3,723 research outputs found
End-To-End Deadlines over Dynamic Topologies
Despite the creativity of the scientific community and the funding agencies, the underlying model of computation behind IoT, WSN, cloud, edge, fog, and mist is fundamentally the same; Computational nodes which are dynamically interconnected to form a system in where both processing capacity and connectivity may vary over time. On top of such a system, we consider applications that need packets to flow along a path and adhere to end-to-end deadlines. This application model is motivated by both control and automation systems, as well as telecom systems. The challenge is to guarantee end-to-end deadlines when allowing nodes and applications to join or leave.
The mainstream, and to some extent natural, approach to this is to relax the stringency of the constraint (e.g. use probabilistic guarantees, soft deadlines). In this paper we take a different approach and keep the end-to-end deadlines as hard constraints and instead partially limit the freedom of how nodes and applications are allowed to leave and join. We present a theoretical framework for modeling such systems along with proofs that deadlines are always honored
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
QuickCast: Fast and Efficient Inter-Datacenter Transfers using Forwarding Tree Cohorts
Large inter-datacenter transfers are crucial for cloud service efficiency and
are increasingly used by organizations that have dedicated wide area networks
between datacenters. A recent work uses multicast forwarding trees to reduce
the bandwidth needs and improve completion times of point-to-multipoint
transfers. Using a single forwarding tree per transfer, however, leads to poor
performance because the slowest receiver dictates the completion time for all
receivers. Using multiple forwarding trees per transfer alleviates this
concern--the average receiver could finish early; however, if done naively,
bandwidth usage would also increase and it is apriori unclear how best to
partition receivers, how to construct the multiple trees and how to determine
the rate and schedule of flows on these trees. This paper presents QuickCast, a
first solution to these problems. Using simulations on real-world network
topologies, we see that QuickCast can speed up the average receiver's
completion time by as much as while only using more
bandwidth; further, the completion time for all receivers also improves by as
much as faster at high loads.Comment: [Extended Version] Accepted for presentation in IEEE INFOCOM 2018,
Honolulu, H
Providing End-to-End Delay Guarantees for Multi-hop Wireless Sensor Networks over Unreliable Channels
Wireless sensor networks have been increasingly used for real-time
surveillance over large areas. In such applications, it is important to support
end-to-end delay constraints for packet deliveries even when the corresponding
flows require multi-hop transmissions. In addition to delay constraints, each
flow of real-time surveillance may require some guarantees on throughput of
packets that meet the delay constraints. Further, as wireless sensor networks
are usually deployed in challenging environments, it is important to
specifically consider the effects of unreliable wireless transmissions.
In this paper, we study the problem of providing end-to-end delay guarantees
for multi-hop wireless networks. We propose a model that jointly considers the
end-to-end delay constraints and throughput requirements of flows, the need for
multi-hop transmissions, and the unreliable nature of wireless transmissions.
We develop a framework for designing feasibility-optimal policies. We then
demonstrate the utility of this framework by considering two types of systems:
one where sensors are equipped with full-duplex radios, and the other where
sensors are equipped with half-duplex radios. When sensors are equipped with
full-duplex radios, we propose an online distributed scheduling policy and
proves the policy is feasibility-optimal. We also provide a heuristic for
systems where sensors are equipped with half-duplex radios. We show that this
heuristic is still feasibility-optimal for some topologies
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