System innovations in open WDM DCI networks

Increasingly, innovation na longer takes place within individual firms, but within networks of organizations. An important requirement tor such network-based innovations to come to fruition is that knowledge flows across organizational boundaries. Yet, it is not self-evident or easy to create and sustain knowledge flows within and across companies. This chapter present a framework for studying knowledge management in alliance network. This ramework is used in subsequent chapters to analyse five case studies of knowledge sharing and innovation in networks. This chapter starts with a brief review of existing literature on alliance network and knowledge management, Ieading to a conceptual model for studying knowledge management in networks. his conceptual model incorporates knowledgesharing problem solution to those problems, and the contingent effects of network and knowledge type. The chapter conclude with a short introduction to the five case studies.

Optimal transport network design for both traffic safety and risk equity considerations

The concept that separates the network's control and forwarding planes has emerged. Since this approach simplifies network management and speeds up network innovations, taking advantage of centralized control, however, the centralized control faces some challenges in large scale networks such as the performance, scalability, reliability. An effective approach to solve this problem is to design distributed architecture of SDN control plane. In this paper, we propose a distributed controller cluster scheme called Cluster-Controller based on the idea of the traditional distributed cluster to load balancing and network performance enhancement, gather the health status of the controller node and keep the network status and topology consistency in each controller nodes to improve services to the data plane. In the end, we prove the feasibility of the solution by experimental proof and show the experiment result.

A method is described for simplifying the optimum design of active networks that use operational amplifiers. The optimum design is based on minimization of the sensitivity of the steady-state frequency response to changes in amplifier gain.

The locus of innovation is not the individual firm anymore but increasingly the network in which the firm is embedded. Hence, in this paper innovation is investigated in the broader context of networks and applied to the traditional food sector. Networking refers to a process of identifying and acting on complementary interests with or without formal means of cooperation and plays an important role for the diffusion and adoption of innovations, because they increase the flow of information. Two main types of networks exist. Vertical networks relate to cooperation of partners belonging to the same chain. Meanwhile, horizontal networks refer to cooperation among firms which are primarily competitors. Data were collected during focus groups and in-depth interviews in three European countries: Belgium, Hungary, and Italy. In each country, data are collected from retailers/wholesalers, food manufacturers and suppliers in the beer, hard and half hard cheese, ham, sausage, or white paprika chain. In the investigated countries both vertical and horizontal networks exist. However, the intensity of using the network differs. On the one hand vertical networks are well developed based on quality assurance schemes and traceability, though these networks often face difficulties due to high lack of trust. On the other hand, horizontal networks are well developed when a producer consortium is involved. However, these networks can be inhibited through strong competition. The partners in traditional food networks focus mainly on innovation related to product characteristics such as new size, form and packaging without changing the traditional character of the product. The main barriers for innovation in the traditional food networks are the lack of understanding the benefits of networking activities for innovation, the lack of trust, the lack of knowledge of appropriate methods and skills, and the lack of financial and physical resources. Our study points out that successful SMEs use their networks to overcome lacks of knowledge and information and to create possibilities of joint use of resources.

Get PDF Email Share Share with Facebook Tweet This Post on reddit Share with LinkedIn Add to CiteULike Add to Mendeley Add to BibSonomy Get Citation Copy Citation Text M. De Leenheer, A. Koshibe, Y. Higuchi, N. Shiota, H. Wu, T. Furusawa, T. Tofigh, and G. Parulkar, "Open and Disaggregated Multi-Layer Networks," in Optical Fiber Communication Conference, OSA Technical Digest (online) (Optica Publishing Group, 2017), paper Tu3L.8. Export Citation BibTex Endnote (RIS) HTML Plain Text Citation alert Save article

The choice of an optimal neural network design for a given problem is addressed. A relationship between optimal network design and statistical model identification is described. A derivative of Akaike's information criterion (AIC) is given. This modification yields an information statistic which can be used to objectively select a ;best' network for binary classification problems. The technique can be extended to problems with an arbitrary number of classes.

Computer networks covered the entire world and a serious and new development has not formed for many years. But companies and consumer organizations complain about the failure to add new features to their networks and according to their need, like much of the works to be done automatically and they also like to develop and expand their networks on the software side so they do not need new expensive hardware for many of the activities and needs of their network. Analysis of the control layers and writing data in Software-Defined Network facilitate network management and accelerate innovation in network. In order to develop broad networks of SDN, often a large number controller is needed and located position of controllers in the SDN networks and can be raised as an important and basic issue in the field of SDN network and have impact on reliability of SDN networks. This paper focused on latency and reliability in SDN networks. The latency here means the delay in response to the request of data path that has a significant impact on network latency. In this paper it is shown that the number of controllers and their position can be effective on two measures; reliability and latency in SDN networks.

This paper presents cross entropy (CE) optimization for optimal design of water distribution networks (WDN) under demand uncertainty. In design of WDNs, it is desired to achieve a minimum cost WDN that provides higher reliability in meeting the demands. To achieve these goals, an optimization model is formulated for design of WDNs with an objective of minimizing the total cost of WDN subject to meeting the nodal demands at a specified system reliability, mass conservation and other physical constraints. The uncertainty in future water demands is modeled using the theory of fuzzy random variable (FRV). The water demand at each node is assumed to be following a normal distribution with a fuzzy mean, and 10 % (or 20 %) of the fuzzy mean as its standard deviation. The water demand is represented as a triangular fuzzy number with the random demand as its kernel, and the interval of ±5 % (or ±10 %) variation of the random demand as its support for two scenarios. The fuzzy random system reliability (R) of WDNs is defined on the basis of necessity measure to assess system performance under fuzzy random demands and crisp head requirements. The latin hypercube sampling method is adopted for sampling of uncertain demands. The methodology is applied to two WDNs, and optimization models are solved through cross entropy optimization for different levels of reliability, and generated tradeoffs between the cost and R. On comparing the solutions obtained with the proposed methodology with earlier reported solutions, it is noted that the proposed method is very effective in producing robust optimal solutions. On analyzing the tradeoffs between reliability and costs, the results show that negligence of uncertainty can lead to under design of the WDNs, and the cost increases steeply at higher levels of reliability. The results of the two case studies demonstrate that the presented CE based methodology is effective for fuzzy-probabilistic design of WDNs.

How does one quantitatively analyze intermodal passenger systems? Can high-speed rail links reduce costs to airline services? A method for analyzing transportation networks that involve more than one mode is presented. With intermodal costs considered in detail from both the operator and the traveler aspects (including time costs and service benefits and negative costs), optimal network designs that reduce overall costs for both stakeholders are created. As a case study, the potential impact on optimization of transportation network design for air and high-speed rail travel around the Iberian Peninsula in southwestern Europe is examined. Key aspects of the model design and assumptions, including the sparse and contrasting intermodal valuations used, weighting of the cost components, and the cost to implement inter modality are evaluated. The optimization procedure, using a linear Boolean mathematical program, shows that the benefits of intermodality are best captured when a more holistic intermodal product is offered, and that high-speed rail becomes progressively less competitive as traveler costs rise and there is a discernible shortage of traveler valuations of intermodal service attributes.

Abstract. This is the second part of a two-part paper considering a measurement network design based on a stochastic Lagrangian particle dispersion model (LPDM) developed by Marek Uliasz, in this case for South Africa. A sensitivity analysis was performed for different specifications of the network design parameters which were applied to this South African test case. The LPDM, which can be used to derive the sensitivity matrix used in an atmospheric inversion, was run for each candidate station for the months of July (representative of the Southern Hemisphere winter) and January (summer). The network optimisation procedure was carried out under a standard set of conditions, similar to those applied to the Australian test case in Part 1, for both months and for the combined 2 months, using the incremental optimisation (IO) routine. The optimal network design setup was subtly changed, one parameter at a time, and the optimisation routine was re-run under each set of modified conditions and compared to the original optimal network design. The assessment of the similarity between network solutions showed that changing the height of the surface grid cells, including an uncertainty estimate for the ocean fluxes, or increasing the night-time observation error uncertainty did not result in any significant changes in the positioning of the stations relative to the standard design. However, changing the prior flux error covariance matrix, or increasing the spatial resolution, did. Large aggregation errors were calculated for a number of candidate measurement sites using the resolution of the standard network design. Spatial resolution of the prior fluxes should be kept as close to the resolution of the transport model as the computing system can manage, to mitigate the exclusion of sites which could potentially be beneficial to the network. Including a generic correlation structure in the prior flux error covariance matrix led to pronounced changes in the network solution. The genetic algorithm (GA) was able to find a marginally better solution than the IO procedure, increasing uncertainty reduction by 0.3 %, but still included the most influential stations from the standard network design. In addition, the computational cost of the GA compared to IO was much higher. Overall the results suggest that a good improvement in knowledge of South African fluxes is available from a feasible atmospheric network, and that the general features of this network are invariable under several reasonable choices in a network design study.

Pipeline transport is the major means for large‐scale and long‐distance CO2 transport in a CO2 capture and sequestration (CCS) project. But optimal design of the pipeline network remains a challenging problem, especially when considering allocation of intermediate sites, like pump stations, and selection of pipeline routes. A superstructure‐based mixed‐integer programming approach for optimal design of the pipeline network, targeting on minimizing the overall cost in a CCS project is presented. A decomposition algorithm to solve the computational difficulty caused by the large size and nonlinear nature of a real‐life design problem is also presented. To illustrate the capability of our models. A real‐life case study in North China, with 45 emissions sources and four storage sinks, is provided. The result shows that our model and decomposition algorithm is a practical and cost‐effective method for pipeline networks design. © 2014 American Institute of Chemical Engineers AIChE J, 60: 2442–2461, 2014

The conference Program Committee has organized an exciting and balanced program comprising presentations from distinguished experts in the field, and important and wide-ranging contributions on state-of-the-art research that provides new insights into the latest innovations in Computational Intelligence, Communication Systems and Networks including modelling and computer simulation of a diverse range of topics within computer communication networks and their interaction with computational intelligence techniques.

Recent advances in Compact and wireless embedded Systems coupled with the technological innovations in Micro Electro Mechanical Systems(MEMS), Wireless Communications and networks paved the way for the development of small, resource constrained devices called Sensor Nodes (SNs). Performance of Sensor Node is highly dependent on the effective and efficient usage of the available limited resources with it, leading to maximum lifetime of Wireless Sensor Network (WSN) which is a primary concern of WSNs. The depletion of a SN energy leads to change in topology of WSNs often over a period of time. Therefore, protocols which consider the dynamic nature of WSNs are crucial for improving the network lifetime. In this paper, we propose bio inspired Ant Colony optimization based Self healing routing scheme inspired by swarm Intelligence technique to improve lifetime of a WSN.

Based on a literature review, this paper classifies network capability into network vision capability, network constructing capability, and network management capability and constructs a model with explorative innovation and exploitative innovation being the mediating variables to analyze the influence of the three dimensions of network capabilities on innovation performance. We obtain 257 effective samples through questionnaire and verify every influencing path. Our findings show that the three dimensions of network capability have a positive effect on innovation performance, clear innovation strategy helps to improve innovation performance, different network capability structures result in different innovation strategy forms, and false innovation strategy forms weaken the effect of network capability on innovation performance.