Optimal mobility-aware admission control in content delivery networks

This paper addresses the problem of mobility management in Content Delivery Networks (CDN). We introduce a CDN architecture where admission control is performed at mobility aware access routers. We formulate a Markov Modulated Poisson Decision Process for access control that captures the bursty nature of data and packetized traffic together with the heterogeneity of multimedia services. The optimization of performance parameters, like the blocking probabilities and the overall utilization, is conducted and the structural properties of the optimal solutions are also studied. Heuristics are proposed to encompass the computational difficulties of the optimal solution when several classes of multimedia traffic are considered

Phenotypic mixing and hiding may contribute to memory in viral quasispecies

Background. In a number of recent experiments with food-and-mouth disease virus, a deleterious mutant, was found to avoid extinction and remain in the population for long periods of time. This observation was called quasispecies memory. The origin of quasispecies memory is not fully understood. Results. We propose and analyze a simple model of complementation between the wild type virus and a mutant that has an impaired ability of cell entry. The mutant will go extinct unless it is recreated from the wild type through mutations. However, under phenotypic mixing-and-hiding as a mechanism of complementation, the time to extinction in the absence of mutations increases with increasing multiplicity of infection (m.o.i.). The mutant's frequency at equilibrium under selection-mutation balance also increases with increasing m.o.i. At high m.o.i., a large fraction of mutant genomes are encapsidated with wild-type protein, which enables them to infect cells as efficiently as the wild type virions, and thus increases their fitness to the wild-type level. Moreover, even at low m.o.i. the equilibrium frequency of the mutant is higher than predicted by the standard quasispecies model, because a fraction of mutant virions generated from wild-type parents will also be encapsidated by wild-type protein. Conclusions. Our model predicts that phenotypic hiding will strongly influence the population dynamics of viruses, particularly at high m.o.i., and will also have important effects on the mutation--selection balance at low m.o.i. The delay in mutant extinction and increase in mutant frequencies at equilibrium may, at least in part, explain memory in quasispecies populations.Comment: 10 pages pdf, as published by BM

Energy-Efficient selective activation in Femtocell Networks

Provisioning the capacity of wireless networks is difficult when peak load is significantly higher than average load, for example, in public spaces like airports or train stations. Service providers can use femtocells and small cells to increase local capacity, but deploying enough femtocells to serve peak loads requires a large number of femtocells that will remain idle most of the time, which wastes a significant amount of power. To reduce the energy consumption of over-provisioned femtocell networks, we formulate a femtocell selective activation problem, which we formalize as an integer nonlinear optimization problem. Then we introduce GREENFEMTO, a distributed femtocell selective activation algorithm that deactivates idle femtocells to save power and activates them on-the-fly as the number of users increases. We prove that GREENFEMTO converges to a locally Pareto optimal solution and demonstrate its performance using extensive simulations of an LTE wireless system. Overall, we find that GREENFEMTO requires up to 55% fewer femtocells to serve a given user load, relative to an existing femtocell power-saving procedure, and comes within 15% of a globally optimal solution

Network recovery from massive failures under uncertain knowledge of damages

This paper addresses progressive network recovery under uncertain knowledge of damages. We formulate the problem as a mixed integer linear programming (MILP), and show that it is NP-Hard. We propose an iterative stochastic recovery algorithm (ISR) to recover the network in a progressive manner to satisfy the critical services. At each optimization step, we make a decision to repair a part of the network and gather more information iteratively, until critical services are completely restored. Three different algorithms are used to find a feasible set and determine which node to repair, namely, 1) an iterative shortest path algorithm (ISR-SRT), 2) an approximate branch and bound (ISR-BB) and 3) an iterative multi-commodity LP relaxation (ISR-MULT). Further, we have modified the state-of-the-Art iterative split and prune (ISP) algorithm to incorporate the uncertain failures. Our results show that ISR-BB and ISR- MULT outperform the state-of-the-Art 'progressive ISP' algorithm while we can configure our choice of trade-off between the execution time, number of repairs (cost) and the demand loss. We show that our recovery algorithm, on average, can reduce the total number of repairs by a factor of about 3 with respect to ISP, while satisfying all critical deman

Adaptation dynamics of the quasispecies model

We study the adaptation dynamics of an initially maladapted population evolving via the elementary processes of mutation and selection. The evolution occurs on rugged fitness landscapes which are defined on the multi-dimensional genotypic space and have many local peaks separated by low fitness valleys. We mainly focus on the Eigen's model that describes the deterministic dynamics of an infinite number of self-replicating molecules. In the stationary state, for small mutation rates such a population forms a {\it quasispecies} which consists of the fittest genotype and its closely related mutants. The quasispecies dynamics on rugged fitness landscape follow a punctuated (or step-like) pattern in which a population jumps from a low fitness peak to a higher one, stays there for a considerable time before shifting the peak again and eventually reaches the global maximum of the fitness landscape. We calculate exactly several properties of this dynamical process within a simplified version of the quasispecies model.Comment: Proceedings of Statphys conference at IIT Guwahati, to be published in Praman

Recombination dramatically speeds up evolution of finite populations

We study the role of recombination, as practiced by genetically-competent bacteria, in speeding up Darwinian evolution. This is done by adding a new process to a previously-studied Markov model of evolution on a smooth fitness landscape; this new process allows alleles to be exchanged with those in the surrounding medium. Our results, both numerical and analytic, indicate that for a wide range of intermediate population sizes, recombination dramatically speeds up the evolutionary advance

Assessment of air management strategies on particulate number and size distributions from a 2-stroke compression-ignition engine operating with gasoline Partially Premixed Combustion concept

[EN] The newly designed partially premixed combustion concept has demonstrated its potential to reduce nitrogen oxides and particulate matter emissions combined with highly indicated efficiencies. However, it is highly dependent of the ignition characteristics of the fuel and the air/fuel mixture preparation. Therefore, the proper selection of an injection strategy, of the combustion chamber design and of the air management strategy are critical to ensuring successful partially premixed combustion operation in the full engine map. The objective of the present investigation is to evaluate the use of multiple air management strategies over the air/fuel effective equivalence ratio (feff) and cylinder charge reactivity and its consequent impact on particle number emissions and particle size distribution. Tests were carried out in a newly designed 2-stroke high-speed direct-injection compression-ignition engine operating with partially premixed combustion concept using 95-research-octane-number gasoline fuel. A scanning mobility particle sizer was used to measure the size distribution of engine-exhaust particles in the range from 6.3 to 237 nm. Three different steady-state operation modes in terms of indicated mean effective pressure and engine speed were investigated. The experiments showed an increase in the particle number emissions and a progressive shift in the particle size toward larger sizes, increasing the accumulation-mode particles and reducing the nucleation-mode particles with the decrease in the differential pressure between intake and exhaust (DP) and the valve overlap period. Finally, the particle formation process was limited by the increase in the exhaust gas recirculation rate.Bermúdez, V.; Ruiz, S.; Novella Rosa, R.; Soto-Izquierdo, L. (2018). Assessment of air management strategies on particulate number and size distributions from a 2-stroke compression-ignition engine operating with gasoline Partially Premixed Combustion concept. International Journal of Engine Research. 1-22. https://doi.org/10.1177/1468087418802706S12

Estimasi Value At Risk (VaR) pada Portofolio Saham dengan Copula

Investasi merupakan salah satu cara yang banyakdilakukan orang untuk mencapai keuntungan di masa mendatang. Saham sebagaisalah satu financial asset menjadisalah satu alternatif banyak orang untuk melakukan investasi. Return yang diperoleh dalam berinvestasisaham lebih tinggi dibandingkan berinvestasi pada perbankan, maka resiko yangditanggung apabila seseorang berinvestasi saham juga lebih tinggi. Penelitianini menggunakan metode Copula untuk mengestimasi Value at Risk (VaR) pada returnsaham Indofood Sukses Makmur (INDF), Telekomunikasi Indonesia (TLKM), GudangGaram (GGRM), Bank Rakyat Indonesia (BBRI), dan Astra International (ASII) padaperiode 1 September 2005 hingga 30 November 2010. Penelitian ini menggunakanpemodelan ARMA-GARCH untuk mendapatkan residual GARCH (1,1) yang selanjutnyadigunakan untuk pemodelan copula dan estimasi VaR. Penelitian ini menunjukkan bahwa pemodelan copula claytonsebagai model copula terbaik mampu menangkap heavy tail lebih baik berdasarkan VaR yang dihasilkan