Modern society has become increasingly reliant on mobile networks for their communication needs. Such networks are characterized by their dynamic, heterogeneous, complex, and data intensive nature, which makes them more amenable to automated optimization performed using "computational intelligence" (CI) techniques rather than manual optimization. CI techniques—which subsume multidisciplinary techniques from machine learning, optimization theory, game theory, control theory, and meta-heuristics—have a rich history in terms of being deployed in networking. Looking ahead, greater integration of CI into mobile networking architectures will likely be an essential component of the future of mobile networking, and will play a leading role in the upcoming 5th generation (5G) wireless mobile networks. It is anticipated that future mobile networks will have characteristics of cognitive networks that will show intelligent network-wide behavior to solve problems such as routing, scheduling, traffic, capacity, coverage and heterogeneous network optimization, etc.
Realizing this vision of the future-generation mobile networking environment requires the seamless integration of CI into the frameworks used for mobile network optimization. From the perspective of mobile networking, CI techniques can be used to propose intelligent solutions that optimize problems such as scheduling and routing, traffic, capacity, coverage and power optimization for mobile networks (current 4G and the future 5G systems). In particular, CI techniques will likely play an important role in future 5G wireless networks since the traditional self-organizing network (SON) techniques deployed for 3G and 4G would not suffice for 5G, keeping in view the stringent requirements of exceptionally high data rates and extremely low latency in the future 5G technology. New mechanisms need to developed that can optimize the capital expenditure (CAPEX) and the operating expenditure (OPEX) of future mobile networks—which will be challenging since the stringent performance requirements of future mobile networks such as 5G add to the network complexity, which will likely make the system management more costly.
With the future of mobile networks linked invariably with the wide support for multiple heterogeneous technologies, the problem of heterogeneous network optimization is of paramount importance for the success of mobile networking. It is foreseen that future wireless networks will allow everything to connect with everything—and mobile networks will play an important role in enabling the vision of Internet of Things (IoT). We can use CI techniques in conjunction with techniques such as Network Function Virtualization (NFV) and Software Defined Networking (SDN) to flexibly optimize the performance and operating costs of the future networks. It is anticipated that mobile network optimization performed using CI will leverage the huge amount of network data (or Big Data) that can be harnessed to optimize in real-time the various performance metrics (in particular the network traffic loads) and realize an exclusive SON for future communication technologies (particularly 5G). The heterogeneity and the dynamic nature of the current and future substrate networks, upon which different networks can be instantiated (thanks to NFV, light weight operating systems, and new virtualization technologies such as Docker’s containers), emphasize the need for cooperative communication among different parts of the overall communication network and optimal, real-time, and efficient resource sharing and allocation.
The aim of this special issue is to bring together researchers from the diverse communities of wireless networking, mobile networking, and computational intelligence and seek to curate the state-of-art work in developing CI-based solutions to problems related to mobile network optimization. Papers are solicited on novel concepts, models, methodologies, and designs of CI-enhanced network models, architectures, and protocols for mobile network optimization.
For more Information: Mobile Network Optimization
We live in a world with growing disparity between the lives of rich and poor. This difference is starkest when one compares the health facilities afforded to the rich living in developed countries and those available to the unprivileged in the developing world. Healthcare in the developing world is fraught with numerous problems—such as lack of health infrastructure and professionals and increasingly limited health coverage. In recent years, the field of health informatics has made great strides towards the improvement of public health systems in the developing world through augmentation of traditional health facilities using state-of-the-art Information and Communication Technologies (ICT). Through real-world deployment of these technologies, there is real hope that the health industry in the developing world will progress from its current, largely dysfunctional state to one that is more effective, personalized, and cost-efficient for all stakeholders. One of the most promising health informatics trends—buoyed by the rapid adoption of mobile phone technology throughout the world—is m-health (mobile-health). Such connected health informaticscan usher a new era of personalized health analytics, with the potential to transform healthcare in the developing world.
In conjunction with m-health many other important health informatics trends are also emerging. Exponentially growing heterogeneous data, with the help of big data analytics, has the potential to provide descriptive, predictive and prescriptive insights into future individual and population healthcare needs. Such systems could enhance the overall process of monitoring, diagnosis, and prognosis of chronic diseases. In particular, there is an immense potential for exploiting Artificial Intelligence (AI) and Machine Learning (ML) based health informatics in combination with cloud computing, and crowdsourcing for processing big health data and providing novel health services such as remote health diagnostics.
The aim of this Special Section in IEEE Access on “Health Informatics for the Developing World’’ is to present a snapshot of state-of-the-art technology in this important field. Our aim is to catalyze a convergence of growing research interest in health informatics from diverse fields such as ICT for development (ICTD); telemedicine; m-health; e-health; big data for development; biomedical engineering; human computer interaction (HCI), and to present a holistic integration of such approaches in this Special Section. Papers are solicited on novel concepts, models/architecture, and methodologies of health informatics, with a special focus on the viability of such approaches for the resource-constrained developing world.
For more Information: Health Informatics for the Developing World
IEEE CICARE 2017 is the first Symposium of its kind, established since 2013, that brings together leading research and clinical scientists, engineers, practitioners, technology and solution providers to discuss state-of-the-art in theory and practice of computational intelligence, for addressing the growing scale and complexity of real-world healthcare and e-health problems. The Symposium will also feature Panel discussions to outline future research directions and challenges in this emerging multi-disciplinary field.
IEEE CICARE 2017 is being held as part of the IEEE Symposium Series on Computational Intelligence (SSCIâ€™2017), Honolulu, Hawaii, USA from Nov. 27 to Dec 1, 2017. The IEEE SSCI is a flagship annual international conference on computational intelligence sponsored by the IEEE Computational Intelligence Society.
For more Information: Computational Intelligence in Healthcare and E-health