The framework that we are proposing is based on Virtual Security Functions (VSF), Openflow, Software Define Network, Mininet, Pox Controller, Virtual Switches. By using Openflow protocol through virtualized environment of SDN, we are able to analyze entire data stream in network environment. By creating DDoS identification virtual security functions, we are capable of increasing the entire network security. VSF will allow for using the capability of this framework in order to protect against different attacks such as DoS, DDoS, MAC address spoofing, NTP amplification attack. All security functions can be activated concurrently, and anomaly detection can be included as well. All functions can run in parallel and based on stream analyses of the Openflow table we can identify anomalies.

Human-object interaction detection is a somewhat recently emerged scientific topic, which is mainly due to the advent of deep learning algorithms. Most current methods are performed on single images, detecting separately humans and objects, using state-of-the-art pose detection and object detection networks. The networks ease the overall task by allowing for learning of the readily inferred features. When adding the time dimension into the equation, this task becomes more complex, as temporal features between frames have to be taken into account. The paper aims to show an approach for detecting human interactions in videos, which utilizes several different methods - YOLOv5 for object detection, CSR-DCF and Kalman Filter for object tracking, and ID Convolutional Neural Network (1D-CNN) for real-time interaction detection. The overall algorithm is purposed for salient and rigid (modern-solid) objects in mind, positioned in closed-door scenes. The dataset and task are privately defined, that is they are relevant to this work only and cannot be compared to other works. The overall algorithm is tested on a subset of the PKU Multi-Modality Dataset (PKUMMD).

Nowadays Security Information and Event Management (SIEM) is a common element of the security stack of every big and medium size company. The SIEM is becoming a vital part of the defense strategy along with firewalls, network Intrusion Prevention System / Intrusion Detection System (IPS/IDS), web/mail security appliances, and Antivirus (AV) solutions. Therefore this paper aims to propose a solution for improving the security posture of an organization by implementing Splunk Enterprise SIEM. The monitoring of various systems in real-time could be a challenge for the security analysts in the Security Operation Center (SOC). With the use of Splunk, all relevant logs are collected and stored in one instance which allows the designing of a “single pane of glass” solution. To illustrate the capabilities of the Splunk Enterprise SIEM, the proposed solution has four real-time alerts for detection of different cases of suspicious and/or malicious activity. One of them is specifically designed to alert for the presence of a Mirai Internet-of- Things (loT) malware infection within the organization.

Summary Failures in computer systems can be often tracked down to software anomalies of various kinds. In many scenarios, it might be difficult, unfeasible, or unprofitable to carry out extensive debugging activity to spot the cause of anomalies and remove them. In other cases, taking corrective actions may led to undesirable service downtime. In this article, we propose an alternative approach to cope with the problem of software anomalies in cloud‐based applications, and we present the design of a distributed autonomic framework that implements our approach. It exploits the elastic capabilities of cloud infrastructures, and relies on machine learning models, proactive rejuvenation techniques, and a new load balancing approach. By putting together all these elements, we show that it is possible to improve both availability and performance of applications deployed to heterogeneous cloud regions and subject to frequent failures. Overall, our study demonstrates the viability of our approach, thus opening the way towards its adoption, and encouraging further studies and practical experiences to evaluate and improve it.

The comparison analyses in this paper is based on Virtual Security Functions, Openflow, Software Define Networks (SDN), Mininet, Pox Controller, Floodlight Controller and Virtual Switches. By using Openflow protocol in the virtualized environment of SDN, we are capable of analyzing the data streams in the network environment. By creating different Virtual Security Functions (VSF), we have the possibility to increase network security, avoid loops and eliminating broadcast storms. In this paper, the process of loop elimination is achieved by automatically reconfiguring the security function by creating spanning tree. The benefit is that different devices like switches, firewalls, will be replaced by the SDN controller and the entire platform is virtualized. The target is to increase availability (based on the classical model of security) by presenting functions that avoid loops and Storm attacks in the network. In addition, VSF will allow to eliminate different attacks, such as: Congestion driven attacks; Distributed Denial-of-Service (DDoS); Layer 2 attacks. All those functions can be run in parallel and we can increase the availability.

The article will test if Long Short Term Memory (LSTM) neural networks are suitable for high frequency foreign exchange (forex) trading. Major world currencies often correlate and affect each other. We will try to take advantage and we will feed time series data of several currency pairs and do correlation analysis on them. When traders do technical analysis they inspect different time periods in order to get better understanding on currency trends. We will also test if feeding the neural network with different time periods will lead to better predictions.

This paper illustrates the effort to integrate a machine learning-based framework which can predict the remaining time to failure of computing nodes with Hadoop applications. This work is part of a larger effort targeting the development of a cloud-oriented autonomic framework to increase the availability of applications subject to software anomalies, and to jointly improve their performance. The framework uses machine-learning, software rejuvenation, and load distribution techniques to proactively prevent failures. We believe that this work allows to set a possible path towards the definition of best practices for the development of systems to support autonomic management of cloud applications, illustrating what are the issues that should be addressed by the research community. Indeed, given the scale and the complexity of modern computing infrastructures, effective autonomic management approaches of cloud applications are becoming mandatory.

All research topics of IEEE NCA*, for more than one decade, have been contributing to the creation of the foundation of the Network/Cloud Computing research and application do domain. Now, Network/Cloud Computing is becoming the major mode of operation of the Information Technology Industry over the Internet. BIG Data, Software Defined Networks (SDN), Network Functions Virtualization (NFI), Internet of Things (IoT) have profound effect on the innovations and modern society. The challenge for Network Cloud Computing is to realize a true Internet of Things, a network capable of supporting potentially trillions of wireless connected devices and with overall bandwidth one thousand times higher that today's wireless networks. Current IT technologies are approaching their limits.

In this paper, we present a novel framework for supporting the management and optimization of application subject to software anomalies and deployed on large scale cloud architectures, composed of different geographically distributed cloud regions. The framework uses machine learning models for predicting failures caused by accumulation of anomalies. It introduces a novel workload balancing approach and a proactive system scale up/scale down technique. We developed a prototype of the framework and present some experiments for validating the applicability of the proposed approaches.

New CMOS processes offer cheaper but less reliable transistors. This trend foreshadows the apparition of processors consisting of hundreds and thousands of cores prone to defects. In this context, the performance of the core interconnect under faults will be critical. In this work, we propose the combination of a novel adaptive routing algorithm and several related router mechanisms, which firstly ensure message transfers under transient and permanent faults and second adapt to congestion in order to improve the interconnect performances. In effect, the widespread 2D mesh topology offers a high redundancy of routes. Hence, a fault-tolerant congestion-aware routing algorithm is able to improve substantially the interconnect efficiency under degraded conditions. Besides, the Virtual Channel allocation is optimized for performance, and a message truncation mechanism is added to cope with dynamic permanent and transient faults.

Cloud computing is defined as a pool of virtualized computer resources. Based on this virtualization, the cloud computing paradigm allows workloads to be deployed and scaled-out quickly through the rapid provisioning of virtual machines or physical machines. A cloud computing platform supports redundant, self-recovering, highly scalable programming models that allow workloads to recover from many inevitable hardware/software failures and monitoring resource use in real time for providing physical and virtual servers, on which the applications can run. A cloud computing platform is more than a collection of computer resources, because it provides a mechanism to manage those resources. In a cloud computing platform, software is migrating from the desktop into the "clouds" of the Internet, promising users anytime, anywhere access to their programs and data. The editor-in-chief provides an overview of the technical articles and features presented in this issue.

This session brings together specialists from the DfT, DfY and DfR domains that will address key problems together with their solutions for the 14 nm node and beyond, dealing with extremely complex chips affected by high defect levels, unpredictable and heterogeneous timing behavior, circuit degradation over time, including extreme situations related with the ultimate CMOS nodes, where all processor nodes, routers and links of single-chip massively parallel tera-device processors could comprise timing faults (such as delay faults or clock skews); a large percentage of these parts are affected by catastrophic failures; all parts experience significant performance degradations over time; and new catastrophic failures occur at low MTBF.

Future applications will require processors with many cores communicating through a regular interconnection network. Meanwhile, the Deep submicron technology foreshadows highly defective chips era. In this context, not only fault-tolerant designs become compulsory, but their performance under failures gains importance. In this paper, we present a deadlock-free fault-tolerant adaptive routing algorithm featuring Explicit Path Routing in order to limit the latency degradation under failures. This is particularly interesting for streaming applications, which transfer huge amount of data between the same source-destination pairs. The proposed routing algorithm is able to route messages in the presence of any set of multiple nodes and links failures, as long as a path exists, and does not use any routing table. It is scalable and can be applied to multicore chips with a 2D mesh core interconnect of any size. The algorithm is deadlock-free and avoids infinite looping in fault-free and faulty 2D meshes. We simulated the proposed algorithm using the worst case scenario, with different failure rates. Experimentation results confirmed that the algorithm tolerates multiple failures even in the most extreme failure patterns. Additionally, we monitored the interconnect traffic and average latency for faulty cases. For 20×20 meshes, the proposed algorithm reduces the average latency by up to 50%.

In this paper, we present a detailed evaluation of a set of well-known Machine Learning classifiers in front of dynamic and non-deterministic software anomalies. The system state prediction is based on monitoring system metrics. This allows software proactive rejuvenation to be triggered automatically. Random Forest approach achieves validation errors less than 1% in comparison to the well-known ML algorithms under a valuation. In order to reduce automatically the number of monitored parameters, needed to predict software anomalies, we analyze Lasso Regularization technique jointly with the Machine Learning classifiers to evaluate how the prediction accuracy could be guaranteed within an acceptable threshold. This allows to reduce drastically (around 60% in the best case) the number of monitoring parameters. The framework, based on ML and Lasso regularization techniques, has been validated using an ecommerce environment with Apache Tomcat server, and MySql database server.

In this paper, a Self-Recovering strategy, which is able to "re-map" dynamically application tasks on a multi-core system, is presented. Based on run-time failure aware techniques, this Self-Recovering strategy guarantees seamlessly termination and delivering the expected results despite multiple node and link failures in a 2D mesh topology. It has been demonstrated, based on a statistical analysis, that the proposed technique is able to re-map the tasks of faulty nodes in a bounded number of steps. The theoretical results have been validated by simulations. The proposed technique is allowing to bypass multiple nodes, routers and links failures with a predictable number of hops. It has been demonstrated that the Motion JPEG-2000 application can be parallelized and formally represented as a Directed Acyclic Graph (DAG). It is worth noting that the proposed technique has been validated by the simulation of a 1000 cores system, in the presence of nodes and links failures up to 10%. Therefore, the proposed technique has been shown to be efficient for seamless execution of parallel streaming applications and to provide the Execution Time Reduction Ratio close to ideal.

In the context of the emerging 3D integration paradigm, chips are built as stacks of several (likely heterogeneous) 2D layers. The topology of their communication network is quite irregular, mainly due to the different topologies of the 2D layers and the partial vertical connection between these layers. In this paper, a reconfigurable inter-layer routing mechanism (RILM) for such topologies is proposed. We firstly present the mechanism of composing the routing algorithms in different layers, through the vertical links, in order to achieve a multi-layer routing algorithm. Reconfiguration of the routing can be done for multiple reasons: to achieve fault-tolerant capability, but also under dynamic changing of the communication requirements, or, simply, to avoid congestions. To obtain a complete routing reconfiguration for the entire stack of layers, we propose a reconfiguration algorithm of the inter-layer routes, as a complement to the 2D routing reconfiguration. Additionally, independently of the 2D routing algorithm properties, RILM tolerates multiple failures of vertical links, as long as the stack of layers is not partitioned.

Future applications will require processors with many cores communicating through a regular interconnection network. Meanwhile, as the Deep submicron technology fore- shadows highly defective chips era, fault-tolerant designs become compulsory. In particular, the fault tolerance of a core interconnect is critical, and inevitably increases its complexity. In this paper, we present a novel adaptive routing algorithm that is able to route messages in the presence of any set of multiple nodes and links failures, as long as a path exists. Compared to the existing solutions, the proposed algorithm provides fault tolerance without using any routing table. It is scalable and can be applied to multicore chips with a 2D mesh core interconnect of any size. The algorithm is deadlock-free and avoids infinite looping in fault-free and faulty 2D meshes, based on Virtual Networks and Virtual Channels. We simulated the proposed algorithm using the worst case scenario, regarding the traffic patterns and the failure rate up to 40%. Experimentation results confirmed that the algorithm tolerates multiple failures even in the most extreme failure patterns. Additionally, we monitored the trade off between the fault tolerance and the average latency for faulty cases, as measurement of the performance degradation. The algorithm detects the interconnects partitioning and enables "preferred paths" for streaming applications.

The seven papers in this special section focus on autonomic network computing.

Dynamic network reconfiguration is a technique in which the routing tables of the nodes in the vicinity of a failure are updated in real-time. The technique has been proved effective only if no failures occur after the reconfiguration process has started. This paper, presents enhancements to Agent NetReconf to allow it tolerate new failures if the reconfiguration was already started for a different failure. Agent NetReconf is an intelligent dynamic network reconfiguration algorithm. The improvements were made on the following three phases: restoration tree construction (phase 1), multiple failures synchronization (phase 2) and routing information update (phase 3). The proposed strategy consists of: 1) activate Agent NetReconf recursively, if a new node/link failure occurs and the reconfiguration of a different failure was started, 2) Use a pair of gateway nodes to help the restoration leaders, to reach consensus and to define the order in which each leader will execute the reconfiguration. The complexity, in terms of the number agents created, is analyzed for all phases. Termination is also proved for all phases.

Fault-tolerant beacon vector routing (FBVR) is an efficient technique for routing in the presence of node failures. Several common wireless topologies exist that can be used with this technique. This paper compares the power consumption of various regular topologies using FBVR and makes appropriate recommendations. The topology types include mesh, torus, communication graph, and F-cycle ring (FCR). An existing analytical method for power consumption prediction is used. The results of this analytical method are compared against simulation results, which match closely, showing a high level of confidence in the power consumption results.

This paper proposes a novel proxy network topology. The proposed network topology exhibits several attributes that strengthen the proxy network's resistance to DoS attacks. Additionally, a novel reconfiguration algorithm for a class of proxy network topologies is proposed, and shown to decrease the topologies' vulnerability to DoS attacks. Proxy networks enable applications to communicate with users without disclosing their IP's. An application's resistance to DoS attacks is improved by hiding it behind a proxy network. We evaluate the proposed topology's fault tolerance and its effectiveness in the resistance to DoS attacks

This paper presents an analytical method for evaluating the reliability improvement for any size of multi-computer system based on Software-Implemented Fault-Tolerance (SIFT). The method is based on the equivalent failure rate Gamma, the single node failure rate lambda, the number of nodes in the system, N, the repair rate mu, the fault coverage factor c, the reconfiguration rate delta, and the percentage of blocking faults b1and b2. The impact of these parameters on the reliability improvement has been evaluated for a gracefully degradable multi-computer system using our proposed analytical technique based on Markov chains. To validate our approach, we used the SIFT method which implements error detection at the node level, combined with a fast reconfiguration algorithm for avoiding faulty nodes. It is worth noting that the proposed method is applicable to any multi-computer systems' topology. The evaluation work presented in this paper focuses on the combination of analytical and experimental approaches, and more precisely on Markov chains. The SIFT method has been successfully implemented for a multi-computer system, nCube. The time overhead (reconfiguration & recomputation time) incurred by the injected fault, and the fault coverage factor c, are experimentally evaluated by means of a parallel version of the Software Object-Oriented Fault-Injection Tool (nSOFIT). The implemented SIFT approach can be used for real-time applications, when the time constraints should be met despite failures in the gracefully degradable multi-computer system

Currently, high-speed networks are indispensable commodities for all users and they have become an integral part of their lifestyles. For this reason, it is necessary for the network to be available most of the time and to achieve transparent network failure recovery. In this paper, it is proposed to use Agent NetReconf, an agent based dynamic network reconfiguration algorithm that is capable of tolerating multiple router and link failures in high-speed networks with arbitrary topology. Agent NetReconf updates the routing tables asynchronously and does not require any global knowledge of the network topology. Agent NetReconf uses mobile and autonomous agents to detect and recover the network from failures. Agent NetReconf highlights the benefits of using smart networking devices as a means of building an active network. The complexity of Agent NetReconf is analyzed and the termination, liveliness and safety are proved

This paper presents a performance analysis for an improved Beacon Vector Routing (BVR) protocol. BVR algorithms are useful for point-to-point routing in wireless sensor networks. The original BVR algorithm is compared through performance analysis to improved three-phase fault-tolerant BVR, known as FBVR-Opt. Finally, FBVR-Opt is compared against an existing fault-tolerant routing technique, known as LRR.The simulator assumptions and performance analysis are discussed. Performance metrics include throughput, latency, overhead, and routing success rate in the presence of multiple node failures. FBVR-Opt is found to significantly improve routing success and throughput in the presence of multiple simultaneous node failures.

This paper presents a method, infrastructure, and prototype that enables adaptive application task migration among a grid environment. Our infrastructure automatically reconfigures distributed applications in response to network performance failures and denial of service (DoS) attacks. Through the use of performance monitoring software we enable network connection failover and automatic application task migration within a heterogeneous distributed computing environment. Our system distinguishes itself from other available adaptive computing frameworks because it is wholly composed of open source grid-enabled components capable of both transparent and dynamic selection of message passing transports based on resource performance

In this paper, correctness is proven for a new clustering method and fault-tolerant routing approach to beacon vector routing. The correctness is proven through termination, liveness, and safety properties. The complexity of the proposed algorithms is analyzed. The clustering approach provides load balancing between clusters, and organizes beacon placement which reduces the number of hops for packet transmissions. The fault-tolerant routing approach improves significantly the percentage of successful packet transmission attempts, and reduces flooding in the network, in the presence of multiple simultaneous faults.

Component failures in high-speed computer networks can result in significant topological changes. In such cases, a network reconfiguration algorithm must be executed to restore the connectivity between the network nodes. Most contemporary networks use either static reconfiguration algorithms or stop the user traffic in order to prevent cyclic dependencies in the routing tables. The goal is to present NetRec, a dynamic network reconfiguration algorithm for tolerating multiple node and link failures in high-speed networks with arbitrary topology. The algorithm updates the routing tables asynchronously and does not require any global knowledge about the network topology. Certain phases of NetRec are executed in parallel, which reduces the reconfiguration time. The algorithm suspends the application traffic in small regions of the network only while the routing tables are being updated. The message complexity of NetRec is analyzed and the termination, liveness, and safety of the proposed algorithm are proven. Additionally, results from validation of the algorithm in a distributed network-validation testbed Distant, based on the MPI 1.2 features for building arbitrary virtual topologies, are presented.

Summary form only given. Component failures in high-speed local and system area networks can result in significant topological changes. In such cases, a network reconfiguration algorithm is executed to restore the connectivity. Most of the current networks use either static reconfiguration algorithms or stop the user traffic to prevent cyclic dependencies in the routing tables. The goal is to validate an extension of the dynamic reconfiguration algorithm NetRec, which was previously published by the authors. The extensions is designed to increase the network availability in the presence of multiple link and node failures. It updates the routing tables asynchronously and doesn't require any global knowledge about the network topology. Certain phases of NetRec are executed in parallel, thus reducing the reconfiguration time. We present results from validation of the algorithm in a distributed network testbed, based on the MPI 1.2 features for building virtual topologies.

High-speed local and system area networks may change their topology due to switching on/off of routers and hosts or due to component failures. In such cases, a reconfiguration algorithm must be executed to restore the network connectivity and thus achieve high system reliability. However, most of the solutions are based either on redundant network paths or on regular network topologies.The purpose of this paper is to specify NetRec, a novel algorithm for dynamically reconfiguring an arbitrary network topology when a permanent node fault occurs. Unlike other reconfiguration algorithms, NetRec is applicable for all high-speed computer networks and is compatible with all modern routing techniques, including wormhole-based system area networks. It restores the network connectivity by building a tree that spans all immediate neighbors of the faulty node that are still connected to the network. The algorithm is distributed and does not require any global knowledge.

New network components joining running highspeed local area networks (LANs) or system area networks (SANs) can require communication path reconfigurations. Currently implemented network reconfiguration protocols stop the user traffic to prevent deadlocks. NetRec was proposed in [1] as a dynamic reconfiguration algorithm to increase the network availability in the presence of multiple faults. In this article, we extend NetRec to dynamically reconfigure the network for the case of newly joining nodes. We provide examples of NetRec operation and obtain an upper bound in terms of the number of messages generated during the reconfiguration.

A closed queueing model of a generalized input-queueing space-division packet switch is presented. The model explicitly reflects the architecture of the router in terms of the number of outputs and the number of packets available for transmission, as well as the distribution of traffic over the ports. The model provides the upper bound on the utilization (throughput) of the router given the number of input and output ports of the router and the distribution of traffic among them. The results obtained by the model are verified by comparison with data generated by a simulator. It is demonstrated that the results are also useful far accurately estimating the throughput of networks.

Focuses on the utilization of alternative communication paths in local and system area networks with static routing. A lot of research work has been devoted to employing such paths for fault tolerance, but the issue of utilizing them for performance enhancement has been largely neglected, especially for static routing networks. This work formally proves that the throughput of multiple paths is maximal if the traffic is uniformly distributed over them. Based on this, a procedure for destination partitioning in static routing networks is introduced. It is applicable to arbitrary multi-path topologies and traffic patterns that lend themselves to partitioning. The procedure is applied to several topologies with different degree of equivalent paths coverage and their performance is evaluated through simulations. The results demonstrate that the network performance is significantly improved when the proposed partitioning procedure is applied.

Dependable network computing is becoming a key part of our daily economic and social life. Every day, millions of users and businesses are utilizing the Internet infrastructure for real-time electronic commerce transactions, scheduling important events, and building relationships. While network traffic and the number of users are rapidly growing, the mean-time between failures (MTTF) is surprisingly short; according to recent studies, in the majority of Internet backbone paths, the MTTF is 28 days. This leads to a strong requirement for highly dependable networks, servers, and software systems. The challenge is to build interconnected systems, based on available technology, that are inexpensive, accessible, scalable, and dependable. This special section provides insights into a number of these exciting challenges.

Since widespread commercial use of wireless technology is still many years off, there is very little data to determine what constitutes an accurate model for wireless traffic. Many studies have shown that landline network traffic does not follow a traditional Poisson model but instead exhibits self-similar behavior. Previous papers have introduced and analyzed the performance of fundamental classes of energy-conserving protocols under traditional Poisson models. In order to evaluate these protocols under a distribution which might more accurately depict future wireless network traffic, we use simulation and proven models to consider the trade-off between energy and delay under a self-similar arrival distribution.

Abstract This paper will center on analysis of the performance characteristics of ServerNet topologies, concentrating on the prediction, through simulation and statistical analysis, of the maximum two-way delivery time, the identification of congested links (hot spots) and tree saturation. ServerNetTM, developed by Tandem Computers Inc., is a wormhole-routed, packet-switched, point-to-point network, with special attention paid to reducing latency and to assuring reliability. ServerNet uses multiple high-speed, low-cost routers to rapidly switch data directly between data sources and destinations. The maximum two-way delivery time is necessary for determining the values of timeout counters, which are relevant to the fault-tolerant aspect of the system, and the QoS guarantees. Hot spots may cause the occurrence of tree saturation in the network i.e., where an individual tree will become congested (tree saturation) while all other trees are mostly idle, which leads to significant performance degradation. Our study is based on data generated by a simulation tool. Statistical analysis and inference methods were used to process the samples generated by the simulator and to obtain estimates for the maximum two-way packet delivery time. These methods were also used to determine the number of the samples that were required to produce estimates of the desired accuracy. Both the degree of confidence and the percentage of packets are determined by the number of samples generated by the simulator. This allows us to control the quality and accuracy of the estimate to suit our needs. Link usage statistics were recorded by the simulator for the purpose of performing a detailed investigation of congestion effects and hot spots. The study of the static and dynamic link usage statistics revealed that the extreme values of the two-way maximum delivery time were caused by links operating under heavy traffic loads and that under certain traffic patterns a tree saturation effect occurs.

We adopt a formalism to describe protocols that is close to the human way of thinking and can be easily used to perform reachability analysis of the described protocol in a state-transition format. This formalism allows for an execution tree (ET) to be generated from a set of assertions such that all paths from the root to the leaves are well-defined formulas. We then extend the formalism with regards to real-time properties. Finally, we present a software verification tool, that implements the aforementioned features in the analysis of protocols.

In this article we introduce and evaluate a method for optimizing the router arbitration policy in point-to-point networks. These networks use multiple high-speed, low-cost routers to rapidly switch data directly between data sources and destinations. We assume that routers use an arbitration algorithm that has the ability to assign different priorities to different links thus controlling the distribution of available bandwidth among channels. We propose an analytical method that allows us to determine the correct priorities for channels so as to achieve fair arbitration thus minimizing latency, increasing throughput and eliminating tree saturation. In our study we used data generated by a simulation tool to validate the proposed analytical model for determining the weights (priorities) of router ports and to evaluate the resulting performance improvements. Link usage statistics were recorded by the simulator for the purpose of performing a detailed investigation on congestion effects particularly tree saturation. The method was applied to the ServerNet™ System Area Network (SAN), developed by Tandem Computers Inc.

The problem of tolerating faulty nodes in hypercubes has been studied by many researchers either by using spares or by reconfiguration. Algorithms for tolerating faulty nodes and links in hypercubes are presented. The algorithms are based on using general spanning trees (GST), complete unbalanced spanning trees (CUST), and balanced spanning trees (BST) for reconfiguring the hypercube to avoid faulty nodes and links. The algorithms contain two phases: the first phase involves the construction of the spanning tree and the second one is for reconfiguring the hypercube should a faulty node be detected. The reconfiguration process consists of two basic steps. First, the faulty node is disconnected from the spanning tree. Then, a new spanning tree is constructed by reconnecting the children of the faulty node to the spanning tree. One hundred percent single fault correction (avoidance) and almost 100 percent fault correction (avoidance) of double and triple faults are achieved by the proposed algorithms for hypercubes having a dimension of n/spl ges/6. Simulation results for the algorithm under more than three faults also are presented. For any k faulty nodes (1/spl les/k/spl les/2/sup n/-1), the reconfiguration algorithm may be applied k times to avoid these k faulty nodes as long as no combination of any two of the faults results in a blocking situation. The proposed reconfiguration algorithms tolerate all possible single-link faults. The reconfiguration algorithms are extended to tolerate (k/spl les/n-1) multiple faults, causing blocking situation, with a backtracking.

We adopt a formalism to describe protocols that is close to the human way of thinking and can be easily used to perform reachability analysis of the described protocol in a state-transition format. This formalism allows for an execution tree (ET) to be generated from a set of assertions such that all paths from the root to the leaves are well-defined formulas. We then extend the formalism with regards to real-time properties. Finally, we present a software verification tool, Verify, that implements the above features in the analysis of protocols.

Proposes a formal approach for adding fault detection to software. An assertion-based formalism is used to represent algorithm specifications. This representation is then used to generate a flowgraph or decision-to-decision graph (ddgraph), which is used to construct an execution path tree. The information gained from this algorithm representation is used to aid in the design of software-based fault tolerance techniques. Algorithm-based fault tolerance (ABFT) techniques are used to detect data structure-corrupting faults and checks are added to detect program flow errors. Flowgraph and ddgraph representations provide information to predict future program flow from the current flow. During execution, the current program location is recorded, along with the expected flow. Checks are placed to verify that the program flow follows the predicted flow. Fault coverage has been estimated through experiments with SOFIT (SOftware-based Fault Injection Tool), and the data is presented to demonstrate the effectiveness of the method.

This study addresses the use of fault injection for explicitly removing design/implementation faults in complex fault-tolerance algorithms and mechanisms (FTAM), viz, fault-tolerance deficiency faults. A formalism is introduced to represent the FTAM by a set of assertions. This formalism enables an execution tree to be generated, where each path from the root to a leaf of the tree is a well-defined formula. The set of well-defined formulas constitutes a useful framework that fully characterizes the test sequence. The input patterns of the test sequence (fault and activation domains) then are determined to fewer specific structural criteria over the execution tree (activation of proper sets of paths). This provides a framework for generating a functional deterministic test for programs that implement complex FTAM. This methodology has been used to extend a debugging tool aimed at testing fault tolerance protocols developed by BULL France. It has been applied successfully to the injection of faults in the inter-replica protocol that supports the application-level fault-tolerance features of the architecture of the ESPRIT-funded Delta-4 project. The results of these experiments are analyzed in detail. In particular, even though the target protocol had been independently verified formally, the application of the proposed testing strategy revealed two fault-tolerance deficiency faults.

Many massively parallel computers in use today utilize simple deterministic XY wormhole routing to transmit messages between nodes. Because XY routing does not provide any routing adaptability, it lacks the ability to avoid congested links, as well as faults. Therefore, the focus of this paper will be two-fold: improving the performance of wormhole routing and providing fault tolerance for up to N-1 faults in an N/spl times/N two-dimensional mesh. A simulation model based on the Intel Paragon is presented that compares several known routing strategies with the proposed strategy to illustrate how local state information can be used to provide a potential network throughput improvement of up to 20%, while achieving fault tolerance.>

Spanning trees have been used extensively in algorithms for hypercube communications and broadcasting. We present algorithms for reconnecting spanning trees and achieving communication among the nonfaulty nodes in the hypercube. The algorithms presented provide reconfiguration for the completely unbalanced spanning tree (CUST), balanced spanning tree (BST), and general spanning tree (GST) in hypercubes in the presence of single node failure. These algorithms can reconfigure around any single fault in 0(1) reconfiguration time with no dilation and will increase the congestion of a link by, at most, one. Simulation results for the algorithms under multiple faults also are presented.