Joint Optimization of Energy Consumption and Data Transmission in Smart Body Area Networks.

In Wireless Body Area Networks (BAN), energy consumption, energy harvesting, and data communication are the three most important issues. In this paper, we develop an optimal allocation algorithm (OAA) for sensor devices, which are carried by or implanted in human body, harvest energy from their surroundings, and are powered by batteries. Based on the optimal allocation algorithm that uses a two-timescale Lyapunov optimization approach, we design a framework for joint optimization of network service cost and network utility to study energy, communication, and allocation management at the network edge. Then, we formulate the utility maximization problem of network service cost management based on the framework. Specifically, we use OAA, which does not require prior knowledge of energy harvesting to decompose the problem into three subproblems: battery management, data collection amount control and transmission energy consumption control. We solve these through OAA to achieve three main goals: (1) balancing the cost of energy consumption and the cost of data transmission on the premise of minimizing the service cost of the devices; (2) keeping the balance of energy consumption and energy collection under the condition of stable queue; and (3) maximizing network utility of the device. The simulation results show that the proposed algorithm can actually optimize the network performance.

A Secure and Decentralized Trust Management Scheme for Smart Health Systems.

The Internet of Things (IoT) growth is extremely fast and it now has found its way to healthcare applications too. Many smart health gadgets and devices are helping practitioners in collecting medical information and monitoring patients. In this distributed system, information or service is sometimes shared and used by other devices. Considering the importance of health-related information and the decisions made based on it, there should be some sort of assurance on the security and quality of the services or information provided. Trust management is an efficient means of promoting application security and reliability in these cases. However, due to some limitations that are specific to IoT, traditional trust evaluation algorithms cannot be employed or do not yield satisfactory results. In this paper, evidence theory is exploited to design a decentralized service-oriented trust management model for healthcare IoT. A measure of evidence distance is used to reward well-behaving healthcare service/information providers as well as referrers and punish malicious entities. In this context-aware model, trust is estimated based on direct experiences and indirect feedbacks of recommenders. The process runs in two contexts; trust to healthcare service and trust to recommendation. When personal direct experience does not exist, trust to a source or service is estimated by applying the combinatorial laws of evidence theory and integrating indirect trust values. The proposed model is secure against bad-mouthing, good-mouthing, and on-off attacks due to its dynamic parameters and using the concept of evidence distance. Our results confirm the robustness and efficiency of this scheme.

Legal framework for health cloud: A systematic review.

BACKGROUND: The complicated nature of cloud computing encompassing internet-based technologies and service models for delivering IT applications, processing capability, storage, and memory space brings along challenging problems. Some issues such as information security, privacy, and legal aspects of cloud computing may become challenging while cross passing with another complex domain like healthcare. OBJECTIVES: The present study was conducted to report the results of a systematic literature review on the legal aspects of health cloud. METHOD: The original English papers published in Pub Med, Scopus, Web of Science, and IEEE Digital Library databases were extracted, among which1582 were related to the legal aspects of health cloud environment and were selected using predefined search strings. CONCLUSION: Through the review process, effective factors in relation to a health cloud legal framework were identified and accordingly, a proper design was developed for this domain. Next, the identified factors were confirmed and adjusted by mapping the contents of the selected papers to different categories and subcategories under the proposed framework. Five Main categories like the issues related to the compliance, data protection, Identity Credential Access Management (ICAM), ownership, and quality of service were selected as the basic pillars in the proposed framework. Finally, 22 papers were selected, among which 19 were mapped to the compliance issues, 18 the issues related to "Data protection" were addressed, and 14 "Identity Credential Access Management (ICAM)" was discussed. Fifteen Papers were mapped to "Data ownership" and "Quality of service" categories. Some papers were found to present some solutions in all the mentioned areas; however, most of them have addressed only a few issues.