22047646
Performance of Fast Routing Algorithms in Large Optical Switches Built on the Vertical Stacking of Banyan Structures
AbstractVertical stacking of multiple optical banyan networks is a novel scheme for building banyan-based nonblocking optical switches. The resulting network, namely vertically stacked optical banyan (VSOB) network, preserves the properties of small depth and absolutely loss uniformity but loses the nice self-routing capability of banyan networks. To guarantee a high switching speed, routing in VSOB network needs special attentions so that paths can be established as fast as possible. The best known global routing algorithm for an N × N nonblocking VSOB network has the time complexity of O(Nlog N), which will introduce an unacceptable long delay in path establishment for a large size optical switch. In this paper, we propose two fast routing algorithms for the VSOB network based on the idea of inputs grouping. The two algorithms, namely plane fixed routing (PFR) algorithm and partially random routing (PRR) algorithm, have the time complexities of O(log N) and O(
$$\sqrt N $$
) respectively, and FR algorithm can actually turn a VSOB network into a self-routing one. Extensive simulation based on a network simulator indicates that for large VSOB networks our new algorithms can achieve a reasonably low blocking probability while guarantee a very high switching speed.
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.
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.
17531595
Dynamic Routing and Wavelength Assignment in WDM Networks with Ant-Based Agents
In this paper, we propose an ant-based algorithm for dynamic routing and wavelength assignment (RWA) in WDM optical networks under the wave- length continuity constraint. By adopting a new routing table structure and keeping a number of ants in the network to cooperatively explore the network states and continuously update the routing tables, our new ant algorithm can ef- ficiently support the ants' foraging tasks of route selection and wavelength as- signment in WDM networks, and allow a connection to be setup promptly on arrival with a small setup time. Extensive simulation results based on the ns-2 network simulator indicate that the proposed algorithm can adapt well to traffic variations and achieves a lower blocking probability than the fixed routing al- gorithm.
2194314
Shared protection based on matrix decomposition in tropical semi-rings
It is observed that the singular value decomposition (SVD) transformation based on min-plus algebra (or called tropical semi-rings) leads to a very good characteristic in zero underestimating the reconstructed matrix. This paper introduces a novel distributed control framework for shared protection in optical networks with reduced routing information based on the tropical semi-rings technique, called sharing with reduced information with tropical semi-rings (SRI-TROP). The design of the proposed framework aims to initiate a compromise between the amount of link-state dissemination and the performance impairment due to the incompleteness of routing information, such that the precision in the link-state matrix reconstruction can efficiently map to the reduction in blocking probability. Based on the framework, a series of novel schemes are proposed, which are verified and compared with the reported counterparts in a simulation. The simulation results show that the performance in terms of the precision in the reconstructed link-state and the resultant blocking probability can be significantly improved.
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.
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.
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.
724770
Learning and inferencing in user ontology for personalized semantic web services
Domain ontology has been used in many Semantic Web applications. However, few applications explore the use of ontology for personalized services. This paper proposes an ontology based user model consisting of both concepts and semantic relations to represent users' interests. Specifically, we adopt a statistical approach to learning a semantic-based user ontology model from domain ontology and a spreading activation procedure for inferencing in the user ontology model. We apply the methods of learning and exploiting user ontology to a semantic search engine for finding academic publications. Our experimental results support the efficacy of user ontology and spreading activation theory (SAT) for providing personalized semantic services.
5818682
Towards an integrated multimedia service hosting overlay
With the proliferation of multimedia data sources on the Internet, we envision an increasing demand for value-added and function-rich multimedia services that transport, process, and analyze multimedia data on behalf of end users. More importantly, multimedia services are expected to be easily accessible and composable by users. In this paper, we propose MSODA, a service-oriented platform that hosts a wide spectrum of media services provided by different parties. From the user's point of view, MSODA is a shared "market" for media service access and composition. For a media service provider, MSODA creates a virtual dedicated environment for service deployment and management. Finally, the underlying MSODA middleware performs the key functions of service composition, configuration, and mapping for users. We discuss key challenges in the design of MSODA and present preliminary results towards its full realization.