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As a replacement for the lecture-driven teaching of the past, we are aiming to establish an individually initiated, efficient independent study environment using a computer network. This paper focuses in particular on the collection of Web information needed by researchers, based on efficient paper retrieval and collection Web sites using XML. XML can handle data on the Web more flexibly than the present HTML, and research into its practical applications is progressing rapidly. In the artificial intelligence field, ontology engineering for authoring tools to be used in creating teaching materials is under way. In this context, because XML has been defined by the W3C, it is an accessible standard, and application examples have appeared. However, few of them focus on retrieval. We describe a “paper retrieval system” for efficient retrieval, constructed only in HTML on the basis of XML, RDF, and XHTML. © 2002 Wiley Periodicals, Inc. Syst Comp Jpn, 34(1): 21–28, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10014 [ABSTRACT FROM AUTHOR]

In this paper, we propose a binary feedback scheme for congestion control in computer networks using a gradient-based mechanism which employs neural network modelling of the system dynamics. The optimal direction for rate adjustment at the source is based on a single bit feedback signal which depends upon the sign of the sensitivity of the system performance index with respect to queue input rate. The paper presents the scheme and the analysis that went into the choice of the various decision mechanisms. Simulation results are presented to show the performance of the gradient based technique as compared to the conventional queue-based approach. Copyright © 2000 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The transmission control protocol (TCP) is one of the most important Internet protocols. It provides reliable transport services between two end-hosts. Since TCP performance affects overall network performance, many studies have been done to model TCP performance in the steady state. However, recent researches have shown that most TCP flows are short-lived. Therefore, it is more meaningful to model TCP performance in relation to the initial stage of short-lived flows. In addition, the next-generation Internet will be an unified all-IP network that includes both wireless and wired networks integrated together. In short, modelling short-lived TCP flows in wireless networks constitutes an important axis of research. In this paper, we propose simple wireless TCP models for short-lived flows that extend the existing analytical model proposed in [IEEE Commun. Lett. 2002; 6(2):85–88]. In terms of wireless TCP, we categorized wireless TCP schemes into three types: end-to-end scheme, split connection scheme, and local retransmission scheme, which is similar to the classification proposed in [IEEE/ACM Trans. Networking 1997; 756–769]. To validate the proposed models, we performed ns-2 simulations. The average differences between the session completion time calculated using the proposed model and the simulation result for three schemes are less than 9, 16, and 7 ms, respectively. Consequently, the proposed model provides a satisfactory means of modelling the TCP performance of short-lived wireless TCP flows. Copyright © 2005 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: Advances in computer networking, storage technologies, and high‐performance computing are helping global communities of researchers to address increasingly ambitious problems in Science collaboratively. E‐Science is the "science of this age"; it is realized through collaborative scientific enquiry which requires the utilization of non‐trivial amounts of computing resources and massive data sets. Core to this is the integrated set of technologies collectively known as e‐Infrastructures. In this paper, we explore the e‐Science and the e‐Infrastructure knowledge base through co‐citation analysis of existing literature. The dataset for this analysis is downloaded from the ISI Web of Science and includes over 12,000 articles. We identify prominent articles, authors, and articles with citation bursts. The detection of research clusters and the underlying seminal papers provide further insights. Our analysis is an important source of reference for academics, researchers, and students starting research in this field. [ABSTRACT FROM AUTHOR]

Traditional vehicular edge computing research usually ignores the mobility of vehicles, the dynamic variability of the vehicular edge environment, the large amount of real‐time data required for vehicular edge computing, the limited resources of edge servers, and collaboration issues. In response to these challenges, this article proposes a vehicular edge computing optimization scheme based on the Lyapunov function and Deep Reinforcement Learning. In this solution, this article uses Digital Twin technology (DT) to simulate the vehicular edge environment. The edge server DT is used to simulate the vehicular edge environment under the edge server, and the base station DT is used to simulate the entire vehicular edge system environment. Based on the real‐time data obtained from DT simulation, this paper defines the Lyapunov function to simplify the migration cost of vehicle tasks between servers into a multi‐objective dynamic optimization problem. It solves the problem by applying the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. Experimental results show that compared with other algorithms, this scheme can effectively optimize the allocation and collaboration of vehicular edge computing resources and reduce the delay and energy consumption caused by vehicle task processing. [ABSTRACT FROM AUTHOR]

Processing queries in wireless sensor networks causes quality of service challenges such as data latency and validity. In fact, this paper is going to shed light on identifying the right trade‐off between latency and the freshness of the data. For this purpose, a fuzzy logic‐based decision‐making system that assigns incoming queries either to the sensor network, where the queries are waiting to be processed into a queue, or a central database which provides stored and potentially stale data or to a cache server which in turn provides acceptable latency and recent data, is provided. Thus, a new rule‐based system decision is introduced, that minimizes the request latency and returns the most recent data. In addition, a comparison between the approach and other work that is restricted to the database server and sensor network with no focus on the caching server is provided. This paper is going to carry on with the theory of Markov Chain which is more complicated compared to the fuzzy logic system. This approach is confirmed in the basis of an experience is developed with python. [ABSTRACT FROM AUTHOR]

Using multiple independent networks (also known as rails) is an emerging technique which is being used to overcome bandwidth limitations and enhance fault tolerance of current high-performance parallel computers. In this paper, we present and analyze various algorithms to allocate multiple communication rails, including static and dynamic allocation schemes. An analytical lower bound on the number of rails required for static rail allocation is shown. We also present an extensive experimental comparison of the behavior of various algorithms in terms of bandwidth and latency. We show that striping messages over multiple rails can substantially reduce network latency, depending on average message size, network load and allocation scheme. The methods compared include a static rail allocation, a basic round-robin rail allocation, a local-dynamic allocation based on local knowledge and a dynamic rail allocation that reserves both communication endpoints of a message before sending it. The last method is shown to perform better than the others at higher loads: up to 49% better than local-knowledge allocation and 37% better than the round-robin allocation. This allocation scheme also shows lower latency and it saturates at higher loads (for long enough messages). Most importantly, this proposed allocation scheme scales well with the number of rails and message size. In addition we propose a hybrid algorithm that combines the benefits of the local-dynamic allocation for short messages with those of the dynamic algorithm for large messages. Copyright © 2003 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The time-dependent Maxwell equations are one of the most important approaches to describing dynamic or wide-band frequency electromagnetic phenomena. A sequential finite-volume, characteristic-based procedure for solving the time-dependent, three-dimensional Maxwell equations has been successfully implemented in Fortran before. Due to its need for a large memory space and high demand on CPU time, it is impossible to test the code for a large array. Hence, it is essential to implement the code on a parallel computing system. In this paper, we discuss an efficient and scalable parallelization of the sequential Fortran time-dependent Maxwell equations solver using High Performance Fortran (HPF). The background to the project, the theory behind the efficiency being achieved, the parallelization methodologies employed and the experimental results obtained on the Cray T3E massively parallel computing system will be described in detail. Experimental runs show that the execution time is reduced drastically through parallel computing. The code is scalable up to 98 processors on the Cray T3E and has a performance similar to that of an MPI implementation. Based on the experimentation carried out in this research, we believe that a high-level parallel programming language such as HPF is a fast, viable and economical approach to parallelizing many existing sequential codes which exhibit a lot of parallelism. Copyright © 2003 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A directory service keeps track of the location and status of mobile objects in a distributed system. This paper describes our experience implementing two distributed directory protocols as part of the Aleph toolkit, a distributed shared object system implemented in Java. One protocol is a conventional home-based protocol, in which a fixed node keeps track of the object's location and status. The other is a novel Arrow protocol, based on a simple path-reversal algorithm. We were surprised to discover that the Arrow protocol outperformed the home protocol, sometimes substantially, across a range of system sizes. This paper describes a series of experiments testing whether the discrepancy is due to an artifact of the Java run-time system (such as differences in thread management or object serialization costs), or whether it is something inherent in the protocols themselves. In the end, we use insights gained from these experimental results to design a new directory protocol that combines advantages of both. Copyright © 2000 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, a queueing system with a preemptive priority limited processor sharing system with some versions of the discipline is considered. The problem of lost probability is an important aspect for developing methods to improve efficiency and productivity of in modern communications system and computer networks. In the paper, the following conditions are considered. The total service rate depends on the number of jobs serviced simultaneously, and this number is limited. The service rate of simultaneously serviced jobs is the same. There are jobs of different priorities. If the maximum quantity of jobs are serviced simultaneously, and a new job arrives, then depending on the priorities of the arriving and serviced jobs, the arriving job can be lost or preempt a serviced job. Four versions of the service discipline are considered. Depending on the discipline version, an arriving job can preempt or not preempt a job of the same priority, and preempted job is lost or its service is resumed later. This paper develops an approach to compute the loss probability of a prescribed priority job for each version of the discipline. [ABSTRACT FROM AUTHOR]

The use of citation data in the computer construction of historical network diagrams is proposed. A new "critical path method" of evaluating the impact of individual scientific discoveries is described as welt as a "critical impact" factor which measures the arborization of specific papers or ideas through the subsequent literature. The danger of indiscriminate, unqualified use of quantitative citation data in sociological evaluations is emphasized. However, citation indexes do make thorough qualitative evaluations possible by providing a practical tool for locating subsequent criticisms of particular papers by specified authors. [ABSTRACT FROM AUTHOR]

Abstract: The intensity in the requirements of Internet of Things and mobile internet makes the efficiency of fifth‐generation (5G) wireless communications very challenging to achieve. Accomplishing the drastically increasing demand of massive connectivity and high spectral efficiency is a strenuous task. Because of the very large number of devices, 5G wireless communication systems are inevitable to satisfy the traffic requirements. Recently, nonorthogonal multiple‐access (NOMA) schemes are immensely being explored to address the challenges in 5G, which include effective bandwidth utilization, support for a massive number of devices, and low latency. This paper provides the reader with a holistic view of multiple‐access schemes, methods, and strategies for optimization in NOMA. First, we discuss the taxonomy of multiple‐access schemes in the literature; then, we provide a detailed discussion of objectives, constraints, problem types, and solution approaches for NOMA. This paper also discusses the decoding methods and key performance indicators used in NOMA. Finally, we outline future research directions. [ABSTRACT FROM AUTHOR]

Modern computer networks' increasing complexity and scale need serious attention towards network anomaly detection. Software‐defined networking (SDN) and graph neural networks (GNN) have emerged as promising approaches for anomaly detection due to their ability to capture dynamic network behavior and learn complex patterns from large‐scale network data. The amalgamation of SDN and GNN for network anomaly detection presents promising opportunities for improving the accuracy and efficiency of network anomaly detection. This paper focuses on various trends, issues, and challenges by integrating GNN on the top of SDN for network anomaly detection. The article highlights the advantages of using SDN for providing fine‐grained control and programmability in network monitoring. At the same time, GNN can model network behavior as a graph and learn representations from graph‐structured data. The authors also discuss the limitations of traditional anomaly detection methods in SDN, such as rule‐based approaches, and the potential of GNN to overcome these limitations by leveraging their ability to capture non‐linear and dynamic patterns in network data. This paper also presents a case study of DoS attack detection using SDN. The result shows that SDN based approach helps to detect attacks with an accuracy of 97% with future research directions. [ABSTRACT FROM AUTHOR]

Summary: In this paper, the design of reliable communication network is solved by genetic algorithm. In order to solve this problem, we must first provide the lowest acceptable network reliability. There are many methods to satisfy the network reliability constraints. The penalty function may produce an invalid solution, so it is not suitable to solve the problem. In order to overcome these difficulties, this paper proposes a heuristic repair method, which is based on the number of spanning trees in the graph. Compared with the heuristic maintenance method with lower cost, this method can generate a better solution with less computation. When the population size is 25, the hybridization rate is 0.96, and the mutation rate is 0.07, the best results can be obtained. This paper analyzes the node fault, grasps the influence rule of the fault on the network, and improves the network reliability. This paper summarizes and classifies the failure modes of communication network nodes. Combined with the classic BA network model in the complex network theory, through the simulation design of MATLAB and OPNET, the influence of node function failure and performance failure on network reliability is studied. [ABSTRACT FROM AUTHOR]

Summary: Software‐defined network (SDN) technology is widely used for computer networks, especially in enterprise data centers and virtualized networking. However, SDN networks encounter severe challenges to security. One such challenge comes from third‐party applications that contain malicious logic and security vulnerabilities, resulting in controller integrity attacks. In this paper, we propose a defensive mechanism of object integrity for SDN (DMoiSDN) to mitigate the issue known as Cross‐App Poisoning (CAP). Our results contribute to increasing the integrity level of the controller's resources by conducting a potential risk analysis, which showed a decrease of 57% in the risk factor for potential attacks. We further examined the results of comparing DMoiSDN's performance with related work that uses information flow control (IFC) policies. The best results among the three conducted scenarios were as follows: we found that decreased latency in our system ranged from 12% to 90%, with an average of 59%, when encountering an increase in requests. It ranged from 78% to 49%, with an average of 63%, when receiving a variable number of total permissions for each application. DMoiSDN is expected to show a perceptible but reasonable latency and, to some extent, be able to avoid a critical impact on performance. [ABSTRACT FROM AUTHOR]

Preface for the special issue on Euro-Par 2008. Copyright © 2009 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Background: Screen‐sharing technologies enable applications such as screen mirroring, video streaming and instant messaging across multiple device screens. Despite their increasing use in many contemporary classrooms, there is a paucity of research directly examining pedagogical benefits and issues of these technologies. Objectives: This study investigated the influence of screen‐sharing technologies on teachers' practices, highlighting pedagogical benefits and issues encountered. Methods: The paper drew on a sample of 321 K‐12 teachers and utilised principal components analysis, descriptive statistics and inductive coding. Results and Conclusions: Teachers reported greater mobility, increased ease of content sharing and deeper learner cognition as attributes of improved learning and teaching with the technologies. However, a minority highlighted technical issues such as network and hardware problems affecting their confidence. Despite increased mobility as an affordance, teachers' perceptions about mobility largely appeared to be predicated on assumptions that the technologies were intended for didactic instruction. Takeaways: The study contributes to a more nuanced understanding of screen‐sharing affordances while underscoring learner‐led screensharing as a focus for future research and practice. Lay Description: What is already known about this topic: Screen‐sharing technologies are becoming commonplace in many contemporary educational settings.The technologies represent integrated systems that enable functions such as mirroring, video streaming, online polls, real‐time editing, screen‐capturing and learner analytics.Screen‐sharing is indirectly examined in several studies with findings indicating improvements in group awareness, emotional engagement, learner confidence to share ideas and teachers' visualization of concepts.Existing findings are largely anecdotal and there are very few studies that have focused directly on screen‐sharing affordances. What this paper adds: An empirical study directly examining teachers' first‐hand perspectives of using screen‐sharing technologies.Benefits relate to greater task focus, deeper thinking, improvements to teaching practice and ease of sharing content.A minority of teachers experienced issues such as technical problems, inappropriate sharing and distraction.Mobility was recognized as a key affordance though remained underutilized by many teachers. Implications for practice and/or policy: Professional learning accompanying the use of screen‐sharing technologies can support teachers to take advantage of all features of screen sharing such as enhanced teacher mobility.Institutions need to provide requisite technical and professional support for teachers to effectively and reliably leverage screen‐sharing in the classroom.There is a need to explore teacher's and learner's screen‐sharing uses in situ to more fully understand issues and possibilities. [ABSTRACT FROM AUTHOR]

With time smart services have become more domineering than ever before however, the pertinent security considerations fade to correspond with growing heterogeneity in the internet of things (IoT) devices and new technologies coupled with resource constraints, crafting IoT‐based systems more susceptible to cyber‐attacks. To ensure a secure IoT environment, pro‐active security mechanisms, like scanning vulnerabilities and prioritizing to remediate them timely, should be embedded in the system. Motivated by the facts, we in this paper, highlight the state of the art of several works trading with a common vulnerability scoring system (CVSS), its limitations, and the emendations recommended to conclude its maturity. CVSS is an industry standard that has been adopted worldwide to quantify the vulnerabilities in organizations for IT and IoT‐based systems. The vulnerabilities mathematical score coalesces with environmental knowledge for finding attack paths and apt score for prioritization. The specific functionality and exclusive dynamics of IoT and cyber‐physical systems in comparison to traditional computer networks, make the legacy cyber‐security exemplars unfit for these advanced networks. This paper studies the relevance of CVSS for smart systems and present an intelligent vulnerability quantification framework for IoT systems grounded on the CVSS v3.1 framework with threat intelligence and machine learning models. Further by applying blockchain technology in the proposed framework, the issues concerning security, lack of trust, and privacy possibly will resolve by hiring a smart contract. [ABSTRACT FROM AUTHOR]

A preface to the periodical "Concurrency and Computation: Practice and Experience" is presented.

Through network programmability, software defined network can simplify network control and management. Since the current software defined network southbound interface level is low and programming situation is complex, it requires a high-level abstract programming language to simplify programming. First, this paper improves the NetCore programming language to generate NetCore-M language, so that it can support deployment of multipolicies combination including packet drop action. This paper describes in detail the syntax, semanteme, and implementation of NetCore-M language forwarding policy service. Secondly, this paper describes the network policy conflict systematically. Finally, this paper shows that the modified multipolicies combination algorithm can effectively detect policies conflicts based on the implementation of the Pyretic project. [ABSTRACT FROM AUTHOR]

Cybersecurity has gained prominence in the decision‐making of firms. Due to the increasing occurrences of threats in the cyberspace, investments in cybersecurity have become critical to mitigate the operational disruption of businesses. This paper surveys the theoretical literature on the firms' incentives to invest in cybersecurity. A taxonomy of the existing contributions is provided to frame them in a common reference scheme and a model is developed to encompass such contributions and discuss their main findings. Papers that investigate the investment problem of an isolated firm are distinguished from those that consider interdependent firms. In turn, interdependent cybersecurity is analyzed in three different contexts: (i) firms that operate their business via a common computer network, but are not competitors in the product market; (ii) firms that are competitors in the product market, but run their business using non‐interconnected computer systems; (iii) firms that are competitors and rely on a common computer network. Finally, promising avenues for future research and policy implications are discussed. [ABSTRACT FROM AUTHOR]

The article discusses papers published within the issue, including one on energy-efficient multipath routing protocol for wireless sensor networks and another on the use of polynomial regression for data representation in wireless sensor networks.

SUMMARY This paper proposes a cooperative quadrature physical layer network coding (CQPNC) scheme for a dual-hop cooperative relay network, which consists of two source nodes, one relay node and one destination node. All nodes in the network have one antenna, and the two source nodes transmit their signals modulated with quadrature carriers. In this paper, a cooperative quadrature physical layer network coded decode-and-forward (DF) relay protocol (CQPNC-DF) is proposed to transmit the composite information from the two source nodes via the relay node to the destination node simultaneously to reduce the number of time slots required for a transmission. The proposed CQPNC-DF relay protocol is compared with time-division multiple-access amplify-and-forward (TDMA-AF), TDMA-DF, cooperative network coded DF (CNC-DF) and cooperative analog network coded AF (CANC-AF) relay protocols to demonstrate its effectiveness in terms of bit error rate (BER) and system throughput under different propagation conditions. The simulation results reveal that the proposed CQPNC-DF relay protocol can significantly improve the network performance. Compared with two TDMA schemes and CNC-DF, the proposal can provide up to 100% and 50% throughput gains, respectively. Moreover, no matter what the scene, the proposed scheme always has the lowest BER in the low SNR region. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper develops a framework to simulate and evaluate pricing policies of spacecraft trading commodities, such as data routing, in a federated satellite network. Federated satellite systems allow the reallocation of underutilized assets, enabling their use as services between owners and third parties. The paper, by means of game theory, focuses on sealed-bid reverse auction pricing schemes, benchmarks first-price and second-price auction strategies, and evaluates the associated trade-offs in terms of performance and cost, and losses in Pareto efficiency introduced by system-level operation constraints. The analysis considers an application case study for federated satellite systems operating in Low Earth Orbit for commercial purposes. Satellite federations are a novel paradigm envisioning on-orbit opportunistic sharing of resources through an ad hoc mobile satellite network. The architecture creates the basis for the realization of a commercial cloud computing environment in orbit, with spacecraft establishing communications links between each other leveraging on system design margins. The results of the case study in space provide new insights on the design of federated satellites and their operations while characterizing emergent behaviors and efficient trade-offs on the Pareto front of the cost-performance curve. [ABSTRACT FROM AUTHOR]

All‐optical cross‐connects need to perform switching not only in the space domain, but also in the wavelength domain. Switching in the wavelength domain requires wavelength converters (WCs), and WCs capable of simultaneously performing multiple wavelength conversions have been invented. We can use multiple stages of such WCs to form a wavelength exchange network to allow an even larger number of simultaneous wavelength conversions. However, WCs with a full conversion range are often difficult to implement. In the paper, we develop new techniques and theories that can reduce the conversion range requirement and still maintain the full connectivity of all‐optical space/wavelength switches. [ABSTRACT FROM AUTHOR]

Cloud computing (CC) is on‐demand deliverable services over computer network for data processing and storage. CC has emerged with multiple datacenters available all over the world and providing services with a pay‐as‐you‐go criteria. Even though the cloud system has numerous advantages still it faces one of the major challenges like vulnerability to security attacks. There are multiple types of attacks categorized to break the security like Man‐in‐the‐middle, Malware injection, and Denial‐of‐service (DOS), etc. In case of deep learning (DL), the network called as convolutional neural network (CNN) is a class of deep neural networks (DNN). It is generally used to explore visual imagery. CNN are computationally comprehensive for a commercial computer. In this paper, the focus is to highlight various security attacks in the cloud with machine and deep learning methods for the detection of attacks. Also review different Machine Learning (ML) methods to overcome the cloud security challenges. [ABSTRACT FROM AUTHOR]

Engineering and technology educators continually strive for realistic, hands‐on laboratory exercises to enhance their students' learning. This research describes the redesign of an undergraduate introductory computer networking course to include new weekly virtual laboratory assignments that culminate in a 'real world' final project of configuring a 'corporate' network. The use of an Internet testbed technology named ISEAGE allows students to design and implement fully functional networks using public IP space that is contained in the testbed. To the students, it appears as if they were directly connected to the Internet while still being protected. This paper shows that 'real world' projects using virtual lab technology can have a positive effect both on objective networking knowledge, as well as subjective self‐assessments of self‐efficacy with regard to implementing the technology. It also demonstrates that 'real world' final projects encourage student thinking at upper levels of Bloom's taxonomy. Practitioner notesWhat is already known about this topic Computer and engineering courses require hands‐on labs.Due to online enrollment and the current COVID pandemic, these hands‐on labs need to be taught virtually.What this paper adds We detail a virtual lab environment for teaching hands‐on skills in computer networking.We longitudinally assess the virtual lab technology across multiple institutions.Implications for practice and/or policy Other practitioners can implement this same technology for teaching hands‐on networking concepts virtually. [ABSTRACT FROM AUTHOR]

Mobile data volume is growing with an annual compound rate of 61% between 2014 and 2019. To cope with the data volume growth, a more dynamic and flexible network is needed. Caching has been deployed by both mobile network operators and content providers to reduce the load on centralized data centers and gateways. In addition, software-defined networking (SDN) is a prominent solution to more flexibly and efficiently utilize the available network resources, especially in the mobile backhaul. However, installation of cache servers into the network means additional capital expenditure (CAPEX) and their daily operations incur operational expenses (OPEX). Thus, the change in cost of deploying and operating in-network caching compared with data center caching is modeled in this paper using a Finnish Long-Term Evolution reference network. In addition, this paper simulates both the SDN-optimized in-network caching system and data center caching, the results of which are utilized in the cost model. The simulation results show that, on average, in-network caching compared with caching only in data centers reduces traffic load by 45% in the network and 6% in the gateways. The cost modeling indicates that in-network caching reduces network-related CAPEX by 1.53% and OPEX by 0.49% compared with caching only in data centers. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of scheduling network tasks that have to be performed in a given computer network. Each network task consists of the transmission of data files between two nodes of the network and has to be performed in an a priori known time window in such a way that the energy consumed by the network equipment during the transmission of all the considered tasks is minimized. The entire mathematical model of this scheduling problem is proposed. Some results of computational experiments are also presented to show energy savings achieved through implementation of the proposed model in the interdata center network. [ABSTRACT FROM AUTHOR]

SUMMARY The paper outlines a framework and software tool intended for simulation of cooperative defence mechanisms against botnets. These framework and software tool are based on agent-oriented approach and packet-level network simulation. They are intended to evaluate and compare different cooperative distributed attacks and defence mechanisms. Botnet and defence components are represented in the paper as a set of collaborating and counteracting agent teams. Agents are supposed to collect information from various network sources, operate different situational knowledge, and react to actions of other agents. The paper describes the results of experiments aimed to investigate botnets and distributed denial of service defence mechanisms. We explore various botnet attacks and counteraction against them on the example of defence against distributed denial of service attacks. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The key features of computer networks available for a disaster situation are reliable, fault tolerance, and self‐configurable. Therefore, using a wireless mesh network for disaster prevention and recovery system has gained much attention from the research community in the last decades. In addition, from the practical aspects of the network infrastructures of the disaster system, we should assume the core capabilities such as wireless connectivity in a wide range, ease of use, and low cost so on. In this paper, we propose an interface mode assignment method for reconstructing a route from an isolated router to a gateway (GW) router in a wireless mesh network based on IEEE 802.11 infrastructure mode after a disaster occurrence. The proposed method assigns an adequate mode to each interface in an isolated router to recover the network reachability in a distributed manner. Simulation results show the effectiveness of the proposed method via two different scenarios. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Abstract: Data center has recently emerged as a common infrastructure that includes numerous servers and host diversity of applications and cloud‐based services. In this paper, a dynamic method is proposed for traffic engineering in software‐defined data center networks helping to design an optimal demand‐path mapping with a tolerable computational complexity. To achieve the aim of this study, we used a linear programming to define the problem statement and then modeled the problem as a Path‐based multicommodity flow. To reduce time complexity, first, a decomposition technique is used to divide the problem model into smaller subproblems, which are then solved simultaneously by applying parallelizing techniques (ie, multiple‐core computing and OpenMP). Next, a suitable iterative algorithm is utilized to quickly converge subproblem solutions leading to an answer to the master problem. Simulation results show that solving time is considerably improved compared with a number of reported schemes devoted to this topic. In addition, implementing the proposed method serially yields an optimum solution, which takes significantly shorter time to reach than that of the generic (the LP model that is not decomposed) approach. [ABSTRACT FROM AUTHOR]

This paper characterizes efficient networks in player and partner heterogeneity models for both the two-way flow and the one-way flow networks. Player (partner) dependent network formation allows benefits and costs to be player (partner) heterogeneous, which is an important extension for modeling social networks in the real world. This paper shows that efficient networks are minimally connected and have either a star-type or a variation of star-type architectures in the two-way flow model, and have the wheel architecture in the one-way flow model. [ABSTRACT FROM AUTHOR]

Summary: Network intrusions are a big security threat to current computer networks. For protection, collaborative intrusion detection networks (CIDNs) are developed attempting to reach better detection performance than a single detector, by allowing a set of detectors to switch data or information with each other. However, there is a need to implement suitable trust management schemes, with the aim to safeguard such distributed detection networks against insider threats. In the literature, previous studies have indicated that the notion of intrusion sensitivity can be used to enhance the effectiveness of trust management, by highlighting the feedback from expert nodes. In addition, machine learning can be used to assign the value of intrusion sensitivity automatically. In this work, we evaluate the performance of typical supervised learning classifiers in allocating the value of intrusion sensitivity, and figure out some limitations under different data sets. Then we investigate the impact of intrusion sensitivity in a real network environment under adversarial conditions. The results demonstrate that a wrongly assigned sensitivity value may greatly degrade the detection effectiveness of insider attacks. There is a significant need to choose a suitable classifier in allocating the value of intrusion sensitivity in practice. [ABSTRACT FROM AUTHOR]

ABSTRACT In earlier work, it has been suggested that processes and applications seem to share many important characteristics and seem to be amenable to similar approaches of modeling, definition, and analysis. In most of this previous work, approaches and technologies for developing applications have been applied to the development of processes, largely with positive results. This paper suggests the opposite, namely that approaches and technologies for developing processes seem likewise to be applicable to developing applications. As an example, this paper notes that resource specification, allocation, and management are central issues in the development of many processes, and suggests that although these capabilities seem to be important for growing classes of application software, the ability to support them seems curiously neglected. The paper also notes that management of rework is a central issue of virtually all creative activities. This is evidenced by the observation that facilities for supporting rework are prominent features in so many creative domains. Accordingly, the paper suggests an analogous need for facilities for supporting rework in application software as well, especially in application software aimed at supporting human creativity. The paper concludes by noting that both application and process software technologies grow through consideration of the relevance of technologies developed for one to the other. This in turn should lead to a clearer understanding of the essence of what they have in common, leading to conjectures about the nature of a more abstract class of entities, that we refer to simply as software. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper focuses on the role of network resources and examines the associated mechanisms that affect the timing of entry into an emerging product market. Linking network theory to market entry research, I analyze the pattern in the structure, relation, and composition of 517 firms' strategic alliances as the firms face the decision of whether and when to enter the networking switches market over a 13-year period from 1989 to 2001. The context for empirical testing is the voice/data convergence between telephony communications and computer networking technologies during which the industry boundary blurs. Firms that have access to information of high quality, large quantity, and compositional heterogeneity are likely to enter the newly developed market more quickly. However, network configuration lock-in and network costs may counterbalance the benefits derived from network resources. I discuss the implications of these findings for research on social networks and the timing of market entry. Copyright © 2007 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

As a promising architecture of next‐generation network, software defined‐information centric network (SD‐ICN) inherits the advantages of software defined network (SDN) and information‐centric network (ICN) to enable flexible and fast content retrieval, especially in the current era of artificial intelligence. However, the existing researches mainly focus on a single respective in this field, which motivates in comprehensively providing a forward‐looking guidance and development direction for scholars and engineers. To this end, the latest developments of SD‐ICN is presented. First, the widely‐accepted concepts and impacts on traditional networks are introduced. Second, the shortcomings of SDN and ICN over conventional networks are respectively analyzed to illustrate the necessity of SD‐ICN. Third, based on extensive analysis and deep deliberation, a methodical taxonomy for existing combination studies is proposed. They are divided into SDN over ICN, ICN over SDN, and mutual immersive pattern. Fourth, the performances of three integration categories are compared and the limitations of related works are highlighted. Fifth, the maturity index from six development indicators are evaluated. Further, the maturity and practicality of these schemes are generalized. Based on the above studies and comparisons, the lessons learned by SDN and ICN developments are concluded. Finally, future research directions and opportunities are discussed for the readers. [ABSTRACT FROM AUTHOR]

Persistent homology is a computationally intensive and yet extremely powerful tool for Topological Data Analysis. Applying the tool on potentially infinite sequence of data objects is a challenging task. For this reason, persistent homology and data stream mining have long been two important but disjoint areas of data science. The first computational model, that was recently introduced to bridge the gap between the two areas, is useful for detecting steady or gradual changes in data streams, such as certain genomic modifications during the evolution of species. However, that model is not suitable for applications that encounter abrupt changes of extremely short duration. This paper presents another model for computing persistent homology on streaming data that addresses the shortcoming of the previous work. The model is validated on the important real‐world application of network anomaly detection. It is shown that in addition to detecting the occurrence of anomalies or attacks in computer networks, the proposed model is able to visually identify several types of traffic. Moreover, the model can accurately detect abrupt changes of extremely short as well as longer duration in the network traffic. These capabilities are not achievable by the previous model or by traditional data mining techniques. [ABSTRACT FROM AUTHOR]

Creating adequate safeguards for physical and online locations (e.g., desktop computers, network servers) where protected health information (PHI) may be breached is critical for management within entities compliant with the Health Information Portability and Accountability Act (HIPAA). With the increasing complexity of cyber breaches and budgetary issues, prioritizing which locations require the most immediate attention by top management through a data‐driven model is more important than ever. Using CORAS threat modeling and five methods for multi‐criteria decision‐making, these locations were ranked from greatest to least risk of data breaches. Statistical methods were subsequently used for consistency and robustness checks. The findings illustrate that each type of covered entity under HIPAA must prioritize a different set of locations to safeguard first: health care providers must focus on the security of network servers, other portable electronic devices, and category of others (i.e., miscellaneous locations); health plans must focus on the security of paper and films, network servers, and others; and business associates must focus on the security of category of others, network servers, and other portable electronic devices. Combined with data on the source of the breaches (external vs. internal) and type of threats (e.g., hacking, theft), these findings provide recommendations for risk identification for privacy officers across health care. [ABSTRACT FROM AUTHOR]

Conventionally, the problem of capacity-flow assignment in packet switching computer networks has been considered mainly for the purpose of improving the network performance and the effective usage of the resources in the networks. The problem of the fair allocation of the network resources to each user (fairness) has been investigated little. Because one of the most important purposes of the computer network is that a plural number are arranged dispersively in the network, we must make sufficient study of fairness in the problem of the flow assignment of the packet and the problem of the distribution of the line capacity. However, no clear definition of the fair allocation has been proposed to data. In this paper, we adopt the "power" (function) as the performance measure and discuss the problem of the network capacity-flow assignment in which maximized network power ensures effective usage of networks, and equalized power for each user realizes the fairness. The results of this study provide a new guideline to solve the problem of distributing the resources effectively and fairly. The method in this paper can be discussed generally without limitation of the network topology. However, since the concrete numerical calculation is so complicated, we take loop networks for the object of the analysis. [ABSTRACT FROM AUTHOR]

Patent is a very important and valuable type of scientific and technical big data. This paper presents how to mine patent text to obtain valuable information/knowledge from large-scale candidates obtained from these patents based on massive patent texts. We firstly propose a patent term extraction method using co-occurrence in the abstract and first-claim sections of patent records. There are three steps: (1) we extract candidate strings according to our definition of a term; (2) we propose an assumption to verify whether a candidate string is a qualified term or not by using the co-occurrence of terms in the abstract and first claim; and (3) we use term frequency-inverse document frequencyAUTHOR: TF-IDF has been defined as 'term frequency-inverse document frequency'. Please check if correct. or mutual information to rank and select candidate terms. Secondly, we propose a new method to obtain valuable long tail term from patents. To fulfill the purpose, (1) we firstly build long tail term-common term pair as candidate set; (2) then we evaluate each candidate pair's value; and finally, (3) to demonstrate our method, we give an example on our result. This study provides a new perspective in extracting terms from free texts of patent records and also proposes a new method to obtain valuable long term to aid information analysis with massive patent texts. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY Cognitive radio (CR) can significantly alleviate the network pressure caused by the rapid development of wireless communications through allowing secondary users (SUs) to obtain spectrum resource from primary users (PUs). One key issue of CR technology is spectrum sharing, that is, how spectrum should be allocated between SUs without causing interference to PUs. In this paper, we propose a bilateral bargaining mechanism to achieve this goal between two SUs. The general network scenario with multiple SUs can be decomposed into multiple pairs of bilateral bargaining studied in this paper. The SUs have to reach a mutual satisfactory agreement on the partition of spectrum by making alternating offers to each other. We model such bargaining process as dynamic finite/infinite horizon multistage game with observed actions and fully characterize the corresponding subgame perfect equilibria. Moreover, theoretical analysis and numerical results indicate that our proposed scheme can effectively allocate spectrum resource between SUs. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY Because of the increasing energy consumption in radio access networks, a new radio access network called Cloud radio access network (C-RAN) has attracted increasing attention. In C-RAN, the distributed radio remote units (RRUs) are located in different sites and the placement of RRUs will influence the system performance. However, few researches investigate the optimal RRU placement from the perspective of energy efficiency, which is one of the most important characteristics of C-RAN. In this paper, we first derive the energy efficiency of C-RAN to achieve certain QoS requirements considering the circuitry energy consumption. Then, we obtain the optimal placement of RRUs by minimizing the consumed energy per bit. Numerical results are also presented to validate the analysis. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper examines the relationship between so-called 'Big Data', the 'Internet of Things' (the internet of People and Things,' and the internet of Everything'), and the internet of Signs.' In particular, we investigate how the 'things' in the internet of Things' generate 'Big Data', and how both are used to generate semiotic 'signs'. In addition, we analyse the importance of context in and the relationships between 'Big Data', the internet of Things', and the internet of Signs'. [ABSTRACT FROM AUTHOR]

SUMMARY Big Web companies, traditional enterprises, physical science researchers, social scientists, are all experiencing (or anticipating) unprecedented growth in the amount of data available in their domain. There are new opportunities and great untapped value in analyzing ' Big Data'.Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The article presents a call for papers dedicated to Many Faces of Distances.