Research on Applications of Information Fusion Technology in WSNs

The wireless sensor networks (WSNs) link the virtual information world and the objective physical world together which changed the interacting mode between human and the nature. This kind of networks can work in the unattended or severe environment for a long time. For this advantage, WSN has important studying value and wide market outlook in many domains such as national defense and military, industries and agriculture, city management system, environment detective and so on. However, there are some defects for the WSN. For example, if its energy is enough for the system, if the working life is long enough, or the saving performance is not good. For this, the WSNs need the information fusion technology for better effect. To different environments, we should use different fusion algorithms, in this paper, we have analyzed the applications of three main algorithms at present in the WSNs. To these algorithms, there are corresponding resolutions in different environments

Reconfigurable middleware architectures for large scale sensor networks

Wireless sensor networks, in an effort to be energy efficient, typically lack the high-level abstractions of advanced programming languages. Though strong, the dichotomy between these two paradigms can be overcome. The SENSIX software framework, described in this dissertation, uniquely integrates constraint-dominated wireless sensor networks with the flexibility of object-oriented programming models, without violating the principles of either. Though these two computing paradigms are contradictory in many ways, SENSIX bridges them to yield a dynamic middleware abstraction unifying low-level resource-aware task reconfiguration and high-level object recomposition. Through the layered approach of SENSIX, the software developer creates a domain-specific sensing architecture by defining a customized task specification and utilizing object inheritance. In addition, SENSIX performs better at large scales (on the order of 1000 nodes or more) than other sensor network middleware which do not include such unified facilities for vertical integration