Providing adapted e-health services, applications, and platforms responds to a growing need for medical institutions like hospitals or even homes. Patients with long-term conditions, elderly, and dependent persons need to receive e-health services and assistance in a simple, continuous, and nonintrusive way. When the e-health ecosystem meets the needs of targeted people, and gains their acceptance, provided services help tackle the problems that face the world's population nowadays such as dependency, aging, and healthcare for all. According to the United Nations projections, in 2050, the old-age dependency ratio of the population aged over 65 years will be ~51.70%. This situation points to an issue of developing autonomic healthcare systems and platforms that help people manage their own health with new services and better adapt institutionally based services. Different standards can be used within the e-health ecosystem hence the network interoperability has to be considered carefully in the design of context-aware applications and services. Heterogeneity is present at different levels, and is still an open issue in e-health systems. In addition to the heterogeneity of patients' profiles and service characteristics, the health environment involves a wide range of required sensors and actuators (e.g., blood pressure and temperature, insulin delivery, appliance control, and presence sensors) that can be sometimes very close to the user like in Body Area Networks (BAN). Sensors usually use different wireless access methods that need to work together and communicate with the rest of the infrastructure (if it exists): gateways, servers, local smart objects, or with the intelligence existing in the medical institution, home, or in the cloud [4]. Due to the strong environmental heterogeneity where e-health services are provided, mechanisms of making autonomic decisions (e.g., diagnostics, continuous monitoring, alerts, and assistance) have to be identified and studied on different levels. For a given service or application, the automatic identification of required sensors and actuators should be ensured and tailored to the context of the person (e.g., health status, mobility, and dependency degree), and the characteristics/constraints of the communication technology and the platform being used. Other open issues concern the deployment and placement of sensors in the communication architecture. Service deployment should be optimized to guarantee the best network coverage, coordination between sensors and middleware or gateways, possible attachment to the network infrastructure, and delay tolerant networking aspects. Cohabitation of different access methods and communication technologies of sensors and other devices involves sensor/device discovery, network