Tuesday, June 19, 2012


In the past few years, wireless sensor networks (WSNs) have been gaining significant attention because of their potentials of enabling of novel and attractive solutions in areas such as industrial automation, environmental monitoring, transportation business, health-care etc. If we add this collection of sensor-derived data to various Web-based social networks or virtual communities, blogs etc., there will be fabulous transitions among and around us. With the faster adoption of micro and nano technologies, everyday things are destined to become digitally empowered and smart in their operations and offerings. Thus the goal is to link smart materials, appliances, devices, federated messaging middleware, enterprise information systems and packages, ubiquitous services, handhelds, and sensors with one another smartly to build and sustain cool, charismatic and catalytic situation-aware applications. Clouds have emerged as the centralized, compact and capable infrastructure to deliver people-centric and context-aware services to users with all the qualities inherently. This long-term target demands that there has to be a cool connectivity and purposeful interactions between clouds and all these pervasive and minuscule systems. In this section, we explain about a robust and resilient a framework to enable this exploration by integrating sensor networks to clouds. But there are many challenges to enable this framework. The authors of this framework have proposed a pub-sub based model, which simplifies the integration of sensor networks with cloud based community-centric applications. Also there is a need for internetworking cloud providers in case of violation of service level agreement with users.

Traditional HPC approach like Sensor-Grid model can be used in this case, but setting up the infrastructure to deploy it so that it can scale out quickly is not easy in this environment. However, the cloud paradigm is an excellent move. But current cloud providers unfortunately did not address the issue of integrating sensor network with cloud applications and thus have no infrastructure to support this scenario. The virtual organization (VO) needs a place that can be rapidly deployed with social networking and collaboration tools, other specialized applications and tools that can compose sensor data and disseminate them to the VO users based on their subscriptions.

Here, the researchers need to register their interests to get various patients’ state (blood pressure, temperature, pulse rate etc.) from bio-sensors for largescale parallel analysis and to share this information with each other to find useful solution for the problem. So the sensor data needs to be aggregated, processed and disseminated based on subscriptions. On the other hand, as sensor data require huge computational power and storage, one cloud provider may not handle this requirement. This insists and induces for a dynamic collaboration with other cloud providers. The framework addresses the above issues and provides competent solutions.

To integrate sensor networks to cloud, the authors have proposed a contentbased pub-sub model. A pub/sub system encapsulates sensor data into events and provides the services of event publications and subscriptions for asynchronous data exchange among the system entities. MQTT-S is an open topic-based pub-sub protocol that hides the topology of the sensor network and allows data to be delivered based on interests rather than individual device addresses. It allows a transparent data exchange between WSNs and traditional networks and even between different WSNs.

In this framework, like MQTT-S, all of the system complexities reside on the broker’s side but it differs from MQTT-S in that it uses content-based pubsub broker rather than topic-based which is suitable for the application scenarios considered. When an event is published, it is transmitted from a publisher to one or more subscribers without the publisher having to address the message to any specific subscriber. Matching is done by the pub-sub broker outside of the WSN environment. In content-based pub-sub system, sensor data has to be augmented with meta-data to identify the different data fields. For example, a meta-data of a sensor value (also event) can be body temperature, blood pressure etc.

To deliver published sensor data or events to subscribers, an efficient and scalable event matching algorithm is required by the pub-sub broker. This event matching algorithm targets a range predicate case suitable to the application scenarios and it is also efficient and scalable when the number of predicates increases sharply. The framework is shown in figure 3.10. In this framework, sensor data are coming through gateways to a pub/sub broker. Pub/sub broker is required in the system to deliver information to the consumers of SaaS applications as the entire network is very dynamic. On the WSN side, sensor or actuator (SA) devices may change their network addresses at any time. Wireless links are quite likely to fail. Furthermore, SA nodes could also fail at any time and rather than being repaired, it is expected that they will be replaced by new ones. Besides, different SaaS applications can be hosted and run on any machines anywhere on the cloud. In such situations, the conventional approach of using network address as communication means between the SA devices and the applications may be very problematic because of their dynamic and temporal nature.

Moreover, several SaaS applications may have an interest in the same sensor data but for different purposes. In this case, the SA nodes would need to manage and maintain communication means with multiple applications in parallel. This might exceed the limited capabilities of the simple and low-cost SA devices. So pub-sub broker is needed and it is located in the cloud side because of its higher performance in terms of bandwidth and capabilities.

Source of Information : Wiley - Cloud Computing Principles and Paradigms
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