Small cluster in cyber physical systems: network topology, interdependence and cascading failures

In cyber physical system (CPS), computational resources and physical resources are strongly correlated and mutually dependent. Cascading failures occur between coupled networks, cause the system more fragile than single network. Besides widely used metric giant component, we study small cluster (small component) in interdependent networks after cascading failures occur. We first introduce an overview on how small clusters distribute in various single networks. Then we propose a percolation theory based mathematical method to study how small clusters be affected by the interdependence between two coupled networks. We prove that the upper bounds exist for both the fraction and the number of operating small clusters. Without loss of generality, we apply both synthetic network and real network data in simulation to study small clusters under different interdependence models and network topologies. The extensive simulations highlight our findings: except the giant component, considerable proportion of small clusters exists, with the remaining part fragmenting to very tiny pieces or even massive isolated single vertex; no matter how the two networks are tightly coupled, an upper bound exists for the size of small clusters. We also discover that the interdependent small-world networks generally have the highest fractions of operating small clusters. Three attack strategies are compared: Inter Degree Priority Attack, Intra Degree Priority Attack and Random Attack. We observe that the fraction of functioning small clusters keeps stable and is independent from the attack strategies.

Variance-covariance based weighing for neural network ensembles

Neural network (NN) is a popular artificial intelligence technique for solving complicated problems due to their inherent capabilities. However generalization in NN can be harmed by a number of factors including parameter's initialization, inappropriate network topology and setting parameters of the training process itself. Forecast combinations of NN models have the potential for improved generalization and lower training time. A weighted averaging based on Variance-Covariance method that assigns greater weight to the forecasts producing lower error, instead of equal weights is practiced in this paper. While implementing the method, combination of forecasts is done with all candidate models in one experiment and with the best selected models in another experiment. It is observed during the empirical analysis that forecasting accuracy is improved by combining the best individual NN models. Another finding of this study is that reducing the number of NN models increases the diversity and, hence, accuracy.

Design and evaluation of coordinated in-network caching model for content centric networking

In-network caching has been widely adopted in Content Centric Networking (CCN) to accelerate data delivery, mitigate server load and reduce network traffic. However, the line-speed requirement makes the in-network caching space very limited. With the rapid growth of network traffic, it is significant challenging to decide content placement in such limited cache space. To conquer this conflict, coordinated in-network caching schemes are needed so as to maximize the profit of ubiquitous caching capacities. In particular, in-network caching in CCN is deployed as an arbitrary network topology and naturally supports dynamic request routing. Therefore, content placement scheme and dynamic request routing are tightly coupled and should be addressed together. In this paper, we propose a coordinated in-network caching model to decide the optimal content placement and the shortest request routing path under constraints of cache space and link bandwidth in a systematic fashion. Via extensive simulations, the effectiveness and efficiency of our proposed model has been validated.

Prediction based location aided routing for mobile ad hoc networks

Routing in ad hoc networks faces significant challenges due to node mobility and dynamic network topology. In this work we propose the use of mobility prediction to reduce the search space required for route discovery. A method of mobility prediction making use of a sectorized cluster structure is described with the proposal of the Prediction based Location Aided Routing (P-LAR) protocol. Simulation study and analytical results of P-LAR find it to offer considerable saving in the amount of routing traffic generated during the route discovery phase.

Mobility prediction based routing for minimizing control overhead in mobile ad hoc networks

Routing in ad hoc networks faces significant challenges due to node mobility and dynamic network topology. In this work we propose the use of mobility prediction to reduce the search space required for route discovery. A method of mobility prediction making use of a sectorized cluster structure is described with the proposal of the Prediction based Location Aided routing (P-LAR) protocol. Simulation study and analytical results of the of P-LAR find it to offer considerable saving in the amount of routing traffic generated during the route discovery phase.

Multimedia stream rate control over MANET based on router feedback

Streaming applications over Mobile Ad-hoc Networks (MANET) require a smooth transmission rate. The Internet is unable to provide this service during traffic congestion in the network. Designing congestion control for these applications is challenging, because the standard TCP congestion control mechanism is not able to handle the special properties of a shared wireless multi hop channel well. In particular, the frequent changes to the network topology and the shared nature of the wireless channel pose major challenges. In this paper, we propose a novel approach, which allows a quick increase of throughput by using explicit feedback from routers.

Progress Toward Robust Polymer Hydrogels

In this review we highlight new developments in tough hydrogel materials in terms of their enhanced mechanical performance and their corresponding toughening mechanisms. These mechanically robust hydrogels have been developed over the past 10 years with many now showing mechanical properties comparable with those of natural tissues. By first reviewing the brittleness of conventional synthetic hydrogels, we introduce each new class of tough hydrogel: homogeneous gels, slip-link gels, double-network gels, nanocomposite gels and gels formed using poly-functional crosslinkers. In each case we provide a description of the fracture process that may be occurring. With the exception of double network gels where the enhanced toughness is quite well understood, these descriptions remain to be confirmed. We also introduce material property charts for conventional and tough synthetic hydrogels to illustrate the wide range of mechanical and swelling properties exhibited by these materials and to highlight links between these properties and the network topology. Finally, we provide some suggestions for further work particularly with regard to some unanswered questions and possible avenues for further enhancement of gel toughness.

An improved Gbest guided artificial bee colony (IGGABC) algorithm for classification and prediction tasks

Artificial Neural Networks (ANN) performance depends on network topology, activation function, behaviors of data, suitable synapse's values and learning algorithms. Many existing works used different learning algorithms to train ANN for getting high performance. Artificial Bee Colony (ABC) algorithm is one of the latest successfully Swarm Intelligence based technique for training Multilayer Perceptron (MLP). Normally Gbest Guided Artificial Bee Colony (GGABC) algorithm has strong exploitation process for solving mathematical problems, however the poor exploration creates problems like slow convergence and trapping in local minima. In this paper, the Improved Gbest Guided Artificial Bee Colony (IGGABC) algorithm is proposed for finding global optima. The proposed IGGABC algorithm has strong exploitation and exploration processes. The experimental results show that IGGABC algorithm performs better than that standard GGABC, BP and ABC algorithms for Boolean data classification and time-series prediction tasks.

A distributed gateway selection algorithm for UAV networks

In recent years, unmanned aerial vehicle (UAV) has been widely adopted in military and civilian applications. For small UAVs, cooperation based on communication networks can effectively expand their working area. Although the UAV networks are quite similar to the traditional mobile ad hoc networks, the special characteristics of the UAV application scenario have not been considered in the literature. In this paper, we propose a distributed gateway selection algorithm with dynamic network partition by taking into account the application characteristics of UAV networks. In the proposed algorithm, the influence of the asymmetry information phenomenon on UAVs' topology control is weakened by dividing the network into several subareas. During the operation of the network, the partition of the network can be adaptively adjusted to keep the whole network topology stable even though UAVs are moving rapidly. Meanwhile, the number of gateways can be completely controlled according to the system requirements. In particular, we define the stability of UAV networks, build a network partition model, and design a distributed gateway selection algorithm. Simulation results show using our proposed scheme that the faster the nodes move in the network, the more stable topology can be found, which is quite suitable for UAV applications.

Graph theory based QoE-driven cooperation stimulation for content dissemination in device-To-device communication

With multimedia dominating the digital contents, Device-To-Device (D2D) communication has been proposed as a promising data offloading solution in the big data area. As the quality of experience (QoE) is a major determining factor in the success of new multimedia applications, we propose a QoEdriven cooperative content dissemination (QeCS) scheme in this work. Specifically, all users predict the QoE of the potential connections characterized by the mean opinion score (MOS), and send the results to the content provider (CP). Then CP formulates a weighted directed graph according to the network topology and MOS of each potential connection. In order to stimulate cooperation among the users, the content dissemination mechanism is designed through seeking 1-factor of the weighted directed graph with the maximum weight thus achieving maximum total user MOS. Additionally, a debt mechanism is adopted to combat the cheat attacks. Furthermore, we extend the proposed QeCS scheme by considering a constrained condition to the optimization problem for fairness improvement. Extensive simulation results demonstrate that the proposed QeCS scheme achieves both efficiency and fairness especially in large scale and density networks.

A performance comparison of three wireless multi hop ad-hoc network routing protocols when streaming MPEG4 traffic

Mobile ad-hoc networks are characterised by constant topology changes, the absence of fixed infrastructure and lack of any centralised control. Traditional routing algorithms prove to be inefficient in such a changing environment. Ad-hoc routing protocols such as dynamic source routing (DSR), ad-hoc on-demand distance vector routing (AODV) and destination-sequence distance vector (DSDV) have been proposed to solve the multi hop routing problem in ad-hoc networks. Performance studies of these routing protocols have assumed constant bit rate (CBR) traffic. Real-time multimedia traffic generated by video-on demand and teleconferencing services are mostly variable bit rate (VBR) traffic. Most of these multimedia traffic is encoded using the MPEG standard. (ISO moving picture expert group). When video traffic is transferred over MANETs a series of performance issues arise. In this paper we present a performance comparison of three ad-hoc routing protocols - DSR, AODV and DSDV when streaming MPEG4 traffic. Simulation studies show that DSDV performs better than AODV and DSR. However all three protocols fail to provide good performance in large, highly mobile network environments. Further study is required to improve the performance of these protocols in mobile ad-hoc networks offering VBR services.

Topology based packet marking for IP traceback

IP source address spoofing exploits a fundamental weakness in the Internet Protocol. It is exploited in many types of network-based attacks such as session hijacking and Denial of Service (DoS). Ingress and egress filtering is aimed at preventing IP spoofing. Techniques such as History based filtering are being used during DoS attacks to filter out attack packets. Packet marking techniques are being used to trace IP packets to a point that is close as possible to their actual source. Present IP spoofing  countermeasures are hindered by compatibility issues between IPv4 and IPv6, implementation issues and their effectiveness under different types of attacks. We propose a topology based packet marking method that builds on the flexibility of packet marking as an IP trace back method while overcoming most of the shortcomings of present packet marking techniques.

Real-time observation of fiber network formation in molecular organogel : supersaturation-dependent microstructure and its related rheological property

Low-molecular mass organic gelators self-organizing into three-dimensional fiber networks within organic solvents have attracted much attention in recent years. However, to date, how the microstructure of fiber network is formed in a gelation process and the key factors that govern the topological structure of a gel network remain to be determined. In this work, we address these issues by investigating the in situ formation of the gel networks in the N-lauroyl-l-glutamic acid di-n-butylamide (GP-1)/propylene glycol (PG) system. By using optical microscopy, the time evolution of the gel network microstructure was investigated under various supersaturation conditions. It is found that supersaturation is one of the key factors that govern the topological structure of a gel network. In particular, the creation of the junctions turns out to be supersaturation-dependent. The rheological experiments further revealed the correlation between topological structure and mechanical properties. It suggests that the rheological properties can be effectively modified by tuning the microstructure topology of the gel network. Our results reported here provide new physical insight into the formation kinetics of a molecular gel. Furthermore, this work could be important in constructing and engineering a supramolecular structure for the purpose of applications.

A physarum-inspired vacant-particle model with shrinkage for transport network design

Physarum can form a higher efficient and stronger robust network in the processing of foraging. The vacant-particle model with shrinkage (VP-S model), which captures the relationship between the movement of Physarum and the process of network formation, can construct a network with a good balance between exploration and exploitation. In this paper, the VP-S model is applied to design a transport network. We compare the performance of the network designed based on the VP-S model with the real-world transport network in terms of average path length, network efficiency and topology robustness. Experimental results show that the network designed based on the VP-S model has better performance than the real-world transport network in all measurements. Our study indicates that the Physarum-inspired model can provide useful suggestions to the real-world transport network design.