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Offline network traffic analysis is very important for an in-depth study upon the understanding of network conditions and characteristics, such as user behavior and abnormal traffic. With the rapid growth of the amount of information on the Internet, the traditional stand-alone analysis tools face great challenges in storage capacity and computing efficiency, but which is the advantages for Hadoop cluster. In this paper, we designed an offline traffic analysis system based on Hadoop (OTASH), and proposed a MapReduce-based algorithm for TopN user statistics. In addition, we studied the computing performance and failure tolerance in OTASH. From the experiments we drew the conclusion that OTASH is suitable for handling large amounts of flow data, and are competent to calculate in the case of single node failure.

Taxi drivers are viewed having more driving experience, being more familiar with road traffic condition, and in turn having more rational route choice behaviors than ordinary drivers. Using floating car data (FCD) of Beijing taxi in 2010, this study discusses the influence of road network conditions and traffic status to taxi drivers route choice behaviors. First, trip information is extracted from FCD using trip-identification method; Second, map matching and K-shortest paths are used to construct the trajectories and the sets of alternate routes, and route similarity evaluation is conducted to build the sample data of route choice behavior analysis; Finally, route choice model for taxi drivers based on Multinomial Logit (MNL) Model is estimated. The result shows that taxi drivers tend to choose the route which has faster driving speed, less frequency of left turns, more proportion of express way and less proportion of minor road, and increasing a left-turn or decreasing travel speed by 2.12km/h has the same effect on route choice utility. This study is expected to be helpful to establish map-matching algorithm of FCD, route guidance scheme and traffic assignment model.

Maintaining connectivity is essential in multi-hop wireless networks since the network topology cannot be pre-determined due to mobility and environmental effects. To maintain the connectivity, a critical point in the network topology should be identified where the critical point is the link or node that partitions the network when it fails. In this paper, we propose a new critical point identification algorithm and also present numerical results that compare the critical points of the network and H-hop sub-network illustrating how effectively sub-network information can detect the network-wide critical points. Then, we propose two localized topological control resilient schemes that can be applied to both global and local H-hop sub-network critical points to improve the network connectivity and the network resilience. Numerical studies to evaluate the proposed schemes under node and link failure network conditions show that our proposed resilient schemes increase the probability of the network being connected in variety of link and node failure conditions.

In this paper, we have compared the performance of IMABN-2 and MALN-2. To compare the performance, data packets were passed via both networks in faulty and non-faulty environments. Results show that MALN-2 performs better than the IMABN-2. Cost of IMABN-2 and MALN-2 is also compared with other existing MINs.

The current view of network emergence is predominantly influenced by path-dependent mechanisms where immediately preceding network structures inform current network positions. However, less explored is the ongoing sensitivity of future network positions to the composition and structure of newcomers' first partnerships. Building on the social categorization literature, we develop a model of the ongoing direct and moderating effects of newcomers' first network partnership on their status. We test our model using a panel of 272 U.S. venture capital firms from the 1980 to 2004 period and show that the reputation of newcomers' first partners exerts a positive influence on their future status (over and above intermediate network conditions). We find that this positive influence is stronger for those newcomers whose first partners formed a cohesive network. Copyright © 2013 John Wiley & Sons, Ltd.

This paper presents a new fault sustainable interconnection network (IN) called as Irregular Augmented Shuffle Exchange Network–3 (IASEN–3) and its routing algorithm. The Performance of IASEN–3 has been evaluated and compared with existing IASEN–2. The experimental results shows that IASEN–3 is more efficient than IASEN–2 in terms of throughput and processor utilization. These results are analyzed in faulty and non–faulty network environments.

Wireless local area network (WLAN) brings us a low cost and high bandwidth experience and thus plays a critically important role in current/future networks to support high-rate transmissions. To better provide quality-of-service (QoS) for WLAN users, we in this paper propose an improved scheme called “A-EDCA” (adaptive EDCA), based on enhanced distributed channel access (EDCA) of IEEE 802.11e under the infrastructure mode. Our proposed scheme aims at efficiently adapting the transmission over WLAN to the time-varying network conditions and mitigating the competition ability unfairness between access point (AP) and non-AP stations (STAs). Specifically, all non-AP STAs adaptively modify the contention window based on the network condition. Moreover, AP skips the backoff phase by setting its backoff counter as zero when non-AP STA completes transmission successfully to relieve the unfairness. At last, simulation results demonstrate the effectiveness of the proposed approach.

In this study we define and solve the traffic statics problem in an open diverge-merge network based on a multi-commodity kinematic wave model, whose entropy conditions are given by invariant junction flux functions derived from macroscopic merging and diverging rules. In this problem, we are interested in finding stationary states on all links when origin demands, destination supplies, and route choice proportions are constant. After discussing the properties of four types of stationary states on a road link and presenting stationary entropy conditions at both the merging and diverging junctions, we derive a system of algebraic equations as necessary conditions for all 16 combinations of stationary states on the two intermediate links. Under different network conditions in road capacities, route choice proportions, and merging priorities, we analytically show that the traffic statics problem always admits stationary solutions, which, however, may not be unique. In particular, such stationary solutions exist even under network conditions when an initially empty diverge-merge network can settle in persistent periodic oscillations after a long time. In the future, we will be interested in discussing the stability property of the stationary states and studying the traffic statics problem in general networks. Analytical insights from the simpler traffic statics problems would be helpful for understanding complex traffic dynamics in a road network.

In this article, we present a novel radial visualization of IDS alerts, named IDSPlanet, which helps administrators identify false positives, analyze attack patterns, and understand evolving network conditions. Inspired by celestial bodies, IDSPlanet is composed of Chrono Rings, Alert Continents, and Interactive Core. These components correspond with temporal features of alert types, patterns of behavior in affected hosts, and correlations amongst alert types, attackers and targets. The visualization provides an informative picture for the status of the network. In addition, IDSPlanet offers different interactions and monitoring modes, which allow users to interact with high-interest individuals in detail as well as to explore overall pattern.

In this paper, we explore the issue of static routing and spectrum/IT resource assignment (RSIA) of elastic all-optical switched intra-datacenter networks (intra-DCNs) by proposing anycast- and manycast-based integer linear programming (ILP) models. The objective is to jointly optimize the DCN resources, i.e., network transmission bandwidth and IT resources, under different situations. First, for given service-request matrices with unknown network transmission bandwidth and IT resources, we propose anycast and manycast ILP models to minimize the maximum numbers of required network and IT resources to accommodate all the service requests. For anycast RSIA issue, we proposed two different ILP models that are based on node-arc and link-path methods, respectively. Node-arc based manycast ILP model is also proposed for the first time to our knowledge. Second, for given network transmission bandwidth and IT resources and known service-request matrices, we propose node-arc based anycast ILP models to maximize the total number of successfully served service requests. To evaluate the efficiency of anycast and manycast models, all proposed ILP models are evaluated and compared with unicast ILP models. Simulation results show that anycast and manycast ILP models perform much better in efficiently using DCN resources and successfully accommodating more service requests when compared to unicast ILP models under the same network conditions.

In current Internet, most of the traffic dedicated to video streaming applications. In recent years, Peer-to-Peer (P2P) streaming approach has gained more attention, due to the high cost of providing the required bandwidth for a large number of users in Client-Server model. Mesh-based peer-to-peer video streaming is a robust approach which recently employed in many multimedia networking applications. Also, these systems provide robustness against peer churn with low maintenance complexity, but these systems suffer from issues related to the overhead and sub-optimal neighbor selection. In this paper, the challenges of Video-on-Demand (VoD) streaming will be addressed to design CMPVoD, a new cluster mesh-based architecture for hybrid CDN-P2P VoD streaming with VCR functions. In the proposed architecture, peers are organized into clusters based on their playback features. So peers with more upload bandwidth in the cluster are gradually located closer to the video servers. Another interesting feature of CMPVoD is using of adaptive buffer-map exchange that reduces bandwidth overhead and increases the availability of video chunks. The performance of CMPVoD evaluated in different network conditions. The results show that CMPVoD efficiently reduces the overhead and achieves a reasonable quality of service in different network conditions.

As the attackers nowadays are getting craftier it is deemed important to have a security system which is easy to maintain and economically affordable and gives suitable defense against attacks both known and novel. In this paper, the concept of genetic programming is applied to recreate open network conditions, using records obtained from KDD Cup'99 dataset. Then the newly created records (network log headers) are assimilated in normal and attack categories using the basic fundamental of clustering i.e. intra-cluster similarity and inter-cluster dissimilarity. Finally results of two prominent partition based clustering approaches i.e. K-Means and K-Medoid are compared and evaluated.

In service function chaining (SFC), an ordered list of service functions (SFs) is specified for network services, and those SFs should be placed in appropriate service nodes (SNs) to satisfy the given service latency requirement. In this paper, we formulate an integer non-linear programming (INLP) problem for the optimal placement of SFs when the latency requirement for network services and network conditions (e.g., link latency and SN capacity) are given. Evaluation results show that the optimal placement can achieve lower latency than conventional schemes.

Nowadays, Dynamic Adaptive Streaming over HTTP (DASH) has become very popular in streaming multimedia contents. In order to offer better user experience and cope with dynamically varying network conditions, a big challenge is to estimate precisely next segment bandwidth, which is a significant premise in determining next multimedia bitrate, especially when multiple clients share the same bottleneck link. In this paper, we address an innovative mechanism to estimate the bandwidth based on MACD indicator and its two thresholds. Then, with the estimated bandwidth, we use GA to determine the next multimedia bitrate. Our simulation demonstrates that our proposed approach outperforms other existing schemes.

Adaptive transmission power control schemes have been introduced in wireless sensor networks to adjust energy consumption under different network conditions. This is a crucial goal, given the constraints under which sensor communications operate. Power reduction may however have counterproductive effects to network performance. Yet, indiscriminate power boosting may detrimentally affect interference. We are interested in understanding the conditions under which coordinated power reduction may lead to better spectrum efficiency and interference mitigation and, thus, have beneficial effects on network performance. Through simulations, we analyze the performance of sensor nodes in an environment with variable interference. Then we study the relation between transmission power and communication efficiency, particularly in the context of Adaptive and Robust Topology (ART) control, showing how appropriate power reduction can benefit both energy and spectrum efficiency. We also identify critical limitations in ART, discussing the potential of more cooperative power control approaches.

In this paper, we propose a novel congestion control framework for delay- and disruption tolerant networks (DTNs). The proposed framework, called Smart-DTN-CC, adjusts its operation automatically as a function of the dynamics of the underlying net- work. It employs reinforcement learning, a machine learning technique known to be well suited to problems in which the environment, in this case the network, plays a crucial role; yet, no prior knowledge about the target environment can be assumed, i.e., the only way to acquire information about the environment is to interact with it through continuous online learning. Smart-DTN-CC nodes get input from the environment (e.g., its buffer occupancy, set of neighbors, etc), and, based on that information, choose an action to take from a set of possible actions. Depending on an action's effectiveness in controlling congestion, it will be given a reward. Smart-DTN-CC's goal is to maximize the over- all reward which translates to minimizing congestion. To our knowledge, Smart-DTN-CC is the first DTN congestion control framework that has the ability to automatically and continuously adapt to the dynamics of the target environment. As demonstrated by our experimental evaluation, Smart-DTN- CC is able to consistently outperform existing DTN congestion control mechanisms under a wide range of network conditions and characteristics.

This paper studies the impact of leveraging both static synchronous compensator (STATCOM) and power system stabilizer (PSS) on multi-machine power systems. Considering a standard IEEE 9-bus test power network, the classic and intelligent controllers are applied and analyzed to achieve a desirable system performance. Simulated tests show the usefulness of STATCOM on network power quality in terms voltage profile. In addition, it can significantly improve the damping oscillations of synchronous generator under normal and abnormal network conditions. The PSS also contributes to improving the synchronous generator parameters. It is also observed that using intelligent controllers with STATCOM and PSS leads to a better performance relative to the classic controllers.

Complexities of smart grid and increasing share of renewable resources require development of intelligent decision-making support systems. Predictive Analysis of the power system extended several hours into near future can provide an insight into potential operational emergencies and assist in taking proactive corrective actions. The proposed prediction of network conditions takes advantage of load forecast, generation forecast, interchange schedules, dynamic line ratings, planned outages, and weather forecast. This paper presents the implementation results of look-ahead analysis for a large US electrical utility. Monitoring of projected violations and the derivatives of their trends provide enhanced monitoring capability to detect dangerous situations developing in the power system. The real-time prediction and intelligent alarming enhances situational awareness of operators in the control room.

Understanding data plane health is essential to improving Internet reliability and usability. For instance, detecting disruptions in distant networks can identify repairable connectivity problems. Currently this task is difficult and time consuming as operators have poor visibility beyond their network's border. In this paper we leverage the diversity of RIPE Atlas traceroute measurements to solve the classic problem of monitoring in-network delays and get credible delay change estimations to monitor network conditions in the wild. We demonstrate a set of complementary methods to detect network disruptions and report them in near real time. The first method detects delay changes for intermediate links in traceroutes. Second, a packet forwarding model predicts traffic paths and identifies faulty routers and links in cases of packet loss. In addition, we define an alarm score that aggregates changes into a single value per AS in order to easily monitor its sanity, reducing the effect of uninteresting alarms. Using only existing public data we monitor hundreds of thousands of link delays while adding no burden to the network. We present three cases demonstrating that the proposed methods detect real disruptions and provide valuable insights, as well as surprising findings, on the location and impact of the identified events.

Although HTTP-based video streaming can easily penetrate firewalls and profit from Web caches, the underlying TCP may introduce large delays in case of a sudden capacity loss. To avoid an interruption of the video stream in such cases we propose the Backward-Shifted Coding (BSC). Based on Scalable Video Coding (SVC), BSC adds a time-shifted layer of redundancy to the video stream such that future frames are downloaded at any instant. This pre-fetched content maintains a fluent video stream even under highly variant network conditions and leads to high Quality of Experience (QoE). We characterize this QoE gain by analyzing initial buffering time, re-buffering time and content resolution using the Ballot theorem. The probability generating functions of the playback interruption and of the initial buffering latency are provided in closed form. We further compute the quasi-stationary distribution of the video quality, in order to compute the average quality, as well as temporal variability in video quality. Employing these analytic results to optimize QoE shows interesting trade-offs and video streaming at outstanding fluency., 9 pages

There is a growing interest in video performance measurements with emphasis on user experience and several initiatives have been taken to conduct active testing of real video services. A deeper understanding of the variations in media bit rate and its influence on the performance of video playback is needed in order to design better measurements. In this paper, we analyze a dataset of YouTube videos from various genres. We show statistically that most YouTube videos can be represented sufficiently well by the first 1 to 3 minutes of the video. This eliminates the need for running longer tests when network conditions are stable as in the case of fixed networks. We test our observation in an active testing environment that measures video metrics, and recommend based on the results that such tests should run at least for one minute, however, a duration of 3 minutes will help achieve better and more stable results.

A recent trend in user-generated content production is the broadcasting of live video streams from mobile devices. A set of upload protocols have been proposed supporting the live transmission of user-generated video. Their performance depends on the environmental conditions, e.g., the mobility of users, the network conditions or the popularity of the streams. Thus, we propose a novel mobile broadcasting framework, which exchanges different uploading protocols during the runtime of the application. Our goal is to use the protocol performing best under given application requirements and environmental conditions. If the requirements or the conditions change, the system dynamically assesses whether the the protocol currently used is still the most appropriate one for streaming. In case a superior protocol is available, the system transitions to the new protocol. By leveraging such transitions for video upload protocols, we achieve a superior overall performance under changing network conditions in comparison to a single upload protocol.

Typing notification of instant messaging APPs improves user experience during online chatting. However, frequent notification leads to high energy consumption of mobile devices. In this paper, we study the trade-off between the frequency of typing notifications for user experience and communication energy saving of mobile device. We propose adaptive typing notification mechanisms, which exploit user's typing pattern and the current network conditions to adjust notification intervals. Simulation results demonstrate the proposed schemes can significantly save energy while improving user experience.

© 2016 by De Gruyter. Relationships and networks are important to how entrepreneurs create value. However, many aspects about relationships and networks remain poorly understood because their characteristics are often reduced to one-dimensional variables or dichotomous measures. This paper unpacks the concept of multiplexity and proposes a hierarchy of four different levels (social, relational, strategic, and closed). Each level is associated with a different level of dynamism which governs how rapidly entrepreneurs can alter their network. The hierarchy of multiplexity and associated levels of dynamism, have implications regarding different value creation processes that are associated with these network conditions.

A class of networked control systems called Model-Based Networked Control Systems (MB-NCSs) is considered. Stabilization of MB-NCSs is studied using feedback controls and simulation of stabilization for different feedbacks is made with the purpose to reduce the network traffic. The feedback control input is applied in a compensated model of the plant that approximates the plant dynamics and stabilizes the plant even under slow network conditions. Conditions for global exponential stabilizability and for the choosing of a feedback control input for a given constant time between the information moments of the network are derived. An optimal control problem to obtain an optimal feedback control is also presented., This work was supported by Portuguese funds through the CIDMA - Center for Research and Development in Mathematics and Applications, and the Portuguese Foundation for Science and Technology (“FCT - Fundação para a Ciência e a Tecnologia”), within project UID/MAT/04106/2013., info:eu-repo/semantics/publishedVersion

In wireless sensor networks (WSNs), each node controls its sleep to reduce energy consumption without sacrificing message latency. In this paper we apply the game theory, which is a powerful tool that explains how each individual acts for his or her own economic benefit, to analyze the optimal sleep schedule for sensor nodes. We redefine this sleep control game as a modified version of the Prisoner’s Dilemma. In the sleep control game, each node decides whether or not it wakes up for the cycle. Payoff functions of the sleep control game consider the expected traffic volume, network conditions, and the expected packet delay. According to the payoff function, each node selects the best wake-up strategy that may minimize the energy consumption and maintain the latency performance. To investigate the performance of our algorithm, we apply the sleep control game to X-MAC, which is one of the recent WSN MAC protocols. Our detailed packet level simulations confirm that the proposed algorithm can effectively reduce the energy consumption by removing unnecessary wake-up operations without loss of the latency performance.

Media production networks deal with large and predictable video transfers and streaming sessions which need to be scheduled to optimally use the limited network capacity. As the time and locality of transfers are predictable, advance bandwidth reservation results in more effective use of the underlying network. To offer reliable reservations, the incorporation of fault-tolerance related features in bandwidth reservation strategies resulting in redundancy is a necessity, but this incurs additional costs and extra performance overheads as network capacity remains unused to offer this protection. In order to mitigate these side-effects, we present an efficient event-driven runtime adaptive approach that continuously monitors the network transfers, dynamically updating the transfer schedule. This dynamic approach re-uses leftover network capacity to improve network utilization. The resulting management system offers protection from failures using resilient advance reservation, while also improving the network utilization and request admittance ratio. Our evaluation shows that the proposed approach leads to significant improvements, up to 13.9% in percentage of admitted requests in stable network conditions, compared to resilient advance reservation algorithms.

Deploying and composing Web of Things entities in scenarios where connections are subject to network constraints, like disconnected operations, intermittent connections or limited bandwidth, requires handling changing network conditions properly. Therefore, this work proposes to utilize both eventual consistent data structures and corresponding eventual consistent communication for such scenarios. This enables composition and collaboration of WoT entities in network constraint scenarios.

Failure detection is at the core of most fault tolerance strategies, but it often depends on reliable communication. We present new algorithms for failure detectors which are appropriate as components of a fault tolerance system that can be deployed in situations of adverse network conditions (such as loosely connected and administered computing grids). It packs redundancy into heartbeat messages, thereby improving on the robustness of the traditional protocols. Results from experimental tests conducted in a simulated environment with adverse network conditions show significant improvement over existing solutions.

In this work, SP frames of the extended profile of H.264 AVC video codec are utilized to obtain efficient switching for actual video streaming experiments on the Internet. An adaptive algorithm is developed and by using this algorithm, performance of SP frames is compared with that of standard I-frame switching. Detailed measurements of network conditions are given for each experiment to indicate that comparisons are carried out in fair conditions. It has been observed that, under certain conditions, SP frames can improve performance considerably whereas in the others, they may only introduce overhead. Based on this observation different GOP patterns are proposed for different video type-congestion level combinations.

In streaming media over the Internet using HTTP, it is often desirable to minimize the duration of the media segments of a stream (for example, to reduce camera-to-viewer delay in streaming a live sports event). The operational behavior of Internet transport protocols limits the minimum duration of segments below which the segments can't be transferred in time to avoid a playback stall. This paper proposes a method to calculate the minimum duration for the segments of a media stream under given network transport conditions to avoid a playback stall. This method can be used to select the segment duration for a media stream under anticipated worst-case network conditions.

Software defined networking is a new approach to networking that aims to make data networks programmable, more flexible, easier to operate and manage, and better able to respond to the changing demands of applications and network conditions. This paper presents a low cost implementation of a programmable switch using OpenFlow v1.0. It can be programmed using pox to act as a hub, l2 learning switch, a l3 learning switch or custom traffic flows can be installed by administrator

This paper describes the realization of the integration of MPEG-DASH (Dynamic Adaptive Streaming over HTTP) software stack into the Android platform. MPEG-DASH protocol includes download of multimedia content, whether it is video on demand or live program. Basic characteristic of a MPEG-DASH protocol is flexibility to network conditions, which means changing the quality of the audio and/or video content depending on the current network speed. The main goal that has been achieved through this approach is platform independent program. Application has been tested on number of links which is provided by MPEG-DASH organization. Achieved results are over 90% successfully played links from MPEG-DASH server including A/V synchronization.

It is well known that oscillations in models of biochemical reaction networks can arise as a result of a single negative cycle. On the other hand, methods for finding general network conditions for potential oscillations in large biochemical reaction networks containing many cycles are not well developed. A biochemical reaction network with any number of species is represented by a simple digraph and is modeled by an ordinary differential equation (ODE) system with non-mass action kinetics. The obtained graph-theoretic condition generalizes the negative cycle condition for oscillations in ODE models to the existence of a pair of subnetworks, where each subnetwork contains an even number of positive cycles. The technique is illustrated with a model of genetic regulation.

The gradual hybrid anti-worm (GHAW) was presented. It changed its confrontation scheme in real time according to the percentage of vulnerable hosts present in the network. For GHAW, its process of countering malicious internet worms was modeled. The performance of GHAW on two factors was also estimated: confronting validity against worms and consumption of network resources. Factors governing its performance, specifically the transformation threshold and the transformation rate, were analyzed. The simulation experiments show that GHAW has dynamical adaptability to changes of network conditions and offers the same level of effectiveness on confronting internet worms as the divide-and-rule hybrid anti-worm, with significantly less cost to network resources. The experiments also indicate that the transformation threshold is the key factor affecting the performance of GHAW.

Distributed denial-of-service (DDoS) attacks present an increasing threat to the global inter-networking infrastructure. While entropy schemes are highly robust to diverse network conditions, they remain vulnerable to distribute attacks that are similar to legitimate traffic. With the knowledge that the objective of a DDoS attack is to saturate as soon as possible the resources of the target, this would engender an unexpected disproportion between the number of received packets and the number of connections. However, in the case of flash crowds, an increase in the number of packets is always accompanied by an increase in the number of connections. In this work, we used joint-entropy that quantifies the degree of disproportion to detect traffic anomalies. We investigate a class of intelligent attacks, which, unlike high-rate attacks, are difficult for entropy schemes to detect. The experimental results indicate that our joint-entropy scheme can detect this type of attacks accurately. Compared with an entropy-based scheme, the improvement is 40% for the distributed attacks. Copyright © 2011 John Wiley & Sons, Ltd. (Distributed denial-of-service (DDoS) attacks present an increasing threat to the global inter-networking infrastructure. While entropy schemes are highly robust to diverse network conditions, they remain vulnerable to distribute attacks that are similar to legitimate traffic. With the knowledge that the objective of a DDoS attack is to saturate as soon as possible the resources of the target, this would engender an unexpected disproportion between the number of received packets and the number of connections.)

An accurate and reliable performance of a state estimation under all network conditions is crucial for the monitoring of power systems and thus their secure operation. State estimation is based on a static representation of the power system, although the most critical operation conditions occur when power system is in dynamic transition from one state to another.

This paper presents a new solution, which adds a new database server on an existing Oracle Multimaster Data replication system with Online Instantiation method. During this time the system is down, because we cannot execute DML statements on replication objects but we can only make queries. The time for adding the new database server depends on the number of objects, on the replication group and on the network conditions. We propose to add a new layer between replication objects and the database sessions, which contain DML statements. The layer eliminates the system down time exploiting our developed packages. The packages will be active only during the addition of a new site process and will modify all DML statements and queries based on replication objects., Comment: 9 pages, 4 figures, in International Journal of Database Management Systems (IJDMS) (2011)

Recently, several researches have suggested an application of formal methods for identifying configuration errors, unveiling design problems and predicting network behavior. In this paper, we contribute to this research area by defining a method able to efficiently check reachability properties in dynamically routed networks. We define a notion of network state that captures different network conditions. Each network state represents a unique combination of link availability. The naive enumeration of network states leads quickly to intractability even for small networks as the number of possible combinations grows exponentially. Instead, we enumerate all available paths and, for each path, we search for state aggregation, in which this path is active.

In this paper, we formulate an analytical model to characterize the spread of malware in decentralized, Gnutella type peer-to-peer (P2P) networks and study the dynamics associated with the spread of malware. Using a compartmental model, we derive the system parameters or network conditions under which the P2P network may reach a malware free equilibrium. The model also evaluates the effect of control strategies like node quarantine on stifling the spread of malware. The model is then extended to consider the impact of P2P networks on the malware spread in networks of smart cell phones.

The HTS cable demonstration project, called the Yokohama Project, supported by Ministry of Economy, Trade and Industry and the New Energy and Industrial Technology Development Organization, was initiated in Japan in 2007. The aim of this project is to operate a 66 kV, 200 MVA high-temperature superconducting (HTS) cable in a network of the Tokyo Electric Power Company to demonstrate cable reliability and stable operation. Total project period was changed from 5 years to 6 years. Chosen as the demonstration site was the Asahi substation in Yokohama. Based on the analysis of the network conditions of the demonstration site, specifications of the HTS cable system were determined. Element technologies were developed and various preliminary tests using short core samples were conducted to confirm the HTS cable design. A 30-meter HTS cable system was manufactured and tested prior to initial demonstration tests. Long-term demonstration tests of the HTS cable system in an actual grid at the Asahi substation are scheduled to be started in 2011.

The frequency of adjustments to the supply temperature set-point in district heating networks influences the overall operating cost in two ways: adaptability to changes in network conditions; and availability of time for determining an appropriate response. In this paper we investigate this trade-off and show that operating costs can be reduced through appropriate control period selection. Eleven hypothetical scenarios spanning five different networks have been simulated under a variety of control policies. When compared to a constant supply temperature strategy, the best policy in each case achieved a loss reduction of 5–24%.

A successful P2P live streaming system must achieve high uploading bandwidth utilization, fast stream distribution, uniform bandwidth distribution among participating peers, flexibility and adaptation to the underlying network conditions and peer behavior. This paper proposes a novel architecture that meets these requirements. By the use of distributed optimization algorithms we propose a dynamically reconfigurable overlay architecture that organizes its peers according to network locality information and heterogeneous uploading capabilities of them. The benefits of our optimized overlay are fully exploited by our proposed scheduler, which guarantees the complete and fast distribution of the stream. The evaluation of our system under a series of scenarios that take into account the all requirements above reveals the advantages of our proposed system.

Efficient delivery under changing network conditions is a major challenge in the design of live streaming systems. This study analyzes the key considerations and factors influencing live stream quality during system operations, and attempts to improve current P2P (peer-to-peer) live streaming systems by allowing users to enjoy high quality of service under the limitations of network resources. The proposed R-D (rate-distortion) optimized dynamic nodes join algorithm is based on multipath streaming concept and receiver-driven approach. This distributed algorithm enables the system to evaluate the current network status in order to optimize the end-to-end distortion of P2P networks. Experimental results of this study demonstrate the effectiveness of the proposed approach.

This paper studies how to generate the reasonable information of travelers' decision in real network. This problem is very complex because the travelers' decision is constrained by different human behavior. The network conditions can be predicted by using the advanced dynamic OD (Origin-Destination, OD) estimation techniques. Based on the improved mesoscopic traffic model, the predictable dynamic traffic guidance information can be obtained accurately. A consistency algorithm is designed to investigate the travelers' decision by simulating the dynamic response to guidance information. The simulation results show that the proposed method can provide the best guidance information. Further, a case study is conducted to verify the theoretical results and to draw managerial insights into the potential of dynamic guidance strategy in improving traffic performance.

The modeling of track circuit (TC) signaling systems is considered to be a valuable tool for their validation (check of operation for exceptional and extreme network conditions and configurations), compatibility assessment (with respect to sources of conducted interference), and pretuning (before on-site tuning). The model can replace a series of preliminary measurements and speed up the on-site tuning procedure. The results of model verification and validation on the Torino-Novara trunk of the Italian High Speed Railway Line are presented. The accuracy and reliability are quite good from an absolute viewpoint and are compared with the traditional on-site TC tuning; the time saving is of an order of magnitude.

The promotion of electricity generation from renewable energy sources (RES) and combined heat and power (CHP) has resulted in increasing penetration levels of distributed generation (DG). However, large-scale connection of DG involves profound changes in the operation and planning of electricity distribution networks. Distribution System Operators (DSOs) play a key role since these agents have to provide flexibility to their networks in order to integrate DG. Article 14.7 of EU Electricity Directive states that DSOs should consider DG as an alternative to new network investments. This is a challenging task, particularly under the current regulatory framework where DSOs must be legally and functionally unbundled from other activities in the electricity sector. This paper proposes a market mechanism, referred to as reliability options for distributed generation (RODG), which provides DSOs with an alternative to the investment in new distribution facilities. The mechanism proposed allocates the firm capacity required to DG embedded in the distribution network through a competitive auction. Additionally, RODG make DG partly responsible for reliability and provide DG with incentives for a more efficient operation taking into account the network conditions.

Recently, the popularity of the internet of things technology has highlighted the importance of performance for gathering data over multi-hop wireless sensor nodes. Data obtained from the sensor nodes is used by individual as well as multiple users. Therefore, a data-centric communication strategy is ideal for efficient data gathering and delivery. This paper proposes the implementation of a new data-centric communication strategy based on the named data network (NDN) to wireless sensor network (WSN) for achieving efficient communication performance. We discuss the modification of the NDN, which is originally developed for a wired network, for achieving better communication performance even in wireless communication networks. Specifically, we discuss the methods for constructing the reverse path of the required contents and for selecting the adequate next hop relay node of the forwarding interest. We propose new methods considering the broadcast nature of the wireless channels. Using computer simulations, we confirm that our proposed methods reduce the redundant transmissions by selecting a proper route based on network conditions.

In this work, we experimentally study how behaviour of the PESQ predictions varies with reference signal characteristic. In particular we investigate the impact of different Active-Speech-Ratios on speech quality prediction in simulated VoIP environment from objective and subjective testing point of view. This reference signal characteristic is defined very broadly by ITU-T Recommendation P.862.3. That is the reason to investigate an impact of this characteristic on speech quality prediction more in-depth. We assess the variability of PESQ's predictions with respect to Active-Speech-Ratio and network conditions, as well as their accuracy, by comparing the predictions with subjective assessments.