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As mobile crowdsourcing techniques are steering many smart-city and Internet-of-Things applications, a new challenge of signal source localization problem arises, which is to infer the locations of signal sources based on crowdsourced data. It will benefit real-world applications such as WiFi advisory systems by locating WiFi access points and urban noise monitoring systems by locating noise sources...
This paper exploits smartphones to design a transportation activity survey system that investigates when, where and how people travel in an urban area. In such a system, the essential requirement is collecting and processing big data which will raise two critical issues, energy-conservation and scalability. To address the former issue, the GPS sleeping interval of a smart-phone is controlled by the...
This paper considers storage management in an isolated WSN, under the constraint that the storage space per node is limited. We formulate the memory spaces of these sensor nodes as a distributed storage system. Assuming that there is a sink in the WSN that will be visited by mobile mules intentionally (e.g., pre-arranged buses) or occasionally (e.g., non-pre-arranged taxis), we address three issues:...
An inherent concern for a wireless sensor network (WSN) is the unbalanced energy consumption problem, where sensors closer to the sink are more likely to exhaust their energy faster than other nodes. To mitigate this problem, this paper considers including some resource-rich mobile nodes, called mobile data-pumps, to conduct data relaying from static sensors to the sink. The network thus becomes a...
While wireless sensor networks (WSNs) are typically targeted at large-scale deployment, due to many practical or inevitable reasons, a WSN may not always remain connected. In this paper, we consider the possibility that a WSN may be spatially separated into multiple subnetworks. Data gathering, which is a fundamental mission of WSN, thus may rely on a mobile mule (ldquomulerdquo for short) to conduct...
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