A Fast ILP-Based Heuristic for the Robust Design of Body Wireless Sensor Networks

D’Andreagiovanni, Fabio; Nardin, Antonella; Natalizio, Enrico

doi:10.1007/978-3-319-55849-3_16

Cited by 11 publications

(9 citation statements)

References 33 publications

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“…1 , 2 are constant scalars. The proposed algorithm minimizes the right-hand side of the Lyapunov drift in Equation (13). From Equation (11), we can get…”

Section: Conflicts Of Interestmentioning

confidence: 99%

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An Optimal Online Resource Allocation Algorithm for Energy Harvesting Body Area Networks

Chen

Guo

et al. 2018

Algorithms

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Abstract:In Body Area Networks (BANs), how to achieve energy management to extend the lifetime of the body area networks system is one of the most critical problems. In this paper, we design a body area network system powered by renewable energy, in which the sensors carried by patient with energy harvesting module can transmit data to a personal device. We do not require any a priori knowledge of the stochastic nature of energy harvesting and energy consumption. We formulate a user utility optimization problem. We use Lyapunov Optimization techniques to decompose the problem into three sub-problems, i.e., battery management, collecting rate control and transmission power allocation. We propose an online resource allocation algorithm to achieve two major goals: (1) balancing sensors' energy harvesting and energy consumption while stabilizing the BANs system; and (2) maximizing the user utility. Performance analysis addresses required battery capacity, bounded data queue length and optimality of the proposed algorithm. Simulation results verify the optimization of algorithm.

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“…1 , 2 are constant scalars. The proposed algorithm minimizes the right-hand side of the Lyapunov drift in Equation (13). From Equation (11), we can get…”

Section: Conflicts Of Interestmentioning

confidence: 99%

“…BAN is composed of some small and mobile sensors with communication capability, whose design problem is often addressed through mathematical optimization techniques (e.g., [7,[11][12][13]). By implanting these sensors into the human body or wearing them on the human body, they form a local area network.…”

Section: Introductionmentioning

confidence: 99%

An Optimal Online Resource Allocation Algorithm for Energy Harvesting Body Area Networks

Chen

Guo

et al. 2018

Algorithms

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“…D'Andreagiovanni et al extended their preliminary work [20] by the new Integer Linear Programming (ILP) heuristic to solve the design problem. Furthermore, new techniques detailed in [21] fix the variables expressing routing decisions and employ an initial deterministic fixing phase of the variables modeling the activation of relay nodes. Experiments conducted in this work show that the proposed approach outperforms the existing optimization solvers' strategies.…”

Section: Related Workmentioning

confidence: 99%

Enhanced IoT-Based End-To-End Emergency and Disaster Relief System

Arbia

Alam

Kadri

et al. 2017

JSAN

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Abstract:In this paper, we present a new enhancement for an emergency and disaster relief system called Critical and Rescue Operations using Wearable Wireless sensors networks (CROW 2 ). We address the reliability challenges in setting up a wireless autonomous communication system in order to offload data from the disaster area (rescuers, trapped victims, civilians, media, etc.) back to a command center. The proposed system connects deployed rescuers to extended networks and the Internet. CROW 2 is an end-to-end system that runs the recently-proposed Optimized Routing Approach for Critical and Emergency Networks (ORACE-Net) routing protocol. The system integrates heterogeneous wireless devices (Raspberry Pi, smart phones, sensors) and various communicating technologies (WiFi IEEE 802.11n, Bluetooth IEEE 802.15.1) to enable end-to-end network connectivity, which is monitored by a cloud Internet-of-Things platform. First, we present the CROW 2 generic system architecture, which is adaptable to various technologies integration at different levels (i.e., on-body, body-to-body, off-body). Second, we implement the ORACE-Net protocol on heterogeneous devices including Android-based smart phones and Linux-based Raspberry Pi devices. These devices act as on-body coordinators to collect information from on-body sensors. The collected data is then pushed to the command center thanks to multi-hop device-to-device communication. Third, the overall CROW 2 system performance is evaluated according to relevant metrics including end-to-end link quality estimation, throughput and end-to-end delay. As a proof-of-concept, we validate the system architecture through deployment and extracted experimental results. Finally, we highlight motion detection and links' unavailability prevention based on the recorded data where the main factors (i.e., interference and noise) that affect the performance are analyzed.

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“…D'Andreagiovanni et al extended their preliminary work [18] by new integer linear programming (ILP) heuristic to solve the design problem. The new techniques detailed in [23] do not only fix the variables expressing routing decisions, but also employ an initial deterministic fixing phase of the variables modeling the activation of relay nodes. Experiment conducted by this work shows that the proposed approach outperforms the existing optimization solvers strategies and the results recorded in [18].…”

Section: Overview Of Key Wwn Applications and Implementationsmentioning

confidence: 99%

Communication Challenges in on-Body and Body-to-Body Wearable Wireless Networks—A Connectivity Perspective

et al. 2017

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Wearable wireless networks (WWNs) offer innovative ways to connect humans and/or objects anywhere, anytime, within an infinite variety of applications. WWNs include three levels of communications: on-body, body-to-body and off-body communication. Successful communication in on-body and body-to-body networks is often challenging due to ultra-low power consumption, processing and storage capabilities, which have a significant impact on the achievable throughput and packet reception ratio as well as latency. Consequently, all these factors make it difficult to opt for an appropriate technology to optimize communication performance, which predominantly depends on the given application. In particular, this work emphasizes the impact of coarse-grain factors (such as dynamic and diverse mobility, radio-link and signal propagation, interference management, data dissemination schemes, and routing approaches) directly affecting the communication performance in WWNs. Experiments have been performed on a real testbed to investigate the connectivity behavior on two wireless communication levels: on-body and body-to-body. It is concluded that by considering the impact of above-mentioned factors, the general perception of using specific technologies may not be correct. Indeed, for on-body communication, by using the IEEE 802.15.6 standard (which is specifically designed for on-body communication), it is observed that while operating at low transmission power under realistic conditions, the connectivity can be significantly low, thus, the transmission power has to be tuned carefully. Similarly, for body-to-body communication in an indoor environment, WiFi IEEE 802.11n also has a high threshold of end-to-end disconnections beyond two hops (approximatively 25 m). Therefore, these facts promote the use of novel technologies such as 802.11ac, NarrowBand-IoT (NB-IoT) etc. as possible candidates for body-to-body communications as a part of the Internet of humans concept.

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A Fast ILP-Based Heuristic for the Robust Design of Body Wireless Sensor Networks

Cited by 11 publications

References 33 publications

An Optimal Online Resource Allocation Algorithm for Energy Harvesting Body Area Networks

An Optimal Online Resource Allocation Algorithm for Energy Harvesting Body Area Networks

Enhanced IoT-Based End-To-End Emergency and Disaster Relief System

Communication Challenges in on-Body and Body-to-Body Wearable Wireless Networks—A Connectivity Perspective

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