Massively Multiplayer Online Games (MMOGs) recently emerged as a popular class of applications with millions of users. To offer acceptable gaming experience, such applications need to render the virtual world surrounding the player with very low latency. However, current state-of-the-art MMOGs based on peer-to-peer overlays fail to satisfy these requirements. This happens because avatar mobility implies many data exchanges through the overlay. As state-of-the-art overlays do not anticipate this mobility, the needed data is not delivered on time, which leads to transient failures at the application level. To solve this problem, we propose Blue Banana, a mechanism that models and predicts avatar movement, allowing the overlay to adapt itself by anticipation to the MMOG needs. Our evaluation is based on large-scale traces derived from Second life. It shows that our anticipation mechanism decreases by 20% the number of transient failures with only a network overhead of 2%.
Delivering on-demand web content to end-users in order to carry out strict QoS metrics is not a trivial task for globally distributed network providers. This task becomes still harder when content popularity varies over the time and the SLA definitions have to include both transfer rate and latency metrics. Current worldwide content delivery approaches and datacenter infrastructures rely on cumbersome replication schemes that are agnostic to edge-network resources, and damage content provision. In this work we present AREN, an novel replication scheme for cloud storage on edge networks. AREN relies on a collaborative cache strategy and bandwidth reservation to adapt the replication degree according to strict SLA contracts and content popularity growth. We have evaluated the performances of replication schemes on edge networks using Caju, a content distribution system for edge networks. Compared to a noncollaborative caching, evaluations show that AREN prevents nearly 99.8% of all SLA violations when the storage system is heavily loaded. We also show that AREN provides a sevenfold decrease in the amount of storage usage for replicas, and it increases by roughly 20% the aggregate bandwidth, hence accelerating content delivery.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.