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Mobile crowd sensing enables large-scale sensing of the physical world at low cost by leveraging the available sensors on the mobile phones. One of the key factors for the success of mobile crowd sensing is uploading the sensing data to the cloud promptly. Traditional data uploading strategies leveraging whenever available networks may incur extra data cost, impact phone performance,, drain battery...
The latest increase in number of smart user mobile devices and user expectations for high-quality rich media services has determined a growing demand for network resources, putting pressure on the existing network infrastructure. Dense Heterogeneous Networks (DenseNets) are a promising solution to this problem, supported by various individual networks and different technologies deployed within the...
Energy consumption and mobile data cost are two key factors affecting users’ willingness to participate in mobile crowd-sensing tasks. While data-plan (DP) users are mostly concerned with energy consumption, non-data-plan (NDP) users are more sensitive to data cost. Traditional ways of data uploading in mobile crowdsensing tasks often go to two extremes: either in real time or completely offline after...
Partitioning and offloading some parts of mobile applications onto remote servers is a promising approach to extend the battery life of mobile devices. However, since available network bandwidths vary in a wireless environment, static partitionings proposed by previous works with a fixed bandwidth assumption are unsuitable for mobile platforms, while dynamic partitionings result in high overhead due...
Although battery capacities keep increasing, the execution demands of modern mobile devices continue to outstrip their battery lives. As a result, battery life is bound to remain a key constraining factor in the design of mobile applications. To save battery power, mobile applications are often partitioned to offload parts of their execution to a remote server. However, partitioning an application...
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