Heuristics

This paper proposes a set of algorithms to extend initially deployed Virtualized Network Functions Forwarding Graphs (VNF-FG or Service Function Chains-SFCs) previously requested and acquired by tenants. The latter are likely to request extension of their already acquired, deployed, and running dedicated slices to embed additional networking functions to handle for instance new application flows requiring additional classification , authentication, authorization, processing, traffic steering, etc. The tenants (or end-user service providers) are also likely to introduce gradually their services as needs arise and as their consumer base and profiles evolve. Increasing traffic load often will also require extension of the service graphs and chaining such as introducing additional load balancers and servers, new security functions, and simply new VNFs related to new tenant services. The related service graph extension problem is addressed first through an ILP algorithm that serves as a reference for performance comparisons with a set of proposed heuristic algorithms. A heuristic directly inspired by and based on the ILP and the proposed alternative approaches are shown to scale much better than the ILP while providing good solutions. The solutions include an adaptation of an eigendecomposition approach that provides very good performance for highly connected graphs. The problem is also cast into the well know Steiner Tree search problem whose complexity and performance are formally characterized in the literature. The Steiner based algorithm is shown to provide the best overall tradeoff (in rejection rate, complexity, and quality) with performance closest to optimal.

We present a decision theory appropriate for use in serious choices such as insurance. It extends standard decision theories like expected utility or cumulative prospect theory which are atemporal single stage theories. Instead it employs stages of knowledge ahead to ...

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In this paper we survey some of the developments with regards to technology-enhanced support of mathematics learning and teaching. Coverage is especially given on how to design systems that work effectively on the Web, particularly in the fields of economics and business studies. This is a rapidly evolving landscape in which general trends in e-learning have raised expectations of the electronic tools to go beyond merely providing mechanical functions: nowadays the teacher expects them to help organise their teaching and even enhance their teaching methods. For the student, there is increasing focus on the learner experience, which seeks a wider range and availability of e-learning support tools together with greater ease of use. Advances in technology mean that options keep changing, setting many challenges for system developers, so this paper seeks to indicate the broad features in these changes, with particular regard to future planning. These general considerations are subsequently brought into focus in later sections of this paper by addressing the question of how e-learning systems may provide judicious support for the uniquely human abilities of solving problems. In this case visualisation is an excellent aid, but any tools provided need to draw on a wide range of online resources that are readily available so as to properly establish the learning context. Finally, we briefly introduce into this context two new systems for teaching mathematics: VisualEconoMath, an integrated environment comprising automated tools for deriving solutions to prescribed mathematical problems and How2SolveIt, which supports the quintessential human learning processes surrounding questions and answers, in this case between students and lecturers.

Studies the partitioning problem, consisting in partitioning a sublist of n positive numbers into m disjoint sublists such that the maximum sublist is minimized. This is equivalent to minimizing the completion time of n jobs on m parallel identical processors. The author establishes upper bounds on the deviation from optimality of two heuristics: the well-known LPT heuristic, and the online RLP heuristic. These bounds serve to establish a probabilistic analysis of these heuristics; for both of them, the absolute deviation from optimality remains finite, when the size of the list of numbers becomes infinite. This is a stronger result than previous convergence theorems, and it is valid whenever the processing times are IID random variables with finite mean and arbitrary distributions. 12 references.

We present a general methodology to study the electricity market of a country or region, under various pricing mechanisms. The approach is based on modifications of a large-scale techno-economic model, and is applied to a realistic model for the Province of Québec. Mathematical programming and a new decomposition procedure are used to simulate different electricity pricing schemes and their effects

In a recent paper [I. Wegener, Simulated Annealing beats Metropolis in combinatorial optimization, in: L. Caires, G.F. Italiano, L. Monteiro, C. Palamidessi, M. Yung (Eds.), Proc. ICALP 2005, in: LNCS, vol. 3580, 2005, pp. 589–601] Wegener gave a first natural example of a combinatorial optimization problem where for certain instances a Simulated Annealing algorithm provably performs better than the Metropolis

The present paper isolates certain domain-general cognitive processes involved in decision making and examines their instantiations in adult second language acquisition (SLA). After reviewing important differences between mature and immature cognition, I discuss the epistemological categories and concepts that underlie decision making. I then address decision making from the point of view of fallibility—for example, maladaptive biases that mediate learners' decisions—and I suggest that some impediments to success in SLA may be the result of mature domain-general decision making. The heuristic value of research in the area of decision making is emphasized.

Prediction in natural environments is a challenging task, and there is a lack of clarity around how a myopic organism can make short-term predictions given limited data availability and cognitive resources. In this context, we may ask what kind of resources are available to the organism to help it address the challenge of short-term prediction within its own cognitive limits. We point to one potentially important resource: ordinal patterns, which are extensively used in physics but not in the study of cognitive processes. We explain the potential importance of ordinal patterns for short-term prediction, and how natural constraints imposed through (i) ordinal pattern types, (ii) their transition probabilities and (iii) their irreversibility signature may support short-term prediction. Having tested these ideas on a massive dataset of Bitcoin prices representing a highly fluctuating environment, we provide preliminary empirical support showing how organisms characterized by bounded rationality may generate short-term predictions by relying on ordinal patterns.

Fairly accurate predictor based on a number of factors. Highly authentic dialectic of lifetimes was used based on an iteration of several models from past-life studies. Based on the past-lives of Nathan Coppedge. Successfully predicts the exact range of past-lives. For example, 22 to 24 could mean 22 full past-lives and two half-lives or up to 48 half-lives at the price of 1/2 a life each, or it could mean the soul was sold at least once and there were zero to 21 full lives and zero to 46 half-lives.

Simple, good suggestions on what is an inventor's best idea based on the year in which they were alive. Mostly a history-based hint system. For example, Nathan Coppedge's best idea might be 'everything', then since his relevant year is 2013, his best idea is 'everything is technology'. However, the output depends on a range of years in history with any year acceptable back to about 7 million B.C.

... Sete de Setembro, 3165, 80230-901 Curitiba, PR, Brazil E-mail {suelen, felizari,lia}@cpgei.cefetpr.br {magatao, stebel, neves, lvrarruda, luders}@utfpr.edu.brbLogistic Division ... 5. F. Neves-Jr, L. Magat, SL Stebel, SN Boschetto, LC Felizari, DI Czaikowski, R. Rocha and PC ...