Distributed Computer Network Research Articles

SELF-STABILIZING COMPUTATION OF 3-EDGE-CONNECTED COMPONENTS

A self-stabilizing algorithm is a distributed algorithm that can start from any initial (legitimate or illegitimate) state and eventually converge to a legitimate state in finite time without being assisted by any external agent. In this paper, we propose a self-stabilizing algorithm for finding the 3-edge-connected components of an asynchronous distributed computer network. The algorithm stabilizes in O(dnΔ) rounds and every processor requires O(n log Δ) bits, where Δ(≤ n) is an upper bound on the degree of a node, d(≤ n) is the diameter of the network, and n is the total number of nodes in the network. These time and space complexity are at least a factor of n better than those of the previously best-known self-stabilizing algorithm for 3-edge-connectivity. The result of the computation is kept in a distributed fashion by assigning, upon stabilization of the algorithm, a component identifier to each processor which uniquely identifies the 3-edge-connected component to which the processor belongs. Furthermore, the algorithm is designed in such a way that its time complexity is dominated by that of the self-stabilizing depth-first search spanning tree construction in the sense that any improvement made in the latter automatically implies improvement in the time complexity of the algorithm.

A Secure Anonymous Identity-based Key Agreement Protocol for Distributed Computer Networks

Recently, Hsu and Chuang proposed an efficient user identification scheme with key preserving user anonymity for distributed computer networks. Their protocol addressed an identity disclosure attack on the Yang et al. and Mangipudi-Katti schemes. Unfortunately, Hsu and Chuang’s new scheme posed vulnerability that the service provider could compute the private key of the user and imitate the user to send the service request to other service provider. In this paper, we analyzed Hsu-Chuang scheme and presented the vulnerability. We further secured their protocol by proposing a novel protocol that overcomes the above limitation while achieving the same security features. Besides, we made a demonstration of the correctness of our new scheme and analyzed the security properties. After compared Hsu-Chuang scheme and the new scheme, we also illustrated an example to illustrate the application of our improved protocol.

Design And Efficient Deployment Of Honeypot And Dynamic Rule Based Live Network Intrusion Collaborative System

The continuously emerging, operationally and managerially independent, geographically distributed computer networks deployable in an evolutionarily manner have created greater challenges in securing them. Several research works and experiments have convinced the security expert that Network Intrusion Detection Systems (NIDS) or Network Intrusion Prevention Systems (NIPS) alone are not capable of securing the Computer Networks from internal and external threats completely. In this paper we present the design of Intrusion Collaborative System which is a combination of NIDS,NIPS, Honeypots, software tools like nmap, iptables etc. Our Design is tested against existing attacks based on Snort Rules and several customized DDOS , remote and guest attacks. Dynamic rules are generated during every unusual behavior that helps Intrusion Collaborative System to continuously learn about new attacks. Also a formal approach to deploy Live Intrusion Collaboration Systems based on System of Systems Concept is Proposed.

МЕтодологичЕскиЕ основЫ синтезА распределенноЙ компьютерноЙ сетИ системЫ офисоВ

In the article the structural models of information technology and informative-reference providing are developed, and also the substantiation of multi-objective optimization models are carried out, depending on the degree of uncertainty of initial information for the synthesis of the distributed computer network of the system of offices

Managing Patient Expectations About Deidentification

Mark Rothstein (2010) convincingly illustrates that deidentification is an insufficient method for protecting patients’ private medical information. The current regulatory distinction between ident...

Design of Networked Control Systems With Explicit Compensation for Time-Delay Variations

In this paper, the effects of network delay among interconnecting elements of a distributed computer network control system are analyzed. Experimental tests have been accomplished to show the influence of the combined effects of the network delay (between sensor/controller and controller/actuator) on the overall performance of a feedback control system. For this purpose, a proportional-plus-integral (PI) controller has been used. This controller has been designed, using the well-known direct synthesis method and implemented in a didactic networked control system platform. Corresponding ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">z</i> -transform) difference equations have been used, assuming time-triggered (regular) samplings. The augmented PI controller (with compensation of the control signal and estimation of missing measurements) is developed. Stability analysis is performed to verify the validity of this scheme. The results presented in the paper show that the dynamic behavior of the closed-loop system can be improved using the proposed technique.

Обобщенная модель синтеза территориально-пространственно распределенной компьютерной сети офиса

The questions related to the synthesis by the territorial-spatially distributed computer network of office are examined in the article. The generalized model of synthesis of the territorial-spatially distributed computer network of office is developed, because of large complication it is decomposed on private models of the generalized model of synthesis.

A cycle-accurate transaction level SystemC model for a serial communication bus

This paper presents a transaction level SystemC model of an avionics mission system data bus that provides cycle-accurate simulation of the bus. The mission system is a complex distributed computer network consisting of a mission control computer, radars, an array of subsystems and sensors. The data bus plays a critical role in the system as it carries all the information between the system components. Therefore modelling the bus at an appropriate level of abstraction using appropriate technology is important for evaluation of the performance of both the bus and the entire system. While models based on traditional hardware description languages (HDL) provide cycle-accurate performance estimates they are very slow and have high code complexity. In order to enhance model performance this paper presents a transaction level model (TLM) utilizing the enhanced SystemC features and levels of abstraction. The TLM model incorporates a clock-based synchronisation strategy thereby providing cycle-accurate performance estimates like the HDL models. The developed model has been validated for various payloads and system sizes. Simulation results show that the proposed SystemC transaction level model is much more efficient than models developed using conventional hardware description languages.

Self-Adaptive Multimethod Search for Global Optimization in Real-Parameter Spaces

Many different algorithms have been developed in the last few decades for solving complex real-world search and optimization problems. The main focus in this research has been on the development of a single universal genetic operator for population evolution that is always efficient for a diverse set of optimization problems. In this paper, we argue that significant advances to the field of evolutionary computation can be made if we embrace a concept of self-adaptive multimethod optimization in which multiple different search algorithms are run concurrently, and learn from each other through information exchange using a common population of points. We present an evolutionary algorithm, entitled A Multialgorithm Genetically Adaptive Method for Single Objective Optimization (AMALGAM-SO), that implements this concept of self adaptive multimethod search. This method simultaneously merges the strengths of the covariance matrix adaptation (CMA) evolution strategy, genetic algorithm (GA), and particle swarm optimizer (PSO) for population evolution and implements a self-adaptive learning strategy to automatically tune the number of offspring these three individual algorithms are allowed to contribute during each generation. Benchmark results in 10, 30, and 50 dimensions using synthetic functions from the special session on real-parameter optimization of CEC 2005 show that AMALGAM-SO obtains similar efficiencies as existing algorithms on relatively simple unimodal problems, but is superior for more complex higher dimensional multimodal optimization problems. The new search method scales well with increasing number of dimensions, converges in the close proximity of the global minimum for functions with noise induced multimodality, and is designed to take full advantage of the power of distributed computer networks.

A novel user identification scheme with key distribution preserving user anonymity for distributed computer networks

Recently, Yang et al. proposed an efficient user identification scheme with key distribution, in which it is possible for the user to anonymously log into a system and establish a secret key shared with the system. Mangipudi and Katti later demonstrated a Deniable-of-Service (DoS) attack on the Yang et al. scheme and then proposed an improvement to withstand such an attack. However, this paper demonstrates an identity disclosure attack to show that neither schemes’ claimed user anonymity requirement can be achieved. We further propose a novel user identification scheme with key distribution preserving user anonymity for distributed computer networks. The proposed scheme not only withstands the attacks mentioned above, but also achieves the following: (i) user anonymity, (ii) key distribution, (iii) mutual authentication, and (iv) key confirmation. The performance of our scheme is of greater efficiency than that of previously proposed schemes in terms of communication costs and computational complexities.

Multidecision Quickest Change-Point Detection: Previous Achievements and Open Problems

The following multidecision quickest detection problem, which is of importance for a variety of applications, is considered. There are N populations that are either statistically identical or where the change occurs in one of them at an unknown point in time. Alternatively, there may be N “isolated” points/hypotheses associated with a change. It is necessary to detect the change in distribution as soon as possible and indicate which population is “corrupted” or which hypothesis is true after a change occurs. Both the false alarm rate and misidentification rate should be controlled by given (usually low) levels. We discuss performance of natural multihypothesis/multipopulation generalizations of the Page and Shiryaev-Roberts procedures, including certain asymptotically optimal properties of these tests when both the false alarm and the misidentification rates are low. Specifically, we show that under certain conditions the proposed multihypothesis detection-identification procedures asymptotically minimize the trade-off between any positive moment of the detection lag and the false alarm/misclassification rates in the worst-case scenario. At the same time, the corresponding sequential detection-identification procedures are computationally simple and can be easily implemented online in a variety of applications such as rapid detection of intrusions in large-scale distributed computer networks, target detection in cluttered environment, and detection of terrorist' malicious activity. Limitations of the existing and proposed solutions to this challenging problem are also discussed.

A Parallel Implementation of the PBSGDS Method for Solving CBAU Optimization Problems

In previous research, we have proposed a parallel block scaled gradient with decentralized step-size (PBSGDS) method. The method circumvents the difficulty of determining a step-size in the distributed computing environment and enables the proposed parallel algorithm to execute in a distributed computer network with limited amount of date transfer. In this paper, we implement the parallel algorithm within two real Independent System Operator (ISO) Networks, including homogeneous and heterogeneous types PCs-Networks environments, and demonstrate the computational efficiency and numerical satiability through numerous simulation test results in solving a Convex Block Additive Unconstrained (CBAU) optimization problem. Furthermore, the test results show that the performance of the proposed parallel algorithm appears more attractive due to the asynchronous effect in the distributed computing environment.

To the correction of analytical models for computer based communication systems

PurposeThis paper considers correction aspects of computer communication networks modelling with emphasis on their performance evaluation. In general, the problem is to achieve the highest possible performance given constraints on the system.Design/methodology/approachThe paper reviews the application of the analytical methods, based on the queueing theory, to the computer communication systems and makes an extension of theory to the improvement of the developed analytical models. In this sense the paper describes the derivation of a correction factor for analytical models to study more precise their basic parameters (end‐to‐end delay, performance, etc.).FindingThe contribution is in incorporating the derived correction factor to account for the real non‐exponential nature of the input to the transmission channels of computer communication systems. The produced results by corrected analytical model are compared with results previously reported in the literature to estimate the magnitude of improvement.Practical implicationsThe improved analytical models were tested under various ranges of parameters, which influence the architecture of the computer communication networks and which are important for practical use.Research limitations/implicationsThe rapid rate of growth of computer‐based communication systems (e.g. distributed computer networks, mobile data networks) has resulted in a renewed and intensive interest in this area. Efficient design of their service facilities leads to the sharing of resources among users. Such public shared networks are largely oversubscribed by independent users, which make random demands on the network resources. The optimal resource allocation to satisfy such demands and the proper settlement of contention when demands exceed the capacity of the resources, constitute the problem of being able to understand and to predict system behaviour.Originality/valueTo behaviour analysis we can use both analytical and simulation methods. Modelling and simulation are methods, which are commonly used by performance analysts to represent constraints and optimise performance. Principally the application of analytical queuing theory results belongs to the preferred method in comparison to the simulation method, because of their ability to analyse also very large networks.

Security policies for sharing knowledge in virtual communities

Knowledge management exploits the new opportunities of sharing knowledge among members of virtual communities in distributed computer networks, and knowledge-management systems are therefore modeled and designed as multiagent systems. In this paper, normative multiagent systems for secure knowledge management based on access-control policies are studied. It is shown how distributed access control is realized by means of local policies of access-control systems for documents of knowledge providers, and by means of global community policies regulating these local policies. Moreover, it is shown how such a virtual community of multiple knowledge providers respects the autonomy of the knowledge providers

Two Attacks on the Wu-Hsu User Identification Scheme

In 2000, Lee and Chang proposed a user identification scheme with key distribution preserving anonymity for distributed computer networks. Recently, Wu and Hsu pointed out that there are two weaknesses in the Lee-Chang scheme. They further not only proposed a new scheme to remedy the security leaks of the Lee-Chang scheme, but also reduced computation complexities and communication cost as compared with the Lee-Chang scheme. However, in this article we show that there are two attacks in their scheme.

Adaptive Diagnosis in Distributed Systems

Real-time problem diagnosis in large distributed computer systems and networks is a challenging task that requires fast and accurate inferences from potentially huge data volumes. In this paper, we propose a cost-efficient, adaptive diagnostic technique called active probing. Probes are end-to-end test transactions that collect information about the performance of a distributed system. Active probing uses probabilistic reasoning techniques combined with information-theoretic approach, and allows a fast online inference about the current system state via active selection of only a small number of most-informative tests. We demonstrate empirically that the active probing scheme greatly reduces both the number of probes (from 60% to 75% in most of our real-life applications), and the time needed for localizing the problem when compared with nonadaptive (preplanned) probing schemes. We also provide some theoretical results on the complexity of probe selection, and the effect of "noisy" probes on the accuracy of diagnosis. Finally, we discuss how to model the system's dynamics using dynamic Bayesian networks (DBNs), and an efficient approximate approach called sequential multifault; empirical results demonstrate clear advantage of such approaches over "static" techniques that do not handle system's changes.

Probabilistic anomaly detection in distributed computer networks

Distributed host-based anomaly detection has not yet proven practical due to the excessive computational overhead during training and detection. This paper considers an efficient algorithm for detecting resource anomalies in event streams with either Poisson or long tailed arrival processes. A form of distributed, lazy evaluation is presented, which uses a model for human–computer interaction based on two-dimensional time and a geometrically declining memory to yield orders of magnitude improvements in memory requirements. A three-tiered probabilistic method of classifying anomalous behaviour is discussed. This leads to a computationally and memory economic means of finding probable faults amongst the symptoms of network and system behaviour.

Electronic Prescribing and HIPAA Privacy Regulation

Electronic prescribing offers the prospect of safer medication management, but fulfillment of that promise depends on ready access to personal health information from many sources, thus raising new concerns about information privacy and security. Federal privacy regulations under the Health Insurance Portability and Accountability Act of 1996 (HIPAA) limit the sharing of health information by providers, and particularly may discourage information sharing over distributed computer networks. This analysis finds that although HIPAA has only a limited effect on current e-prescribing practices, future electronic prescribing systems will likely fall short of their potential benefits, absent policy refinements designed to encourage clinically appropriate, networked sharing of patient health information.

Efficient user identification scheme with key distribution preserving anonymity for distributed computer networks

In 2000, Lee and Chang (Comput Syst Sci Eng 15 (2000) 211) presented a user identification scheme that also can simultaneously achieve key exchange requirement while preserving the user anonymity. Their idea is valuable especially when it is applied to some applications in which the identity of the user should be protected from the public in the distributed computer networks. Unfortunately, our paper shows that their scheme is insecure under two attacks and we further proposed a more efficient identification scheme preserving the same merits. The proposed scheme not only effectively eliminates the security leaks of the Lee–Chang scheme, but also reduces computational complexities and communication costs as compared with their scheme.

Authorization administration in a distributed multi-application environment

To meet the authorization administration requirements in a distributed computer network environment, this paper extends the role-based access control model with multiple application dimensions and establishes a new access control model ED-RBAC(Extended Role Based Access Control Model) for the distributed environment. We propose an extendable hierarchical authorization assignment framework and design effective role-registering, role-applying and role-assigning protocol with symmetric and asymmetric cryptographic systems. The model can be used to simplify authorization administration in a distributed environment with multiple applications.