Metabolic P Systems： A Discrete Model for Biological Dynamics

A recent methodology to model biochem- ical systems is here presented. It is based on a concep- tual framework rooted in membrane computing and de- veloped with concepts typical of discrete dynamical sys- tems. According to our approach, from data observed at suitable macroscopic temporal scales, one can deduce, by means of algebraic and algorithmic procedures, a dis- crete model （called Metabolic P system） which accounts for the experimental data, and opens the possibility to under- stand the systemic logic of the investigated phenomenon. The procedures of such a method have been implemented within a computational platform, a Java software called MetaPlab, processing data and simulating behaviors of metabolic models. In the paper, we briefly describe the theory underlying the modeling of biochemical systems by Metabolic P systems, along with its development stages and the related extensive literature.     

Arithmetic Expression Evaluations with Membranes

Arithmetic operations and expression eval- uations are fundamental in computing models. This paper firstly designs arithmetic membranes without priority rules for basic arithmetic operations, and then proposes an algo- rithm to construct expression P systems based on several of such membranes after designing synchronous and asyn- chronous transmission strategies among the membranes. For any arithmetic expression, an expression P system can be built to evaluate it effectively. Finally, we discuss differ- ent parallelism strategies through which different expres- sion P systems can be built for an arithmetic expression.     

Application of Adaptive Fuzzy Spiking Neural P Systems in Fault Diagnosis of Power Systems

Adaptive fuzzy spiking neural P systems （AFSN P systems） are a novel kind of computing mod- els with parallel computing and learning ability. Based on our existing works, AFSN P systems are applied to deal wlth the fault diagnosis problems of power systems and the uncertainty of action messages about protective relays and breakers, and a new fault diagnosis model of power systems is proposed with simple reasoning process and fast speed with parallel processing capabilities. The effectiveness of the fault diagnosis model is verified by some examples of fault diagnosis. Furthermore, the learning ability of AFSN P systems can be applied to adjust the weights in the fault diagnosis model automatically.     

Evaluating Logical Expressions by Membrane Systems

Boolean and relational operations, which are defined for solving mathematically logical problems, are always required in computing models. Membrane com- puting is a kind of distributed parallel computing model. In this paper, we design different membranes for imple- menting primary Boolean and relational operations respec- tively. And based on these membranes, a membrane sys- tem can be constructed by a present algorithm for eval- uating a logical expression. Some examples are given to illustrate how to perform the Boolean, relational opera- tions and evaluate the logical expression correctly in these membrane systems.     

Study of Intrusion Detection Systems

Modern network systems have much trouble in security vulnerabilities such as buffer overflow, bugs in Microsoft Internet, sensor network routing protocol too simple, security flaws of applications, and operating systems. Moreover, wireless devices such as smart phones, personal digital assistants （PDAs）, and sensors have become economically feasible because of technological advances in wireless communication and manufacturing of small and low-cost sensors. There are typologies of vulnerabilities to be exploited in these devices. In order to improve securities, many mechanisms are adopted, including authentication, cryptography, access control, and intrusion detection systems （IDS）. In general, intrusion detection techniques can be categorized into two groups： misuse detection and anomaly detection. The misuse detection systems use patterns of weB-known attacks or weak spots of the systems to identify intrusions. The weakness of misuse detection systems is unable to detect any future （unknown） intrusion until corresponding attack signatures are intruded into the signature database. Anomaly detection methods try to determine whether the deviation is from the established normal usage patterns or not. The critical success of anomaly detection relies on the model of normal behaviors.     

Applying HOSVD to Alleviate the Sparsity Problem in Context-aware Recommender Systems

It is quite a great challenge for Context- aware recommender systems （CARS） to generate accurate recommendations with only a few available none-zero con= textual user preferences. This paper presents a new ap- proach to alleviate this high sparslty problem by applying the Higher order singular value decomposition （HOSVD） technique. Firstly, it constructs an N-order tensor to rep- resent multidimensional contextual user preferences and decompose it into （N- 2） 3-order tensors according to different types of context （such as time, location and ac- tivity）. Secondly, it introduces HOSVD to automatically discover the latent associations among these different 3- dimensional objects and predicts unknown unidimensional contextual user preferences. Finally, it calculates every contextual influence coefficient that each type of context factor influences user preferences and then constructs a new N-order tensor using weighted linearization method in order to provide recommendations. Experimental eval- uation on a simulated personalized mobile services envi- ronment demonstrates the efficacy of our approach against the other baseline ones.     

Joint Optimization of Subchannel Reassignment and Power Adaptation for Multicarrier Cooperative Systems

An amplify-and-forward multicarrier cooperative system was proposed in this paper. The optimal resource-allocation problem was investigated in terms of improving data rate. An effective resource-allocation algorithm was proposed based on three techniques, adaptive modulation, subchannel reassignment design and transmit power adaptation. The designed subchannel reassignment not only increases the average data rate, but also raises the threshold of ＂water-filling＂ in optimizing power allocation that can further increase data rate. Since the power allocation is based on the designed subchannel reassignment, the complexity of the proposed algorithm is reduced greatly. Simulation results show that the proposed algorithm effectively increases the system＇s average data rate.     

On the Design and Temporal Petri Net Verification of Grid Commerce Architecture

The emergence of Grid Computing settings lays a solid foundation for designing and constructing a next generation E-commerce environment. This work presents a new E-commerce architecture based on a Grid Computing environment, and models and analyzes the architecture using Temporal Petri nets （TPNs）. It can make sufficiently use of the Grid resources to implement various electronic bargains between the geographically dispersed users. By means of its TPN model, some main temporal properties are represented and verified formally.     

Self-Organization Approaches for Optimization in Cognitive Radio Networks

Cognitive radio （CR） is regarded as a promising technology for providing a high spectral efficiency to mobile users by using heterogeneous wireless network architectures and dynamic spectrum access techniques. However, cognitive radio networks （CRNs） may also impose some challenges due to the ever increasing complexity of network architecture, the increasing complexity with configuration and management of large-scale networks, fluctuating nature of the available spectrum, diverse Quality-of-Service （QoS） requirements of various applications, and the intensifying difficulties of centralized control, etc. Spectrum management functions with self-organization features can be used to address these challenges and realize this new network paradigm. In this paper, fundamentals of CR, including spectrum sensing, spectrum management, spectrum mobility and spectrum sharing, have been surveyed, with their paradigms of self-organization being emphasized. Variant aspects of self- organization paradigms in CRNs, including critical functionalities of Media Access Control （MAC）- and network-layer operations, are surveyed and compared. Furthermore, new directions and open problems in CRNs are also identified in this survey.     

Best Effort Spectrum Allocation Scheme for Femtocell Networks in Dense Deployment

In orthogonal frequency division multiple access（OFDMA） based femtocell networks,the co-tier interference among femto base stations（FBS） becomes important in multiuser and densely deployed environment.In order to mitigate the co-tier interference and enhance the system total throughput,this paper proposed a best effort spectrum allocation scheme based on the extension of graph theory.In the scheme,a controller was proposed to collect the channel state information（CSI）of all femtocell user equipments（FUEs） in a certain range.Then,the controller evaluated the signal-to-interference Ratio（SIR） of each FUE and determined the set of its interference neighbors.By calculating the received power matrix（RPM） among FUEs and building interference graph matrix（IGM）,different spectrum resource blocks（RBs） were assigned to the users with interference relation,while users without interference relation shared the same RBs,which could increase the spectrum efficiency.Simulation results show that the proposed algorithm can significantly improve the RB usage efficiency compared with the basic graph coloring theory,and more than 80% improvement can be acquired in dense deployment scenario.Besides,the throughput of both cell edge macro user equipments（MUEs） and cell edge FUEs is guaranteed on the premise of low interference.     

A Novel Surface Treatment Method for Improving the Antenna System Performance of Mobile Phones with Stainless Steel Frame

A novel surface treatment method of plat-ing Cu＋PPS film/coating on a mobile phone＇s stainless steel frame for improving the antenna system efficiencies is proposed. The mobile phone was measured in free space, in a silicon cover, and in the hand and cover si- multaneously. It＇s found that with this surface treat-ment, the total efficiency of the antenna system can be improved in all the four cases respectively by 14.22%, 1.38%, 15.19% and 1.72% at 940MHz （GSM900：880- 960MHz）, 2.59%, 3.21%, 4.81% and 1.43% at 1720MHz （DCS：1710-1880MHz） and 6.34%, 2.85%, 9.83% and 2.32% at 2100 MHz （WCDMA：1920-2170MHz）. This low- cost surface treatment method is an important break- through to improve antenna system performance of mobile phones especially for those with a stainless steel frame, and suitable for mass production.     

A Fuzzy Similarity-based Clustering Optimized by Particle Swarm Optimization

Traditional fuzzy clustering algorithms based on objective function is unable to determine the optimum number of clusters, sensitive to the initial cluster centers, and easily sunk into the issue of local optimum. A Fuzzy similarity-based clustering （FSBC） algorithm is proposed in this paper. This method consists three phases： first, the objective function is modified by integrating Fuzzy C-means （FCM） and Possibilistic C-means （PCM） method; second, using the density function from data for similarity-based clustering to automatically generate initial prototype without requesting users to specify; finally, the iteration process optimized by Particle swarm optimization （PSO） to obtain appropriate adjustment parameters that can provide better results, which avoids the local minimum problems of traditional methods. The experimental results on the synthetic data and UCI standard data sets show that the proposed algorithm has greater searching capability, less computational complexity, higher clustering precision.     

Optimal energy efficiency capacity under joint design of sensing and transmission duration for cognitive radio system

Due to its opportunistic spectrum sharing capability, cognitive radio （CR） has been proposed as a fundamental solution to alleviate the contradiction between spectrum scarcity and inefficient utilization of licensed spectrum. In CR system （CRS）, to efficiently utilize the spectrum resource, one important issue is to allocate the sensing and transmission duration reasonably. In this paper, the evaluation metric of energy efficiency, which represented the total number of bits that were delivered with per joule of energy consumed, is adopted to evaluate the proposed scheme. We study a joint design of energy efficient sensing and transmission durations to maximize energy efficiency capacity （EEC） of CRS. The tradeoff between EEC and sensing and transmission durations are formulized as an optimization problem under constraints on target detection probability of secondary users （SUs） and toleration interference threshold of primary users （PUs）. To obtain the optimal solution, optimizing sensing duration and transmission duration will be first performed separately. Then, a joint optimization iterative algorithm is proposed to search the optimal pair of sensing and transmission durations. Analytical and simulation results show that there exists a unique duration pair where the EEC is maximized, and that the EEC of the proposed joint optimization algorithm outperforms that of existed algorithms. Furthermore, the simulation results also reveal that the performance of the proposed low complexity iterative algorithm is comparable with that of the exhaustive search scheme.     

A Scalable Peer-to-Peer Web Services Overlay for Semantic Discovery

The growing number of web services advocates distributed discovery infrastructures which are semantics-enabled. We introduce a novel approach for semantic discovery of web services in structured P2P-based （Peer-to-Peer） registries. We partition concepts into different CGs （Concept groups） and index these ordered concept sets in a two-phase semantic routing mechanism. Each node and query has one concept set as its unique ID. For each concept in the query, current node first route the query to a node with nodeID that shares a prefix as long as with the query, but a longer CG. Second, the query will be routed to a node sharing a longer prefix than that of the current node. Combining with semantic similarity calculation, our proposal guarantees that most existing services matching a query will be found with bounded costs in terms of number of nodes involved. The scalability and reliability of our approach are also confirmed through emulation tests.     

Novel Active Contour Model for Image Segmentation Based on Local Fuzzy Gaussian Distribution Fitting

A novel active contour model is proposed, which incorporates local information distributions in a fuzzy energy function to effectively deal with the intensity inhomogeneity. Moreover, the proposed model is convex with respect to the variable which is used for extracting the contour. This makes the model independent on the initial condition and suitable for an automatic segmentation. Furthermore, the energy function is minimized in a computationally efficient way by calculating the fuzzy energy alterations directly. Experiments are carried out to prove the performance of the proposed model over some existing methods. The obtained results confirm the efficiency of the method.     

PTCP Incast in Data Center Networks

In recent years, dual-homed topologies have appeared in data centers in order to offer higher aggregate bandwidth by using multiple paths simultaneously. Multipath TCP （MPTCP） has been proposed as a replacement for TCP in those topologies as it can efficiently offer improved throughput and better fairness. However, we have found that MPTCP has a problem in terms of incast collapse where the receiver suffers a drastic goodput drop when it simultaneously requests data over multiple servers. In this paper, we investigate why the goodput collapses even if MPTCP is able to actively relieve hot spots. In order to address the problem, we propose an equally-weighted congestion control algorithm for MPTCP, namely EW-MPTCP, without need for centralized control, additional infrastructure and a hardware upgrade. In our scheme, in addition to the coupled congestion control performed on each subflow of an MPTCP connection, we allow each subflow to perform an additional congestion control operation by weighting the congestion window in reverse proportion to the number of servers. The goal is to mitigate incast collapse by allowing multiple MPTCP subflows to compete fairly with a single-TCP flow at the shared bottleneck. The simulation results show that our solution mitigates the incast problem and noticeably improves goodput in data centers.     

A New Key Management Protocol to MANET

MANET （Mobile ad-hoc networks） are networks in which nodes are mobile and link connectivity might be changing all the time. The wireless and dis- tributed nature of MANET pose a great challenge to system security. Key management is an important and complex problem to the authentication and system security. The paper proposes a new method to the key management with high efficiency. Which,making use of the ideas of self-organization and local driven by intercross authenti-cation of CAs and threshold encryption. It＇s proved that the new method can reduce the communications delay and time delay in the key management process compared to other methods. So, it is a contribution to the field of key management in MANET.     

A Probability Driven Quadri-Stage Contention Protocol for Mobile Ad Hoc Networks

The paper proposes a new contention based Time division multiple access （TDMA） Medium access control （MAC） protocol in wireless ad hoc networks, which can be termed Quadri-stage contention protocol （QSCP）. The QSCP protocol is free of both the ＂hidden terminal＂ and the ＂exposed terminal＂ problems. It is distributive and arbitrarily scalable. In the dedicated contention stage, nodes exchange their ＂Normalized accumulation and dissipation rate of payload （NADROP）＂ messages in 2-hop neighborhood, and then run a contention probability calculation algorithm to decide the probability of sending a contention frame. The algorithm guaran- tees that the number of time slot reserved by a node is proportional to its NADROP value, which can remarkably improve the end-to-end throughput when network load is heavy, and is more efficient in energy consumption. The simulation results demonstrate that QSCP performs better than the existing protocols.     

Mechanism Design Based Nodes Selection Model for Threshold Key Management in MANETs

The design of threshold based distributed Certification authority （CA） has been proposed to provide secure and efficient key management service in Mobile ad hoc networks （MANETs）, but most of previous work ig- nore the efficiency and effectiveness and assuming there are always honest nodes performing the service. Focus- ing on developing a model to select a coalition of nodes dynamically and optimally to carry out the threshold key management service in MANETs, we formulate the dy- namic nodes selection problem as combinatorial optimiza- tion problem, with the objectives of maximizing the success ratio of the service and minimizing the nodes, cost of secu- rity and energy, and then extend the payment structure of the classical Vickrey, Clarke and Groves （VCG） mechanism design framework to ensure truth-telling is the dominant strategy for any node in our scenario. Compared with ex- isting works in the presence of selfish nodes, the proposed model enjoys an improvement of both the success ratio of key management service and lifetime of the network, and a reduction of both the cost of participating nodes and compromising probability of MANETs.     

Labeling Algorithm for Face Detection Using Skin and Hair Characteristics

This research presents an algorithm for face detection based on color images using three main components： skin color characteristics, hair color characteristics, and a decision structure which converts the obtained information from skin and hair regions to labels for identifying the object dependencies and rejecting many of the incorrect decisions. Here we use face color characteristics that have a good resistance against the face rotations and expressions. This algorithm is also capable of being combined with other methods of face recognition in each stage to improve the detection.