ILP Algorithms Research Articles

Energy-Efficient UAV Trajectory Planning based on Flexible Segment Clustering Algorithm

This paper plans the energy-efficient UAV trajectory when a UAV gathers data from massive IoT devices in a given area. The UAV trajectory design is addressed by two steps, i.e., IoT node clustering and UAV flight path planning for scanning the clusters, which are formulated as Cluster Minimization (CM) problem and Traveling Salesman Problem (TSP) in this work, respectively. The CM aims to contribute fewest clusters with minimal overlap to cover all the IoT devices and the per cluster size approaching the UAV communication coverage. On the other hand, the TSP seeks to design the shortest flight path to cover all the grouped clusters while minimizing energy consumption. Specifically, this work mainly focuses on the CM problem since the TSP issues have been well addressed in the past. In particular, we design a two-stage ILP optimization model to formulate the CM problem and propose two flexible clustering algorithms with low complexity, i.e., segment clustering (SC) and its variant, saying shifted SC (SSC). For the proposed ILP model and algorithms, we conduct extensive simulations under five different topologies and compare the performance results with existing methods. The simulation results indicate that the performance achieved by the proposed SSC algorithm is closest to the optimal results obtained from the ILP model. Moreover, it outperforms the existing methods under most topologies regarding cluster numbers, trajectory path length, and power consumption.

Joint Multi-layer Survivability Techniques for IP-Over-Elastic-Optical-Networks

The traffic in metro and core networks is forecasted to grow in volume but also in dynamicity. Network operators dimension their optical networks and their IP edges for the expected traffic peak, and also reserve additional resources for the required survivability level. The latter is typically done by protection mechanisms at the optical or IP layer only. Multi-layer proactive restoration techniques can reduce the cost by enabling resource sharing while providing the same level of survivability. In this work we formulate the multi-layer survivability problem for an IP-over-elastic-optical-network and present ILP formulations to solve it, targeting two survivability levels: (i) single optical link and (ii) single optical link or optical and IP node failure. The proposed ILP algorithms are also distinguished with respect to their failure consideration point: (i) sequential, where we assume that the network is dimensioned for normal operation and then re-dimensioned to be resilient, and (ii) joint, where the network is dimensioned in a single step, considering normal and all single failure operation. We exploit the proactive (a priori provisioning) restoration concept to achieve sharing of the backup resources among different failure states. The proposed multi-layer techniques enable even higher efficiency, exploiting the IP grooming capabilities to enable the sharing of backup resources for a specific failure state but also the sharing of primary and backup resources. Compared to traditional single-layer protection approaches, the proposed joint multi-layer techniques were shown to yield significant cost savings.

The lattice structure and refinement operators for the hypothesis space bounded by a bottom clause

Searching the hypothesis space bounded below by a bottom clause is the basis of several state-of-the-art ILP systems (e.g. Progol, Aleph). These systems use refinement operators together with search heuristics to explore a bounded hypothesis space. It is known that the search space of these systems is limited to a sub-graph of the general subsumption lattice. However, the structure and properties of this sub-graph have not been properly characterised. In this paper firstly, we characterise the hypothesis space considered by the ILP systems which use a bottom clause to constrain the search. In particular, we discuss refinement in Progol as a representative of these ILP systems. Secondly, we study the lattice structure of this bounded hypothesis space. Thirdly, we give a new analysis of refinement operators, least generalisation and greatest specialisation in the subsumption order relative to a bottom clause. The results of this study are important for better understanding of the constrained refinement space of ILP systems such as Progol and Aleph, which proved to be successful for solving real-world problems (despite being incomplete with respect to the general subsumption order). Moreover, characterising this refinement sub-lattice can lead to more efficient ILP algorithms and operators for searching this particular sub-lattice. For example, it is shown that, unlike for the general subsumption order, efficient least generalisation operators can be designed for the subsumption order relative to a bottom clause.

Ultra-fast and efficient algorithm for energy optimization by gradient-based stochastic voltage and task scheduling

This paper presents a new technique, called Adaptive Stochastic Gradient Voltage-and-Task Scheduling (ASG-VTS), for power optimization of multicore hard realtime systems. ASG-VTS combines stochastic and energy-gradient techniques to simultaneously solve the slack distribution and task reordering problem. It produces very efficient results with few mode transitions. Our experiments show that ASG-VTS reduces number of mode transitions by 4.8 times compared to traditional energy-gradient-based approaches. Also, our heuristic algorithm can quickly find a solution that is as good as the optimal for a real-life GSM encoder/decoder benchmark. The runtime of ASG-VTS is 150 times and 1034 times faster than energy-gradient based and optimal ILP algorithms, respectively. Since the runtime of ASG-VTS is very low, it is ideal for design space exploration in system-level design tools. We have also developed a web-based interface for ASG-VTS algorithm.

An efficient list scheduling algorithm for time placement problem

The partially reconfigurable FPGAs allows an overlap between the execution and the reconfiguration of tasks. The partial approach can be used to fit a large application into the FPGA device by partitioning the application over time. The executions being partitioned over time and the configurations of tasks are done so that the imposed constraints are satisfied. The main aim of this work consists in answering the question when will a task be mapped in the FPGA? A time placement algorithm based on the list scheduling technique is developed to solve efficiently the above question. We have just used the list scheduling algorithm because of its fast run time. Compared to the run time of other algorithms used in this filed like the spectral and ILP algorithms, the list scheduling algorithm remains a good temporal placement candidate, especially, for a several nodes graph. Also, a part of this paper is devoted for the study and the implementation of DCT task graph. This graph is the most computationally intensive part of the Color Layout Descriptor algorithm of a low-level visual descriptor of MPEG 7. The studied case shows that the use of the partial approach is very efficient in terms of latency of the whole application than the full one.

Heuristic and optimal techniques for light-trail assignment in optical ring WDM networks

In this paper we address the problem of constrained optimization (ILP formulation) and propose a set of heuristic algorithms for assigning light-trails [1–4,7,10] to WDM ring networks to facilitate IP centric dynamic communication at the optical layer. A light-trail is a generalization of a lightpath such that multiple nodes can take part in communication along the path without the need for optical switching. A light-trail represents an opportunistic medium in which multiple spatially distributed sub-lambda flows can be groomed despite without the need for optical switching. A light-trail is analogous to an optical bus such that multiple connections between source–destination pairs can be provisioned under the constraint that no two connections have overlapping time-intervals. This enables traffic grooming at the optical layer. In this paper we first describe a constrained optimization procedure for assigning light-trails in WDM ring networks. We then show five heuristic algorithms that solve the light-trail assignment problem in polynomial time. The heuristic algorithms are based on dynamic (unknown traffic) and static (known traffic) approaches. A simulation study compares the performance of ILP and heuristic algorithms.

Relational knowledge discovery in a chinese character database

This article describes a novel application ofInductive Logic Programming (ILP) to the problem of data mining relational databases. The task addressed here consists in mining a relational database ofmore than 200,000 ground facts describing 6768 Chinese characters. Mining this relational database may be recast in an ILP setting, where the form ofthe association rules searched are represented as nondeterminate Horn clauses, a type of clause known for being computationally hard to learn. We have introduced a new kind of language bias, S-structural indeterminate clauses, which takes into account the meaning of part-of predicates that play a key role in the complexity oflearning in structural domains. The ILP algorithm REPART has been specifically developed to learn S-structural indeterminate clauses. Its efficiency lies in a particular change ofrepresentation, so as to enable one to use propositional learners. This article presents original results discovered by REPART that exemplify how ILP algorithms may not only scale up efficiently to large relational databases but also discover useful and computationally hard to learn patterns.

Coal and Conflict: A Study of Industrial Relations at Collieries.W. H. Scott , Enid Mumford , L. C. McGivering , J. M. Kirkby

Previous articleNext article No AccessBook ReviewsCoal and Conflict: A Study of Industrial Relations at Collieries. W. H. Scott , Enid Mumford , L. C. McGivering , J. M. Kirkby Louis KriesbergLouis Kriesberg Search for more articles by this author PDFPDF PLUS Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by American Journal of Sociology Volume 70, Number 1Jul., 1964 Article DOIhttps://doi.org/10.1086/223760 Views: 1Total views on this site Citations: 7Citations are reported from Crossref Copyright 1964, 1965, University of ChicagoPDF download Crossref reports the following articles citing this article:Krzysztof Walkowiak, Michal Kucharzak, Pawel Kopec, Andrzej Kasprzak ILP model and algorithms for restoration of anycast flows in Elastic Optical Networks, (Nov 2014): 102–108.https://doi.org/10.1109/RNDM.2014.7014938Xiao-yan Xing, Yi-yong Xiao, Ren-qian Zhang Parameter selection optimization for parametric cost estimation based on Simulated Annealing, (Oct 2010): 231–236.https://doi.org/10.1109/ICIEEM.2010.5646651Zhufang Wang, Donghong Cui A Hybrid Algorithm Based on Genetic Algorithm and Simulated Annealing for Solving Portfolio Problem, (Jul 2009): 106–109.https://doi.org/10.1109/BIFE.2009.34Zhengbing Hu, Rabah Moh'd, Al Shboul The Application of Ant Colony Optimization Technique (ACOT) for Employees Selection and Training, (Apr 2009): 497–502.https://doi.org/10.1109/DBTA.2009.172Jonas C. P. Yu, H. M. Wee, K. J. Wang An integrated three-echelon supply chain model for deteriorating items via simulated annealing method, (Jul 2008): 3921–3926.https://doi.org/10.1109/ICMLC.2008.4621088Humberto Brandao De Oliveira, Germano Vasconcelos, Guilherme Alvarenga A Multi-Start Simulated Annealing Algorithm for the Vehicle Routing Problem with Time Windows, (Oct 2006): 24–24.https://doi.org/10.1109/SBRN.2006.4C. Muller, E.H. Magill, P. Prosser, D.G. Smith Artificial intelligence in telecommunications, (): 883–887.https://doi.org/10.1109/GLOCOM.1993.318205