Inter-organizational collaboration among health and social care: TRT©, a transactional approach

Inter-organizational collaboration (IOC) supported by information and communication technologies (ICTs) faces challenges on many fronts in 21st century England as well as globally. Between the somewhat desirable ideal of 'joined up' systems providing efficient services to customers and clients on one side of the continuum, and the costs and risk factors associated with integrating data or constructing large databases on the other side, a fundamental tension exists. This paper addresses this issue in two parts. Firstly, it argues that there is a way forward for information sharing among heterogeneous organizations which does not involve the integration of systems, interoperability, joined up recordkeeping, database linkage, or construction of yet another large database. Transactions in Real Time© (TRT©), the transaction by transaction information sharing approach, satisfies all the requirements of each collaborating organization for information sharing. Secondly, this paper briefly considers the future of IOC among health and social care and possible pathways forward through this uncertain area. The health and social care information sharing transaction is often unique among the particular transaction situation, and the micro and macro environments

Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing

[EN] Internet of Things (IoT) is a developing technology for supporting heterogeneous physical objects into smart things and improving the individuals living using wireless communication systems. Recently, many smart healthcare systems are based on the Internet of Medical Things (IoMT) to collect and analyze the data for infectious diseases, i.e., body fever, flu, COVID-19, shortness of breath, etc. with the least operation cost. However, the most important research challenges in such applications are storing the medical data on a secured cloud and make the disease diagnosis system more energy efficient. Additionally, the rapid explosion of IoMT technology has involved many cyber-criminals and continuous attempts to compromise medical devices with information loss and generating bogus certificates. Thus, the increase in modern technologies for healthcare applications based on IoMT, securing health data, and offering trusted communication against intruders is gaining much research attention. Therefore, this study aims to propose an energy-efficient IoT e-health model using artificial intelligence with homomorphic secret sharing, which aims to increase the maintainability of disease diagnosis systems and support trustworthy communication with the integration of the medical cloud. The proposed model is analyzed and proved its significance against relevant systems.Prince Sultan University, Riyadh Saudi Arabia, (SEED-CCIS-2021{85}) under Artificial Intelligence & Data Analytics Research Lab. CCIS.Rehman, A.; Saba, T.; Haseeb, K.; Marie-Sainte, SL.; Lloret, J. (2021). Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing. Energies. 14(19):1-15. https://doi.org/10.3390/en14196414S115141

Energy-Efficient Resource Allocation in Multiuser OFDM Systems with Wireless Information and Power Transfer

In this paper, we study the resource allocation algorithm design for multiuser orthogonal frequency division multiplexing (OFDM) downlink systems with simultaneous wireless information and power transfer. The algorithm design is formulated as a non-convex optimization problem for maximizing the energy efficiency of data transmission (bit/Joule delivered to the users). In particular, the problem formulation takes into account the minimum required system data rate, heterogeneous minimum required power transfers to the users, and the circuit power consumption. Subsequently, by exploiting the method of time-sharing and the properties of nonlinear fractional programming, the considered non-convex optimization problem is solved using an efficient iterative resource allocation algorithm. For each iteration, the optimal power allocation and user selection solution are derived based on Lagrange dual decomposition. Simulation results illustrate that the proposed iterative resource allocation algorithm achieves the maximum energy efficiency of the system and reveal how energy efficiency, system capacity, and wireless power transfer benefit from the presence of multiple users in the system.Comment: 6 pages. The paper has been accepted for publication at the IEEE Wireless Communications and Networking Conference (WCNC) 2013, Shanghai, China, Apr. 201

Astral: An algebraic approach for sensor data stream querying

The use of sensor based applications is in expansion in many contexts. Sensors are involved at several scales ranging from the individual (e.g. personal monitoring, smart homes) to regional and even world wide contexts (i.e. logistics, natural resource monitoring and forecast). Easy and efficient management of data streams produced by a large number of heterogeneous sensors is a key issue to support such applications. Numerous solutions for query processing on data streams have been proposed by the scientific community. Several query processors have been implemented and offer heterogeneous querying capabilities and semantics. Our work is a contribution on the formalization of queries on data streams in general, and on sensor data in particular. This paper proposes the Astral algebra; defining operators on temporal relations and streams which allow the expression of a large variety of queries. This proposal extends several aspects of existing results: it presents precise formal definitions of operators which are (or may be) semantically ambiguous and it demonstrates several properties of such operators. Such properties are an important result for query optimization as they are helpful in query rewriting and operator sharing. This formalization deepens the understanding of the queries and facilitates the comparison of the semantics implemented by existing systems. This is an essential step in building mediation solutions involving heterogeneous data stream processing systems. Cross system data exchange and application coupling would be facilitated. This paper discusses existing proposals, presents the Astral algebra, several properties of the operators

Blockchain leveraged task migration in body area sensor networks

Blockchain technologies emerging for healthcare support secure health data sharing with greater interoperability among different heterogeneous systems. However, the collection and storage of data generated from Body Area Sensor Net-works(BASN) for migration to high processing power computing services requires an efficient BASN architecture. We present a decentralized BASN architecture that involves devices at three levels; 1) Body Area Sensor Network-medical sensors typically on or in patient's body transmitting data to a Smartphone, 2) Fog/Edge, and 3) Cloud. We propose that a Patient Agent(PA) replicated on the Smartphone, Fog and Cloud servers processes medical data and execute a task offloading algorithm by leveraging a Blockchain. Performance analysis is conducted to demonstrate the feasibility of the proposed Blockchain leveraged, distributed Patient Agent controlled BASN. © 2019 IEEE.E

Using XML views to improve data-independence of distributed applications that share data

The development and maintenance of distributed software applications that support and make efficient use of heterogeneous networked systems is very challenging. One aspect of the complexity is that these distributed applications often need to access shared data, and different applications sharing the data may have different needs and may access different parts of the data. Maintenance and modification are especially difficult when the underlying structure of the data is changed for new requirements. The eXtensible Markup Language, or XML, has emerged as the universal standard for exchanging and externalizing data. It is also widely used for information modeling in an environment consisting of heterogeneous information sources. CORBA is a distributed object technology allowing applications on heterogeneous platforms to communicate through commonly defined services providing a scalable infrastructure for today\u27s distributed systems. To improve data independence, we propose an approach based on XML standards and the notion of views to develop and modify distributed applications which access shared data. In our approach, we model the shared data using XML, and generate different XML views of the data for different applications according to the DTDs of the XML views and the application logic. When the underlying data structure changes, new views are generated systematically. We adopt CORBA as the distributed architecture in our approach. Our thesis is that: views to support data-independence of distributed computing applications can be generated systematically from application logic, CORBA IDL and XML DTD.Dept. of Computer Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2002 .L86. Source: Masters Abstracts International, Volume: 41-04, page: 1113. Adviser: Richard Frost. Thesis (M.Sc.)--University of Windsor (Canada), 2002

Efficient and portable multi-tasking for heterogeneous systems

Modern computing systems comprise heterogeneous designs which combine multiple and diverse architectures on a single system. These designs provide potentials for high performance under reduced power requirements but require advanced resource management and workload scheduling across the available processors. Programmability frameworks, such as OpenCL and CUDA, enable resource management and workload scheduling on heterogeneous systems. These frameworks fully assign the control of resource allocation and scheduling to the application. This design sufficiently serves the needs of dedicated application systems but introduces significant challenges for multi-tasking environments where multiple users and applications compete for access to system resources. This thesis considers these challenges and presents three major contributions that enable efficient multi-tasking on heterogeneous systems. The presented contributions are compatible with existing systems, remain portable across vendors and do not require application changes or recompilation. The first contribution of this thesis is an optimization technique that reduces host-device communication overhead for OpenCL applications. It does this without modification or recompilation of the application source code and is portable across platforms. This work enables efficiency and performance improvements for diverse application workloads found on multi-tasking systems. The second contribution is the design and implementation of a secure, user-space virtualization layer that integrates the accelerator resources of a system with the standard multi-tasking and user-space virtualization facilities of the commodity Linux OS. It enables fine-grained sharing of mixed-vendor accelerator resources and targets heterogeneous systems found in data center nodes and requires no modification to the OS, OpenCL or application. Lastly, the third contribution is a technique and software infrastructure that enable resource sharing control on accelerators, while supporting software managed scheduling on accelerators. The infrastructure remains transparent to existing systems and applications and requires no modifications or recompilation. In enforces fair accelerator sharing which is required for multi-tasking purposes