Nikolaos Laoutaris

Meta algorithms for hierarchical Web caches

Large scale hierarchical caches for Web content have been deployed widely in an attempt to reduce delivery delays and bandwidth consumption and also to improve the scalability of content dissemination through the World Wide Web. Irrespective of the specific replacement algorithm employed in each cache, a de facto characteristic of contemporary hierarchical caches is that a hit for a document at an l-level cache leads to the caching of the document in all intermediate caches (levels l-1,..., 1) on the path towards the leaf cache that received the initial request. This paper presents various algorithms that revises this standard behavior and attempts to be more selective in choosing the caches that gets to store a local copy of the requested document. As these algorithms operate independently of the actual replacement algorithm running in each individual cache, they are referred to as meta algorithms. Three new meta algorithms are proposed and compared against the de facto one and a recently proposed one by means of synthetic and trace-driven simulations. The best of the new meta algorithms appears to be leading to improved performance under most simulated scenarios, especially under a low availability of storage. The latter observation makes the presented meta algorithms particularly favorable for the handling of large data objects such as stored music files or short video clips. Additionally, a simple load balancing algorithm that is based on the concept of meta algorithms is proposed and evaluated. The algorithm is shown to be able to provide for an effective balancing of load thus possibly addressing the recently discovered filtering-effect in hierarchical Web caches.

Intrastream synchronization for continuous media streams: a survey of playout schedulers

The transmission of real-time streams over best effort networks has been an interesting research area for over a decade. An important objective of the research community has been to devise methods that cope with the variations of the network delay-also called delay jitter-that are an inherent characteristic of best effort networks. Jitter destroys the temporal relationships between periodically transmitted media units, that constitute a real-time media stream, thus hindering the comprehension of the stream. Playout adaptation algorithms undertake the labor of the temporal reconstruction of the stream, which is sometimes referred to as the restoration of its intrastream synchronization quality. This article surveys the work in the area of playout adaptation, aiming to concisely organize ideas that have been presented in isolation and identify the main points of differentiation among different schemes. The survey, discusses issues related to timing information, handling of late media units, quality evaluation metrics, and adaptation to changing delay conditions.

Adaptive playout strategies for packet video receivers with finite buffer capacity

Due to random delay variations in current best effort networks, packet video applications rely on end-system buffering and playout adaptation to reduce the effects of disruptions on the required smooth stream presentation. To study the effect of buffering and playout adaptation, we present an analytical model based on the M/G/1 queueing system with finite buffer capacity, and traffic intensity equal to or greater than unity. This model fits well a range of new applications that have limited buffer resources for the reception of incoming frames. We introduce the variance of distortion of playout (VDoP), a new metric that accounts for the overall presentation disruption caused by buffer underflows, intentionally introduced gaps during slowdown periods and data loss from overflows. VDoP is an elegant and fair metric for the estimation of playout quality and will hopefully assist the development of better adaptation algorithms. Furthermore, the effect of finite buffer capacity is examined in relation to stream continuity revealing a system behavior not previously accounted for. The sensitivity of the system to the variance of the arrival process is also examined by means of simulation. Finally, an online algorithm is presented for the exploitation of our study on implemented systems.

Distributed Selfish Caching

Although cooperation generally increases the amount of resources available to a community of nodes, thus improving individual and collective performance, it also allows for the appearance of potential mistreatment problems through the exposition of one nodes resources to others. We study such concerns by considering a group of independent, rational, self-aware nodes that cooperate using online caching algorithms, where the exposed resource is the storage at each node. Motivated by content networking applications - including Web caching, content delivery networks (CDNs), and peer-to-peer (P2P) - this paper extends our previous work on the offline version of the problem, which was conducted under a game-theoretic framework and limited to object replication. We identify and investigate two causes of mistreatment: 1) cache state interactions (due to the cooperative servicing of requests) and 2) the adoption of a common scheme for cache management policies. Using analytic models, numerical solutions of these models, and simulation experiments, we show that online cooperation schemes using caching are fairly robust to mistreatment caused by state interactions. To appear in a substantial manner, the interaction through the exchange of miss streams has to be very intense, making it feasible for the mistreated nodes to detect and react to exploitation. This robustness ceases to exist when nodes fetch and store objects in response to remote requests, that is, when they operate as level-2 caches (or proxies) for other nodes. Regarding mistreatment due to a common scheme, we show that this can easily take place when the outlier characteristics of some of the nodes get overlooked. This finding underscores the importance of allowing cooperative caching nodes the flexibility of choosing from a diverse set of schemes to fit the peculiarities of individual nodes. To that end, we outline an emulation-based framework for the development of mistreatment-resilient distributed selfish caching schemes.

Swarming on Optimized Graphs for n-Way Broadcast

In an n-way broadcast application each one of n overlay nodes wants to push its own distinct large data file to all other n-1 destinations as well as download their respective data files. BitTorrent-like swarming protocols are ideal choices for handling such massive data volume transfers. The original BitTorrent targets one-to-many broadcasts of a single file to a very large number of receivers and thus, by necessity, employs an almost random overlay topology, n-way broadcast applications on the other hand, owing to their inherent n-squared nature, are realizable only in small to medium scale networks. In this paper, we show that we can leverage this scale constraint to construct optimized overlay topologies that take into consideration the end-to-end characteristics of the network and as a consequence deliver far superior performance compared to random and myopic (local) approaches. We present the Max-Min and Max- Sum peer-selection policies used by individual nodes to select their neighbors. The first one strives to maximize the available bandwidth to the slowest destination, while the second maximizes the aggregate output rate. We design a swarming protocol suitable for n-way broadcast and operate it on top of overlay graphs formed by nodes that employ Max-Min or Max-Sum policies. Using trace-driven simulation and measurements from a PlanetLab prototype implementation, we demonstrate that the performance of swarming on top of our constructed topologies is far superior to the performance of random and myopic overlays. Moreover, we show how to modify our swarming protocol to allow it to accommodate selfish nodes.

The Impact of Playout Policy on the Performance of P2P Live Streaming : or how not to kill your P2P advantage

In this paper we examine the impact of the adopted playout policy on the performance of P2P live streaming systems. We argue and demonstrate experimentally that (popular) playout policies which permit the divergence of the playout points of different nodes can deteriorate drastically the performance of P2P live streaming. Consequently, we argue in favor of keeping different playout points near-in-time, even if this requires sacrificing (dropping) some late frames that could otherwise be rendered (assuming no strict bidirectional interactivity requirements are in place). Such nearly synchronized playout policies create positive correlation with respect to the available frames at different playout buffers. Therefore, they increase the number of upstream relay nodes from which a node can pull frames and thus boost the playout quality of both single-parent (tree) and multiple-parent (mesh) systems. On the contrary, diverging playout points reduce the number of upstream parents that can offer a gapless relay of the stream. This is clearly undesirable and should be avoided as it contradicts the fundamental philosophy of P2P systems which is to supplement an original service point with as many additional ones presented by the very own users of the service.