Active queue management (AQM) is an effective method used in Internet routers to enhance congestion control, and to achieve a trade off between link utilization and delay. The de facto standard, the random early detec...
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Active queue management (AQM) is an effective method used in Internet routers to enhance congestion control, and to achieve a trade off between link utilization and delay. The de facto standard, the random early detection (RED) AQM scheme, and most of its variants use queue length as a congestion indicator to trigger packet dropping. Random early detection (RED) is a widely studied active queue management (AQM) scheme implemented in routers for Internet congestion control. Although certain stability conditions for various RED controllers are discussed, no efficient method for dynamically adapting control gains or result on control gain optimization has been proposed so far. Therefore based on control theory, this paper proposes proportional and integral RED (PI-RED) algorithm, that not only considers the average queue length at the current time slot, but also takes into consideration the past average queue lengths within a round trip time. We provide guidelines for the selection of the feedback gains (the proportional parameter and the integral parameter) for TCP/RED system to stabilize the dynamics, make the congested queue converge at a certain target and hence to improve network performance. Simulations demonstrate that indeed satisfactory performance can be achieved if the control gains are selected based on the guidelines. Based on the stability condition and control gains selection method, extensive simulations with ns2 demonstrate that indeed satisfactory performance can be achieved in terms of robustness, drop probability and stability if the control gains are selected based on the guidelines
Progress has been made in using machine learning techniques such as SVM and neural networks for intrusion detection, but the non-understandable detection results have prevented those algorithms from being thoroughly u...
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Progress has been made in using machine learning techniques such as SVM and neural networks for intrusion detection, but the non-understandable detection results have prevented those algorithms from being thoroughly utilized. In this paper, the authors put forward a novel huge-data oriented method, which was based on the popular association rules extraction algorithm and targeted at the result of intrusion detection, to build real-time rules for enhancing the under standing of detection results and therefore decrease possible loss. The algorithm, by introducing local support, global confidence, CI-Tree and IX-Tree structure, employed these tree structures to build online rules for currently active intrusion. This algorithm solved a number of problems that exist in applying association rules algorithm to intrusion detection;(1) multi-scan (twice at least);(2) mass useless rules due to unbalanced distribution of attacking data;(3) unwanted frequent set produced in the old two-phase rule-building method. Experimental results have demonstrated the method's good performance in both rule building efficacy and time efficiency.
With the widespread use of Internet and the development of information technology, there are a tremendous amount of news information resource. The ability to quickly obtain useful resource from the huge news informati...
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With the widespread use of Internet and the development of information technology, there are a tremendous amount of news information resource. The ability to quickly obtain useful resource from the huge news information is a crucial problem at present. Based on the analysis of news information, this paper introduces an approach of semi-automatically extracting news information from Web resource. Moreover, it gives the system which extracts useful Olympic news information and its experiment results.
An increasingly important requirement for software systems is the capability to evolve dynamically according to the changes of computing environment and users' need during runtime. In this paper, a dynamic softwar...
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An increasingly important requirement for software systems is the capability to evolve dynamically according to the changes of computing environment and users' need during runtime. In this paper, a dynamic software architecture oriented approach is proposed to support online evolution. Notably, architecture information is reified as explicit and manipulable entities to organize a runtime architecture meta-model, which is causally connected to software implementation and specification. By using reflection, the evolved architecture meta-model modifies running system, and updates specification simultaneously. The well-defined architecture meta-model supervises all evolutionary behaviors to ensure system consistency, integrity, and evolution traceability. Based on this model, a visualized integrated development platform entitled Artemis-ARC is also successfully implemented. It supports component and service design, development and assembly, especially dynamic evolution. Furthermore, a simple application case is developed with Artemis-ARC to illustrate the effect of online evolution.
Service Composition enables a new way to create new services by assembling independent service components. One of the important goals in service composition is load balancing across service replicas. In this paper, a ...
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Service Composition enables a new way to create new services by assembling independent service components. One of the important goals in service composition is load balancing across service replicas. In this paper, a novel adaptive distributed load capacity based (LCB) algorithm is presented to solve the load balancing problem in service composition. LCB algorithm uses service routing mechanism to search services and transfer the application data. By self-adaptively calculating the load capacity (LC) metric, LCB algorithm can choose a reasonable service path. LC metric reflects the workload of the service node, and is adaptively adjusted according to the variations of the server's load. Compared with the previous researches, LCB algorithm needn't the global topology information and load information. It is much suitable for dynamic service composition in distributed systems. Simulations show that LCB algorithm performs well in terms of load balancing across the service replicas.
Trusted channel provides various security services for information products in the environment of insecure networks. It has become a focused problem that whether the services of trusted channel provided by security pr...
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Trusted channel provides various security services for information products in the environment of insecure networks. It has become a focused problem that whether the services of trusted channel provided by security products wholly satisfy the security function requirement. Now most evaluation methods are very uncertain and incomplete because they are almost empirical and without theoretical support. This paper proposes an evaluation framework based on the Common Criteria with generalization and reusability in some sense. The formal verification methods are applied in the framework, combined with empirical analysis. As an example, SSH protocol is verified by Cord calculus with type system, cryptographic function, and extended inference rules.
With the increase of multicast data applications, research interests have focused on the design of congestion control schemes for multicast communications. This paper describes a novel control-theoretic multicast cong...
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With the increase of multicast data applications, research interests have focused on the design of congestion control schemes for multicast communications. This paper describes a novel control-theoretic multicast congestion control scheme, which is based on the distributed self-tuning proportional plus integrative (SPI) controller. The control parameters can be designed to ensure the stability of the control loop in terms of source rate. The distributed explicit rate SPI overcomes the vulnerability that suffers from the heterogeneous multicast receivers. It is suggested that the congestion controller is located at the multipoint-to-multipoint multicast source to regulate the transmission rate. We further analyze the theoretical aspects of the proposed algorithm, and show how the control mechanism can be used to design a controller to support multicast transmissions. Simulation results demonstrate the efficiency of the proposed scheme in terms of system stability and fast response of the buffer occupancy, as well as controlled sending rates, low packet loss, and high scalability
In this paper, circuit design of an arithmetic module applied to cryptography - modulo multiplicative inverse is presented and implemented using FPGA hardware technology. This modular arithmetic function contains iter...
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In this paper, circuit design of an arithmetic module applied to cryptography - modulo multiplicative inverse is presented and implemented using FPGA hardware technology. This modular arithmetic function contains iterative computations of division, multiplication and accumulation with variable loop times. Besides standard HDL programming and schematic input, Simulink-to-FPGA has been tried as a different design flow. Experimental results are compared between different design methods with discussion of their pros and cons
The problem of n-connection subgraph discovery (n-CSDP for short) is to find a small sized subgraph that can well capture the relationship among the n given nodes in a large graph. However there have been very few res...
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The problem of n-connection subgraph discovery (n-CSDP for short) is to find a small sized subgraph that can well capture the relationship among the n given nodes in a large graph. However there have been very few researches directly addressing the CSDP problem. Furthermore the currently available methods, for example, the electricity analogues based algorithm can only be suitable for tackling the 2-keynodes CSDP and does not work any more when n is greater than two. To deal with this problem, we propose an effective approach to discover the subgraph in two stages. In the first stage, we propose a neighbor-growth based method to extract a relatively bigger candidate subgraph compared with that of result subgraph. In the second stage, an evolutionary algorithm for optimizing the result subgraph is proposed. For this purpose, UTM code, a transformed representation of the adjacent matrix of graphs is designed to encode the topology of subgraph as individuals. Then corresponding evolutionary operators able to be directly performed on UTM code are given. Thus the efficiency of the algorithm is largely improved. The experimental results obtained on two real large scale graphs with different topology characteristics demonstrate that our method solves n-connection subgraph discovery problems effectively
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