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Cloud-assisted Wireless Body Area Networks
Ref: CISTER-TR-140804       Publication Date: Aug 2014

Cloud-assisted Wireless Body Area Networks

Ref: CISTER-TR-140804       Publication Date: Aug 2014

Abstract:
Wireless Body Area Networks (WBANs) have emerged as a promising technology for medical and non-medical applications. WBANs consist of a number of miniaturized, portable, and autonomous sensor nodes that are used for long-term health monitoring of patients. These sensor nodes continuously collect information of patients, which are used for ubiquitous health monitoring. In addition, WBANs may be used for managing catastrophic events and increasing the effectiveness and performance of rescue forces. The huge amount of data collected by WBAN nodes demands scalable, on-demand, powerful, and secure storage and processing infrastructure. Cloud computing is expected to play a significant role in achieving the aforementioned objectives. The cloud computing environment links different devices ranging from miniaturized sensor nodes to high-performance supercomputers for delivering people-centric and context-centric services to the individuals and industries. The possible integration of WBANs with cloud computing (WBAN-cloud) will introduce viable and hybrid platform that must be able to process the huge amount of data collected from multiple WBANs. This WBAN-cloud will enable users (including physicians and nurses) to globally access the processing and storage infrastructure at competitive costs. Because WBANs forward useful and life-critical information to the cloud – which may operate in distributed and hostile environments, novel security mechanisms are required to prevent malicious interactions to the storage infrastructure. Both the cloud providers and the users must take strong security measures to protect the storage infrastructure. The objective of this special issue was to collect high quality work in cloud-assisted WBANs, articulate new perspectives and highlight open research issues. We have received around twenty-three articles in different research domains such as resource allocation algorithms, fault tolerance and reliability, scalability and storage infrastructure, cloud monitoring, and security. All the papers were rigorously peer-reviewed by experts and six papers were finally recommended for publication.

Authors:
Sana Ullah
,
Athanasios Vasilakos
,
Han-Chieh Chao
,
Junichi Suzuki


Published in Information Science (INS), Elsevier, Volume 284, pp 81-83.

DOI:10.1016/j.ins.2014.07.050.

Notes: Impact Factor: 3.893



Record Date: 27, Aug, 2014