The link loss rate of access network has asymmetry.However,single and multiple source network tomography can only infer the link performance of one direction.Therefore,a full source measurement pattern was proposed and link loss rate inference technology based on full source network tomography was researched in this paper.A method of transforming the full source network to the identifiable network was proposed.Furthermore,the EM algorithm and the MCMC algorithm which infer the link loss rate were derived,and their effectiveness was validated by simulation results.

The measurability is the basis for performance evaluation and management of Ad Hoc networks. We present an interior link loss rate inference algorithm for Ad Hoc networks on the basis of multi-source & multi-destination measurement method. The four steps of this algorithm are as follows: (1) obtain the measurement time window through a link topology snapshot algorithm; (2) build up a measurement model and link loss analysis model for Ad Hoc networks; (3) complete end-to-end multi-source & multi-destination measurement; (4) infer interior link loss rate of Ad Hoc networks according to measurement data sample, correlation among mobile nodes in Ad Hoc network topology, link loss analysis model and statistics theory. Results of simulation indicate that the loss rate inference algorithm based on multi-source & multi-destination measurement is better than that based on one-source & multi-destination measurement. In addition, because of its short computing time, the algorithm is adaptable to interior link performance inference for Ad Hoc networks.

Without the cooperation of internal nodes, the traceroute-based approaches and the SNMP-based approaches will fail to identify the topology of the work. Meanwhile, network tomography techniques can infer the logical topology of network without the cooperation of nodes. This paper focuses on the multiple source, multiple destination network tomography problem. The main contributions are as follows. First, A new measurement method is proposed to evaluate the link utilization of the shared path of the 2-by-1 component in the M-by-N network. Second, with the novel methodology, we firstly resolve the key problem of logical topology identification by multiple source network tomography. Additionally, The accuracy and efficiency of methodology is validated by the simulation results.

Link topology lifetime is not only an important metric to evaluate the dynamic characteristic of Ad Hoc network, but also is a direct and effective method to determine the time to perform Ad Hoc network measurement. This paper introduces the concept of  “snapshot” to take the picture of link topology of three classical mobile mobility (i.e., RPGM, Freeway and Manhattan) respectively. Simulation results show that link topology snapshots method is not only a new  idea to obtain the link topology lifetime of Ad Hoc network, but also the ratio of link connection, variety ratio of link topology and link topology lifetime curve could  also be derived.

The link utilization is an important parameter to describe the running state of the network.At present the research on the link parameter inference technology of network tomography is based on the single source measurements.And the multiple source network tomography has many advantages.The link utilization estimation technology based on multiple source tomography was researched.The joining measurement method was proposed and multiple source link utilization is identifiable if the network is measured by the new method.Furthermore,the necessary and sufficient condition of the measurement sub-network selection to make the link identifiable was proposed.At last,the maximum likelihood estimation of link utilization computed by the EM algorithm was derived and the effectiveness of that was validated by the model simulation and network simulation results.

网络节点的不断运动造成Ad Hoc网络拓扑的动态性。描述和量化动态性是设计、仿真以及测量Ad Hoc网络的基础。首先推导出Ad Hoc网络的链路持续时间分布和拓扑持续时间分布的计算公式,并进行了仿真验证。然后提出利用TTL值感知拓扑变化的方法,并研究了此方法的感知率。最后基于以上结果,提出将网络断层扫描技术应用于Ad Hoc网络时,在测量时间内网络拓扑不发生变化的概率计算公式,并在Ad Hoc网络步行速度场景下给出了仿真结果。研究结果为Ad Hoc网络动态性和端到端测量技术研究提供基础。

Network tomography techniques can infer the logical topology of network without the cooperation of nodes.Multiple source network tomography can obtain more information about the topology detail and the link performance than single source network tomography. How to differ from each other between the six 2-by-2 structures is the core technique of the multiple source network tomography.This paper proposed a 2-by-2 components identification methodology based on the bidirectional measurements and a logical topologies emerging algorithm. The accuracy and efficiency of methodology is validated by the simulation results.

Tactical mobile wireless network is a non-center, self-organization and multi-hop network with a distinct hierarchical architecture. Although many mobility models have been put forward recently, they could not be used for tactical mobile wireless network for its no-hierarchical architecture. The paper not only brings forth a multi-hierarchical group mobility model for tactical mobile wireless network, but also analyzes the dynamic characteristic of the mobility model by using link topology snapshot method. At last, the network performance is conducted by using NS-2 tool. The results demonstrate that the multi-hierarchical group mobility model not only has good dynamic characteristics, but also has a good adaptability to proactive and reactive route protocol. Copyright © 2009 Binary Information Press.

Without the cooperation of internal nodes, the traceroute-based approaches and the SNMP-based approaches will fail to identify the routing topology of the work. Meanwhile, network tomography techniques can infer the logical topology of network without the cooperation of nodes, but loss part information of the routing topology. This paper proposes a new methodology to infer the hop count of the shared path of destinations based on the end-to-end measurements named digging measurement framework, which consists of a series of sandwich probing with different the initial TTL value of the large packet, for each 1-by-2 component and then the routing topology can be inferred by the hop count tree glassification algorithm. The methodology has higher accuracy and efficiency and is validated by the simulation results and the Internet experiences.

The dynamic nature of topology makes it challengeable to estimate link loss rates in mobile ad hoc network (MANET). Firstly, simulation results based on existing mobility models have the unrealistic movement scenarios which may not correctly reflect true MANET performance. Secondly, it is difficult to identify MANET topology under these models due to phantasmagoric movements. This paper presents the circle movement mobility model (CMMM), which is superior to previous models, and its topology identification algorithm to characterize the dynamic MANET topology. Moreover, we present a loss inferring algorithmic based on modeling and computational methodology of factor graphs, which iteratively updates the estimates of link losses. The inference is a process based on unicast back-to-back packets probes sent from a sender to pairs of receivers. Without internal nodes' cooperations, the inference can be calculated using only information recorded at the end hosts. NS2 simulations show that the proposed algorithms exhibit good performance.

This paper focuses on the multiple source, multiple destination network tomography problem. The main contributions are as follows. First, the performance stable delay difference measured by the back-to-back packet pair with different size is used firstly as path metrics to identify the topology. Second, this paper proposes a novel probing meathead to infer the hop count of the shared path for each 1-by-2 component and each 2-by-1 component. Third, with the novel methodology, we firstly resolve the key problem of routing topology identification by multiple sources network tomography. The accuracy and efficiency of methodology is validated by the simulation results.

The performances of the Ad Hoc networks vary rapidly because of the change of topology. How to describe and quantify this dynamic characteristic is the basis of designing and simulating the Ad Hoc network. Describing the move patterns of the nodes is the customary way. This way is called mobility model, which have been found several faults. In this paper, Topology Variety Model (TVM) is proposed to describe the dynamic characteristic from the link layer by means of link duration and connectivity probability and it is realized in the simulator ns-2. The simulation results indicate that with appropriate PDF of link duration for scenario, TVM can replace mobility model to simulate Ad Hoc networks. Meanwhile, the relationship between mobility and TVM is studied. The influence of dynamic on network performance is simulated based on TVM.

Network tomography techniques can infer the logical topology of network without the cooperation of nodes. Multiple source network tomography can obtain more information about the topology detail and the link performance than single source network tomography.How to differ from each other between the four 2-by-2 structures is the core technique of the multiple source network tomography.Based on the analysis of structures,the problem can be conver- ted into how to judge whether two paths have a shared link.A new sandwich probing method is proposed to resolve the problem based on checking the variety of the end-to-end packets delay or loss.The simulation results indicate correct- ness and effectualness of the method.

Link duration is an important metrics to measure the mobility of mobile Ad Hoc network and it directly influences the performance of networks and the routing protocols.But no exact calculating method of link duration has been proposed at present.This paper proposes a calculating model which adapts to many mobile Ad Hoc network mobility models,derives the exact statistic distribution equation of link duration and some calculating equations of metrics to measure mobility(such as average link duration,path duration and link change rate),analyzes the contribution of mobility model direct metrics to the link duration.The correctness of the equation is validated by simulations using ns-2 simulator.This research provides theoretical foundations for calculating path duration,designing mobile Ad Hoc network routing protocols,measuring mobility and researching on performance of network protocols.

Based on the analysis of existing network topology identification algorithms,an improved network topology identification method based on end-to-end loss performance was proposed.The proposed algorithm identified network topology using Hamming distance of the sibling nodes and inferred number of received probe packets at sibling nodes.The proposed algorithm required no support from internal nodes.The theoretic analysis and comparison shown that the improved algorithm can significantly improve the inference accuracy.To validate its accuracy and efficiency,the pro-posed algorithm was implemented in a simulated network.The simulation result shown that the inference accuracy is im-proved more than 20%.

The internal link performance inference is an increasingly important role in evaluating network. In this paper, we explore the use of end-to-end unicast traffic measurements, which consist of back-to-back packets sent from a sender to pairs of receivers, to estimate the delay probability distribution of mobile ad hoc network (MANET) internal links. Since the majority of existing mobility models for MANET do not provide realistic movement scenarios, we propose a novel mobility model based on circle movement. It can be applied to military patrol or search and rescue activities. Using this model, we can infer the stable topology within the identifiable time slot. We then extend the exiting inference algorithm of delay probability distribution in wired network for MANET delay tomography. NS2 simulations with different network scenarios validate the proposed models and inference arithmetic.

Ad Hoc network has become increasingly important in military and commercial applications.However, the dynamic properties of the Ad Hoc network are so complicated and troublesome that Ad Hoc network performance efficient measurement method is still dubious.In this paper, on the basis of analysis of the Ad Hoc network’s dynamic properties and traditional network measurement and Network Tomography technologies, an Ad Hoc network performance measurement architecture and some key problems are presented.

In recent years, Botnet has been one of the emerging serious threats to the Internet and attracted wide atten- tion from researchers. By analyzing the characteristics of abnormal behavior shown by Botnet at its different stages, the paper proposes a Botnet-detecting method based on abnormal-behavior-monitoring, describes the principle and the struc- tural framework of the system, including the design and implementation of its key technology.

The internal link performance inference has become an increasingly important issue in operating and evaluating a sensor network. Since it is usually impractical to directly monitor each node or link in the wireless sensor network, we consider the problem of inferring the internal link loss characteristics from passive end-to-end measurement in this paper. Specifically, the link loss performance inference based on the data aggregation is considered. Under the assumptions that the link losses are mutually independent, we formulate the problem of link loss estimation as a Bayesian inference problem and propose a Markov Chain Monte Carlo algorithm to solve it. Through the simulation, we can safely reach the conclusion that the internal link loss rate can be inferred accurately, comparable to the sampled internal link loss rate, and the simulation also shows that the proposed algorithm scales well according to the sensor network size.

Network Identification, one of the studies of the network tomography, is the proposition of the network link-level performance inference. The present methods rely either on the network performance or on the posterior distribution, and the time spent on the identification increase as the size of the network, which may restrict the technique to be used in practice. To overcome the above problems, we propose a fast approach to identify the logical network topology in this paper. Compared with the previous methods, the proposed one only needs to calculate the Manhattan distance based on the measurements to identify the network topology, which saves more time than the present ones, and the time spent on the identification do not increase sharply as the size of the network. From the simulation study, we find that the fraction of correctly classified trees fast converge, and accurately identify the trees even under the conditions that just hundreds of probe packets are injected. So the proposed method is very promising in the real network.