DTDOR: An Efficient Routing Algorithm for Torus Networks

Cluster networks are seen as the future access networks for multimedia streaming, e-commerce, network storage, etc. For these applications, performance and high availability are particularly crucial. Regular topologies are preferred when performance is the primary concern. However, due to spatial constraints or fault-related issues, the network structure may become irregular, which makes more difficult to find deadlock-free minimal paths. Over the recent years, several solutions have been proposed. One of them is the LASH routing, which enables minimal routing by assigning paths to different virtual layers. In this paper, we propose an extension of LASH in order to reduce the number of required virtual layers by allowing transitions between virtual layers. Evaluation results show that the new routing scheme (LASH-TOR) is able to obtain full minimal routing with a reduced number of virtual channels. For torus and mesh networks, with only two virtual channels, LASH throughput is increased by an average factor of improvement of 3.30 for large networks. For regular networks with some unconnected (faulty) links, equal performance improvements are achieved. Even for highly irregular networks of size up to 128 switches the new routing scheme only needs three virtual channels for guaranteeing minimal routing. Besides, LASH-TOR performs well compared to dimension order routing for mesh and torus networks.

Providing the optimal configuration for a software router poses a lot of technical challenges that do not present in the dedicated hardware router. One of them is how to characterize performance varying due to different configurations on commodity hardware. This paper addresses the problem of configuring a software router that provides the minimum of average packet latency. Since changing all combinations of hardware configurations of a software router for searching the optimum is cumbersome, we propose a prediction model to accurately estimate the packet latency of a software router. We first analyze the relationship of the packet latency distribution with the configured and observed parameters. Empirical measurements suggest that the Erlang-k distribution is a reasonable model for estimating the packet latency distribution. Motivated by the parameter relationship analysis, we propose a prediction model for packet latency of a software router based on the Erlang- k distribution. Our prediction model requires measurement of only two different configurations, i.e., one and two Rx queues of a network interface card, to predict the average packet latency of all combinations of configurations. We use the measured data from the testbed experiments and the data of curve fitting method to cross-verify the accuracy of our prediction model. Underlying the prediction model, we propose the optimal configuration selection (OCS) algorithm to justify which configuration yields the minimum of average packet latency. Our prediction model based OCS results in the same optimal configuration with the measured data based ones.

As applications scale to increasingly large processor counts, the interconnection network is frequently the limiting factor in application performance. In order to achieve application scalability, the interconnect must maintain high bandwidth while minimizing variation in packet latency. As the offered load in the network increases with growing problem sizes and processor counts, so does the expected maximum packet latency in the network, directly impacting performance of applications with any synchronized communication. Age-based packet arbitration reduces the variance in packet latency as well as average latency. This paper describes the Cray XT router packet aging algorithm which allows globally fair arbitration by incorporating age in the packet output arbitration. We describe the parameters of the aging algorithm and how to arrive at appropriate settings. We show that an efficient aging algorithm reduces both the average packet latency and the variance in packet latency on communication-intensive benchmarks.

A new deadlock prevention scheme for nonminimal adaptive wormhole routing

We develop on-line routing and wavelength assignment (RWA) algorithms for WDM bidirectional ring and torus networks with N nodes. The algorithms dynamically support all k-allowable traffic matrices, where k denotes an arbitrary integer vector [k/sub 1/, k/sub 2/,... k/sub N/], and node i, 1 /spl les/ i /spl les/ N, can transmit at most k/sub i/ wavelengths and receive at most k/sub i/ wavelengths. Both algorithms support the changing traffic in a rearrangeably nonblocking fashion. Our first algorithm, for a bidirectional ring, uses [(/spl Sigma//sub i=1//sup N/ k/sub i/)/3] wavelengths in each fiber and requires at most three lightpath rearrangements per new session request regardless of the number of nodes N and the amount of traffic k. When all the k/sub i/'s are equal to k, the algorithm uses [kN/3] wavelengths, which is known to be the minimum for any off-line rearrangeably nonblocking algorithm. Our second algorithm, for a torus topology, is an extension of a known off-line algorithm for the special case with all the k/sub i/'s equal to k. For an R /spl times/ C torus network with R /spl ges/ C nodes, our on-line algorithm uses [kR/2] wavelengths in each fiber, which is the same as in the off-line algorithm, and is at most two times a lower bound obtained by assuming full wavelength conversion at all nodes. In addition, the on-line algorithm requires at most C - 1 lightpath rearrangements per new session request regardless of the amount of traffic k. Finally, each RWA update requires solving a bipartite matching problem whose time complexity is only O (R), which is much smaller than the time complexity O(kCR/sup 2/) of the bipartite matching problem for an off-line algorithm.

HPC systems have shifted to burst buffer storage and high radix interconnect topologies in order to meet the challenges of large-scale, data-intensive scientific computing. Both of these technologies have been studied in detail independently, but the interaction between them is not well understood. I/O traffic and communication traffic from concurrently scheduled applications may interfere with each other in unexpected ways, and this behavior may vary considerably depending on resource allocation, scheduling, and routing policies.In this work, we analyze I/O and network traffic interference on burst-buffer-equipped dragonfly-based systems using the high-resolution packet-level simulations provided by the CODES storage and interconnect simulation framework. The analysis is performed using realistic I/O workload sizes, a variety of resource allocation and network routing strategies employed in production environments, and a dragonfly network configuration modeled after current vendor options. We analyze the impact of interference on both I/O and communication traffic.We observe that although average network packet latency is stable across a wide variety of configurations, the maximum network packet latency in the presence of concurrent I/O traffic is highly sensitive to subtle policy changes. Our simulations reveal a worst-case single packet latency of 4,700 times the average latency for sub-optimal configurations. While a topology-aware mapping of compute nodes to burst buffer storage nodes can minimize the variation in maximum packet latency, it can slow down the I/O traffic by creating contention on the burst buffer nodes. Overall, balancing I/O and network performance requires careful selection of routing, data placement, and job placement policies.

All optical path interconnection networks employing dense wavelength division multiplexing can provide vast improvements in supercomputer performance. However, the lack of efficient optical buffering requires investigation of new topologies and routing techniques. This paper introduces and evaluates the data vortex optical switching architecture which uses cylindrical routing paths as a packet buffering alternative. In addition, the impact of the number of angles on the overall network performance is studied through simulation. Using optimal topology configurations, the data vortex is compared to two existing switching architectures-butterfly and omega networks. The three networks are compared in terms of throughput, accepted traffic ratio, and average packet latency. The data vortex is shown to exhibit comparable latency and a higher acceptance rate (2times at 50 percent load) than the butterfly and omega topologies

Design of conventional protocols for wireless sensor networks(WSN) are mainly based on energy management. The solutions for layered protocol of the WSN network are inefficient as sensors network mainly delivers real-time content thus, cross layer communication between layers of the protocol stack is highly required. In this paper, a reliable cross layer routing scheme (CL - RS) is proposed to balance energy to achieve prolonged lifetime through controlled utilization of limited energy. CL - RS considers 2 adjacent layers namely, MAC layer and network layer. Optimization issues are identified in these two layers and solutions are provided to reduce energy consumption thereby increasing network lifetime. To achieve higher energy efficiency MAC layer protocols compromise on packet latency. It is essential to attempt reduce the end-to-end delay and energy consumption using low duty cycle cross layer MAC (CL-MAC). The joint optimization design is formulated as a linear programming problem. The network is partitioned into four request zones to enable increase in network performance by using an appropriate duty cycle and routing scheme. We demonstrate by simulations that the strategy designed by combining (CL - RS) and (CL-MAC) algorithms at each layer significantly increases the network lifetime and a relation exists between the network lifetime maximization and the reliability constraint. We evaluate the performance of the proposed scheme under different scenarios using ns-2. Experimental results shows that proposed scheme outperforms the layered AODV in terms of packet loss ratio, end-to-end delay, control overhead and energy consumption.

Routing schemes with the ability to tolerate the faults are important in the massively parallel multiprocessors networks. In this paper, we propose a kind of fault-tolerant routing schemes called positive-first and negative-first (PFNF) for orthogonal concave and convex fault blocks in torus network, which is based on the turn property of PFNF adaptive routing algorithm. In comparison with previous methods, the computation cost of our routing schemes is very low and it can not only easily apply in convex fault block but also in concave fault block, so the disabled healthy nodes can be reduced at the most level. Due to the mutual-switching of turn schemes between two virtual networks, the virtual channel utilization is greatly increased, which is benefic for the traffic-balance and the improvement of system throughput. Sufficient simulation results are presented to demonstrate the effectiveness of the proposed algorithm.

Software-Defined Vehicular Networks (SDVNs) technology has been attracting significant attention as it can make Vehicular Ad Hoc Network (VANET) more efficient and intelligent. SDVN provides a flexible architecture which can decouple the network management from data transmission. Compared to centralized SDVN, hybrid SDVN is even more flexible and has less overhead. This hybrid technology can eliminate the burden on the central controller by moving regional routing tasks from the central controller to local controllers or vehicular nodes. In the literature, different routing protocols have been reported for SDVNs. However, these existing routing protocols lack flexibility and adaptive approaches to deal with changing and dynamic traffic conditions. Thus, this paper proposes a new software-defined routing method, namely, Novel Adaptive Routing and Switching Scheme (NARSS), deployed in the controller. This adaptive method can dynamically select routing schemes for a specific traffic scenario. To achieve this, this paper firstly presents a method for collecting road network information to describe traffic condition where the method extracts the feature data used to generate the routing scheme switching model. Secondly, we train the feature data through an artificial neural network with high training speed and accuracy. Finally, we use the model as a basis for establishing the NARSS and deploy it in the controller. Simulation results show that the proposed scheme outperforms the single traditional routing protocol in terms of both packet delivery ratio and end-to-end delay.

Opportunistic network is the current area of research which facilitates message delivery between the nodes where there is no end-to-end connectivity. The most of the existing routing schemes in Opportunistic networks consume high resources and leads to decline in network efficiency. So, designing an efficient routing scheme for OppNets always remains a stimulating task due to high mobility of nodes, absence of an end-to-end connectivity and the lack of further knowledge about the network topology. In this research paper we propose a novel Fuzzy based Social relationshipAware Routing (F-SAR) scheme in which the decision of the best forwarder to forward the message depend on fuzzy inference system considering residual energy, buffer availability and social relationship of nodes. This routing scheme is simulated in “The ONE” simulator and the results shows that it outperforms SnW, Prophet, and FLDEAR in terms of delivery rate, message transmission overhead, and average latency

In randomly-deployed wireless mission critical networks, the crucial steps of ad hoc route setup and node localization are vulnerable to various security breaches and attacks. In this paper, we introduce SIRLoS, a lightweight secure integrated routing and localization scheme which addresses this problem by exploiting the security benefits of link directionality in directed networks that have found popularity for multimedia networking. SIRLoS is a circuit-based algorithm that leverages the resources of the base station and the hierarchical structure of the network to reconstruct the graph of the network, and detect any security violations in the neighborhood discovery and routing schemes. We demonstrate the performance of our algorithm, and provide security and attack analysis.

We present a link capacity estimation model and a hybrid routing scheme for wireless mesh networks which aims at improving throughput. The multi-source interference between links and frame capture behaviors of nodes are analyzed. Our model provides estimated values which can indicate the relative quality of wireless links. And we present a routing metric which combines multiple factors based on the estimated values. The proposed routing scheme which is independent of special routing protocols adopts different strategies for the traffic of accessing the Internet and the end-to-end traffic. Besides, we introduce a new gateway-assisted routing technique to further improve the performance. Simulation results show that the estimation model provides accurate estimated values enough for route selection, and the routing scheme improves end-to-end throughput by 185% compared with legacy AODV[14] protocol.

The integration of passive optical networks (PONs) and wireless mesh networks (WMNs) into Fiber- Wireless (FiWi) networks can lead to effective access networks. Existing routing schemes for FiWi networks consider mainly hop-count and delay metrics over a flat WMN node topology and do not specifically prioritize the local network structure, i.e., the local wireless-optical network gateway. In this study, we explore a simple, yet effective routing algorithm for FiWi networks with a WMN organized into zones operating on different radio channels. We examine the effects of routing the traffic into and out of a zone through one or more cluster heads. We investigate the effectiveness of localized routing that prioritizes transmissions over the local gateway to the optical network and avoids wireless packet transmissions in zones that do not contain the packet source or destination. We find that this combination of clustered and localized routing (CluLoR) gives good throughput-delay performance compared to routing schemes that transmit packets wirelessly through “transit zones” (that do not contain the packet source or destination) following minimum hop-count routing.

In this paper, we present a methodology employing statistical analysis and stochastic geometry to study geometric routing schemes in wireless ad hoc networks. In particular, we analyze the network-layer performance of one such scheme, the random [ 1/ 2]disk routing scheme, which is a localized geometric routing scheme in which each node chooses the next relay randomly among the nodes within its transmission range and in the general direction of the destination. The techniques developed in this paper enable us to establish the asymptotic connectivity and the convergence results for the mean and variance of the routing path lengths generated by geometric routing schemes in random wireless networks. In particular, we approximate the progress of the routing path toward the destination by a Markov process and determine the sufficient conditions that ensure the asymptotic connectivity for both dense and large-scale ad hoc networks deploying the random [ 1/ 2]disk routing scheme. Furthermore, using this Markov characterization, we show that the expected length (hop count) of the path generated by the random [ 1/ 2]disk routing scheme normalized by the length of the path generated by the ideal direct-line routing, converges to 3π/4 asymptotically. Moreover, we show that the variance-to-mean ratio of the routing path length converges to 9π <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> /64-1 asymptotically. Through simulation, we show that the aforementioned asymptotic statistics are in fact quite accurate even for finite granularity and size of the network.