71 resultados para IP routing


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The authors present a novel and efficient multicast algorithm that aims to reduce delay and communication cost for the registration between mobile nodes and mobility agents and solicitation for foreign agent services based on the mobile IP. The protocol applies anycast group technology to support multicast transmissions for both mobile nodes and home/foreign agents. Mobile hosts use anycast tunnelling to connect to the nearest available home/foreign agent where an agent is able to forward the multicast messages by selecting an anycast route to a multicast router so as to reduce the end-to-end delay. The performance analysis and experiments demonstrated that the proposed algorithm is able to enhance the performance over existing remote subscription and bidirectional tunnelling approaches regardless of the locations of mobile nodes/hosts

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Cluster computation has been used in the applications that demand performance, reliability, and availability, such as cluster server groups, large-scale scientific computations, distributed databases, distributed media-on-demand servers and search engines etc. In those applications, multicast can play the vital roles for the information dissemination among groups of servers and users. This paper proposes a set of novel efficient fault-tolerant multicast routing algorithms on hypercube interconnection of cluster computers using multicast shared tree approach. We present some new algorithms for selecting an optimal core (root) and constructing the shared tree so as to minimize the average delay for multicast messages. Simulation results indicate that our algorithms are efficient in the senses of short end-to-end average delay, load balance and less resource utilizations over hypercube cluster interconnection networks.

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One of the key challenges in geographic routing is how to deal with dead-ends, where greedy routing fails to find a neighbor node which is closer to the destination. Most existing geographic routing algorithms just switch to the deterministic face routing or limits its face searching range. In this paper, we demonstrate that we can improve routing performance by considering local connectivity status at each node before making routing decision. We present a protocol, Density Ripple Exchange (DRE), that maintains local density information at each node, and a new geographic routing algorithm, Geographic Ripple Routing (GRR), that achieves better routing performance in both hop stretch and transmission stretch than existing geographic routing algorithms by exploiting available connectivity information. Our simulations demonstrate that we increased the performance for GRR over Greedy Perimeter Stateless Routing (GPSR) by about 15%. The cost of this improved performance is a small amount of additional local connectivity information required for our algorithm.

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This study contributes to work in baggage handling system (BHS) control, specifically dynamic bag routing. Although studies in BHS agent-based control have examined the need for intelligent control, but there has not been an effort to explore the dynamic routing problem. As such, this study provides additional insight into how agents can learn to route in a BHS. This study describes a BHS status-based routing algorithm that applies learning methods to select criteria based on routing decisions. Although numerous studies have identified the need for dynamic routing, little analytic attention has been paid to intelligent agents for learning routing tables rather than manual creation of routing rules. We address this issue by demonstrating the ability of agents to learn how to route based on bag status, a robust method that is able to function in a variety of different BHS designs.

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Internet Protocol (IP) traceback is the enabling technology to control Internet crime. In this paper, we present a novel and practical IP traceback system called Flexible Deterministic Packet Marking (FDPM) which provides a defense system with the ability to find out the real sources of attacking packets that traverse through the network. While a number of other traceback schemes exist, FDPM provides innovative features to trace the source of IP packets and can obtain better tracing capability than others. In particular, FDPM adopts a flexible mark length strategy to make it compatible to different network environments; it also adaptively changes its marking rate according to the load of the participating router by a flexible flow-based marking scheme. Evaluations on both simulation and real system implementation demonstrate that FDPM requires a moderately small number of packets to complete the traceback process; add little additional load to routers and can trace a large number of sources in one traceback process with low false positive rates. The built-in overload prevention mechanism makes this system capable of achieving a satisfactory traceback result even when the router is heavily loaded. The motivation of this traceback system is from DDoS defense. It has been used to not only trace DDoS attacking packets but also enhance filtering attacking traffic. It has a wide array of applications for other security systems.

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Sensor nodes are closely tied with their geographic location and their connectivity. In recent years many routing protocols have been developed to provide efficient strategy. But most of them are either focus on the geographic proximity or on connectivity. However in sparse network, Geographic routing would fail at local dead ends where a node has no neighbour closer to destination. In contrast, connectivity-based routing may result in non-optimal path and overhead management. In this paper we designed a scalable and distributed routing protocol, GeoConnect, which considers geographic proximity and connectivity for choosing next hop. In GeoConnecl, we construct a new naming system that integrates geographic and connectivity information into a node identification. We use dissimilarity function to compute the dissimilarity and apply a distributed routing algorithm to route packets. The experimental results show that GeoConnect routing provides robust and better performance than sole geographic routing or connectivity routing.

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This paper presents the Multi-level Virtual Ring (MVR), a new name routing scheme for sensor networks. MVR uses selection algorithm to identify sensor nodes' virtual level and uses Distribution Hash Table (DHT) to map them to the MVR, The address routing performs well in wired network, but it's not true in sensor network. Because when nodes are moving, the address of the nodes must be changed Further, the address routing needs servers to allocate addresses to nodes. To solve this problem, the name routing is being introduced, such as Virtual Ring Routing (VRR). MVR is a new name routing scheme, which improves the routing performance significantly by introducing the multi-level virtual ring and cross-level routing. Experiments show this embedded name routing is workable and achieves better routing performance.

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We developed a new content routing based on the virtual backbone structure, which groups wireless nodes and contents into a virtual architecture. Our approach is scalable, works with local information, and does not rely on address information. The naming system uses flat naming to identify nodes and contents, and organizes these identifiers together. Backbone nodes can be selected automatically or predefined to direct their associated normal nodes in a local area. The normal nodes are guided by the backbone nodes to full fill the searching and routing processes. With a virtual structure, the searching performance can be improved by using the DHT technique.

Experiments using ns2 simulator demonstrate that this virtual backbone routing architecture has the following significances: workable without being aware address in a mobile situation; scalable with the size of network; efficient in terms of the reduced hop counts and short end-to-end delay, and also resistant to the dead-end problem.

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This paper examines the value of real-time traffic information gathered through Geographic Information Systems for achieving an optimal vehicle routing within a dynamically stochastic transportation network. We present a systematic approach in determining the dynamically varying parameters and implementation attributes that were used for the development of a Web-based transportation routing application integrated with real-time GIS services. We propose and implement an optimal routing algorithm by modifying Dijkstra’s algorithm in order to incorporate stochastically changing traffic flows. We describe the significant features of our Web application in making use of the real-time dynamic traffic flow information from GIS services towards achieving total costs savings and vehicle usage reduction. These features help users and vehicle drivers in improving their service levels and productivity as the Web application enables them to interactively find the optimal path and in identifying destinations effectively.

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In this paper we studied several virtual routing structures (ring, ring-tree, cord, and mesh) which are scalable, independent on addresses, based on local information and partial global information for routing packets. These virtual routing structures are built on the top of the backbone nodes which are selected by considering power, connections, and immobility metrics.Our experimental results on the ns2 simulator and both TelosBand MicaZ sensor nodes tested platform prove that the virtual backbone structures are superior to the existing routing schemes and the different virtual structures fit in with the different physical scenarios.

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Distributed Denial-of-Service (DDoS) attacks are a critical threat to the Internet. However, the memoryless feature of the Internet routing mechanisms makes it extremely hard to trace back to the source of these attacks. As a result, there is no effective and efficient method to deal with this issue so far. In this paper, we propose a novel traceback method for DDoS attacks that is based on entropy variations between normal and DDoS attack traffic, which is fundamentally different from commonly used packet marking techniques. In comparison to the existing DDoS traceback methods, the proposed strategy possesses a number of advantagesit is memory nonintensive, efficiently scalable, robust against packet pollution, and independent of attack traffic patterns. The results of extensive experimental and simulation studies are presented to demonstrate the effectiveness and efficiency of the proposed method. Our experiments show that accurate traceback is possible within 20 seconds (approximately) in a large-scale attack network with thousands of zombies.