A robust PID controller for active queue management (AQM) based on modern H<sub>∞</sub> optimal control theory is presented in this paper. Taken both robustness and closed loop performance into consideration, most desirable parameters value can
be gotten through some straightforward analytical formulas. Our robust PID controller is determined only by one
parameter, other than traditional PID controller is by three or more. Additionally, this new parameters determining
method can not only be extended to other AQM controller based on classical control theory or optimal control theory, but
also be easily understood and implementation. We evaluate the performances of the controller extensively. The results
show that the robust PID congestion controller outperform the existing controller, such as PI, RED, on keeping the router
queue size at the target value. The most obvious property of the controller is that it takes on robustness such that it can
adapt the network dynamic.
The energy-constrained nature of wireless ad hoc networks calls for the protocols that use the energy efficiency as its
primary design goal. In order to evaluate and compare the energy-aware protocols in terms of their energy efficiency, an
energy-consumption model which can accurately compute the energy consumed by the data communication activities is
crucial. In this paper, we firstly give a comprehensive summary of the existing energy-consumption models. All energyconsumption
models are categorized into three types, and the characteristics of each type are discussed in detail.
Secondly, we propose a new efficient energy-consumption model which is a collection of functions of the packet size
and the RF (Radio Frequency) power level. The main contribution of our model is that all nodes in the model can change
their RF power-rate and radio states (e.g. transmitting, receiving, idle and sleep) according to the communication
requirement, and their energy cost can be calculated correctly. Finally, by comparing DSDV against dPAMEEL, we
show that our energy model can effectively calculate the energy consumption for different energy-aware protocols.
Load distribution across multiple parallel paths is an important consideration. In many practical contexts, the aggregate traffic from source to sink may be such that no single link can carry the load. In an MPLS domain, this problem can be addressed by instantiating multiple paths. The main objective of this paper balances traffic at the flow level among the parallel Label Switched Paths (LSPs) in MPLS networks. Different from other proposals, our new framework is based on the distributable traffic (DT), where cross-traffic in real networks is considered, and each LSP is modeled as an M/G/1 processor-sharing queue. We define a flow to be a sequence of packet having the same identifier, and dispatch packet belonging to one flow to the same path, so the packet disorder problem is avoided effectively. This mechanism only needs to be implemented in the ingress LSRs and the egress LSRs. A new defined cost function is being used to distribute traffic to path. We computer the cost function based on the delay and packet loss of each LSPs, and minimize the cost function. The minimized cost function is inverse ratio to DT. If the cost function of a certain LSP is smaller, it means that more traffic can be distributed on this LSP. Extensive simulations using NS2 are performed with MPLS modules. Simulation results show that our approach so effective that the throughput is increased significantly and reduces the end-to-end delay and the packet drop rate, and it can distribute the traffic onto parallel LSPs more evenly and fairly.
KEYWORDS: Computer intrusion detection, Pattern recognition, Detection and tracking algorithms, Neural networks, Feature selection, Data modeling, Data centers, Data processing, Data conversion, Computer science
Today, cyber attacks such as worms, scanning, active attackers are pervasive in Internet. A number of security
approaches are proposed to address this problem, among which the intrusion detection system (IDS) appears
to be one of the major and most effective solutions for defending against malicious users. Essentially, intrusion
detection problem can be generalized as a classification problem, whose goal is to distinguish normal behaviors
and anomalies. There are many well-known pattern recognition algorithms for classification purpose. In this
paper we describe the details of applying pattern recognition methods to the intrusion detection research field.
Experimenting on the KDDCUP 99 data set, we first use information gain metric to reduce the dimensionality
of the original feature space. Two supervised methods, the support vector machine as well as the multi-layer
neural network have been tested and the results display high detection rate and low false alarm rate, which is
promising for real world applications. In addition, three unsupervised methods, Single-Linkage, K-Means, and
CLIQUE, are also implemented and evaluated in the paper. The low computational complexity reveals their
application in initial data reduction process.
Although IPv4 is still working, IPv6 is considered as the backbone and characteristic of the NGI. With the
development of Internet, new protocols and network equipments are required to develop. It is necessary to test the new
protocols and network equipments extensively before deployment. This paper proposes the design and implementation of
RENEW, a useable and accurate network emulator which supports both IPv4 and IPv6 protocols. Besides, it also works
on Windows platform. In our IPv6 testbed, we use RENEW to emulate various network characteristics and conditions
including bandwidth, delay packet loss and jitter. Compared with the expected values, results are acceptable. Through
implementation and experimentation study, we have shown that RENEW does provide the real-time control and change
on the parameters of IPv6 network conditions effectively and expediently on Windows. It also gives enough accuracy
and more satisfactory convenience to the development and test work for the new protocols.
We propose a congestion controller based on the Proportional-Integral-Differential Neuron Network (PIDNN). As
existing controllers, our controller employs the queue size in bottleneck link router as a congestion indicator to trigger
packet dropping. The target queue length and the feedback, actual queue length, act as the controller's two input signals.
The packet dropping probability is computed by PIDNN controller with its simple embedded algorithm in term of the
predefined state function and output function. Thus, the dropping probability decides to drop or to accept an incoming
packet so that the queue length is kept at (or near) the target level. This controller's performance is examined under
various network configurations, and compared to proposed congestion algorithms, including PI and RED. Our simulation
results show that, with comparable simple implementation, this scheme has short response time, better robustness, and
more adaptability, especially under highly dynamic network and heavy traffic load.
As the use of streaming media applications increased dramatically in recent years, streaming media security
becomes an important presumption, protecting the privacy. This paper proposes a new encryption scheme in view of
characteristics of streaming media and the disadvantage of the living method: encrypt the control message in the
streaming media with the high security lever and permute and confuse the data which is non control message according
to the corresponding control message. Here the so-called control message refers to the key data of the streaming media,
including the streaming media header and the header of the video frame, and the seed key. We encrypt the control
message using the public key encryption algorithm which can provide high security lever, such as RSA. At the same time
we make use of the seed key to generate key stream, from which the permutation list P responding to GOP (group of
picture) is derived. The plain text of the non-control message XORs the key stream and gets the middle cipher text. And
then obtained one is permutated according to P. In contrast the decryption process is the inverse process of the above.
We have set up a testbed for the above scheme and found our scheme is six to eight times faster than the conventional
method. It can be applied not only between PCs but also between handheld devices.
Since most ad hoc mobile devices today operate on batteries, energy-aware routings and power control techniques in
wireless networks have drawn considerable research interests recently. This paper presents a reliable energy-aware
routing algorithm (REARP) for unreliable ad hoc networks. The lifetime of the whole network and the energy cost for
each packet are considered simultaneously in the routing processes of the REARP. Different from the formers, the
energy cost of the link layer retransmission is also computed into the total energy consumption. Moreover, the REARP
appropriately adjusts the transmission power by systematically integrating the reliability and power control techniques.
We conducted extensive simulations to evaluate the performance of the new routing algorithms compared to a number of
existing routing algorithms.
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