A new deadlock prevention scheme for nonminimal adaptive wormhole routing

The adaptive routing approach has been expected as a promising way to improve network performance by utilizing available network bandwidth. Previous adaptive routing strategies in wormhole-routed multicomputer networks restrict the routing of messages by the routing algorithm to prevent deadlock. This results in low degree of adaptivity and low utilization of physical or virtual channels. In this paper, we examine the possibility of performing restriction-free adaptive routing in wormhole-routed networks as an approach to further improving the performance of these networks. A new flow control policy, called message cutting-in, is proposed, and two adaptive routing strategies are presented. Freedom of communication deadlock is achieved by the proposed flow control policy. The proposed adaptive routing strategies do not restrict routing and maximally utilize the physical and virtual channels. Simulation results show that the restriction-free adaptive routing approach is promising from the fact that it has the lowest latency and highest throughput depending on the number of virtual channels per physical channel and patterns of message traffic.

Adaptive Multicast Wormhole Routing in 2D Mesh Multicomputers

The performance of interconnection networks can be improved drastically by using wormhole routing and virtual channel flow control. Adaptive routing strategies, which are superior to oblivious routing, supply a set of alternative output virtual channels associated with different physical links, when a message is routed. A selection function selects a free one from the set. In this paper, we have evaluated the performance of three adaptive wormhole routing algorithms with minimum paths in 3D mesh networks: Dynamic Routing proposed by Dally and Aoki, Negative Last routing developed by Glass and Ni based on their Turn Model and Full Dynamic Routing proposed by us based on Duato’s adaptive routing theory. Three different selection functions, namely Static, Random and Greedy have been compared.

Digital microfluidic biochips (DMFBs) based on a micro-electrode-dot-array (MEDA) architecture provide fine-grained control and sensing of droplets in real-time. However, excessive actuation of microelectrodes in MEDA biochips can lead to charge trapping during bioassay execution, causing the failure of microelectrodes and erroneous bioassay outcomes. A recently proposed enhancement to MEDA allows run-time measurement of microelectrode health information, thereby enabling synthesis of adaptive routing strategies for droplets. However, existing synthesis solutions are computationally infeasible for large MEDA biochips that have been commercialized. In this paper, we propose a synthesis framework for adaptive droplet routing in MEDA biochips via deep reinforcement learning (DRL). The framework utilizes the real-time microelectrode health feedback to synthesize droplet routes that proactively minimize the likelihood of charge trapping. We show how the adaptive routing strategies can be synthesized using DRL. We implement the DRL agent, the MEDA simulation environment, and the bioassay scheduler using the OpenAI Gym environment. Our framework obtains adaptive routing policies efficiently for COVID-19 testing protocols on large arrays that reflect the sizes of commercial MEDA biochips available in the marketplace, significantly increasing probabilities of successful bioassay completion compared to existing methods.

Wormhole routing makes the communication latency insensitive of the network diameter and reduces the buffer size of each router. It has been widely adopted in many new generation distributed memory multiprocessor systems (DMMPs). The concept of virtual system is invented for deadlock-free routing design. Using a great deal of virtual channels is quite expensive to be implemented in practice and is not limitless. In this paper experimental results are given to evaluate the tradeoff between network congestion delay and throughput. Some results show that the congestion delay does not reduce visibly when the number of virtual channels is greater than that of internal channels by 2. A reasonable number of virtual channels can be derived from the results. A virtual networks system using only four virtual networks, two virtual channels in each direction, is presented. It shows that the minimum number of virtual networks to support a partially adaptive, minimal and deadlock free routing in k-ary n-cubes is just four. It uses only four virtual networks but can get a high degree of adaptiveness and high traffic capacity. Simulation results are presented to verify the performance.

We present a model for designing wormhole routing algorithms that are deadlock free, livelock free, minimal or nonminimal, and maximally adaptive. A unique feature of this model is that it is not based on adding physical or virtual channels to network topologies (though it can be applied to networks with extra channels). Instead, the model is based on analyzing the directions in which packets can turn in a network and the cycles that the turns can form. Prohibiting just enough turns to break all of the cycles produces routing algorithms that are deadlock free, livelock free, minimal or nonminimal, and maximally adaptive for the network. In this paper, we focus on the two most common network topologies for wormhole routing,n-dimensional mesh, just a quarter of the turns must be prohibited to prevent deadlock. The remaining three quarters of the turns permit partial adaptiveness in routing. Partially adaptive routing algorithms are described for 2D meshes,n-dimensional meshes,k-aryn-cubes, and hypercubes. Simulations of partially adaptive and nonadaptive routing algorithms for 2D meshes and hypercubes show that which algorithm has the lowest latencies and highest sustainable throughput depends on the pattern of message traffic. For nonuniform traffic, partially adaptive routing algorithms perform better than non-adaptive ones.

In order to obtain the lowest possible latency, routing algorithms should try to avoid a message waiting for resources (network links) blocked by other messages or multiplexing of more messages over one physical channel. This requirement becomes especially important in the case of long messages. The only type of protocols able to guarantee waiting free routing under heavy load are algorithms based on deflection (also called nonminimal adaptive or hot potato) routing. This paper deals with problems connected with the use of deflection algorithms. In contrast to the case of nonadaptive or partially (e.g., minimal) adaptive routing, it is very infrequent that an unrestricted deflection routing becomes deadlocked and, similarly, livelock is not a serious problem. On the other hand, there is another phenomenon, called a deflection jam, that limits throughput of deflection algorithms used to route long messages. It has been observed for many deflection heuristics, interconnection network topologies, and both virtual cut-through and wormhole routing. A deflection jam is a sudden and persistent saturation of a network which sometimes occur, after a very long period of undisturbed communication. This paper describes events that trigger this saturation which suggest ways to design improved and stable deflection routing algorithms.

Exascale systems will require large networks with hundreds of thousands of endpoints. Ethernet technology is employed in a significant fraction of the Top500 systems, and will remain as a cost-effective alternative for HPC interconnection. However, its current design is not scalable to Exascale systems. Different solutions have been proposed for scalable Ethernet fabrics for data center, but not specifically for HPC applications. This work identifies the major differences in network requirements from both environments. Based on them, it studies the application of Ethernet to Exascale HPC systems, considering the topology, routing, forwarding table management, and address assignment, with a focus on performance and power. Our scalability solution relies on OpenFlow switches to implement hierarchical MAC addressing with the introduction of compaction mechanisms for TCAM table reduction. To simplify deployment, a protocol denoted DMP performs automated address assignment without interfering with layer-2 service announcement protocols. An analysis of latency requirements of HPC applications shows that their communication phases are very short, making controller-centric adaptive routing unfeasible. We introduce Conditional OpenFlow rules as an instrument which allows for adaptive routing with proactive rule instantiation. Routing decisions are taken in the switch depending on network status, without controller interaction. This mechanism supports multiple topologies which require minimal or non-minimal adaptive routing and improve performance and power. Altogether, this work introduces a realistic and competitive implementation of a scalable lossless Ethernet network for Exascale-level HPC environments, considering low-diameter and low-power topologies such as Flattened Butterflies or Dragonflies, and allowing for power savings up to 54%.

Networks with torus interconnection topology are widely used due to the symmetry in traffic distribution. In order to ensure deadlock-freedom and provide adaptive routing in torus, at least two Virtual Channels (VCs) per physical channel are required to break the cyclic channel dependencies. However, VCs increase the arbitration latency and consume large power/area overheads which is undesirable, particularly for on-chip networks with limited power/area budgets. In this paper, we propose a novel technique for routing in wormhole-switched 2D torus networks. The proposed method relies on the Abacus Turn Model (AbTM) and Worm-Bubble Flow Control (WBFC) to support adaptive and deadlock-free routing without using VCs. Furthermore, the network blocking is reduced by providing on-demand routing adaptiveness through reconfiguration. The experimental results demonstrate the efficiency of the proposed scheme in terms of performance and hardware overhead.

A theory for the design of deadlock-free adaptive routing algorithms for wormhole networks, proposed by the author (1991, 1993), supplies sufficient conditions for an adaptive routing algorithm to be deadlock-free, even when there are cyclic dependencies between channels. Also, two design methodologies were proposed. Multicast communication refers to the delivery of the same message from one source node to an arbitrary number of destination nodes. A tree-like routing scheme is not suitable for hardware-supported multicast in wormhole networks because it produces many headers for each message, drastically increasing the probability of a message being blocked. A path-based multicast routing model was proposed by Lin and Ni (1991) for multicomputers with 2D-mesh and hypercube topologies. In this model, messages are not replicated at intermediate nodes. This paper develops the theoretical background for the design of deadlock-free adaptive multicast routing algorithms. This theory is valid for wormhole networks using the path-based routing model. It is also valid when messages with a single destination and multiple destinations are mixed together. The new channel dependencies produced by messages with several destinations are studied. Also, two theorems are proposed, developing conditions to verify that an adaptive multicast routing algorithm is deadlock-free, even when there are cyclic dependencies between channels. As an example, the multicast routing algorithms of Lin and Ni are extended, so that they can take advantage of the alternative paths offered by the network.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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.

Adaptive deadlock-free routing mechanisms are required to handle variable traffic patterns in dragonfly networks. However, distance-based deadlock avoidance mechanisms typically employed in Dragonflies increase the router cost and complexity as a function of the maximum allowed path length. This paper presents on-the-fly adaptive routing (OFAR), a routing/flow-control scheme that decouples the routing and the deadlock avoidance mechanisms. OFAR allows for in-transit adaptive routing with local and global misrouting, without imposing dependencies between virtual channels, and relying on a deadlock-free escape subnetwork to avoid deadlock. This model lowers latency, increases throughput, and adapts faster to transient traffic than previously proposed mechanisms. The low capacity of the escape subnetwork makes it prone to congestion. A simple congestion management mechanism based on injection restriction is considered to avoid such issues. Finally, reliability is considered by introducing mechanisms to find multiple edge-disjoint Hamiltonian rings embedded on the dragonfly, allowing to use multiple escape subnetworks.

Compressionless Routing (GR) is a new adaptive routing framework which provides a unified framework for efficient deadlock-free adaptive routing and fault-tolerance. CR exploits the tight-coupling between wormhole routers for flow control to detect potential deadlock situations and recover from them. Fault-tolerant Compressionless Routing (FCR) extends Compressionless Routing to support end-to-end fault-tolerant delivery. Detailed routing algorithms, implementation complexity and performance simulation results for CR and FCR are presented.CR has the following advantages: deadlock-free adaptive routing in torus networks with no virtual channels, simple router designs, order-preserving message transmission, applicability to a wide variety of network topologies, and elimination of the need for buffer allocation messages. FCR has the following advantages: tolerates transient faults while maintaining data integrity (nonstop fault-tolerance), tolerates permanent faults, can be applied to a wide variety of network topologies, and eliminates the need for software buffering and retry for reliability. These advantages of CR and FCR not only simplify hardware support for adaptive routing and fault-tolerance, they also can simplify communication software layers.

Mobile security is one of the most fundamental problems in Wireless Sensor Networks (WSNs). The data transmission path will be compromised for some disabled nodes. To construct a secure and reliable network, designing an adaptive route strategy which optimizes energy consumption and network lifetime of the aggregation cost is of great importance. In this paper, we address the reliable data aggregation route problem for WSNs. Firstly, to ensure nodes work properly, we propose a data aggregation route algorithm which improves the energy efficiency in the WSN. The construction process achieved through discrete particle swarm optimization (DPSO) saves node energy costs. Then, to balance the network load and establish a reliable network, an adaptive route algorithm with the minimal energy and the maximum lifetime is proposed. Since it is a non-linear constrained multi-objective optimization problem, in this paper we propose a DPSO with the multi-objective fitness function combined with the phenotype sharing function and penalty function to find available routes. Experimental results show that compared with other tree routing algorithms our algorithm can effectively reduce energy consumption and trade off energy consumption and network lifetime.

The issue of transaction routing in a heterogeneous database environment is examined where transaction characteristics like reference locality implies that certain processing systems can be identified as being, in general, more suitable than others for a given transaction class. Routing which ignores these distinctions in an attempt to balance system load can degrade system performance. An adaptive routing strategy is considered which: (1) estimates the response time based on a steady-state analysis; (2) monitors how well actual response time conforms to the estimate; and (3) adaptively adjusts future estimates through a feedback control based on (2). It is found that the adaptive strategy greatly enhances performance robustness as compared to the results of the strategy without feedback. The feedback process used alleviates the sensitivity to accurate estimations of workload and system parameters. Various simulation studies are used to illustrate the adaptive strategy's robustness. >