Earticle

Due to abuse by insiders or penetration by outsiders, network systems usually suffer various security issues. In order to achieve high dependable and low cost monitoring, this paper proposes a dependable monitoring mechanism combining static threshold-based and dynamic anomaly detection. Firstly, the performance metrics of host and network are collected through different methods. In static threshold-based detection phase, the secondary metrics are combined to several group items. When any group item exceeds its threshold, dynamic detection methods are adopt to further detect anomaly. In dynamic detection phase, PCA, joint Gaussian distribution, and Bayesian classification are combined to achieve low cost and efficient anomaly detection. Experimental results in a campus-wide network system show that the proposed dependable monitoring mechanism achieves low false negative (FN) rate and low false positive (FP) rate. The proposed monitoring mechanism outperforms PCA & Bayesian, and grouping detection methods.

A cognitive radio wireless network is an emerging communication paradigm to effectively address spectrum scarcity challenge. In this paper, we investigate the performance improvement gained by applying cognitive radio to a multiple Wireless Service Providers (WSPs). We consider several independent WSPs and two types of users: primary (licensed) and secondary (unlicensed) users. We have proposed a scheme for secondary users to manage their handoff based on a threshold on the number of channels fixed by the WSP. As each WSP evolves in a random environment, we propose a game theoretic framework to find a Nash equilibrium and a stochastic learning algorithm to converge to this equilibrium. A Markov process, with continuous time and finite state space, models the system. Numerical results show the system equilibrium points and the conditions to converge to the best one of them to increase the spectrum utilization of cognitive users.

OFDM technology has become the core technology of the next generation mobile communication system because of the high bandwidth efficiency, the strong ability to resist inter-carrier interference and anti-channel interference. However, because OFDM system is a multicarrier modulation system, the system will be very sensitive to its synchronization errors. Synchronization estimation is an important part of the OFDM system. Based on the research of Schmidl & Cox and Minn synchronization algorithms, this paper proposed an improved timing synchronization algorithm which adopted the training sequence, and the timing synchronization estimation function has been optimized for this improved algorithm. The peak platform issue of Schmidl & Cox algorithm, the no sharp peak issue of Minn (1) algorithm and the vice peak issue of Minn (2) algorithm were eliminated based on the improved algorithm. The simulation results showed that the timing judgment curve of the improved algorithm had a very sharp peak at the timing synchronization position. Compared with the conventional algorithm, the timing synchronization performance of the improved algorithm was better. The overall performance of OFDM system was improved.

If there is a certain distance between the primary users and the second, there are asynchronous interferences because of existing nonsynchronous signals. And the interferences do not influence only the primary user system, but they could also affect second user system and increase interference. To solve this problem and to eliminate interference to primary and secondary asynchronous users among which there are influences in wireless communication system, a novel kind of precoding method based on the minimum mean square error is put forward in this paper. In this method, asynchronous interferences are eliminated in the precoding process and this process also satisfies users’ server quality. Analysis and simulation show that the proposed scheme effectively ,under the condition of the limitation of interferences in main user system, enhance the second user system capacity and improve the reliability of the transmission system of second users system.

Wireless sensor networks (WSNs) has gained more and more popularity in the field of intensive meteorological observation. Generally, each existing sensor node is a constrained device with restricted computation capability, and limited energy resources. The effective communication range of existing sensor nodes is unable to meet our requirements. In this paper, we present an improved system architecture of wireless sensor node that is capable of meeting the strict requirements of intensive meteorological observation systems. We add a solar power supply module to replenish node energy and adopt a network processor and a data acquisition processor collaborating with each other to improve the computation and computation capacity. Furthermore, we designed a dual-band data transmission mechanism so as to adapt to requirements of different transmission distances. Our tests have indicated that using solar power can fulfill a node’s energy demand; whereas the design on computing and computing can dynamically meet the specific requirements of different applications. Moreover, our nodes is compatible with a variety of digital and analog sensor signal types, so it can be connected to various professional meteorological sensors directly. In addition, the communication distance of the node is significantly improved, which can reach more than 2000 meters in an open environment and 1000 meters with building obstruction or slight signal interference.

During operation of a cellular system, unexpected growth of traffic may develop in various regions, create traffic congestion. Among many methods to solve problem of large blocking probability, dynamic cell sectoring using smart array antenna is specially interested. In this paper, we investigate the relationship between antenna parameters (main beamwidth, sidelobe attenuation...) and blocking probability of multibeam CDMA system under the presence of hotbeam. From that, we consider deployment sectoring dynamically based on Generalized Sidelobe Canceller (GSC) structure to get blocking probability below 1%. In addition, we consider the way to decrease the complexity of array antenna using sparse array.

During the random access process of LTE system, PRACH needs to perform significant amount of computations (e.g. IFFT, FFT) on received signals. Therefore conducting downsampling on received signals is necessary to decrease the complexity of the subsequent signal processing work. Downsampling usually employs a multi-stage filter which consists of a CIC filter, a compensation filter and a half-band filter. This paper introduced a new donwsampling method using a multi-stage half-band filter with three half-band decimation filters. Compared with the traditional one, the new method showed a great increase in computing efficiency. The new filter was designed and a plan of implementing this filter on FPGA was suggested. MATLAB simulation was performed and the simulating results showed that the method proposed in this paper is capable of conducting downsampling on received signals, especially in the random access channel.

CAN bus is ISO international standard serial communication protocol. It is one of the most widely used fieldbus in the world. It has become the standard bus of embedded industrial control LAN. Ethernet is the most common communication protocol standard that is applied in the existing LAN. Networked industrial control usually adopts fieldbus and Ethernet network, thus the protocol conversion problems of the heterogeneous network composed of Ethernet and CAN bus has become one of the research hotspots in the technology of the industrial control network. STM32F103RC ARM microprocessor was used in the design of the Ethernet-CAN protocol conversion module, the simplified TCP/IP communication protocol - uIP protocol was adopted to improve the efficiency of the protocol conversion and guarantee the stability of the system communication. The results of the experiments show that the designed module can realize high-speed and transparent protocol conversion.

A single flow stream could be divided into several sub-flows to be sent across multiple paths. This method obtains obvious advantages against traditional TCP as it maintains higher reliability and makes bettaer use of the network resources. Congestion control algorithm is an essential part to be considered. This paper first reviews the existing multipath TCP congestion control algorithms and then analyzes and formulates the goals and problems need to be achieved and solved. A delay-based congestion control algorithm named Weighted Vegas (wVegas) is provided. Finally, two possible modifications are demonstrated including adjusting the congestion control window according to how far the path is from congestion and redefining the behavior when loss occurs.

In this paper, we made a comprehensive simulative study on the performance assessment of a MIMO MC CDMA wireless communication system. The proposed system under investigation consider a communication link between three multi antenna supported units such as a mobile user unit, base station and relaying node. The system incorporates four low-complexity channel equalization techniques, various digital modulations and Block cipher encryption based channel coding schemes. From MATLAB based simulated study on synthetic data transmission, it is found a quite noticeable impact on deploying a single relaying node on performance enhancement of the presently considered MIMO MCCDMA system. The system is also capable of showing its robustness in retrieving transmitted data over hostile multipath fading channels in a scenario of thickly populated urban area.

The mobile devices in resource-constrained mobile ad-hoc networks (MANETs) usually communicate with each other without going through base stations. When the communication between mobile devices gets complicated due to fast changing technical developments and increased mobile devices, how to maintain transmission paths efficiently in order to elevate the network performance becomes a critical issue. To this purpose, this paper presents an advanced tree-based multicast routing protocol which uses an improved label mechanism to maintain the topology and multicast groups of a MANET, and uses the built backup paths to secure better transmission stability. Simulation results show that, with slightly more control overhead, the new routing protocol is able to yield constantly higher delivery ratios vs. increased data flow, when compared with other multicast routing protocols.

Out-of-band (OOB) power emission is a conventional issue in orthogonal frequency division multiplexing (OFDM) system. The spectral leakage results in interference to licensed users (LU) in OFDM-based cognitive radio (CR) system. In this article, an adaptive precoding scheme based on the adaptive orthogonal projection matrix is proposed for OOB power suppression. Low complexity is the main feature of this preceding scheme. Simulation and analysis show that this method reduces the out-of-band power significantly by forcing the power spectrum density (PSD) of several frequency points in OOB to be zero. An advanced precoding scheme proposed later achieves a tradeoff between performance of OOB power suppression and bit error rate (BER) in the receiver. With those schemes, an adaptive precoder is proposed, which has three ways to adaptively adjust precoding matrix to achieve a balance among the complexity of system, the performance of out-of-band power reduction and BER in the receiver.

Nowadays, the research and application about delay-tolerant network (DTN) have become more and more popular. A communications network that is capable of storing packets temporarily in intermediate nodes, until the time an end-to-end route is re-established or regenerated is known as a delay tolerant network/s, in short, DTN.Routing of the packets in DTN is based on store-carry-and forward paradigm. When a node receives a message but no availability of paths towards destination node, the message should be buffered in the current node and wait for opportunities to encounter other nodes. This paper aims to detail basic & general aspects specific to information needs in DTN routing and present classification chart. We discuss some detail of routing issues and classifications of routing protocols. Routing is one of the major issues affecting the overall performance of DTN networks in terms of resource consumption, data delivery. Over the past few years a number of routing protocols have been proposed for DTN networks. In this paper mainly three DTN routing protocols Epidemic, PROPHET and Spray and Wait Routing protocols are discussed.

Aiming at the limited energy characteristics of wireless sensor networks, we apply game theory to solve the power control problem to reduce energy consumption in wireless sensor networks. In this paper, a distributed power control algorithm based on non-cooperative game theory under incomplete information is proposed, which adopts Signal-to-Interference Noise Ratio (SINR) as utility function. The purpose of power control algorithm for non-cooperative game is to achieve the largest utility by optimal power control strategy, thus improve the total network energy efficiency. Moreover, Bayesian Nash equilibrium theorem is introduced to study the existence and uniqueness proof of Nash equilibrium algorithm. Simulation results show that there exist points for each of the cost functions considered, which give the maximum net utility given the strategies taken by all other nodes as fixed. And the proposed algorithm is efficient and can achieve better performance.

Sink mobility has been viewed as an important technique to improve network performance for wireless sensor networks (WSNs) such as energy consumption and balancing, network lifetime, throughput, end-to-end delay etc. Also, it can largely mitigate the hot spots near sink node as sink node moves randomly or autonomously. In many applications of WSNs, sensors are deployed in areas accessed by laid roads and sinks can be assembled on mobile devices like bus or handcart. In this paper, we propose a Global Best Path (GBP) data gathering algorithm based on wireless Sensor Networks with single Mobile Sink (GBP-MSSN). It aims at determining the best position for the single mobile sink and further using global sensors information to generate the best scheme to gather data from specified node. Generating of best scheme is conducted by GBP algorithm which can balance energy consumption among whole sensor networks and further prolong the network lifetime. Simulation results show that our GBP-MSSN algorithm outperforms conventional algorithms like LEACH, GAF, etc.

The complex social network theory is applied to solve the group doctor-patient conflict in present paper. Results showed that there were different interests in the evolution process of doctor-patient conflict. A complex network structure was developed around core interests and core nodes in the process of doctor-patient conflict. And this network structure can be reinforced under the law of "robustness" and "self organized criticality" .With the probability of the occurrence of events, the model of social behavior will change suddenly and make the events out of control.

With increasing video service consumption through IP network, HTTP Adaptive Streaming (HAS) technology has become popular. The chunked transmission and application-layer adaption create a different traffic pattern than traditional progressive download where the entire video is downloaded with a single request. Its start and stop activity cause burst and retransmission timeout (RTO) which result in more packet loss and longer packet transfer delay. Both of them can substantially degrade the achievable throughput of HAS streams. However, few works studied the impact of HAS activity pattern on TCP performance. In this paper, the reason caused the poor performance of HAS is pointed out, and the two server-based algorithms are proposed to improve the achievable throughput of HAS streams. The two algorithms are implemented at the beginning and end of a chunk transmission separately. They aim to improve the performance of HAS through smoothing the burst and avoiding RTO. The simulation results show that these proposed algorithms increase the achievable throughput of HAS streams greatly and keep HAS streams friendly with other TCP flows at the same time.

Nowadays, Dense Wavelength Division Multiplexing (DWDM) has become a key component of the world’s communications infrastructure. The significant improvement in high-speed electronics and optical components, and multi-level modulation formants and coherent receiver technology has enabled high rate data transmission. DWDM promises to increase the bandwidth per fiber as the bit rate and the number of wavelengths increase. According to ITU-T G.694.1, mostly used DWDM systems have been operating with 40, 80 and 120 wavelengths, and with advanced modulation schemes and coherent receiver technology along better dispersion management, a single wavelength in today’s world can able to transmit upto 100Gbps; thus total maximum bandwidth is an amazing 4Tbps, 8Tbps, and 12Tbps, respectively. However, today’s commercial systems have a fiber transmission requirement for around 10Tbps, and globally demand has been increasing about 35% to 45% per year. Hence, to meet this increasing demand transponders transmission rate must have to be increased. This paper reviews the progress and techniques used to increase wavelength throughput from 2.5Gbps to 100Gbps, and investigates the challenges to transmit data beyond 100Gbps in a single operational cycle.

As a mainstream technology in the 4G systems, TD-LTE (Time Division-Long Term Evolution) introduces Femto nodes to improve spectral efficiency per unit area. However, inter-cell cross-slot interference and uplink/downlink configuration are the key problems in TDD (Time Division Duplexing) system. In the paper, a traffic adaptation scheme with consideration of traffic demands and interference level is proposed to select optimal uplink/downlink configuration and efficiently improves system capacity.

In this paper, a enhanced DFT-based channel estimation for OFDM systems is proposed. Conventional DFT-based channel estimations improve the performance by suppressing time domain noise beyond the length of the cyclic prefix (CP), so it does not completely suppress the noise. However, they potentially require information on channel impulse responses and may also result in mean-square error (MSE) floor due to incorrect channel information such as channel delay spread. In order to overcome the disadvantage, our proposed channel estimation can improve the performance by deciding significant channel taps adaptively. Significant channel taps are detected on the basis of cluster discriminant analysis. Simulation results demonstrate that the proposed algorithm outperforms the conventional DFT-based estimation in terms of BER and MSE performance.

This paper presents an flexible architecture for Internet of things utilizing a local manager with the goal to solve many issues. The solution is described from both the system architecture and example applications. The component design and the communication between these components are introduced. The Local Manager architecture is composed of a gateway, Message Broker, Message Relay Bridge and several small applications (Apps) with different purposes. The Local Manager can be used as a platform for future integration of things into cloud services via the Internet.

Web services have been widely applied in e-business or organizations to establish versatile applications. However, service composition with constraint to QoS constraints still remains as a challenging issue, because both the service performance and the QoS requirements of applications tend to be dynamically changed at runtime. To address this problem, in this paper we present a novel service composition framework, which takes advantage of flexibility provided by cloud systems and applies evolution strategy to solve the optimal programming problem of multiple QoS constrained service composition. Furthermore, a QoS negation mechanism is proposed to satisfy the dynamical and elastic cloud environments. Massive experiments are conducted to investigate the effectiveness of the proposed framework, and the results show that it can significantly reduce the costs of large-scale service-based application in terms of various QoS metrics.