, some adjacent nodes have to share the same channel and may interfere with each other. This interference can be mitigated by reducing the transmit power of the interfering nodes. In this paper, we propose to jointly coordinate the transmit power and the multi-channel allocation to maximize the network throughput performance by fully exploiting multi-channel availability. This coordination enables each node to use high transmission power as long as different orthogonal channels can be assigned to its adjacent nodes. Then, we propose a simple multi-channel media access control (MAC) protocol that allows the nodes on different channels to perform efficient data exchanges without interference in multi-channel networks. We show that the proposed scheme improves the network throughput performance in comparison with other existing schemes.

This letter presents a method to adaptively counter false data injection attacks (FDIAs) in wireless sensor networks, in which a fuzzy rule-based system detects FDIAs and chooses the most appropriate countermeasures. The method does not require en-route verification processes and manual parameter settings. The effectiveness of the method is shown with simulation results.

Content-centric networking (CCN) is an innovative network architecture that is being considered as a successor to the Internet. In recent years, CCN has received increasing attention from all over the world because its novel technologies (e.g., caching, multicast, aggregating requests) and communication based on names that act as addresses for content have the potential to resolve various problems facing the Internet. To implement these technologies, however, requires routers with performance far superior to that offered by today's Internet routers. Although many researchers have proposed various router components, such as caching and name lookup mechanisms, there are few router-level designs incorporating all the necessary components. The design and evaluation of a complete router is the primary contribution of this paper. We provide a concrete hardware design for a router model that uses three basic tables — forwarding information base (FIB), pending interest table (PIT), and content store (CS) — and incorporates two entities that we propose. One of these entities is the name lookup entity, which looks up a name address within a few cycles from content-addressable memory by use of a Bloom filter; the other is the interest count entity, which counts interest packets that require certain content and selects content worth caching. Our contributions are (1) presenting a proper algorithm for looking up and matching name addresses in CCN communication, (2) proposing a method to process CCN packets in a way that achieves high throughput and very low latency, and (3) demonstrating feasible performance and cost on the basis of a concrete hardware design using distributed content-addressable memory.

Radio Frequency based Device-Free Localization (RFDFL) is an emerging localization technique without requirements of attaching any electronic device to a target. The target can be localized by means of measuring the shadowing of received signal strength caused by the target. However, the accuracy of RFDFL deteriorates seriously in environment with WiFi interference. State-of-the-art methods do not efficiently solve this problem. In this paper, we propose a dual-band method to improve the accuracy of RFDFL in environment without/with severe WiFi interference. We introduce an algorithm of fusing dual-band images in order to obtain an enhanced image inferring more precise location and propose a timestamp-based synchronization method to associate the dual-band images to ensure their one-one correspondence. With real-world experiments, we show that our method outperforms traditional single-band localization methods and improves the localization accuracy by up to 40.4% in real indoor environment with high WiFi interference.

In mobile ad hoc networks, a malicious node can respond with a faked route reply (RREP) message to a source that explores a route in order to make the source establish a false route leading to the malicious node. Then, the malicious node can absorb all transmitted packets like a black hole. This paper proposes a totally secure defense against the black hole attack with low control overhead and high reliability. The proposed approach, named a bullet-proof verification (BPV) method, consists of a detection phase, in which a node detects a suspicious node by analyzing the data routing information of its neighbors and a verification phase, in which a node initiates the verification of a suspicious node conditionally only if it receives RREP from the suspicious node. The crux of this approach lies in using an encrypted verification message that goes straight to the destination through the path that may include some malicious nodes and also in using both destination sequence number and hop distance for verification. In addition, a distributed watchdog mechanism is employed to track down any malicious nodes. Simulation results show that the BPV approach reduces control overhead significantly and defends against black hole attack reliably.

Recently network bandwidth becomes a performance concern particularly for collective communication since bisection bandwidths of supercomputers become far less than their full bisection bandwidths. In this context we propose the use of a network coding technique to reduce the number of unicasts and the size of data transferred in latency-sensitive collective communications in supercomputers. Our proposed network coding scheme has a hierarchical multicasting structure with intra-group and inter-group unicasts. Quantitative analysis show that the aggregate path hop counts by our hierarchical network coding decrease as much as 94% when compared to conventional unicast-based multicasts. We validate these results by cycle-accurate network simulations. In 1,024-switch networks, the network reduces the execution time of collective communications as much as 70%. We also show that our hierarchical network coding is beneficial for any packet size.