42869695
Dynamic RWA Based on the Combination of Mobile Agents Technique and Genetic Algorithm in WDM Networks with Sparse Wavelength Conversion
In this paper, we study the dynamic RWA problem in WDM networks with sparse wavelength conversion and propose a novel hybrid algorithm for it based on the combination of mobile agents technique and genetic algorithm. By keeping a suitable number of mobile agents in the network to cooperatively explore the network states and continuously update the routing tables, the new hybrid algorithm has the ability to promptly determine the first population of routes for a new request based on the routing table of its source node without requiring the time consuming process associated with the available GA-based dynamic RWA algorithms. To achieve a good load balance in WDM networks with sparse wavelength conversion, we adopt in our hybrid algorithm a new reproduction scheme and a new fitness function that simultaneously takes into account the path length, number of free wavelengths and wavelength conversion capability in route selection. Our new algorithm has the capabilities of achieving a better load balance and resulting a significantly lower blocking probability than that of the promising fixed-alternate routing algorithm for both the optical networks with sparse and full-range wavelength converters and the optical networks with sparse and limited-range wavelength converters, as verified by an extensive simulation study upon the ns-2 network simulator. The ability to guarantee both a low blocking probability and a small setup delay makes the new hybrid dynamic RWA algorithm very attractive for both the optical circuit switching networks and future optical burst switching networks.
30106346
A Genetic Algorithm for Dynamic Routing and Wavelength Assignment in WDM Networks
In this paper, we study the challenging problem of Dynamic Routing and Wavelength Assignment (DRWA) in WDM (Wavelength-Division-Multiplexing) networks with wavelength continuity constraint, and propose an improved genetic algorithm (GA) for it. By adopting a new fitness function to consider simultaneously the path length and number of free wavelengths in cost estimation of a route, the new genetic RWA algorithm can achieve a good load balance among route candidates and result in a lower blocking probability than both the fixed alternative routing algorithm and the previous GA-based algorithm for DRWA, as verified by an extensive simulation study upon the ns-2 network simulator and some typical network topologies.
61072281
A new scheme for lightpath restoration in wdm networks
All-optical networks with wavelength division multiplexing capability are the promising candidates for the next generation Internet. As these networks carry enormous bandwidth, it is not optional for them to be survivable. Although the available proactive restoration schemes provide 100% restoration guarantee, they require a huge extra capacity and usually result in an extremely high blocking probability. In this paper, we propose a novel active scheme that uses multiple predefined but not reserved backup paths along a working path to restore the lightpath in the event of link-failure. Simulation results based on two typical networks indicate that our new restoration method can reduce blocking probability and capacity requirement significantly while guaranteeing a very high restoration probability.
325582
Virtual Playgrounds for Worm Behavior Investigation
To detect and defend against Internet worms, researchers have long hoped to have a safe convenient environment to unleash and run real-world worms for close observation of their infection, damage, and propagation. However, major challenges exist in realizing such “worm playgrounds”, including the playgrounds' fidelity, confinement, scalability, as well as convenience in worm experiments. In this paper, we present a virtualization-based platform to create virtual worm playgrounds, called vGrounds, on top of a physical infrastructure. A vGround is an all-software virtual environment dynamically created for a worm attack. It has realistic end-hosts and network entities, all realized as virtual machines (VMs) and confined in a virtual network (VN). The salient features of vGround include: (1) high fidelity supporting real worm codes exploiting real vulnerable services, (2) strict confinement making the real Internet totally invisible and unreachable from inside a vGround, (3) high resource efficiency achieving sufficiently large scale of worm experiments, and (4) flexible and efficient worm experiment control enabling fast (tens of seconds) and automatic generation, re-installation, and final tear-down of vGrounds. Our experiments with real-world worms (including multi-vector worms and polymorphic worms) have successfully exhibited their probing and propagation patterns, exploitation steps, and malicious payloads, demonstrating the value of vGrounds for worm detection and defense research.
38206015
A Scalable HLA-Based Distributed Simulation Framework for VR Application
HLA-based Distributed Simulation technology is employed widely in Virtual Reality (VR) applications, such as military simulation, internet games, roaming etc. To support larger number of participants, scalability is becoming a key issue of VR applications. In this paper, we explore the characteristics of distributed simulation, and analyze the scalability of servers and participants, and classify our approach to improve scalability of VR applications into three aspects: a three-tier node management mode to accommodate more participants, an efficient management of servers to manage scalable number of clients and software development interface to achieve reusability and interoperability of VR applications. We present our middleware platform, HIVE, providing a scalable HLA-based distributed simulation framework for VR applications, on which users can develop VR applications easily and quickly. Then we give the method and view of application integration with HIVE. Finally an experimental demo is given.
11399358
Constructing and training feed-forward neural networks for pattern classification
A new approach of constructing and training neural networks for pattern classification is proposed. Data clusters are generated and trained sequentially based on distinct local subsets of the training data. Obtained clusters are then used to construct a feed-forward network, which is further trained using standard algorithms operating on the global training set. The network obtained using this approach effectively inherits the knowledge from the local training procedure before improving on its generalization ability through the subsequent global training. Various experiments demonstrate the superiority of this approach over competing methods.
7279689
An Architectural Approach to Preventing Code Injection Attacks
Code injection attacks, despite being well researched, continue to be a problem today. Modern architectural solutions such as the execute-disable bit and PaX have been useful in limiting the attacks; however, they enforce program layout restrictions and can oftentimes still be circumvented by a determined attacker. We propose a change to the memory architecture of modern processors that addresses the code injection problem at its very root by virtually splitting memory into code memory and data memory such that a processor will never be able to fetch injected code for execution. This virtual split memory system can be implemented as a software-only patch to an operating system and can be used to supplement existing schemes for improved protection. Furthermore, our system is able to accommodate a number of response modes when a code injection attack occurs. Our experiments with both benchmarks and real-world attacks show the system is effective in preventing a wide range of code injection attacks while incurring reasonable overhead.
40200748
Optimal Vertex Ordering of Graphs
In this paper we consider an optimal vertex ordering problem of graphs. The vertex ordering and an optimality measure are defined. It is proved that the optimal ordering problem under consideration can be transformed into the well-known minimum-weight spanning tree problem and is therefore solvable in low-polynomial time. We also investigate some properties of optimal vertex orderings.