mobile and cloud computing are converging as the prominent technologies that are leading the change to the post personal computing (PC) era. Computational offloading and data binding are the core techniques that foste...
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ISBN:
(纸本)9781479944248
mobile and cloud computing are converging as the prominent technologies that are leading the change to the post personal computing (PC) era. Computational offloading and data binding are the core techniques that foster to elastically augment the capabilities of low-power devices, such as smartphones. mobile applications may be bonded to cloud resources by following a task delegation or code offloading criteria. In a delegation model, a handset can utilize the cloud in a service-oriented manner to delegate asynchronously a resource-intensive mobile task by direct invocation of the service. In contrast, in an offloading model, a mobile application is partitioned and analyzed so that the most computational expensive operations at code level can be identified and offloaded to a remote cloud-based surrogate. We compared in this paper, the mobile cloud computing models for offloading and delegation. We utilized our own frameworks for computational offloading and data binding in the analysis. While in principle, offloading and delegation are viable methods to augment the capabilities of the mobile devices with cloud power, they enrich the mobile applications from different perspectives at diverse computational scales.
In this paper, we present a QoS-Aware node Selection Algorithm (QASA) for routing protocols to be suitable for a particular class of opportunistic networks, when applied to the Vehicular Ad hoc Networks. Our algorithm...
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In this paper, we present a QoS-Aware node Selection Algorithm (QASA) for routing protocols to be suitable for a particular class of opportunistic networks, when applied to the Vehicular Ad hoc Networks. Our algorithm aims to select the next-hop vehicle to communicate with, by exploiting the “bridging approach” for message forwarding i.e. , vehicles on the east (west) select from west (east). The QoS metrics that are being optimized are the throughput in the network, and packets end-to-end delay. In order to provide the best network performance, the algorithm utilizes a probabilistic rebroadcasting scheme based on different network parameters including vehicle density, inter-vehicle distance, and the transmission range for the vehicles. Moreover, QASA utilizes a transmission range-based metric that can be changed as per application requirements, whether it is high throughput or minimum end-to-end delay. Simulation results show the effectiveness of our approach in terms of improved QoS metrics in different vehicular network scenarios.
The last decade has seen explosive growth in the development of mobile applications. This has increased the demand on the wireless communication services. The capability to achieve wireless access anywhere, anytime, a...
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The last decade has seen explosive growth in the development of mobile applications. This has increased the demand on the wireless communication services. The capability to achieve wireless access anywhere, anytime, and anyplace has become common expectation as it provides significant flexibility and freedom in mobility. But to achieve global mobility in heterogeneous networks for any mobile device requires seamless connectivity using vertical handoff. Since none of the existing wireless frameworks provide practical solutions for vertical handoff. End-to-End Vertical Handoff (E2EVH) proposed in this paper offers a new concept to perform vertical handoff between heterogeneous wireless networks. To deliver network services without interruption, E2EVH present a novel design to monitor the network availability, it then picks the best accessible network for application layer. Since this approach relies only on existing technologies, deployed protocols and lightweight calculations, our approach can be easily implemented. In this paper, we present a proof-of-concept of E2EVH, and preliminary simulation results using OPNET Modeler 14.5. The results for different tested scenarios indicate the effectiveness of the proposed approach. Future research activities will integrate several additional wireless technologies that are presented and discussed in the paper.
In a wireless mobilecomputing system such as ad hoc network or sensor network, it is very difficult to manage resources - the precious bandwidth shared by the mobile terminals and the energy in each mobile terminal -...
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In a wireless mobilecomputing system such as ad hoc network or sensor network, it is very difficult to manage resources-the precious bandwidth shared by the mobile terminals and the energy in each mobile terminal-in ...
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In a wireless mobilecomputing system such as ad hoc network or sensor network, it is very difficult to manage resources-the precious bandwidth shared by the mobile terminals and the energy in each mobile terminal-in an efficient manner, due to the lack of network infrastructure support. The difficulties are aggravated by the fact that the wireless link is highly unreliable with high-error rate and bursty errors, and thus, is a CSI (Channel State Information) dependent time-varying function. In this paper, we consider two important issues in mobilecomputingsystems-routing in wireless ad hoc network and energy management in sensor network. We argue that the time-varying property of the wireless link can have a great influence on these two issues, and propose two schemes-channel adaptive routing in ad hoc network and channel adaptive energy management in sensor network under such CSI fluctuating environment. As indicated in our numerical studies, our proposed schemes outperform other algorithms without channel adaptation in that higher network throughput and energy efficiency are achieved in their respective application scenarios.
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