The origin of bursts and heavy tails in human dynamics

The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behavior into a central question of modern science. Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes. In contrast, there is increasing evidence that the timing of many human activities, ranging from communication to entertainment and work patterns, follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity. Here we show that the bursty nature of human behavior is a consequence of a decision based queuing process: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, most tasks being rapidly executed, while a few experience very long waiting times. In contrast, priority blind execution is well approximated by uniform interevent statistics. These findings have important implications from resource management to service allocation in both communications and retail.Comment: Supplementary Material available at http://www.nd.edu/~network

Performance modelling of a multiple threshold RED mechanism for bursty and correlated Internet traffic with MMPP arrival process

Access to the large web content hosted all over the world by users of the Internet engage many hosts, routers/switches and faster links. They challenge the internet backbone to operate at its capacity to assure e±cient content access. This may result in congestion and raises concerns over various Quality of Service (QoS) issues like high delays, high packet loss and low throughput of the system for various Internet applications. Thus, there is a need to develop effective congestion control mechanisms in order to meet various Quality of Service (QoS) related performance parameters. In this paper, our emphasis is on the Active Queue Management (AQM) mechanisms, particularly Random Early Detection (RED). We propose a threshold based novel analytical model based on standard RED mechanism. Various numerical examples are presented for Internet traffic scenarios containing both the burstiness and correlation properties of the network traffic

Adaptive TTL-Based Caching for Content Delivery

Content Delivery Networks (CDNs) deliver a majority of the user-requested content on the Internet, including web pages, videos, and software downloads. A CDN server caches and serves the content requested by users. Designing caching algorithms that automatically adapt to the heterogeneity, burstiness, and non-stationary nature of real-world content requests is a major challenge and is the focus of our work. While there is much work on caching algorithms for stationary request traffic, the work on non-stationary request traffic is very limited. Consequently, most prior models are inaccurate for production CDN traffic that is non-stationary. We propose two TTL-based caching algorithms and provide provable guarantees for content request traffic that is bursty and non-stationary. The first algorithm called d-TTL dynamically adapts a TTL parameter using a stochastic approximation approach. Given a feasible target hit rate, we show that the hit rate of d-TTL converges to its target value for a general class of bursty traffic that allows Markov dependence over time and non-stationary arrivals. The second algorithm called f-TTL uses two caches, each with its own TTL. The first-level cache adaptively filters out non-stationary traffic, while the second-level cache stores frequently-accessed stationary traffic. Given feasible targets for both the hit rate and the expected cache size, f-TTL asymptotically achieves both targets. We implement d-TTL and f-TTL and evaluate both algorithms using an extensive nine-day trace consisting of 500 million requests from a production CDN server. We show that both d-TTL and f-TTL converge to their hit rate targets with an error of about 1.3%. But, f-TTL requires a significantly smaller cache size than d-TTL to achieve the same hit rate, since it effectively filters out the non-stationary traffic for rarely-accessed objects

Analysis of Buffer Starvation with Application to Objective QoE Optimization of Streaming Services

Our purpose in this paper is to characterize buffer starvations for streaming services. The buffer is modeled as an M/M/1 queue, plus the consideration of bursty arrivals. When the buffer is empty, the service restarts after a certain amount of packets are \emph{prefetched}. With this goal, we propose two approaches to obtain the \emph{exact distribution} of the number of buffer starvations, one of which is based on \emph{Ballot theorem}, and the other uses recursive equations. The Ballot theorem approach gives an explicit result. We extend this approach to the scenario with a constant playback rate using T\`{a}kacs Ballot theorem. The recursive approach, though not offering an explicit result, can obtain the distribution of starvations with non-independent and identically distributed (i.i.d.) arrival process in which an ON/OFF bursty arrival process is considered in this work. We further compute the starvation probability as a function of the amount of prefetched packets for a large number of files via a fluid analysis. Among many potential applications of starvation analysis, we show how to apply it to optimize the objective quality of experience (QoE) of media streaming, by exploiting the tradeoff between startup/rebuffering delay and starvations.Comment: 9 pages, 7 figures; IEEE Infocom 201

Optimal mobility-aware admission control in content delivery networks

This paper addresses the problem of mobility management in Content Delivery Networks (CDN). We introduce a CDN architecture where admission control is performed at mobility aware access routers. We formulate a Markov Modulated Poisson Decision Process for access control that captures the bursty nature of data and packetized traffic together with the heterogeneity of multimedia services. The optimization of performance parameters, like the blocking probabilities and the overall utilization, is conducted and the structural properties of the optimal solutions are also studied. Heuristics are proposed to encompass the computational difficulties of the optimal solution when several classes of multimedia traffic are considered

Performance analysis of MANET routing protocols in the presence of self-similar traffic

A number of measurement studies have convincingly demonstrated that network traffic can exhibit a noticeable self-similar nature, which has a considerable impact on queuing performance. However, many routing protocols developed for MANETs over the past few years have been primarily designed and analyzed under the assumptions of either CBR or Poisson traffic models, which are inherently unable to capture traffic self-similarity. It is crucial to re-examine the performance properties of MANETs in the context of more realistic traffic models before practical implementation show their potential performance limitations. In an effort towards this end, this paper evaluates the performance of three well-known and widely investigated MANET routing protocols, notably DSR, AODV and OLSR, in the presence of the bursty self-similar traffic. Different performance aspects are investigated including, delivery ratio, routing overhead, throughput and end-to-end delay. Our simulation results indicate that DSR routing protocol performs well with bursty traffic models compared to AODV and OLSR in terms of delivery ratio, throughput and end-to-end delay. On the other hand, OLSR performed poorly in the presence of self-similar traffic at high mobility especially in terms of data packet delivery ratio, routing overhead and delay. As for AODV routing protocol, the results show an average performance, yet a remarkably low and stable end-to-end delay

User behaviour modelling for resource management in a hybrid UMTS/DVB-T network

Third generation mobile networks such as UMTS are designed to enhance the deployment of multimedia services providing high data rates and new flexible communication capabilities. However, these systems are interference limited and as such their performance is lowered in the case of a large number of users generating heavy traffic. A solution to this problem is to interconnect the UMTS network to a Digital Video Broadcasting-Terrestrial (DVB-T) network, so that the lack of capacity of UMTS during busy periods can be offset by the high bit rate available on the broadcast network. In order to justify this choice a prediction of the number of subscribers requesting the new multimedia applications designed for this scenario is needed. This paper focuses on the user behaviour modelling for multimedia services in a hybrid UMTS/DVB-T platform. The aim of the paper is to provide operators with a forecast of the demand for new multimedia services showing how they can be subject to a very high number of subscriptions, which UMTS would hardly be able to handle