Green and friendly media transmission algorithms for wireless body sensor networks

Multimedia Tools and Applications - Video transmission is considered as a quite significant step towards health monitoring of the emergency patients during any critical incident. However, the...     

A lightweight portable intrusion detection communication system for auditing applications

The goal of this paper is to develop, deploy, test, and evaluatea a lightweight portable intrusion detection system (LPIDS) over wireless networks by adopting two different string matching algorithms: Aho‐Corasick algorithm and Knuth‐Morris‐Pratt algorithm (KMP). Thus, this research contributes in three ways. First, an efficient and lightweight IDS (LPIDS) is proposed. Second, the LPIDS was developed, implemented, tested, and evaluated using Aho‐Corasick and KMP on two different hardware platforms: Wi‐Fi Pineapple and Raspberry Pi. Third, a comparative analysis of proposed LPIDS is done in terms of network metrics such as throughput, power consumption, and response time with regard to their counterparts. Additionally, the proposed LPIDS is suggested for consultants while performing security audits. The experimental results reveal that Aho‐Corasick performs better than KMP throughout the majority of the process, but KMP is typically faster in the beginning with fewer rules. Similarly, Raspberry Pi shows remarkably higher performance than Wi‐Fi Pineapple in all of the measurements. Moreover, we compared the throughput between LPIDS and Snort, it is observed and analyzed that former has significantly higher throughput than later when most of the rules do not include content parameters. This paper concludes that due to computational complexity and slow hardware processing capabilities of Wi‐Fi Pineapple, it could not become suitable IDS in the presence of different pattern matching strategies. Finally, we propose modification of Snort to increase the throughput of the system.     

Green media-aware medical IoT system

Rapid proliferation in state-of-the art technologies has revolutionized the medical market for providing urgent, effective and economical health facilities to aging society. In this context media (i.e., video) transmission is considered as a quite significant step during first hour of the emergency for presenting a big and better picture of the event. However, the energy hungry media transmission process and slow progress in battery technologies have become a major and serious problem for the evolution of video technology in medical internet of things (MIoT) or internet of medical things (IoMT). So, promoting Green (i.e., energy-efficient) transmission during voluminous and variable bit rate (VBR) video in MIoT is a challenging and crucial problem for researchers and engineers. Therefore, the need arose to conduct research on Green media transmission techniques to cater the need of upcoming wearable healthcare devices. Thus, this research contributes in two distinct ways; first, a novel and sustainable Green Media Transmission Algorithm (GMTA) is proposed, second, a mathematical model and architecture of Green MIoT are designed by considering a 8-min medical media stream named, ‘Navigation to the Uterine Horn, transection of the horn and re-anastomosis’ to minimize transmission energy consumption in media-aware MIoT, and to develop feasible media transmission schedule for sensitive and urgent health information from physian to patients and vice vers through extremely power hungry natured wearable devices. The experimental results demonstrate that proposed GMTA saves energy up to 41%, to serve the community.