Adaptive Routing Method Research Articles

Study of Adaptive Routing Method in Peer-to-Peer Network

This paper aim To analyze and discuss a Query-based Routing Method in P2P network (QRM) , In this algorithm,the node records the received query and the nodes that can answer the query very well,in these nodes, Simulation experiments demonstrate that the method can enhance the searching efficiency very well with the number of queries becoming more and more.

A reconfigurable and adaptive routing method for fault-tolerant mesh-based networks-on-chip

High reliability against undesirable effects is one of the key objectives in the design of on-chip networks. This paper presents a very low cost fault-tolerant routing method to tolerate faulty links and routers in mesh-based Networks-on-Chip. This new algorithm can be dynamically reconfigured to support irregular topologies caused by faulty components in a mesh network. In addition, it is a distributed, adaptive and congestion-aware routing algorithm where only two virtual channels are used for both adaptiveness and fault-tolerance. The proposed routing method has a multi-level fault-tolerance capability and therefore it is capable to tolerate more faulty components in more complicated faulty situations with additional hardware costs. The network performance, fault-tolerance capability and hardware overhead are evaluated through appropriate simulations and syntheses. The experimental results show that the overall reliability of a Network-on-Chip is significantly enhanced against multiple component failures with only a small hardware overhead.

A generic adaptive path-based routing method for MPSoCs

Several unicast routing protocols have been presented for unicast traffic in MPSoCs. Exploiting the unicast routing algorithms for multicast traffic increases the likelihood of deadlock and congestion. In order to avoid deadlock for multicast traffic, the Hamiltonian path strategy was introduced. The traditional Hamiltonian path routing protocols supporting both unicast and multicast traffic are based on deterministic models, leading to lower performance. In this paper, we propose an adaptive routing protocol for both unicast and multicast traffic without using virtual channels. The proposed method maximizes the degree of adaptiveness of the routing functions which are based on the Hamiltonian path while guaranteeing deadlock freedom. Furthermore, both unicast and multicast aspects of the presented method have been widely investigated separately. Results obtained in both synthetic and real traffic models show that the proposed adaptive method for multicast and unicast aspects has lower latency and power dissipation compared to previously proposed path-based multicasting algorithms with negligible hardware overhead.

From P2P to reliable semantic P2P systems

Current research to harness the power of P2P networks involves building reliable Semantic Peer-to-Peer (SP2P) systems. SP2P systems combine two complementary technologies: P2P networking and ontologies. There are several types of SP2P systems with applications to knowledge management systems, databases, the Semantic Web, emergent semantics, web services, and information systems. Correct semantic mapping is fundamental for success of SP2P systems where semantic mapping refers to semantic relationship between concepts from different ontologies. Current research on SP2P systems has emphasized semantics at the cost of dealing with the traditional issues of P2P networks of reliability and scalability. As a result of their lack of resilience to temporary mapping faults, SP2P systems can suffer from disconnection failures. Disconnection failures arise when SP2P systems that use adaptive query routing methods treat temporary mapping faults as permanent mapping faults. This paper identifies the disconnection failure problem due to temporary semantic mapping faults and proposes an algorithm to resolve it. To identify the problem, we will use a simulation model of SP2P systems. The Fault-Tolerant Adaptive Query Routing (FTAQR) algorithm proposed to resolve the problem is an adaptation of the generous tit-for-tat method originally developed in evolutionary game theory. The paper demonstrates that the reliability of an SP2P system increases by using the algorithm.

Adaptive routing of multiple taxis by mutual exchange of pathways

The tremendous development of information and communication technology has a large influence for service management in the taxi dispatching work. However, taxi drivers who want to drive in 'cruising taxis' decide their travel routes by depending on their own heuristics. As a result, traffic jams and local excess supplies have often been occurred. In this paper, we propose an adaptive routing method in the cruising taxis. In our method, pathways where many customers are expected to exist are assigned to drivers. This assignment adapts dynamically to carrying customers. Our simulation experiment shows that our method was able to pick up more customers than the existing means of cruising taxis.

Indirect adaptive routing on large scale interconnection networks

Recently proposed high-radix interconnection networks [10] require global adaptive routing to achieve optimum performance. Existing direct adaptive routing methods are slow to sense congestion remote from the source router and hence misroute many packets before such congestion is detected. This paper introduces indirect global adaptive routing (IAR) in which the adaptive routing decision uses information that is not directly available at the source router. We describe four IAR routing methods: credit round trip (CRT) [10], progressive adaptive routing (PAR), piggyback routing (PB), and reservation routing (RES). We evaluate each of these methods on the dragonfly topology under both steady-state and transient loads. Our results show that PB, PAR, and CRT all achieve good performance. PB provides the best absolute performance, with 2-7% lower latency on steady-state uniform random traffic at 70% load, while PAR provides the fastest response on transient loads. We also evaluate the implementation costs of the indirect adaptive routing methods and show that PB has the lowest implementation cost requiring <1% increase in the total storage of a typical high-radix router.

On-demand multipath protocol with adaptive routing method by back propagation neural networks

Two representative multipath routing protocol strategies have been utilised currently, one is described as primary routing protocol and the other is load-balancing protocol. In the former routing protocol, the source selects the pre-computed shortest or fastest route as the primary one for the following data transmission. On the other hand, the latter routing protocol utilises multiple routes in rotation to equalise transmission load in the network. However, these solutions suffer during high mobility since they are lacking in global perspective for the following data transmission, resulting in low packet delivery ratio and prolonged delay time. Hence, to find the optimum routing protocol strategy, we present an adaptive multipath routing protocol by means of applying golden section search and back propagation neural networks. We evaluated our protocol using Omnet simulator. Simulation results show that the proposed solution has a good real-time performance than those of other protocols.

An Adaptive Routing Method for VoIP Gateways Based on Packet Delay Information

In order to improve the quality of VoIP services, an adaptive routing method is proposed in the application layer of Internet gateways. This method determines routing paths based on the average one-way delays in a predetermined re-routing interval. In order to evaluate the performance of the method, five different routing policies are specifically designed and tested. Experimental results show that the method can improve the QoS of Internet phone services.

Performance Evaluation of a Genetic Algorithm based Routing Method for High-speed Networks

High-speed transmission rates bring forward their specific issues influencing the network design. To cope with high-speed networks the routing algorithms should give a fast decision. The conventional routing algorithms of slow-speed networks are generally inapplicable for high-speed networks. The traffic control methods for high-speed networks must be adaptive, flexible, and intelligent for efficient network management. The intelligent routing algorithms based on Genetic Algorithms (GA), Neural Networks (NN), and Fuzzy Theory (FT) can prove to be efficient in high speed networks. In this paper, we propose a new adaptive routing method called ARGA (Adaptive Routing using GA). In the ARGA method, the network is modeled by a tree and the tree is reduced in the part where there are the same routes. In the reduced tree model, the tree junctions are represented by individual genes. By using a novel gene coding method, the chromosomes have the same length, which results in easy genetic operations and a fast routing can be achieved. Performance evaluation via simulations show that the ARGA method has a faster routing decision compared with the Genetic Load Balancing Routing (GLBR) method.

Adaptive wormhole routing in k-ary n-cubes

Distributed memory multiprocessor (DMMP) systems have gained much attention because their performance can be easily scaled up by increasing the number of processor-memory modules. The k-ary n-cube is the most popular interconnection network topology currently used in DMMPs. Wormhole routing is one of the most promising switching technology and has been used in many new generation multicomputers. Wormhole routing makes the communication latency insensitive to the network diameter and reduces the size of the channel buffer of each router. The concept of virtual channels and virtual networks are widely invented for deadlock-free design. A fully adaptive wormhole routing method for k-ary n-cubes has been proposed by Linder in 1991 [10]. Unfortunately, the need of 2n − 1 virtual networks makes it unreasonable. In this paper, we propose a virtual network system to support an adaptive, minimal and deadlock free routing in k-ary n-cubes. It uses only four virtual networks but can get a higher degree of adaptability and higher traffic capacity. Simulation results are presented to verify the performance.

Adaptive Multicast Wormhole Routing in 2D Mesh Multicomputers

The issues of adaptive multicast wormhole routing in 2D mesh multicomputers are studied. Three adaptive multicast wormhole routing strategies are proposed and evaluated. The methods include minimal partially adaptive, minimal fully adaptive, and nonminimal adaptive routing. All the algorithms are shown to be deadlock-free. A study has been conducted that compares the performance of these multicast algorithms. The results show that the minimal fully adaptive routing method creates the least traffic; however, double vertical channels are required in order to avoid deadlock. The nonminimal routing algorithm exhibits the best adaptivity, although it creates more network traffic than the other methods.

Minimal fully adaptive wormhole routing on hypercubes

Wormhole routing is an advanced switching technique used in new generation multicomputers. Since such a machine may suffer serious performance degradation under heavy or uneven traffic load, an adaptive routing method is particularly called upon. In minimal fully adaptive routing, the paths between any source and destination pair to be used are exactly all the shortest paths. We propose in this paper a minimal fully adaptive routing algorithm for n-dimensional hypercube with ⌈( n+1)/2⌉ virtual channels per physical channel.

An analytical model for adaptive routing networks

Real-time network routing (RTNR) is a new adaptive routing method. With RTNR, switches have a simple way of exchanging link status bit map information, thereby determining the availability and load conditions of the direct and all two-link paths to the destination. Link busy-idle status is exchanged between the network nodes using a bit map data exchange through the common channel signaling (CCS) network, and calls are set up where there is the most available capacity in the network. To date the analysis of RTNR networks has been limited to simulation models. The present authors develop an analytical model for the AT&T network under RTNR, which is shown to provide good agreement with simulation models. The analytical model for RTNR networks uses an Erlang fixed point method to solve the nonlinear equations describing dynamical network behavior. The equations include the link state probability, network flows, link arrival rates, adaptive trunk reservation level, and adaptive path selection depth. The link state model provides the aggregate link state probabilities through solution of the birth-death equations, and models the adaptive nature of trunk reservation. The network flow model provides a method to calculate the traffic flow using the least busy concept employed in RTNR, and also models the adaptive nature of the path selection depth. The analytical model addresses asymmetrical networks, and computational examples show the differences from the simulation model to be small. The authors also use the analytical model to examine key RTNR parameters over a range of values.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

An adaptive routing method for computer networks by electric‐circuit modeling

AbstractThe computer network and multiprocessor system have been developed and studied. They are based on a network composed of nodes containing processors, aiming at the improvement of performance by distributed processing as well as the improvement of reliability by resource distribution. To realize high system performance, adequate routing and flow controls are required in the communication of information among nodes. This paper proposes a new routing control scheme to be used in the packet communication in the computer network or multiprocessor system. The scheme is called potential routing, which models the computer network by an electric circuit, and the packet routing from the source node to the destination node is performed to the potential difference between the adjacent nodes. The node potential is determined first by Kirchhoff's law and is modified dynamically according to the traffic situation during the routing procedure, providing an adequate criterion for the routing. The proposed scheme has a feature in that ping‐pong and loop phenomena, which cause traffic congestion, are not produced in principle. It was verified by simulation that the transmission delay is reduced when the traffic is high or unbalanced.