1,382 research outputs found
Concurrent counting is harder than queuing
We compare the complexities of two fundamental distributed coordination problems, distributed counting and distributed queuing, in a concurrent setting. In both distributed counting and queuing, processors in a distributed system issue operations which are organized into a total order. In counting, each participating processor receives the rank of its operation in the total order, where as in queuing, a processor receives the identity of its predecessor in the total order. Many coordination applications can be solved using either distributed counting or queuing, and it is useful to know which of counting or queuing is the easier problem. Our results show that concurrent counting is harder than concurrent queuing on a variety of processor interconnection topologies, including high and low diameter graphs. For all these topologies, we show that the concurrent delay complexity of a particular solution to queuing, the arrow protocol, is asymptotically smaller than a lower bound on the complexity of any solution to counting
Distributed Queuing in Dynamic Networks
We consider the problem of forming a distributed queue in the adversarial
dynamic network model of Kuhn, Lynch, and Oshman (STOC 2010) in which the
network topology changes from round to round but the network stays connected.
This is a synchronous model in which network nodes are assumed to be fixed, the
communication links for each round are chosen by an adversary, and nodes do not
know who their neighbors are for the current round before they broadcast their
messages. Queue requests may arrive over rounds at arbitrary nodes and the goal
is to eventually enqueue them in a distributed queue. We present two algorithms
that give a total distributed ordering of queue requests in this model. We
measure the performance of our algorithms through round complexity, which is
the total number of rounds needed to solve the distributed queuing problem. We
show that in 1-interval connected graphs, where the communication links change
arbitrarily between every round, it is possible to solve the distributed
queueing problem in O(nk) rounds using O(log n) size messages, where n is the
number of nodes in the network and k <= n is the number of queue requests.
Further, we show that for more stable graphs, e.g. T-interval connected graphs
where the communication links change in every T rounds, the distributed queuing
problem can be solved in O(n+ (nk/min(alpha,T))) rounds using the same O(log n)
size messages, where alpha > 0 is the concurrency level parameter that captures
the minimum number of active queue requests in the system in any round. These
results hold in any arbitrary (sequential, one-shot concurrent, or dynamic)
arrival of k queue requests in the system. Moreover, our algorithms ensure
correctness in the sense that each queue request is eventually enqueued in the
distributed queue after it is issued and each queue request is enqueued exactly
once. We also provide an impossibility result for this distributed queuing
problem in this model. To the best of our knowledge, these are the first
solutions to the distributed queuing problem in adversarial dynamic networks.Comment: In Proceedings FOMC 2013, arXiv:1310.459
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
Measurements As First-class Artifacts
The emergence of programmable switches has sparked a significant amount of
work on new techniques to perform more powerful measurement tasks, for
instance, to obtain fine-grained traffic and performance statistics. Previous
work has focused on the efficiency of these measurements alone and has
neglected flexibility, resulting in solutions that are hard to reuse or
repurpose and that often overlap in functionality or goals.
In this paper, we propose the use of a set of reusable primitive building
blocks that can be composed to express measurement tasks in a concise and
simple way. We describe the rationale for the design of our primitives, that we
have named MAFIA (Measurements As FIrst-class Artifacts), and using several
examples we illustrate how they can be combined to realize a comprehensive
range of network measurement tasks. Writing MAFIA code does not require expert
knowledge of low-level switch architecture details. Using a prototype
implementation of MAFIA, we demonstrate the applicability of our approach and
show that the use of our primitives results in compiled code that is comparable
in size and resource usage with manually written specialized P4 code and can be
run in current hardware.Comment: Infocom 2019 extended versio
Capacity of an IEEE 802.11b wireless LAN supporting VoIP
In this paper we evaluate the capacity of an IEEE 802.11b network carrying voice calls in a wide range of scenarios, including varying delay constraints, channel conditions and voice call quality requirements. We consider both G.711 and G.729 voice encoding schemes and a range of voice packet sizes. We first present an analytical..
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