234 research outputs found

    CANS: Composable, adaptive network services infrastructure

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    Ubiquitous access to sophisticated internet services from diverse end devices across heterogeneous networks requires the injection of additional functionality into the network to handle protocol conversion, data transcoding, and in general bridge disparate network portions. Several researchers have proposed infrastructures for injecting such functionality; however, many challenges remain before these can be widely deployed. CANS is an application-level infrastructure for injecting application-specific components into the network that focuses on three such challenges: (a) efficient and dynamic composition of individual components; (b) distributed adaptation of injected components in response to system conditions; and (c) support for legacy applications and services. The CANS network view comprises applications, stateful services, and data paths built from mobile soft-state objects called drivers. Both services and data paths can be dynamically created and reconfigured: a planning and event propagation model assists in distributed adaptation, and a flexible type-based composition model dictates how new services and drivers are integrated with existing components. Legacy components plug into CANS using an interception layer that virtualizes network bindings and a delegation model. This paper describes the CANS architecture, and a case study involving a shrink-wrapped client application in a dynamically changing network environment where CANS improves overall user experience.

    Energy Conservation Potential Assessment Method for Table Grapes Supply Chain

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    Energy consumption is one of the most crucial issues in the table grapes supply chain. However, the potential for energy conservation assessment is still limited because of the complexity of the process. The aim of this paper is to propose an energy conservation potential assessment method in order to increase energy consumption transparency and help managers take appropriate energy conservation measures to reduce the energy consumption in the table grapes supply chain. The conservation potential assessment in three kinds of the supply chain modes (the normal chain, the cold insulation chain and the cold chain), were realized by integrating the actual energy consumption investigated with the unified energy consumption per unit energy factor that represents the energy consumption throughout the entire product lifecycle. According to the comprehensive analysis of the energy consumption compared with the energy conservation potential in actual supply chain of table grapes, the proposed energy conservation potential assessment method could provide a unified method for evaluating the energy conservation potential in different supply chain mode of table grapes. The energy conversation potential in cold insulation chain, which was about 0.985, was the highest and that in cold chain, which was about 0.935, was the smallest. However, the cold chain was still the optimal supply chain for the table grapes because of the characteristics of the longest storage shelf life and the lowest quality decay, and the cold chain energy consumption would be further reduced by adopting the more advanced refrigeration and preservation technologies. The proposed energy conservation potential assessment method could be extended for other supply chain applications to evaluate their own energy conservation potential, and thus, reduce their energy consumption

    Carbon Footprint Constrained Profit Maximization of Table Grapes Cold Chain

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    Low-carbon production is one of the dominating issues in the sustainable development of the food industry with high energy consumption, especially in the table grapes cold chain. The aim of this paper is to propose a profit maximization strategy of table grapes cold chain by integrating the carbon footprint to improve the low-carbon production and sustainability of the cold chain system. The carbon footprint was evaluated by life cycle assessment (LCA) in entire cold chain system of table grapes, and the economic order quantity (EOQ) model was used to develop the profit maximization model with minimal carbon footprint and to maintain the optimal balance between stock and cost. The profit optimization performance, the sensitivity performance and the influencing factors of the decay rate, the carbon emission price, and the distance and carbon emission coefficient in refrigerated transport were analyzed according to the profit maximization model and the inventory data in actual cold chain investigated. The sensitivity performance analysis illustrated that the selling price had the highest sensitivity, and the carbon emission coefficient in storage had the lowest sensitivity. The comprehensive analysis results indicated that there is an optimal combination point between the economy and environment in actual cold chain, which not only reduced the carbon emission, but also had minimal impact on the profit in cold chain. The enterprises should integrate the carbon footprint cost into the profit maximization once the carbon emission tax is levied. The proposed strategy of the profit maximization with carbon footprint constraint is also suitable for improving profit maximization of other low-carbon supply chain applications
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