17,438 research outputs found
RCD: Rapid Close to Deadline Scheduling for Datacenter Networks
Datacenter-based Cloud Computing services provide a flexible, scalable and
yet economical infrastructure to host online services such as multimedia
streaming, email and bulk storage. Many such services perform geo-replication
to provide necessary quality of service and reliability to users resulting in
frequent large inter- datacenter transfers. In order to meet tenant service
level agreements (SLAs), these transfers have to be completed prior to a
deadline. In addition, WAN resources are quite scarce and costly, meaning they
should be fully utilized. Several recently proposed schemes, such as B4,
TEMPUS, and SWAN have focused on improving the utilization of inter-datacenter
transfers through centralized scheduling, however, they fail to provide a
mechanism to guarantee that admitted requests meet their deadlines. Also, in a
recent study, authors propose Amoeba, a system that allows tenants to define
deadlines and guarantees that the specified deadlines are met, however, to
admit new traffic, the proposed system has to modify the allocation of already
admitted transfers. In this paper, we propose Rapid Close to Deadline
Scheduling (RCD), a close to deadline traffic allocation technique that is fast
and efficient. Through simulations, we show that RCD is up to 15 times faster
than Amoeba, provides high link utilization along with deadline guarantees, and
is able to make quick decisions on whether a new request can be fully satisfied
before its deadline.Comment: World Automation Congress (WAC), IEEE, 201
Datacenter Traffic Control: Understanding Techniques and Trade-offs
Datacenters provide cost-effective and flexible access to scalable compute
and storage resources necessary for today's cloud computing needs. A typical
datacenter is made up of thousands of servers connected with a large network
and usually managed by one operator. To provide quality access to the variety
of applications and services hosted on datacenters and maximize performance, it
deems necessary to use datacenter networks effectively and efficiently.
Datacenter traffic is often a mix of several classes with different priorities
and requirements. This includes user-generated interactive traffic, traffic
with deadlines, and long-running traffic. To this end, custom transport
protocols and traffic management techniques have been developed to improve
datacenter network performance.
In this tutorial paper, we review the general architecture of datacenter
networks, various topologies proposed for them, their traffic properties,
general traffic control challenges in datacenters and general traffic control
objectives. The purpose of this paper is to bring out the important
characteristics of traffic control in datacenters and not to survey all
existing solutions (as it is virtually impossible due to massive body of
existing research). We hope to provide readers with a wide range of options and
factors while considering a variety of traffic control mechanisms. We discuss
various characteristics of datacenter traffic control including management
schemes, transmission control, traffic shaping, prioritization, load balancing,
multipathing, and traffic scheduling. Next, we point to several open challenges
as well as new and interesting networking paradigms. At the end of this paper,
we briefly review inter-datacenter networks that connect geographically
dispersed datacenters which have been receiving increasing attention recently
and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial
cISP: A Speed-of-Light Internet Service Provider
Low latency is a requirement for a variety of interactive network
applications. The Internet, however, is not optimized for latency. We thus
explore the design of cost-effective wide-area networks that move data over
paths very close to great-circle paths, at speeds very close to the speed of
light in vacuum. Our cISP design augments the Internet's fiber with free-space
wireless connectivity. cISP addresses the fundamental challenge of
simultaneously providing low latency and scalable bandwidth, while accounting
for numerous practical factors ranging from transmission tower availability to
packet queuing. We show that instantiations of cISP across the contiguous
United States and Europe would achieve mean latencies within 5% of that
achievable using great-circle paths at the speed of light, over medium and long
distances. Further, we estimate that the economic value from such networks
would substantially exceed their expense
On the Benefit of Information Centric Networks for Traffic Engineering
Current Internet performs traffic engineering (TE) by estimating traffic
matrices on a regular schedule, and allocating flows based upon weights
computed from these matrices. This means the allocation is based upon a guess
of the traffic in the network based on its history. Information-Centric
Networks on the other hand provide a finer-grained description of the traffic:
a content between a client and a server is uniquely identified by its name, and
the network can therefore learn the size of different content items, and
perform traffic engineering and resource allocation accordingly. We claim that
Information-Centric Networks can therefore provide a better handle to perform
traffic engineering, resulting in significant performance gain.
We present a mechanism to perform such resource allocation. We see that our
traffic engineering method only requires knowledge of the flow size (which, in
ICN, can be learned from previous data transfers) and outperforms a min-MLU
allocation in terms of response time. We also see that our method identifies
the traffic allocation patterns similar to that of min-MLU without having
access to the traffic matrix ahead of time. We show a very significant gain in
response time where min MLU is almost 50% slower than our ICN-based TE method
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