50,686 research outputs found
Cross-layer Congestion Control, Routing and Scheduling Design in Ad Hoc Wireless Networks
This paper considers jointly optimal design of crosslayer congestion control, routing and scheduling for ad hoc
wireless networks. We first formulate the rate constraint and scheduling constraint using multicommodity flow variables, and formulate resource allocation in networks with fixed wireless channels (or single-rate wireless devices that can mask channel variations) as a utility maximization problem with these constraints.
By dual decomposition, the resource allocation problem
naturally decomposes into three subproblems: congestion control,
routing and scheduling that interact through congestion price.
The global convergence property of this algorithm is proved. We
next extend the dual algorithm to handle networks with timevarying
channels and adaptive multi-rate devices. The stability
of the resulting system is established, and its performance is
characterized with respect to an ideal reference system which
has the best feasible rate region at link layer.
We then generalize the aforementioned results to a general
model of queueing network served by a set of interdependent
parallel servers with time-varying service capabilities, which
models many design problems in communication networks. We
show that for a general convex optimization problem where a
subset of variables lie in a polytope and the rest in a convex set,
the dual-based algorithm remains stable and optimal when the
constraint set is modulated by an irreducible finite-state Markov
chain. This paper thus presents a step toward a systematic way
to carry out cross-layer design in the framework of ālayering as
optimization decompositionā for time-varying channel models
Minimum Cost Multicast with Decentralized Sources
In this paper we study the multisource multicast problem where every sink in
a given directed acyclic graph is a client and is interested in a common file.
We consider the case where each node can have partial knowledge about the file
as a side information. Assuming that nodes can communicate over the capacity
constrained links of the graph, the goal is for each client to gain access to
the file, while minimizing some linear cost function of number of bits
transmitted in the network. We consider three types of side-information
settings:(ii) side information in the form of linearly correlated packets; and
(iii) the general setting where the side information at the nodes have an
arbitrary (i.i.d.) correlation structure. In this work we 1) provide a
polynomial time feasibility test, i.e., whether or not all the clients can
recover the file, and 2) we provide a polynomial-time algorithm that finds the
optimal rate allocation among the links of the graph, and then determines an
explicit transmission scheme for cases (i) and (ii)
Achieving High Speed CFD simulations: Optimization, Parallelization, and FPGA Acceleration for the unstructured DLR TAU Code
Today, large scale parallel simulations are fundamental tools to handle complex problems. The number of processors in current computation platforms has been recently increased and therefore it is necessary to optimize the application performance and to enhance the scalability of massively-parallel systems. In addition, new heterogeneous architectures, combining conventional processors with specific hardware, like FPGAs, to accelerate the most time consuming functions are considered as a strong alternative to boost the performance.
In this paper, the performance of the DLR TAU code is analyzed and optimized. The improvement of the code efficiency is addressed through three key activities: Optimization, parallelization and hardware acceleration. At first, a profiling analysis of the most time-consuming processes of the Reynolds Averaged Navier Stokes flow solver on a three-dimensional unstructured mesh is performed. Then, a study of the code scalability with new partitioning algorithms are tested to show the most suitable partitioning algorithms for the selected applications. Finally, a feasibility study on the application of FPGAs and GPUs for the hardware acceleration of CFD simulations is presented
Recent Advances in Graph Partitioning
We survey recent trends in practical algorithms for balanced graph
partitioning together with applications and future research directions
Optimal Joint Routing and Scheduling in Millimeter-Wave Cellular Networks
Millimeter-wave (mmWave) communication is a promising technology to cope with
the expected exponential increase in data traffic in 5G networks. mmWave
networks typically require a very dense deployment of mmWave base stations
(mmBS). To reduce cost and increase flexibility, wireless backhauling is needed
to connect the mmBSs. The characteristics of mmWave communication, and
specifically its high directional- ity, imply new requirements for efficient
routing and scheduling paradigms. We propose an efficient scheduling method,
so-called schedule-oriented optimization, based on matching theory that
optimizes QoS metrics jointly with routing. It is capable of solving any
scheduling problem that can be formulated as a linear program whose variables
are link times and QoS metrics. As an example of the schedule-oriented
optimization, we show the optimal solution of the maximum throughput fair
scheduling (MTFS). Practically, the optimal scheduling can be obtained even for
networks with over 200 mmBSs. To further increase the runtime performance, we
propose an efficient edge-coloring based approximation algorithm with provable
performance bound. It achieves over 80% of the optimal max-min throughput and
runs 5 to 100 times faster than the optimal algorithm in practice. Finally, we
extend the optimal and approximation algorithms for the cases of multi-RF-chain
mmBSs and integrated backhaul and access networks.Comment: To appear in Proceedings of INFOCOM '1
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