The Experts below are selected from a list of 11193 Experts worldwide ranked by ideXlab platform
Jean-paul Rodrigue - One of the best experts on this subject based on the ideXlab platform.
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The waves of Containerization: shifts in global maritime transportation
Journal of Transport Geography, 2014Co-Authors: David Guerrero, Jean-paul RodrigueAbstract:This paper provides evidence of the cyclic behavior of Containerization through an analysis of the phases of a Kondratieff wave (K-wave) of global container ports development. The container, like any technical innovation, has a functional (within transport chains) and geographical diffusion potential where a phase of maturity is eventually reached. Evidence from the global container port system suggests five main successive waves of Containerization with a shift of the momentum from advanced economies to developing economies, but also within specific regions. These waves are illustrative of major macroeconomic, technological and sometimes political shifts within the global economy. They do not explain the causes, but simply the consequences in the distribution in container traffic and growth (or decline). Yet, they provide strong evidence that Containerization has a cyclic behavior and that inflection points are eventually reached, marking the end of the diffusion of Containerization in a specific port or port range. Future expectations about the growth of Containerization thus need to be assessed within an economic cycle perspective instead of the rather linear perspectives.
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Looking inside the box: evidence from the Containerization of commodities and the cold chain
Maritime Policy & Management, 2014Co-Authors: Jean-paul Rodrigue, Theo NotteboomAbstract:Conventional investigations about containerized transportation tend to overlook the goods being carried to focus upon the associated modes and terminals. Containerization is entering a new phase in its global diffusion and adoption by freight distribution systems. The emerging phase of Containerization encompasses a complementarity with the commodity sector and the extraction of niche market opportunities to satisfy new demands. This phase is driven by a commodity-wise approach, which inherently creates an array of challenges. For instance, niche markets develop or disappear based on temporary market conditions, the balance of flows on trade routes, and the need for market size. Still, the nature of the commodities being carried is a fundamental element in the emerging Containerization of commodities. This article aims at analyzing this emerging niche in the Containerization process by 'looking inside the box'. It particularly unravels the dynamics for a number of commodities and demonstrates which role the container fulfills in these commodity markets. The underlying factors that enable the growth or decline of commodity-based niche markets in Containerization are discussed. It also looks at the dynamics of the specialized reefer market of cold chain logistics.
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The waves of Containerization: shifts in global maritime transportation
2013Co-Authors: David Guerrero, Jean-paul RodrigueAbstract:This paper provides evidence of the cyclic behavior of Containerization through an analysis of long, medium and short waves of container ports. The container, like any technical innovation, has a market and diffusion potential where a phase of maturity is eventually reached. Evidence from the global container port system suggests five successive major long waves of Containerization with a shift of the momentum from advanced economies to developing economies, but also within developed and developing economies. While long, medium and short wave patterns have been clearly identified within the global container port system, these waves are simply illustrative of major macroeconomic, technological and sometimes political shifts within the global economy. They do not explain the causes, but simply the consequences in the distribution in traffic and growth (or decline). Yet, they provide strong evidence that Containerization has a cyclic behavior illustrative of economic processes and that inflection points are eventually reached, marking the end of the diffusion of Containerization in a specific port or port range. Future expectations about the growth of Containerization thus need to be assessed within an economic cycle perspective instead of the rather linear perspectives in which Containerization is generally considered.
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The Waves of Containerization
2012Co-Authors: David Guerrero, Jean-paul RodrigueAbstract:This paper provides evidence of the cyclic behavior of Containerization through an analysis of long, medium and short waves of container ports. The container, like any technical innovation, has a market and diffusion potential where a phase of maturity is eventually reached. Evidence from the global container port system suggests five successive major long waves of Containerization with a shift of the momentum from advanced economies to developing economies, but also within developed and developing economies. While long, medium and short wave patterns have been clearly identified within the global container port system, these waves are simply illustrative of major macroeconomic, technological and sometimes political shifts within the global economy. They do not explain the causes, but simply the consequences in the distribution in traffic and growth (or decline). Yet, they provide strong evidence that Containerization has a cyclic behavior illustrative of economic processes and that inflection points are eventually reached, marking the end of the diffusion of Containerization in a specific port or port range. Future expectations about the growth of Containerization thus need to be assessed within an economic cycle perspective instead of the rather linear perspectives in which Containerization is generally considered.
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The future of Containerization: perspectives from maritime and inland freight distribution
GeoJournal, 2008Co-Authors: Theo Notteboom, Jean-paul RodrigueAbstract:As Containerization enters its peak growth years, its potential future developments over maritime and inland freight transport systems are being questioned. A series of issues can either further accelerate the adoption of Containerization worldwide or, alternatively, could impose an upper limit to the extraordinary contribution that containers have implied for logistics systems and global commodity chains. These mainly include macro-economic, technical/operational and governance factors. Future Containerization will be largely determined by interactions within and between four domains ranging from a functional to a spatial perspective. The logistical domain involves the functional organization of transport chains and their integration in supply chains. The transport domain involves the operation of transport services and intermodal operations. The infrastructural domain involves the provision and management of basic infrastructure for both links and nodes in the transport system. The locational domain relates to the geographical location of nodes and sites in the economic space and forms a basic element for their intrinsic accessibility in terms of centrality or intermediacy. It is underlined that the future of Containerization will dominantly be shaped by inland transport systems.
Encarnacion Rodriguez - One of the best experts on this subject based on the ideXlab platform.
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methodology to evaluate the environmental impact of urban solid waste Containerization system a case study
Journal of Cleaner Production, 2017Co-Authors: Javier Perez, Julio Lumbreras, Encarnacion RodriguezAbstract:Abstract Integrated systems for municipal solid waste (MSW) management have to be planned and designed to satisfy the needs of citizens and minimise the environmental impact of any of its stages: collection, transport and treatment. The collection step is usually performed through Containerization systems which are not analysed from the environmental impact perspective. Accordingly, this paper describes a methodology to evaluate the environmental impact of the urban Containerization systems by using the life cycle assessment (LCA) methodology. The methodology designed determines the environmental impact associated with the total Containerization of a city, as well as for each district. This methodology consists of three phases: i) detailed data collection for the city; ii) LCA for each Containerization system applied in the city; and iii) LCA aggregation for each district and for the city as a whole, including result discussion and conclusion extraction. Therefore, the methodology allows an assessment of the differences among districts and establishes a correlation among environmental impact, number of containers and collection effectiveness, as well as their relationship with depending demographic and socioeconomic variables. To verify the methodology, it has successfully been applied to the city of Madrid (Spain). Results show that: i) the environmental impact of the Containerization systems is mainly driven by the type of container employed and capacity allocation; ii) the container's environmental impact depends on the weight/volume ratio, the type and weight of each component materials and the container's lifetime; iii) the Containerization overcapacity in certain districts leads to a higher impact per capita; and iv) those districts with lower waste collection effectiveness (kg of waste collected per litre of container) or with higher Containerization capacity for the collection of MSW fractions whose collection is less effective (paper and cardboard), have a greater impact per mass of waste collected. The proposed methodology showed that its application to a city allows the analysis of the Containerization from the environmental perspective and gives a useful tool for decision makers to improve the environmental performance of the whole MSW management system.
Santonu Sarkar - One of the best experts on this subject based on the ideXlab platform.
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fitness aware Containerization service leveraging machine learning
IEEE Transactions on Services Computing, 2019Co-Authors: Sreekrishnan Venkateswaran, Santonu SarkarAbstract:Containerized deployment of microservices has gained immense traction across industries. To meet demand, traditional cloud providers offer container-as-a-service, where selection of the container and Containerization of workloads remain developer's responsibility. This task is arduous for a developer since the choice of containers across different cloud providers is many. Furthermore, there does not exist any mechanism using which one can compare and contrast the capabilities of containers across different providers. In this scenario, we envisage the need for a smart cloud broker that can automatically deploy a chosen IT service into the best-fit container environment mapped to performance requirements, from among the set of available underpinning brokered container hosting systems spread across multiple cloud providers. We propose a novel fitness-aware Containerization-as-a-service to achieve this. We show why a best-fit container selection process is operationally complex and time consuming, and how we heuristically prune the associated decision tree in two phases so that it becomes viable to implement this as an on-demand service. We propose a new metric called fitness quotient (FQ) to evaluate containers obtained from heterogeneous providers. We leverage machine learning techniques to inject automation into these two phases: unsupervised K-Means clustering in the first-level build-time phase to accurately classify IaaS cost and performance data, and polynomial regression during the second-level provisioning-time phase to discover relationships between SaaS performance and container strength.
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Best-Fit Containerization as a Brokered Service
2018 IEEE Intl Conf on Parallel & Distributed Processing with Applications Ubiquitous Computing & Communications Big Data & Cloud Computing Social Com, 2018Co-Authors: Santonu Sarkar, Sreekrishnan VenkateswaranAbstract:IT consumption is rapidly moving to an everything-as-a-Service (XaaS) model wherein a cloud broker, or in general, a digital marketplace, maintains a portfolio of infrastructure, platform and software services. In the meanwhile, Containerization of workloads and the immutable microservices paradigm of application software architecture has witnessed a dramatic upswing across industries. In this scenario, we see the need for a smart fulfillment engine within a cloud broker that can automatically deploy a chosen cataloged IT service into the best-performing container environment from among the set of available underpinning brokered container hosting systems. More broadly, the problem statement we address in this paper is to supply best-performing container deployment as a provisioning-time service to applications that are part of a broker's SaaS catalog, in an on-demand and pay-as-you-go manner. We show why this problem is operationally complex and time consuming, and how we heuristically prune the associated decision tree in two phases so that it becomes viable to implement this service on the fly during SaaS provisioning time. We also show that the utility of the algorithmic framework that we propose is not limited to the container fitness use case that we analyze in this paper; rather it can be extended to address a class of problems where overall time and cost complexity for provisioning-time decision making needs to be controlled under a given set of constraints. Our contribution can hence be seen as an abstraction framework for infrastructure consumption when viewed in the larger context of research devoted to simplifying the leverage of hybrid clouds.
Elisa Bertino - One of the best experts on this subject based on the ideXlab platform.
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overview of mobile Containerization approaches and open research directions
IEEE Symposium on Security and Privacy, 2017Co-Authors: Oyindamola Oluwatimi, Daniele Midi, Elisa BertinoAbstract:When a mobile device is used for both personal and business purposes, securing enterprise content and preserving employees' privacy are vital. Containerization is a promising approach to address such requirements.
Sreekrishnan Venkateswaran - One of the best experts on this subject based on the ideXlab platform.
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fitness aware Containerization service leveraging machine learning
IEEE Transactions on Services Computing, 2019Co-Authors: Sreekrishnan Venkateswaran, Santonu SarkarAbstract:Containerized deployment of microservices has gained immense traction across industries. To meet demand, traditional cloud providers offer container-as-a-service, where selection of the container and Containerization of workloads remain developer's responsibility. This task is arduous for a developer since the choice of containers across different cloud providers is many. Furthermore, there does not exist any mechanism using which one can compare and contrast the capabilities of containers across different providers. In this scenario, we envisage the need for a smart cloud broker that can automatically deploy a chosen IT service into the best-fit container environment mapped to performance requirements, from among the set of available underpinning brokered container hosting systems spread across multiple cloud providers. We propose a novel fitness-aware Containerization-as-a-service to achieve this. We show why a best-fit container selection process is operationally complex and time consuming, and how we heuristically prune the associated decision tree in two phases so that it becomes viable to implement this as an on-demand service. We propose a new metric called fitness quotient (FQ) to evaluate containers obtained from heterogeneous providers. We leverage machine learning techniques to inject automation into these two phases: unsupervised K-Means clustering in the first-level build-time phase to accurately classify IaaS cost and performance data, and polynomial regression during the second-level provisioning-time phase to discover relationships between SaaS performance and container strength.
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Best-Fit Containerization as a Brokered Service
2018 IEEE Intl Conf on Parallel & Distributed Processing with Applications Ubiquitous Computing & Communications Big Data & Cloud Computing Social Com, 2018Co-Authors: Santonu Sarkar, Sreekrishnan VenkateswaranAbstract:IT consumption is rapidly moving to an everything-as-a-Service (XaaS) model wherein a cloud broker, or in general, a digital marketplace, maintains a portfolio of infrastructure, platform and software services. In the meanwhile, Containerization of workloads and the immutable microservices paradigm of application software architecture has witnessed a dramatic upswing across industries. In this scenario, we see the need for a smart fulfillment engine within a cloud broker that can automatically deploy a chosen cataloged IT service into the best-performing container environment from among the set of available underpinning brokered container hosting systems. More broadly, the problem statement we address in this paper is to supply best-performing container deployment as a provisioning-time service to applications that are part of a broker's SaaS catalog, in an on-demand and pay-as-you-go manner. We show why this problem is operationally complex and time consuming, and how we heuristically prune the associated decision tree in two phases so that it becomes viable to implement this service on the fly during SaaS provisioning time. We also show that the utility of the algorithmic framework that we propose is not limited to the container fitness use case that we analyze in this paper; rather it can be extended to address a class of problems where overall time and cost complexity for provisioning-time decision making needs to be controlled under a given set of constraints. Our contribution can hence be seen as an abstraction framework for infrastructure consumption when viewed in the larger context of research devoted to simplifying the leverage of hybrid clouds.