4,006 research outputs found
An Optimal Transmission Strategy for Kalman Filtering over Packet Dropping Links with Imperfect Acknowledgements
This paper presents a novel design methodology for optimal transmission
policies at a smart sensor to remotely estimate the state of a stable linear
stochastic dynamical system. The sensor makes measurements of the process and
forms estimates of the state using a local Kalman filter. The sensor transmits
quantized information over a packet dropping link to the remote receiver. The
receiver sends packet receipt acknowledgments back to the sensor via an
erroneous feedback communication channel which is itself packet dropping. The
key novelty of this formulation is that the smart sensor decides, at each
discrete time instant, whether to transmit a quantized version of either its
local state estimate or its local innovation. The objective is to design
optimal transmission policies in order to minimize a long term average cost
function as a convex combination of the receiver's expected estimation error
covariance and the energy needed to transmit the packets. The optimal
transmission policy is obtained by the use of dynamic programming techniques.
Using the concept of submodularity, the optimality of a threshold policy in the
case of scalar systems with perfect packet receipt acknowledgments is proved.
Suboptimal solutions and their structural results are also discussed. Numerical
results are presented illustrating the performance of the optimal and
suboptimal transmission policies.Comment: Conditionally accepted in IEEE Transactions on Control of Network
System
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
ATP: a Datacenter Approximate Transmission Protocol
Many datacenter applications such as machine learning and streaming systems
do not need the complete set of data to perform their computation. Current
approximate applications in datacenters run on a reliable network layer like
TCP. To improve performance, they either let sender select a subset of data and
transmit them to the receiver or transmit all the data and let receiver drop
some of them. These approaches are network oblivious and unnecessarily transmit
more data, affecting both application runtime and network bandwidth usage. On
the other hand, running approximate application on a lossy network with UDP
cannot guarantee the accuracy of application computation. We propose to run
approximate applications on a lossy network and to allow packet loss in a
controlled manner. Specifically, we designed a new network protocol called
Approximate Transmission Protocol, or ATP, for datacenter approximate
applications. ATP opportunistically exploits available network bandwidth as
much as possible, while performing a loss-based rate control algorithm to avoid
bandwidth waste and re-transmission. It also ensures bandwidth fair sharing
across flows and improves accurate applications' performance by leaving more
switch buffer space to accurate flows. We evaluated ATP with both simulation
and real implementation using two macro-benchmarks and two real applications,
Apache Kafka and Flink. Our evaluation results show that ATP reduces
application runtime by 13.9% to 74.6% compared to a TCP-based solution that
drops packets at sender, and it improves accuracy by up to 94.0% compared to
UDP
Control Aware Radio Resource Allocation in Low Latency Wireless Control Systems
We consider the problem of allocating radio resources over wireless
communication links to control a series of independent wireless control
systems. Low-latency transmissions are necessary in enabling time-sensitive
control systems to operate over wireless links with high reliability. Achieving
fast data rates over wireless links thus comes at the cost of reliability in
the form of high packet error rates compared to wired links due to channel
noise and interference. However, the effect of the communication link errors on
the control system performance depends dynamically on the control system state.
We propose a novel control-communication co-design approach to the low-latency
resource allocation problem. We incorporate control and channel state
information to make scheduling decisions over time on frequency, bandwidth and
data rates across the next-generation Wi-Fi based wireless communication links
that close the control loops. Control systems that are closer to instability or
further from a desired range in a given control cycle are given higher packet
delivery rate targets to meet. Rather than a simple priority ranking, we derive
precise packet error rate targets for each system needed to satisfy stability
targets and make scheduling decisions to meet such targets while reducing total
transmission time. The resulting Control-Aware Low Latency Scheduling (CALLS)
method is tested in numerous simulation experiments that demonstrate its
effectiveness in meeting control-based goals under tight latency constraints
relative to control-agnostic scheduling
ABC: A Simple Explicit Congestion Controller for Wireless Networks
We propose Accel-Brake Control (ABC), a simple and deployable explicit
congestion control protocol for network paths with time-varying wireless links.
ABC routers mark each packet with an "accelerate" or "brake", which causes
senders to slightly increase or decrease their congestion windows. Routers use
this feedback to quickly guide senders towards a desired target rate. ABC
requires no changes to header formats or user devices, but achieves better
performance than XCP. ABC is also incrementally deployable; it operates
correctly when the bottleneck is a non-ABC router, and can coexist with non-ABC
traffic sharing the same bottleneck link. We evaluate ABC using a Wi-Fi
implementation and trace-driven emulation of cellular links. ABC achieves
30-40% higher throughput than Cubic+Codel for similar delays, and 2.2X lower
delays than BBR on a Wi-Fi path. On cellular network paths, ABC achieves 50%
higher throughput than Cubic+Codel
Cross-Layer Adaptive Feedback Scheduling of Wireless Control Systems
There is a trend towards using wireless technologies in networked control
systems. However, the adverse properties of the radio channels make it
difficult to design and implement control systems in wireless environments. To
attack the uncertainty in available communication resources in wireless control
systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS)
scheme is developed, which takes advantage of the co-design of control and
wireless communications. By exploiting cross-layer design, CLAFS adjusts the
sampling periods of control systems at the application layer based on
information about deadline miss ratio and transmission rate from the physical
layer. Within the framework of feedback scheduling, the control performance is
maximized through controlling the deadline miss ratio. Key design parameters of
the feedback scheduler are adapted to dynamic changes in the channel condition.
An event-driven invocation mechanism for the feedback scheduler is also
developed. Simulation results show that the proposed approach is efficient in
dealing with channel capacity variations and noise interference, thus providing
an enabling technology for control over WLAN.Comment: 17 pages, 12 figures; Open Access at
http://www.mdpi.org/sensors/papers/s8074265.pd
- …