Network traffic efficiency analysis for logical clustering of flow-sensors
Rahim Rahmani, Hasibur Rahman, Theo Kanter · International Journal of Advancements in Computing Technology · 2013
In the current era, access to information has become ubiquitous for anything and anyone, and the trend will continue in the foreseeable future as well. Sensor networks have been an integral part of pervasive computing and are expected to play a pivotal role in the future Networked Society. Context information is ubiquitous due to the deployment of sensors in Internet infrastructure and availability to services. This corresponds to the phenomena where any situation can be sensed and analyzed anywhere. Services can access heterogeneous context information anywhere through the distributed acquisition and dissemination of sensor data assembled from physical objects. The novel approach of logical clustering is beneficial for heterogeneous interoperability of physical objects, thereby, heterogeneous contexts. The idea enables resources (data, services) to be shared among physically distributed objects. The approach provides topological sensor networks with scalability, robustness, mobility, heterogeneity support, adaptability to different contexts, etc. A performance study demonstrates feasibility and scalability, adaptability, heterogeneity, and robustness of the proposed approach. Computational efficiency plays a significant role so that network traffic does not encounter abrupt and frequent fluctuations. In this paper, further computational efficiency analysis in terms of network traffic for logical clustering is highlighted.