Convergence of MANET and WSN in IoT Urban Scenarios

被引:247
作者
Bellavista, Paolo [1 ]
Cardone, Giuseppe [1 ]
Corradi, Antonio [1 ]
Foschini, Luca [1 ]
机构
[1] Univ Bologna, Dept Comp Sci & Engn, I-40136 Bologna, Italy
关键词
Mobile ad hoc networks; routing protocols; wireless sensor networks; WIRELESS; INTERNET; THINGS;
D O I
10.1109/JSEN.2013.2272099
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Ubiquitous smart environments, equipped with low-cost and easy-deployable wireless sensor networks (WSNs) and widespread mobile ad hoc networks (MANETs), are opening brand new opportunities in wide-scale urban monitoring. Indeed, MANET and WSN convergence paves the way for the development of brand new Internet of Things (IoT) communication platforms with a high potential for a wide range of applications in different domains. Urban data collection, i.e., the harvesting of monitoring data sensed by a large number of collaborating sensors, is a challenging task because of many open technical issues, from typical WSN limitations (bandwidth, energy, delivery time, etc.) to the lack of widespread WSN data collection standards, needed for practical deployment in existing and upcoming IoT scenarios. In particular, effective collection is crucial for classes of smart city services that require a timely delivery of urgent data such as environmental monitoring, homeland security, and city surveillance. After surveying the existing WSN interoperability efforts for urban sensing, this paper proposes an original solution to integrate and opportunistically exploit MANET overlays, impromptu, and collaboratively formed over WSNs, to boost urban data harvesting in IoT. Overlays are used to dynamically differentiate and fasten the delivery of urgent sensed data over low-latency MANET paths by integrating with latest emergent standards/specifications for WSN data collection. The reported experimental results show the feasibility and effectiveness (e. g., limited coordination overhead) of the proposed solution.
引用
收藏
页码:3558 / 3567
页数:10
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