International Journal of Computer Science & Emerging Technologies (E-ISSN: 2044-6004) 19 Volume 1, Issue 3, October 2010 Real Time Tactic for Knowledge Placement & Management in Wireless Sensor Networks Arabinda Nanda*, Saroj Kumar Rout*, Amiya Kumar Rath† * Department of Computer Science, Krupajal Engineering College, Bhubaneswar, India †Department of Computer Science & IT, College of Engineering , Bhubaneswar, India aru.nanda@rediffmail.com , rout_sarojkumar@yahoo.co.in , amiyaamiya@rediffmail.com Abstract: Knowledge Placement & Management in wireless sensor networks has been a research area in recent years. Many existing Sensor Knowledge Management Systems view sensor data as a continuous stream that is sensed, filtered, processed, and aggregated as it “flows” from sensors to users. We argue that the Knowledge Management infrastructure will need substantial redesign to fully exploit the presence of local storage and processing capability in order to reduce expensive communication. In this paper we propose an architectural framework for Knowledge Placement and Management. We propose a reliable and real time tactic for Knowledge placement and achieving data integrity using self organized sensor clusters. Instead of storing information in individual cluster heads as suggested in some protocols, in our architecture we suggest storing of information of all clusters within a cell in the corresponding base station and finally we are trying to calculate Sensor Network Knowledgebase Query Processing time and space complexity. Keywords: Cluster Head, Data Reliability, Knowledge Management, Real Time Communication, Wireless Sensor Networks. 1. Introduction The fact of knowing about the world is known as knowledge. Data store in a database where as knowledge store in knowledge base. Knowledge is closely related with intelligence. A person having more knowledge is called highly intelligence person. The artificial intelligence area has developed techniques for representing knowledge in forms that can be exploited by computational procedures and heuristics. Database management systems research produced techniques that support the representation and management of large amounts of relatively simple Knowledge. Knowledge management is concerned with the representation, organization, creation, acquisition, usage, and evolution of knowledge in its many forms. To build successful technologies for knowledge management, we need to further our understanding of how individuals, groups and organizations use knowledge. Given that more and more knowledge is becoming encoded in computer readable forms, we also need to build tools which can effectively search through databases, files, web sites and the like, to extract information, capture its meaning, organize it and make it available. The main goal of our research paper is to development of a Knowledge Placement & Management System (KPMS) to store knowledge. Wireless Sensor Networks (WSNs) provide a new model for sensing and collecting information from various environments, with the possible to serve many and different applications. Current WSNs typically communicate directly with a centralized controller or satellite. On the other hand, a elegant WSN consists of a number of sensors spread across a geographical area; each sensor has wireless communication capability and sufficient intelligence for signal processing and networking of the data. Accessing and processing knowledge and data produced in a WSN using a database-like approach [2]–[3] has several advantages. Sensors can be deployed in the physical environment and applications that manipulate their knowledge and data can be created, refined, and modified afterwards without any physical involvement on the sensors themselves. The data management activity performed in the network can be remotely controlled by interactively issuing queries, expressed in a high level language, which specify what knowledge and data are of interest for a certain task, and how they should be manipulated. In this paper we propose an architectural framework for reliable and real time placement and dissemination of knowledge in WSN. We focus on middleware technology, and describe details of some existing research prototypes, then address challenges and future perspectives on the middleware. This study highlights that middleware needs to provide a common interface for various functional components of WSN: Detection and knowledge collection, signal processing, knowledge and data aggregation, and notification. By integrating sensing, signal processing, and communication functions, a WSN provides a natural platform for hierarchical information processing. 2. Related Work [4] and [1] are two proposals providing real time data delivery services in sensor networks. They are based on an idealized model that takes into account both the remaining