Bursty Nature Research Articles

Rate-Based End-to End Closed Loop Control for ABR Traffic Management

ATM has one common feature which guarantees its success, namely the possibility to transport any ATM service, irrespective of its characteristics such as the bit rate, its quality requirements or its bursty nature. ATM also has high flexibility in allocate the bandwidth, and thus allows more calls to enter the network. Unfortunately, this advantage has a negative consequences. ATM presents congestion problems in the network as well as in the end terminals. This research describes about congestion control mechanism that will be applied for Available Bit Rate (ABR) Service in ATM networks, namely, the Rate-Based Congestion Control Scheme. This method supports end-to-end closed-loop control and has been indentified as the most appropriate for the support of this service by ATM Forum. ABR Service is a new ATM Service category. This kind of service automatically and dynamically allocates the available bandwidth to users by controlling the traffic flow based on feedback information. The source increases or decreases the source rate of cells transmission based on the information in the feedback Resource Management (RM) cell it receives. This method minimizes the duties of intermediate nodes and the destination node, so it is expected the source will receive the feedback information faster.

An SDN Architecture for Privacy-Friendly Network-Assisted DASH

Dynamic Adaptive Streaming over HTTP (DASH) is the premier technology for Internet video streaming. DASH efficiently uses existing HTTP-based delivery infrastructures implementing adaptive streaming. However, DASH traffic is bursty in nature. This causes performance problems when DASH players share a network connection or in networks with heavy background traffic. The result is unstable and lower quality video. In this article, we present the design and implementation of a so-called DASH Assisting Network Element (DANE). Our system provides target bitrate signaling and dynamic traffic control. These two mechanisms realize proper bandwidth sharing among clients. Our system is privacy friendly and fully supports encrypted video streams. Trying to improve the streaming experience for users who share a network connection, our system increases the video bitrate and reduces the number of quality switches. We show this through evaluations in our Wi-Fi testbed.

Burstiness and tie activation strategies in time-varying social networks

The recent developments in the field of social networks shifted the focus from static to dynamical representations, calling for new methods for their analysis and modelling. Observations in real social systems identified two main mechanisms that play a primary role in networks’ evolution and influence ongoing spreading processes: the strategies individuals adopt when selecting between new or old social ties, and the bursty nature of the social activity setting the pace of these choices. We introduce a time-varying network model accounting both for ties selection and burstiness and we analytically study its phase diagram. The interplay of the two effects is non trivial and, interestingly, the effects of burstiness might be suppressed in regimes where individuals exhibit a strong preference towards previously activated ties. The results are tested against numerical simulations and compared with two empirical datasets with very good agreement. Consequently, the framework provides a principled method to classify the temporal features of real networks, and thus yields new insights to elucidate the effects of social dynamics on spreading processes.

BlackOut: Enabling fine-grained power gating of buffers in Network-on-Chip routers

The Network-on-Chip (NoC) router buffers play an instrumental role in the performance of both the interconnection fabric and the entire multi-/many-core system. Nevertheless, the buffers also constitute the major leakage power consumers in NoC implementations. Traditionally, they are designed to accommodate worst-case traffic scenarios, so they tend to remain idle, or under-utilized, for extended periods of time. The under-utilization of these valuable resources is exemplified when one profiles real application workloads; the generated traffic is bursty in nature, whereby high traffic periods are sporadic and infrequent, in general. The mitigation of the leakage power consumption of NoC buffers via power gating has been explored in the literature, both at coarse (router-level) and fine (buffer-level) granularities. However, power gating at the router granularity is suitable only for low and medium traffic conditions, where the routers have enough opportunities to be powered down. Under high traffic, the sleeping potential rapidly diminishes. Moreover, disabling an entire router greatly affects the NoC functionality and the network connectivity. This article presents BlackOut, a fine-grained power-gating methodology targeting individual router buffers. The goal is to minimize leakage power consumption, without adversely impacting the system performance. The proposed framework is agnostic of the routing algorithm and the network topology, and it is applicable to any router micro-architecture. Evaluation results obtained using both synthetic traffic patterns and real applications in 64-core systems indicate energy savings of up to 70%, as compared to a baseline NoC, with a near-negligible performance overhead of around 2%. BlackOut is also shown to significantly outperform–by 35%, on average–two current state-of-the-art power-gating solutions, in terms of energy savings.

EDUCATION FOR HEALTH SOCIETY: INDICATORS OF BURSTINESS IN RESEARCH

Background: Education for health society attracts more and more research efforts as it facilitates the quality of society’s life. However, research on education for health society is of bursty nature. The phenomenon of burstiness is of particular research interest as it influences the flow of a number of processes including research and the quality of society’s life in general. Research question : What are indicators of burstiness in research? Approach: Interdisciplinary research was applied to the study of the meaning of the key concepts of burstiness, criteria, indicators and research . Moreover, the analysis demonstrates how the key concepts are related to the idea of education for health society and shows how the steps of the process are related following a logical chain: theoretical framework → empirical study → conclusions. Experiment: Qualitative study was applied for empirical analysis. The empirical study was carried out in February 2016. Conclusion: The theoretical findings on the inter-relationship between burstiness and gap processes allow determining the indicators of burstiness of research. The empirical findings of the research allow drawing the conclusions on a high level of research burstiness. A newly formulated research question is presented. Further research directions are proposed. KEY WORDS: Research, burstiness, criteria, indicators, interdisciplinary research. DOI: http://dx.doi.org/ 10.15181//atee.v1i0.1315

Aging and percolation dynamics in a Non-Poissonian temporal network model.

We present an exhaustive mathematical analysis of the recently proposed Non-Poissonian Activity Driven (NoPAD) model [Moinet et al., Phys. Rev. Lett. 114, 108701 (2015)PRLTAO0031-900710.1103/PhysRevLett.114.108701], a temporal network model incorporating the empirically observed bursty nature of social interactions. We focus on the aging effects emerging from the non-Poissonian dynamics of link activation, and on their effects on the topological properties of time-integrated networks, such as the degree distribution. Analytic expressions for the degree distribution of integrated networks as a function of time are derived, exploring both limits of vanishing and strong aging. We also address the percolation process occurring on these temporal networks, by computing the threshold for the emergence of a giant connected component, highlighting the aging dependence. Our analytic predictions are checked by means of extensive numerical simulations of the NoPAD model.

QUASI-PERIODIC PULSATIONS DURING THE IMPULSIVE AND DECAY PHASES OF AN X-CLASS FLARE

ABSTRACT Quasi-periodic pulsations (QPPs) are often observed in X-ray emission from solar flares. To date, it is unclear what their physical origins are. Here, we present a multi-instrument investigation of the nature of QPP during the impulsive and decay phases of the X1.0 flare of 2013 October 28. We focus on the character of the fine structure pulsations evident in the soft X-ray (SXR) time derivatives and compare this variability with structure across multiple wavelengths including hard X-ray and microwave emission. We find that during the impulsive phase of the flare, high correlations between pulsations in the thermal and non-thermal emissions are seen. A characteristic timescale of ∼20 s is observed in all channels and a second timescale of ∼55 s is observed in the non-thermal emissions. SXR pulsations are seen to persist into the decay phase of this flare, up to 20 minutes after the non-thermal emission has ceased. We find that these decay phase thermal pulsations have very small amplitude and show an increase in characteristic timescale from ∼40 s up to ∼70 s. We interpret the bursty nature of the co-existing multi-wavelength QPPs during the impulsive phase in terms of episodic particle acceleration and plasma heating. The persistent thermal decay phase QPPs are most likely connected with compressive magnetohydrodynamic processes in the post-flare loops such as the fast sausage mode or the vertical kink mode.

Optimizing the data-collection time of a large-scale data-acquisition system through a simulation framework

The ATLAS detector at CERN records particle collision “events” delivered by the Large Hadron Collider. Its data-acquisition system identifies, selects, and stores interesting events in near real-time, with an aggregate throughput of several 10 GB/s. It is a distributed software system executed on a farm of roughly 2000 commodity worker nodes communicating via TCP/IP on an Ethernet network. Event data fragments are received from the many detector readout channels and are buffered, collected together, analyzed and either stored permanently or discarded. This system, and data-acquisition systems in general, are sensitive to the latency of the data transfer from the readout buffers to the worker nodes. Challenges affecting this transfer include the many-to-one communication pattern and the inherently bursty nature of the traffic. The main performance issues brought about by this workload are addressed in this paper, focusing in particular on the so-called TCP incast pathology. Since performing systematic studies of these issues is often impeded by operational constraints related to the mission-critical nature of these systems, we developed a simulation model of the ATLAS data-acquisition system. The resulting simulation tool is based on the well-established, widely-used OMNeT++ framework. This tool was successfully validated by comparing the obtained simulation results with existing measurements of the system’s behavior. Furthermore, the simulation tool enables the study of the theoretical behavior of the system in numerous what-if scenarios and with modifications that are not immediately applicable to the real system. In this paper, we take advantage of this to analyze the behavior of the system using different traffic shaping and scheduling policies, and with network hardware modifications. This analysis leads to conclusions that could be used to devise future system enhancements.

Aging Aware Random Channel Access for Battery-Powered Wireless Networks

Energy harvesting is becoming a key technology in mobile wireless networks, and especially sensor systems. The bursty nature of energy arrival generated by renewable resources may apply considerable stress to the battery, and degrade its state of health (SoH) by generating deep charging and discharging cycles. In this letter, a novel random channel access scheme is proposed that tunes transmission parameters to reduce SoH degradation while preserving the network performance.

Raman–Brillouin interplay for inertial confinement fusion relevant laser–plasma interaction

The co-existence of the Raman and Brillouin backscattering instability is an important issue for inertial confinement fusion. The present paper presents extensive one-dimensional (1D) particle-in-cell (PIC) simulations for a wide range of parameters extending and complementing previous findings. PIC simulations show that the scenario of reflectivity evolution and saturation is very sensitive to the temperatures, intensities, size of plasma and boundary conditions employed. The Langmuir decay instability is observed for rather small $k_{epw}{\it\lambda}_{D}$ but has no influence on the saturation of Brillouin backscattering, although there is a clear correlation of Langmuir decay instability modes and ion-fractional decay for certain parameter ranges. Raman backscattering appears at any intensity and temperature but is only a transient phenomenon. In several configurations forward as well as backward Raman scattering is observed. For the intensities considered, $I{\it\lambda}_{o}^{2}$ above $10^{15}~\text{W}~{\rm\mu}\text{m}^{2}/\text{cm}^{2}$ , Raman is always of bursty nature. A particular setup allows the simulation of multi-speckle aspects in which case it is found that Raman is self-limiting due to strong modifications of the distribution function. Kinetic effects are of prime importance for Raman backscattering at high temperatures. No unique scenario for the saturation of Raman scattering or Raman–Brillouin competition does exist. The main effect in the considered parameter range is pump depletion because of large Brillouin backscattering. However, in the low $k_{epw}{\it\lambda}_{D}$ regime the presence of ion-acoustic waves due to the Langmuir decay instability from the Raman created electron plasma waves can seed the ion-fractional decay and affect the Brillouin saturation.

CPB: a classification-based approach for burst time prediction in cascades

Studying the bursty nature of cascades in social media is practically important in many real applications such as product sales prediction, disaster relief, and stock market prediction. Although both the cascade size prediction and the burst patterns of the cascades have been extensively studied, how to predict when a burst will come remains an open problem. It is challenging for traditional time-series-based models such as regression models to address this task directly. Firstly, times-series-based prediction models focus on predicting the future values based on previously observed ones. It is hard to apply them to predict the time of a bursts with the "quick rise-and-fall" pattern. Secondly, besides the cascade popularity, a lot of other side information like user profile and social relation are available in social media. Although the potential utility of such information can be high, it is also hard for time-series-based models to capture and integrate these rich information with diverse formats seamlessly. This paper proposes a classification-based approach for burst time prediction by exploiting rich knowledge in information diffusion. Particularly, we first propose a time-window-based transformation to predict in which time window the burst will appear. By dividing the time spans of all the cascades into the same number of time windows K, the cascades with diverse time spans can thus be handled uniformly. To exploit the rich and heterogenous information in social media, we next propose a scale-independent feature extraction framework to model the heterogenous knowledge in a scale-independent manner. Systematical evaluations are conducted on the Sina Weibo reposting dataset and MemeTracker dataset. Besides the superior performance of the proposed approach, we also observe that: (1) surprisingly, social/structure knowledge is more indicative of the bursts than the cascade popularity information, especially for the bursts occurring in a farther future. (2) Larger cascades are harder to predict as the spreading process of the cascades with higher popularity is usually more diverse and fluctuant. (3) The proposed approach is robust in the sense that the result is not much sensitive to the popularity of the training cascades.

Toward Automated Testing of Geo-Distributed Replica Selection Algorithms

Many geo-distributed systems rely on a replica selection algorithms to communicate with the closest set of replicas. Unfortunately, the bursty nature of the Internet traffic and ever changing network conditions present a problem in identifying the best choices of replicas. Suboptimal replica choices result in increased response latency and reduced system performance. In this work we present GeoPerf, a tool that tries to automate testing of geo-distributed replica selection algorithms. We used GeoPerf to test Cassandra and MongoDB, two popular data stores, and found bugs in each of these systems.

IP packet interleaving for UDP bursty losses

The bursty nature of losses over the Internet is constantly asking for effective solutions. In this work, we use a comprehensive approach to study packet interleaving for coping with loss burstiness. Our aim is to assess if and how packet interleaving can be employed in real networks at the IP layer and what benefits real UDP-based applications may expect. Through an analytical study we determine the interleaving configuration to be used as a function of the loss characteristics. Then, in simulation we confirm these findings and highlight also potential counter effects. Afterwards, we design and develop a real application for packet interleaving. We move a step ahead towards real networks using a testbed that comprises an emulated WAN. Thanks to it, we study and solve a number of issues arising in real environments such as network dynamics and interleaving performance. Finally, we deploy the packet interleaver in the wild and we study the improvements achievable in general and by a real application. Our work shows that providing benefits to real applications is not an easy task. However, our packet interleaver can effectively decorrelate losses at the IP layer in real networks and highly increase real application performance, for example, video distortion can be reduced 65%.

M2M Challenges and Opportunities in 4G

4G technology includes a profile for M2M communications in order to improve the efficiency of the foreseeable connection of hundreds of devices to the broadband wireless networks. These devices impose different requirements to those of human communications, most significantly their bursty nature and the small payload usually associated with each transmission. Due to this, typical signalling procedures overload the network causing a very low efficiency for these communications. This paper is a review of current literature, commenting on challenges that LTE technology must overcome to be a true opportunity for M2M devices.

A Novel Traffic Rate Measurement Algorithm for Quality of Experience-Aware Video Admission Control

With the inevitable dominance of video traffic on the Internet, providing perceptually good video quality is becoming a challenging task. This is partly due to the bursty nature of video traffic, changing network conditions and limitations of network transport protocols. This growth of video traffic has made Quality of Experience (QoE) of the end user the focus of the research community. In contrast, Internet service providers are concerned about maximizing revenue by accepting as many sessions as possible, as long as customers remain satisfied. However, there is still no entirely satisfactory admission algorithm for flows with variable rate. The trade-off between the number of sessions and perceived QoE can be optimized by exploiting the bursty nature of video traffic. This paper proposes a novel algorithm to determine the upper limit of the aggregate video rate that can exceed the available bandwidth without degrading the QoE of accepted video sessions. A parameter $\beta$ that defines the exceedable limit is defined. The proposed algorithm results in accepting more sessions without compromising the QoE of on-going video sessions. Thus it contributes to the optimization of the QoE-Session trade-off in support of the expected growth of video traffic on the Internet.

The role of feedback in accretion on low-luminosity AGN: Sgr A* case study

We present numerical models of the gas dynamics in the inner parsec of the Galactic centre. We follow the gas from its origin as stellar winds of several observed young massive stars, until it is either captured by the central black hole, or leaves the system. Unlike our previous models, we include an outflow from the inner accretion flow. Two different kinds of outflows are modelled: (i) an instantaneous-response feedback mode, in which the outflow rate is directly proportional to the current black hole gas capture rate; and (ii) an outburst mode, which is stronger but lasts for a limited time. The latter situation may be particularly relevant to Sgr A*, since there is evidence that Sgr A* was much brighter in the recent past. We find that both types of outflow perturb the gas dynamics near the Bondi radius and the black hole capture rate significantly. The effects persist longer than the outflow itself. We also compare the effects of spherically symmetric and collimated outflows, and find that the latter are far less efficient in transferring its energy to the surrounding gas near the capture radius. Our results imply that accretion feedback is important for non-radiative accretion flows not only within but also outside the capture radius. Steady-state Bondi accretion rate estimates that do not account for feedback outflows over-predict not only the accretion rate onto the black hole but also the capture rate at the Bondi radius itself. Finally, the steady-state assumption under which non-radiative flows have been routinely studied in the literature may have to be abandoned if accretion feedback is bursty in nature.

Assessing Capabilities of Commercial WiMAX Networks for Deliverling Real-Time Surveillance Video Traffic in Uplink

Abstract Streaming video in uplink is an interesting opportunity for network operators for capitalizing unused part of bandwidth (due to Internet asymmetry). The uplink seems not optimized nowadays due to lack of business cases. The main challenge however is bursty and unpredictable nature of wireless channel observed especially as mobility comes into play in current broadband networks. That is why in this paper, we have approached the diagnosis of commercial mobile WiMAX network towards the capabilities of assuring real-time video in uplink direction. We present results of drive tests showing that delay in WiMAX networks for LOS-NLOS (Line of sight - No n line of sight) mobile conditions is largely contributed by uplink direction (60-90% of RTT (Round trip time)) whereas downlink directions hardly ever exceeds 40ms. We show that enabling MIMO-A(Multiple Input Multiple Output) can decrease delays by 100ms in NLOS conditions and decrease delay variation by up to 90%. For each of tests we have presented exact probabilities of particular modulations involved based on channel realizations.

Burst Time Prediction in Cascades

Studying the bursty nature of cascades in social media is practically important in many applications such as product sales prediction, disaster relief, and stock market prediction. Although the cascade volume prediction has been extensively studied, how to predict when a burst will come remains an open problem. It is challenging to predict the time of the burst due to the ``quick rise and fall'' pattern and the diverse time spans of the cascades. To this end, this paper proposes a classification based approach for burst time prediction by utilizing and modeling rich knowledge in information diffusion. Particularly, we first propose a time window based approach to predict in which time window the burst will appear. This paves the way to transform the time prediction task to a classification problem. To address the challenge that the original time series data of the cascade popularity only are not sufficient for predicting cascades with diverse magnitudes and time spans, we explore rich information diffusion related knowledge and model them in a scale-independent manner. Extensive experiments on a Sina Weibo reposting dataset demonstrate the superior performance of the proposed approach in accurately predicting the burst time of posts.

Impact of device unavailability on the reliability of multicast transport in IEEE 802.11 networks

Multicast transport is an efficient solution to deliver the same content simultaneously to many receivers. This transport mode is mainly used these days to deliver real-time video streams. However, multicast transmissions support over IEEE 802.11 networks does not provide any feedback policies, which implies a definite loss of missing packets. This impacts the reliability of the multicast transport and the application employing it. An alternative to improve the reliability of multicast streaming over 802.11 networks is to prevent packet losses. In this perspective, it is necessary to identify the loss causes and to perform the required prevention actions. It is well known that collisions and path loss are two fundamental sources of transmission failures. Their impact can be eliminated by means of collision prevention and data rate adaptation. However, several works show that the loss rate of multicast packets may be considerable even in collisions-free environments and using an appropriate transmission rate. Particularly they show that losses may have a bursty nature which does not correspond to the bit error rate model of the PHY layer as defined by the chipset manufacturers. Therefore, in this paper, we carry out a thorough investigation of the loss causes in wireless networks. We show that device unavailability may be the principal cause of the significant packet losses that occur and their bursty nature. Particularly, our results show that the CPU overload may incur a loss rate of 100%, and that the delivery ratio may be limited to 35% when the device is in the power save mode.

A Cross-Layer Optimized Scheme and Its Application in Mobile Multimedia Networks With Q<roman>o</roman>S Provision

To cope with the rapid growth of multimedia applications that requires dynamic levels of quality of service (QoS), cross-layer (CL) design, where multiple protocol layers are jointly combined, has been considered to provide diverse QoS provisions for mobile multimedia networks. However, there is a lack of a general mathematical framework to model such CL scheme in wireless networks with different types of multimedia classes. In this paper, to overcome this shortcoming, we therefore propose a novel CL design for integrated real-time/non-real-time traffic with strict preemptive priority via a finite-state Markov chain. The main strategy of the CL scheme is to design a Markov model by explicitly including adaptive modulation and coding at the physical layer, queuing at the data link layer, and the bursty nature of multimedia traffic classes at the application layer. Utilizing this Markov model, several important performance metrics in terms of packet loss rate, delay, and throughput are examined. In addition, our proposed framework is exploited in various multimedia applications, for example, the end-to-end real-time video streaming and CL optimization, which require the priority-based QoS adaptation for different applications. More importantly, the CL framework reveals important guidelines as to optimize the network performance.