## 3 Air Pollution Monitoring System Infrastructure
### e-Science Infrastructure Based on Grid Computing  
#### 3.3.1 e-Science and Grid  
Today's research depends increasingly on communication and cooperation. More and more, scientists need to share resources through distributed computing and databases, gaining access to specialized and expensive facilities by developing national and international collaborations. Often, this involves integrating complex data repositories, terascale computing and high performance visualization now available in many research areas.  
The term Enhanced Science, or e-Science is'refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet. Typically, a feature of such collaborative scientific enterprises is that they will require access to very large data collections, very large scale computing resources and high performance visualization back to the individual user scientists.' [10]  
In this description, as in many others, e-Science is closely associated with Grid computer network architecture that enables much of the global collaboration considered basic to e-Science [11; 12]. The Grid is an architecture proposed to bring all these issues together and make a reality of such a vision for e-Science. [PERSON] and [PERSON], inventors of the Globus approach to the Grid, define the Grid as an enabler for Virtual Organizations: 'An infrastructure that enables flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions and resources.' It is important to recognize that resource in this context includes computational systems and data storage and specialized experimental facilities [10].  
Currently, some research groups are working on the e-Science architecture design and development, including the TIME-EACM [13] project based at the University of Cambridge Computer Laboratory, and the North East Regional e-Science Centre (NEReSC) [14] based at the University of Newcastle, etc. Most of their researches address the issues of real-time data query, distributed data access and heterogeneity management.  
However, MoDisNet aims to develop and deliver a making system for pervasive mobile environmental sensors. The work is based on developing a 'Mobile Sensor Data Grid' for processing, integrating, and analyzing heterogeneous sensor data. Based on the former research 'Discovery Net EPSRC e-Science Pilot Project' [8], we have developed a service-based infrastructure for scientific informatics that supports the analysis of data generated from statically located urban pollution monitoring sensors. However, the support of a high-number of mobile sensors within a dynamic environment presents new challenges to Discovery Net. The number and nature of such sensor networks mean that in most instances the data cannot realistically be warehoused and then analyzed off-line. A new paradigm is required where much of the analysis is performed within the network itself using pervasive computing technologies such as the Peer-to-Peer (P2P) model [15]. This is feasible as even rudimentary sensors will have processing capability and sensor-to-sensor protocols can be extended to support the dynamic real-time execution of analysis and mining algorithms.