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MultiNets is a system supporting seamless switch-over between wireless interfaces on mobile devices in real-time. MultiNets is configurable to run in three different modes: (i) Energy Saving mode-for choosing the interface that saves themost energy based on the condition of the device, (ii) Offload mode-for offloading data traffic from the cellular toWiFi network, and (iii) Performance mode-for selecting the network for the fastest data connectivity. MultiNets also provides a powerful API that gives the application developers: (i) the choice to select a network interface to communicate with a specific server, and (ii) the ability to simultaneously transfer data over multiple network interfaces. MultiNets is modular, easily integrable, lightweight, and applicable to various mobile operating systems. We implement MultiNets on Android devices as a show case. MultiNets does not require any extra support from the network infrastructure and runs existing applications transparently. To evaluate MultiNets, we first collect data traces from 13 actual Android smartphone users over three months. We then use the collected traces to show that, by automatically switching to WiFi whenever it is available, MultiNets can offload on average 79.82% of the data traffic. We also illustrate that, by optimally switching between the interfaces, MultiNets can save on average 21.14 KJ of energy per day, which is equivalent to 27.4% of the daily energy usage. Using our API, we demonstrate that a video streaming application achieves 43-271% higher streaming rate when concurrently using WiFi and 3G interfaces. We deploy MultiNets in a real-world scenario and our experimental results show that depending on the user requirements, it outperforms the state-of-the-art Android system either by saving up to 33.75% energy, achieving near-optimal offloading, or achieving near-optimal throughput while substantially reducing TCP interruptions due to switching. [ABSTRACT FROM AUTHOR]

For many sensor network applications, such as military surveillance, it is necessary to provide full sensing coverage to a security-sensitive area while, at the same time, minimizing energy consumption and extending system lifetime by leveraging the redundant deployment of sensor nodes. In this paper, we propose a surveillance service for sensor networks based on a distributed energy-efficient sensing coverage protocol. In the protocol, each node is able to dynamically decide a schedule for itself to guarantee a certain degree-of-coverage (DOC) with average energy consumption inversely proportional to the node density. Several optimizations and extensions are proposed to enhance the basic design with a better load-balance feature and a longer network lifetime. We consider and address the impact of the target size and the unbalanced initial energy capacity of individual nodes to the network lifetime. Several practical issues such as the localization error, irregular sensing range, and unreliable communication links are addressed as well. Simulation shows that our protocol extends system lift-time significantly with low energy consumption. It outperforms other state-of-the-art schemes by as much as 50% reduction in energy consumption and as much as 130% increase in the half-life of the network. [ABSTRACT FROM AUTHOR]

The article focuses on opportunities and obligations for physical computing systems. Seamlessly integrating computing with the physical world via sensors and actuators, physical computing systems promise to give society an improved living standard, greater security, and unparalleled convenience and efficiency. To better understand physical computing's advantages, this article gives emphasis on three application areas. These include assisted living, emergency response systems for natural or man-made disasters, and protecting critical infrastructures at the national level.