Development Of Sensor Network Applications Research Articles

센서네트워크상에서 능동규칙 이동에이전트의 역 방향 이주

For the activeness and autonomy of a sensor network, the efficient migration method of a mobile agent and the consistent naming services are the required components of a sensor network. Accordingly, this paper presented the implementation of backward migration of an active rule mobile agent applying the naming method based on RMI that used the meta_table including the informations about the components of a sensor network. This study implemented based on the extension of the forward migration[12], and the results of the various experiments present the efficacy of mobile agent middleware system and the possibility of constructing efficient sensor network application environment. And, the results of this study are able to enhance the adaptability on dynamic changes of environment in sensor network application development.

DAVIM: Adaptable Middleware for Sensor Networks

Middleware services facilitate the development of sensor network applications. In a business context, multiple executing applications can use these services concurrently. In addition, network applications can change during the network's potentially long lifetime. DAVIM, the first step toward a lightweight service platform, enables dynamic management of services and isolation between simultaneously running applications.

Wireless sensor network application programming and simulation system

We present, a wireless sensor network application programming and simulation system, suitable for wireless sensor network application development for both resource constrained and unconstrained hardware. Developed programs can be tested inside simulator, or (with source unchanged) executed directly on hardware. Main contribution of our project is uniform object oriented programming model with predefined basic concurrency abstractions.

Mobile-agent-based collaborative sensor fusion

Information fusion can assist in the development of sensor network applications by merging capabilities, raw data and decisions from multiple sensors through distributed and collaborative integration algorithms. In this paper, we introduce a multi-layered, middleware-driven, multi-agent, interoperable architecture for distributed sensor networks that bridges the gap between the programmable application layer consisting of software agents and the physical layer consisting of sensor nodes. We adopt an energy-efficient, fault-tolerant approach for collaborative information processing among multiple sensor nodes using a mobile-agent-based computing model. In this model the sink/base-station deploys mobile agents that migrate from node to node following a certain itinerary, either pre-determined or determined on-the-fly, and fuse the information/data locally at each node. This way, the intelligence is distributed throughout the network edge and communication cost is reduced to make the sensor network energy-efficient. We evaluate the performance of our mobile-agent-based approach as well as that of the traditional client/server-based computing model, vis-à-vis energy consumption and execution time, through both analytical study and simulation. We draw important conclusions based on our findings. Finally, we consider a collaborative target classification application, supported by our architectural framework, to illustrate the efficacy of the mobile-agent-based computing model.

Architecture design principles to support adaptive service orchestration in WSN applications

Our goal is to facilitate the development of sensor network applications in an open system, where applications arrive and leave dynamically and execute concurrently. We identify design principles that govern the creation of these systems, such as having a network-wide programming model, late binding and global resource management. In accordance with these principles, we assume that an application is modeled as a composite service, and propose an architecture for its adaptive orchestration on a WSN. Adaptivity here refers to automatic runtime selection of service implementations and network resources to execute the application specification in a resource-efficient and context-aware manner.