3,548 research outputs found
OSCAR: A Collaborative Bandwidth Aggregation System
The exponential increase in mobile data demand, coupled with growing user
expectation to be connected in all places at all times, have introduced novel
challenges for researchers to address. Fortunately, the wide spread deployment
of various network technologies and the increased adoption of multi-interface
enabled devices have enabled researchers to develop solutions for those
challenges. Such solutions aim to exploit available interfaces on such devices
in both solitary and collaborative forms. These solutions, however, have faced
a steep deployment barrier.
In this paper, we present OSCAR, a multi-objective, incentive-based,
collaborative, and deployable bandwidth aggregation system. We present the
OSCAR architecture that does not introduce any intermediate hardware nor
require changes to current applications or legacy servers. The OSCAR
architecture is designed to automatically estimate the system's context,
dynamically schedule various connections and/or packets to different
interfaces, be backwards compatible with the current Internet architecture, and
provide the user with incentives for collaboration. We also formulate the OSCAR
scheduler as a multi-objective, multi-modal scheduler that maximizes system
throughput while minimizing energy consumption or financial cost. We evaluate
OSCAR via implementation on Linux, as well as via simulation, and compare our
results to the current optimal achievable throughput, cost, and energy
consumption. Our evaluation shows that, in the throughput maximization mode, we
provide up to 150% enhancement in throughput compared to current operating
systems, without any changes to legacy servers. Moreover, this performance gain
further increases with the availability of connection resume-supporting, or
OSCAR-enabled servers, reaching the maximum achievable upper-bound throughput
A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing
Data Grids have been adopted as the platform for scientific communities that
need to share, access, transport, process and manage large data collections
distributed worldwide. They combine high-end computing technologies with
high-performance networking and wide-area storage management techniques. In
this paper, we discuss the key concepts behind Data Grids and compare them with
other data sharing and distribution paradigms such as content delivery
networks, peer-to-peer networks and distributed databases. We then provide
comprehensive taxonomies that cover various aspects of architecture, data
transportation, data replication and resource allocation and scheduling.
Finally, we map the proposed taxonomy to various Data Grid systems not only to
validate the taxonomy but also to identify areas for future exploration.
Through this taxonomy, we aim to categorise existing systems to better
understand their goals and their methodology. This would help evaluate their
applicability for solving similar problems. This taxonomy also provides a "gap
analysis" of this area through which researchers can potentially identify new
issues for investigation. Finally, we hope that the proposed taxonomy and
mapping also helps to provide an easy way for new practitioners to understand
this complex area of research.Comment: 46 pages, 16 figures, Technical Repor
A versatile model for TCP bandwidth sharing in networks with heterogeneous users.
Enabled by the emergence of various access technologies (such as ADSL and wireless LAN), the number of users with high-speed access to the Internet is growing rapidly, and their expectation with respect to the quality-of-service of the applications has been increasing accordingly. With TCP being the ubiquitous underlying end-to-end control, this motivates the interest in easy-to-evaluate, yet accurate, performance models for a TCP-based network shared by multiple classes of users. Building on the vast body of existing models, we develop a novel versatile model that explicitly captures user heterogeneity, and takes into consideration dynamics at both the packet level and the flow level. It is described how the resulting multiple time-scale model can be numerically evaluated. Validation is done by using NS2 simulations as a benchmark. In extensive numerical experiments, we study the impact of heterogeneity in the round-trip times on user-level characteristics such as throughputs and flow transmission times, thus quantifying the resulting bias. We also investigate to what extent this bias is affected by the networks' `packet-level parameters', such as buffer sizes. We conclude by extending the single-link model in a straightforward way to a general network setting. Also in this network setting the impact of heterogeneity in round-trip times is numerically assesse
The Role of Responsive Pricing in the Internet
The Internet continues to evolve as it reaches out to a wider user population. The recent introduction of user-friendly navigation and retrieval tools for the World Wide Web has triggered an unprecedented level of interest in the Internet among the media and the general public, as well as in the technical community. It seems inevitable that some changes or additions are needed in the control mechanisms used to allocate usage of Internet resources. In this paper, we argue that a feedback signal in the form of a variable price for network service is a workable tool to aid network operators in controlling Internet traffic. We suggest that these prices should vary dynamically based on the current utilization of network resources. We show how this responsive pricing puts control of network service back where it belongs: with the users.Internet, pricing, feedback, networks
Measuring and Managing Answer Quality for Online Data-Intensive Services
Online data-intensive services parallelize query execution across distributed
software components. Interactive response time is a priority, so online query
executions return answers without waiting for slow running components to
finish. However, data from these slow components could lead to better answers.
We propose Ubora, an approach to measure the effect of slow running components
on the quality of answers. Ubora randomly samples online queries and executes
them twice. The first execution elides data from slow components and provides
fast online answers; the second execution waits for all components to complete.
Ubora uses memoization to speed up mature executions by replaying network
messages exchanged between components. Our systems-level implementation works
for a wide range of platforms, including Hadoop/Yarn, Apache Lucene, the
EasyRec Recommendation Engine, and the OpenEphyra question answering system.
Ubora computes answer quality much faster than competing approaches that do not
use memoization. With Ubora, we show that answer quality can and should be used
to guide online admission control. Our adaptive controller processed 37% more
queries than a competing controller guided by the rate of timeouts.Comment: Technical Repor
Network Neutrality and the Evolution of the Internet
In order to create incentives for Internet traffic providers not to discriminate with respect to certain applications on the basis of network capacity requirements, the concept of market driven network neutrality is introduced. Its basic characteristics are that all applications are bearing the opportunity costs of the required traffic capacities. An economic framework for market driven network neutrality in broadband Internet is provided, consisting of congestion pricing and quality of service differentiation. However, network neutrality regulation with its reference point of the traditional TCP would result in regulatory micromanagement of traffic network management. --Broadband Internet,network neutrality,quality of service differentiation,congestion pricing,interclass externality pricing,interconnection agreements
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