182,368 research outputs found
Cost-Aware Resource Management for Decentralized Internet Services
Decentralized network services, such as naming systems, content
distribution networks, and publish-subscribe systems, play an
increasingly critical role and are required to provide high
performance, low latency service, achieve high availability in the
presence of network and node failures, and handle a large volume
of users. Judicious utilization of expensive system resources,
such as memory space, network bandwidth, and number of machines,
is fundamental to achieving the above properties. Yet, current
network services typically rely on less-informed, heuristic-based
techniques to manage scarce resources, and often fall short of
expectations.
This thesis presents a principled approach for building high
performance, robust, and scalable network services. The key
contribution of this thesis is to show that resolving the
fundamental cost-benefit tradeoff between resource consumption and
performance through mathematical optimization is practical in
large-scale distributed systems, and enables decentralized network
services to meet efficiently system-wide performance goals. This
thesis presents a practical approach for resource management in
three stages: analytically model the cost-benefit tradeoff as a
constrained optimization problem, determine a near-optimal
resource allocation strategy on the fly, and enforce the derived
strategy through light-weight, decentralized mechanisms. It
builds on self-organizing structured overlays, which provide
failure resilience and scalability, and complements them with
stronger performance guarantees and robustness under sudden
changes in workload. This work enables applications to meet
system-wide performance targets, such as low average response
times, high cache hit rates, and small update dissemination times
with low resource consumption. Alternatively, applications can
make the maximum use of available resources, such as storage and
bandwidth, and derive large gains in performance.
I have implemented an extensible framework called Honeycomb to
perform cost-aware resource management on structured overlays
based on the above approach and built three critical network
services using it. These services consist of a new name system for
the Internet called CoDoNS that distributes data associated with
domain names, an open-access content distribution network called
CobWeb that caches web content for faster access by users, and an
online information monitoring system called Corona that notifies
users about changes to web pages. Simulations and performance
measurements from a planetary-scale deployment show that these
services provide unprecedented performance improvement over the
current state of the art
Fronthaul-Constrained Cloud Radio Access Networks: Insights and Challenges
As a promising paradigm for fifth generation (5G) wireless communication
systems, cloud radio access networks (C-RANs) have been shown to reduce both
capital and operating expenditures, as well as to provide high spectral
efficiency (SE) and energy efficiency (EE). The fronthaul in such networks,
defined as the transmission link between a baseband unit (BBU) and a remote
radio head (RRH), requires high capacity, but is often constrained. This
article comprehensively surveys recent advances in fronthaul-constrained
C-RANs, including system architectures and key techniques. In particular, key
techniques for alleviating the impact of constrained fronthaul on SE/EE and
quality of service for users, including compression and quantization,
large-scale coordinated processing and clustering, and resource allocation
optimization, are discussed. Open issues in terms of software-defined
networking, network function virtualization, and partial centralization are
also identified.Comment: 5 Figures, accepted by IEEE Wireless Communications. arXiv admin
note: text overlap with arXiv:1407.3855 by other author
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