2,820 research outputs found
A Finite-Time Cutting Plane Algorithm for Distributed Mixed Integer Linear Programming
Many problems of interest for cyber-physical network systems can be
formulated as Mixed Integer Linear Programs in which the constraints are
distributed among the agents. In this paper we propose a distributed algorithm
to solve this class of optimization problems in a peer-to-peer network with no
coordinator and with limited computation and communication capabilities. In the
proposed algorithm, at each communication round, agents solve locally a small
LP, generate suitable cutting planes, namely intersection cuts and cost-based
cuts, and communicate a fixed number of active constraints, i.e., a candidate
optimal basis. We prove that, if the cost is integer, the algorithm converges
to the lexicographically minimal optimal solution in a finite number of
communication rounds. Finally, through numerical computations, we analyze the
algorithm convergence as a function of the network size.Comment: 6 pages, 3 figure
Integrative Dynamic Reconfiguration in a Parallel Stream Processing Engine
Load balancing, operator instance collocations and horizontal scaling are
critical issues in Parallel Stream Processing Engines to achieve low data
processing latency, optimized cluster utilization and minimized communication
cost respectively. In previous work, these issues are typically tackled
separately and independently. We argue that these problems are tightly coupled
in the sense that they all need to determine the allocations of workloads and
migrate computational states at runtime. Optimizing them independently would
result in suboptimal solutions. Therefore, in this paper, we investigate how
these three issues can be modeled as one integrated optimization problem. In
particular, we first consider jobs where workload allocations have little
effect on the communication cost, and model the problem of load balance as a
Mixed-Integer Linear Program. Afterwards, we present an extended solution
called ALBIC, which support general jobs. We implement the proposed techniques
on top of Apache Storm, an open-source Parallel Stream Processing Engine. The
extensive experimental results over both synthetic and real datasets show that
our techniques clearly outperform existing approaches
Optimized Cell Planning for Network Slicing in Heterogeneous Wireless Communication Networks
We propose a cell planning scheme to maximize the resource efficiency of a
wireless communication network while considering quality-of-service
requirements imposed by different mobile services. In dense and heterogeneous
cellular 5G networks, the available time-frequency resources are orthogonally
partitioned among different slices, which are serviced by the cells. The
proposed scheme achieves a joint optimization of the resource distribution
between network slices, the allocation of cells to operate on different slices,
and the allocation of users to cells. Since the original problem formulation is
computationally intractable, we propose a convex inner approximation.
Simulations show that the proposed approach optimizes the resource efficiency
and enables a service-centric network design paradigm.Comment: This article has been accepted for publication in a future issue of
the IEEE Communications Letters,
https://ieeexplore.ieee.org/document/8368293, (c) 2018 IEE
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