248,028 research outputs found
COBACABANA (control of balance by card based navigation):an alternative to kanban in the pure flow shop?
Kanban systems are widely applied in practice as they represent a simple yet effective means of controlling production. But they suffer from a lack of load balancing capabilities, which hinders their application even to pure flow shops if there is variability. In response, this study focuses on COBACABANA (Control of Balance by Card Based Navigation), a card-based production control approach based on the Workload Control concept that was recently introduced in the literature. COBACABANA was developed for high-variety job shop contexts, but we argue it can also provide an important control alternative to kanban systems in pure flow shops. We first show that, in the pure flow shop, the control loop structure of COBACABANA resembles that of a kanban system when the flow of jobs is controlled. But a distinct difference is COBACABANA׳s unique focus on load balancing. Using simulation, we then demonstrate the potential of COBACABANA to improve performance in a pure flow shop with high demand and processing time variability. Results show that a fixed gateway station – inherent to a pure flow shop – presents a structural constraint that makes COBACABANA׳s original starvation avoidance mechanism, which injects work to a starving station, dysfunctional. An alternative is prioritizing jobs with short processing times at upstream stations to ensure quick replenishment takes place at downstream stations threatened by starvation. This has important implications not only for COBACABANA but for priority dispatching. Although card-based systems are typically combined with first-come-first-served dispatching, our results suggest this may be inappropriate in flow shops with processing time variability
Joint Energy Efficient and QoS-aware Path Allocation and VNF Placement for Service Function Chaining
Service Function Chaining (SFC) allows the forwarding of a traffic flow along
a chain of Virtual Network Functions (VNFs, e.g., IDS, firewall, and NAT).
Software Defined Networking (SDN) solutions can be used to support SFC reducing
the management complexity and the operational costs. One of the most critical
issues for the service and network providers is the reduction of energy
consumption, which should be achieved without impact to the quality of
services. In this paper, we propose a novel resource (re)allocation
architecture which enables energy-aware SFC for SDN-based networks. To this
end, we model the problems of VNF placement, allocation of VNFs to flows, and
flow routing as optimization problems. Thereafter, heuristic algorithms are
proposed for the different optimization problems, in order find near-optimal
solutions in acceptable times. The performance of the proposed algorithms are
numerically evaluated over a real-world topology and various network traffic
patterns. The results confirm that the proposed heuristic algorithms provide
near optimal solutions while their execution time is applicable for real-life
networks.Comment: Extended version of submitted paper - v7 - July 201
An Approximately Optimal Algorithm for Scheduling Phasor Data Transmissions in Smart Grid Networks
In this paper, we devise a scheduling algorithm for ordering transmission of
synchrophasor data from the substation to the control center in as short a time
frame as possible, within the realtime hierarchical communications
infrastructure in the electric grid. The problem is cast in the framework of
the classic job scheduling with precedence constraints. The optimization setup
comprises the number of phasor measurement units (PMUs) to be installed on the
grid, a weight associated with each PMU, processing time at the control center
for the PMUs, and precedence constraints between the PMUs. The solution to the
PMU placement problem yields the optimum number of PMUs to be installed on the
grid, while the processing times are picked uniformly at random from a
predefined set. The weight associated with each PMU and the precedence
constraints are both assumed known. The scheduling problem is provably NP-hard,
so we resort to approximation algorithms which provide solutions that are
suboptimal yet possessing polynomial time complexity. A lower bound on the
optimal schedule is derived using branch and bound techniques, and its
performance evaluated using standard IEEE test bus systems. The scheduling
policy is power grid-centric, since it takes into account the electrical
properties of the network under consideration.Comment: 8 pages, published in IEEE Transactions on Smart Grid, October 201
Low Power Dynamic Scheduling for Computing Systems
This paper considers energy-aware control for a computing system with two
states: "active" and "idle." In the active state, the controller chooses to
perform a single task using one of multiple task processing modes. The
controller then saves energy by choosing an amount of time for the system to be
idle. These decisions affect processing time, energy expenditure, and an
abstract attribute vector that can be used to model other criteria of interest
(such as processing quality or distortion). The goal is to optimize time
average system performance. Applications of this model include a smart phone
that makes energy-efficient computation and transmission decisions, a computer
that processes tasks subject to rate, quality, and power constraints, and a
smart grid energy manager that allocates resources in reaction to a time
varying energy price. The solution methodology of this paper uses the theory of
optimization for renewal systems developed in our previous work. This paper is
written in tutorial form and develops the main concepts of the theory using
several detailed examples. It also highlights the relationship between online
dynamic optimization and linear fractional programming. Finally, it provides
exercises to help the reader learn the main concepts and apply them to their
own optimizations. This paper is an arxiv technical report, and is a
preliminary version of material that will appear as a book chapter in an
upcoming book on green communications and networking.Comment: 26 pages, 10 figures, single spac
Distributive Network Utility Maximization (NUM) over Time-Varying Fading Channels
Distributed network utility maximization (NUM) has received an increasing
intensity of interest over the past few years. Distributed solutions (e.g., the
primal-dual gradient method) have been intensively investigated under fading
channels. As such distributed solutions involve iterative updating and explicit
message passing, it is unrealistic to assume that the wireless channel remains
unchanged during the iterations. Unfortunately, the behavior of those
distributed solutions under time-varying channels is in general unknown. In
this paper, we shall investigate the convergence behavior and tracking errors
of the iterative primal-dual scaled gradient algorithm (PDSGA) with dynamic
scaling matrices (DSC) for solving distributive NUM problems under time-varying
fading channels. We shall also study a specific application example, namely the
multi-commodity flow control and multi-carrier power allocation problem in
multi-hop ad hoc networks. Our analysis shows that the PDSGA converges to a
limit region rather than a single point under the finite state Markov chain
(FSMC) fading channels. We also show that the order of growth of the tracking
errors is given by O(T/N), where T and N are the update interval and the
average sojourn time of the FSMC, respectively. Based on this analysis, we
derive a low complexity distributive adaptation algorithm for determining the
adaptive scaling matrices, which can be implemented distributively at each
transmitter. The numerical results show the superior performance of the
proposed dynamic scaling matrix algorithm over several baseline schemes, such
as the regular primal-dual gradient algorithm
High-level synthesis under I/O Timing and Memory constraints
The design of complex Systems-on-Chips implies to take into account
communication and memory access constraints for the integration of dedicated
hardware accelerator. In this paper, we present a methodology and a tool that
allow the High-Level Synthesis of DSP algorithm, under both I/O timing and
memory constraints. Based on formal models and a generic architecture, this
tool helps the designer to find a reasonable trade-off between both the
required I/O timing behavior and the internal memory access parallelism of the
circuit. The interest of our approach is demonstrated on the case study of a
FFT algorithm
- …