Agent Based Context Aware Data Aggregation and Dissemination in Distributed Multimedia Sensor Networks

Being equipped with appropriate multimedia sensor nodes, DMSNs can enable detection of object, temperature and identification of the location of fire attack in the forest. Sensor nodes deployed in forest environment enables to gather context information such as air pressure, temperature, object awareness, location of fire, fire condition (emergency level or non emergency level), and energy awareness about each node. Data aggregation plays an important role to conserve the network life of DMSN. Hence, in this paper we propose an software agent based energy efficient context aware data aggregation and dissemination in DMSN for the targeted area. The proposed model considers the context information such as temperature, air-pressure, energy, object awareness and helps in identifying the location of fire attack in the forest. Static and mobile software agents are used along with context awareness to improve the performance of the proposed scheme. To test the operation, proposed scheme is simulated using NS2. The performance of the proposed scheme is evaluated by considering some of the parameters such as energy consumption, routing overhead, rate of redundancy of data, aggregation time and rate of dissemination of data. © 2017 IEEE

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201