Distributed Cache Management for Context-Aware Services in Large-Scale Networks

Author(s):  
Masaaki Takase ◽  
Takeshi Sano ◽  
Kenichi Fukuda ◽  
Akira Chugo
Author(s):  
Davy Preuveneers ◽  
Koen Victor ◽  
Yves Vanrompay ◽  
Peter Rigole ◽  
Manuele Kirsch Pinheiro

In recent years, many researchers have studied context-awareness to support non-intrusive adaptability of context-aware applications. Context-aware applications benefit from emerging technology that connects everyday objects and provides opportunities to collect and use context information from various sources. Context-awareness helps to adapt continuously to new situations and to turn a static computing environment into a dynamic ecology of smart and proactive applications. In this chapter, we present our framework that manages and uses context information to adapt applications and the content they provide. We show how application adaptation can be handled at the composition level, by reconfiguring, redeploying and rewiring components, e.g. to fall back into reduced functionality mode when redeploying an application on a handheld. The key features of our context-aware adaptation framework notonly include local adaptations of context-aware applications and content, but also the addressing of context in large scale networks and the contextaware redeployment of running applications in a distributed setting. We discuss how adaptation is handled along various levels of abstraction (user, content, application, middleware, network) and illustrate the flexibility of context-aware content and application adaptation by means of a realistic use case scenario.


2018 ◽  
Vol 33 (1-2) ◽  
pp. 1-34
Author(s):  
Mohammad Rashedul Hasan ◽  
Anita Raja ◽  
Ana Bazzan

2006 ◽  
Author(s):  
Mikio Kataoka ◽  
Kunihiko Toumura ◽  
Hideki Okita ◽  
Junji Yamamoto ◽  
Toshiaki Suzuki

2021 ◽  
Author(s):  
Miguel Dasilva ◽  
Christian Brandt ◽  
Marc Alwin Gieselmann ◽  
Claudia Distler ◽  
Alexander Thiele

Abstract Top-down attention, controlled by frontal cortical areas, is a key component of cognitive operations. How different neurotransmitters and neuromodulators flexibly change the cellular and network interactions with attention demands remains poorly understood. While acetylcholine and dopamine are critically involved, glutamatergic receptors have been proposed to play important roles. To understand their contribution to attentional signals, we investigated how ionotropic glutamatergic receptors in the frontal eye field (FEF) of male macaques contribute to neuronal excitability and attentional control signals in different cell types. Broad-spiking and narrow-spiking cells both required N-methyl-D-aspartic acid and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor activation for normal excitability, thereby affecting ongoing or stimulus-driven activity. However, attentional control signals were not dependent on either glutamatergic receptor type in broad- or narrow-spiking cells. A further subdivision of cell types into different functional types using cluster-analysis based on spike waveforms and spiking characteristics did not change the conclusions. This can be explained by a model where local blockade of specific ionotropic receptors is compensated by cell embedding in large-scale networks. It sets the glutamatergic system apart from the cholinergic system in FEF and demonstrates that a reduction in excitability is not sufficient to induce a reduction in attentional control signals.


2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Siddharth Arora ◽  
Alexandra Brintrup

AbstractThe relationship between a firm and its supply chain has been well studied, however, the association between the position of firms in complex supply chain networks and their performance has not been adequately investigated. This is primarily due to insufficient availability of empirical data on large-scale networks. To addresses this gap in the literature, we investigate the relationship between embeddedness patterns of individual firms in a supply network and their performance using empirical data from the automotive industry. In this study, we devise three measures that characterize the embeddedness of individual firms in a supply network. These are namely: centrality, tier position, and triads. Our findings caution us that centrality impacts individual performance through a diminishing returns relationship. The second measure, tier position, allows us to investigate the concept of tiers in supply networks because we find that as networks emerge, the boundaries between tiers become unclear. Performance of suppliers degrade as they move away from the focal firm (i.e., Toyota). The final measure, triads, investigates the effect of buying and selling to firms that supply the same customer, portraying the level of competition and cooperation in a supplier’s network. We find that increased coopetition (i.e., cooperative competition) is a performance enhancer, however, excessive complexity resulting from being involved in both upstream and downstream coopetition results in diminishing performance. These original insights help understand the drivers of firm performance from a network perspective and provide a basis for further research.


2009 ◽  
Vol 10 (1) ◽  
pp. 19 ◽  
Author(s):  
Tatsunori B Hashimoto ◽  
Masao Nagasaki ◽  
Kaname Kojima ◽  
Satoru Miyano

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