604 research outputs found
Delay Considerations for Opportunistic Scheduling in Broadcast Fading Channels
We consider a single-antenna broadcast block fading
channel with n users where the transmission is packetbased.
We define the (packet) delay as the minimum number of channel uses that guarantees all n users successfully receive m packets. This is a more stringent notion of delay than average delay and is the worst case (access) delay among the users. A delay optimal scheduling scheme, such as round-robin, achieves the delay of mn. For the opportunistic scheduling (which is throughput optimal) where the transmitter sends the packet to the user with the best channel conditions at each channel use, we derive the mean and variance of the delay for any m and n. For large n and in a homogeneous network, it is proved that the expected delay in receiving one packet by all the receivers scales as n log n, as opposed to n for the round-robin scheduling. We also show that when m grows faster than (log n)^r, for some r > 1, then the delay scales as mn. This roughly determines the timescale required for the system to behave fairly in a homogeneous network. We then propose a scheme to significantly reduce the delay at the expense of a small throughput hit. We further look into the advantage of multiple transmit antennas on the delay. For a system with M antennas in the transmitter where at each channel use packets are sent to M different users, we obtain the expected delay in receiving one packet by all the users
Dynamic algorithms for multicast with intra-session network coding
The problem of multiple multicast sessions with
intra-session network coding in time-varying networks is considered.
The network-layer capacity region of input rates that can be
stably supported is established. Dynamic algorithms for multicast
routing, network coding, power allocation, session scheduling, and
rate allocation across correlated sources, which achieve stability
for rates within the capacity region, are presented. This work
builds on the back-pressure approach introduced by Tassiulas
et al., extending it to network coding and correlated sources. In
the proposed algorithms, decisions on routing, network coding,
and scheduling between different sessions at a node are made
locally at each node based on virtual queues for different sinks.
For correlated sources, the sinks locally determine and control
transmission rates across the sources. The proposed approach
yields a completely distributed algorithm for wired networks.
In the wireless case, power control among different transmitters
is centralized while routing, network coding, and scheduling
between different sessions at a given node are distributed
Self-Evaluation Applied Mathematics 2003-2008 University of Twente
This report contains the self-study for the research assessment of the Department of Applied Mathematics (AM) of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente (UT). The report provides the information for the Research Assessment Committee for Applied Mathematics, dealing with mathematical sciences at the three universities of technology in the Netherlands. It describes the state of affairs pertaining to the period 1 January 2003 to 31 December 2008
Towards a Queueing-Based Framework for In-Network Function Computation
We seek to develop network algorithms for function computation in sensor
networks. Specifically, we want dynamic joint aggregation, routing, and
scheduling algorithms that have analytically provable performance benefits due
to in-network computation as compared to simple data forwarding. To this end,
we define a class of functions, the Fully-Multiplexible functions, which
includes several functions such as parity, MAX, and k th -order statistics. For
such functions we exactly characterize the maximum achievable refresh rate of
the network in terms of an underlying graph primitive, the min-mincut. In
acyclic wireline networks, we show that the maximum refresh rate is achievable
by a simple algorithm that is dynamic, distributed, and only dependent on local
information. In the case of wireless networks, we provide a MaxWeight-like
algorithm with dynamic flow splitting, which is shown to be throughput-optimal
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