An Architecture for M2M Enabled Social Networks

Social Networks (SNs), such as Facebook, Twitter, Google+, are becoming more and more popular nowadays. People are now more connected than before. They share information, pictures, videos and news with their family and friends. However, sharing physical phenomena in SNs is still a manual process done by people themselves. For instance, people would like to share current health status, feelings, thoughts, weather or riding information with friends. The sharing of ambient information automatically in SNs can promote independent living. Moreover, it can enhance the autonomy and confidence of elderly people via continuous monitoring and health support. A set of biometric sensors, for example, placed within a patient body can inform a doctor about patient’s health status; hence the doctor can perform a remote diagnosis. Nowadays people are surrounded by devices like smartphone, sensors, cameras, computers and many other devices known as machines. These devices can automatically collect contextual information from the neighborhood. This thesis proposes an architecture for posting contextual information in SNs to support the automatic sharing of physical phenomena. In the proposed architecture, machines collect the contextual data through an overlay-based gateway to support scalability in terms of number of devices. Considering the resource-constrained devices, the architecture makes use of the Constrained Application Protocol (CoAP), a lightweight standard protocol. An SN processes that data into shareable information and disseminates it as appropriate within the users’ Community of Interests (COIs) (e.g., family, friends). A proof of concept prototype is developed to verify the feasibility of the proposed architecture and its performance has been partially evaluated

Designing and predicting QoS of a wireless system for medical telemetry

Guaranteeing high reliability and acceptable latency are major QoS considerations in the design of life-critical healthcare applications. To achieve those goals over error-prone wireless networks, proper error control is required. We propose a reference system model for wireless telemetry with medical-grade QoS. The system includes the combination of delay-predictable medium access control and interleaved forward error correction (FEC) based on Reed-Solomon (RS) coding. This combination is effective in correcting error bursts and bounding the service latency. However, variation in the delay incurred by RS decoding can lead to service dropout. We therefore determine the size of buffer required to absorb this jitter, and to stochastically guarantee seamless services over a fading channel, using a worst-case execution time analysis. But this buffering itself leads to an increase in service latency, which grows with the level of block interleaving. The QoS analysis tool which we have developed investigates this tradeoff, and hence it is effective in finding service parameters that simultaneously satisfy the requirements of reliability and latency in medical applications. �� 2012 IEEE