Overview of WSN Infrastructure Models, Design & Management

Network management for Wireless Sensor Network Infrastructure is a challenging area where the management operation is to run on very minimal or zero cost. The network data packets routing costs more, hence managing this unstructured network improves the network efficiency and extend the network life time. The deployed sensor nodes have a fixed battery life and there are also some attempts made to manage this WSN network efficiently. In this paper we focus on different networking parameters used to measure efficiency, different network functionality and different design structure evolved in this area

EEHC: Event-driven Energy Optimization in Heterogeneous Clustered Wireless Sensor Networks

Wireless sensor networks are used in various applications worldwide. Large numbers small sized, inexpensive, low-powered sensor nodes are deployed in the target field to monitor or track particular objects. Sensor nodes have limited energy and computation capability. Energy optimization is an important task should be performed to improve the lifetime of the wireless sensor networks. Many researches focus only on continuous delivery model. This paper proposed energy efficient event-driven heterogeneous clustered wireless sensor network (EEHC) system. The results show that the proposed system reduced the energy consumption and longer lifetime than its comparatives

The Distributed Convergence Classifier Using the Finite Difference

The paper presents a novel distributed classifier of the convergence, which allows to detect the convergence/the divergence of a distributed converging algorithm. Since this classifier is supposed to be primarily applied in wireless sensor networks, its proposal makes provision for the character of these networks. The classifier is based on the mechanism of comparison of the forward finite differences from two consequent iterations. The convergence/the divergence is classifiable only in terms of the changes of the inner states of a particular node and therefore, no message redundancy is required for its proper functionality

DATA REPOSITORY FOR SENSOR NETWORK: A DATA MINING APPROACH

ABSTRAC

Corl8: A System for Analyzing Diagnostic Measures in Wireless Sensor Networks

Due to an increasing demand to monitor the physical world, researchers are deploying wireless sensor networks more than ever before. These networks comprise a large number of sensors integrated with small, low-power wireless transceivers used to transmit data to a central processing and storage location. These devices are often deployed in harsh, volatile locations, which increases their failure rate and decreases the rate at which packets can be successfully transmitted. Existing sensor debugging tools, such as Sympathy and EmStar, rely on add-in network protocols to report status information, and to collectively diagnose network problems. Some protocols rely on a central node to initiate the diagnosis sequence. These methods can congest network channels and consume scarce resources, including battery power. In this thesis, we present Corl8, a system for analyzing diagnostic traces in wireless sensor networks. Our method relies on diagnostic data that is periodically transmitted to a network sink as a part of the standard sensor payload to enable fault diagnosis. Corl8 does not require any specific data to be present in the system, making it flexible. Our system provides an interactive environment for exploring correlated changes across different diagnostic measures within an individual node. It also supports processing on a batch level to automatically flag interesting correlations. The system\u27s flexibility makes it applicable for use in any wireless sensor network that transmits diagnostic measures. The analysis methods are user-configurable, but we suggest settings and analyze their performance. For our evaluation, we use data from five real-world deployments from the Intelligent River(R) project consisting of 36 sensor nodes

Time constrained fault tolerance and management framework for k-connected distributed wireless sensor networks based on composite event detection

Wireless sensor nodes themselves are exceptionally complex systems where a variety of components interact in a complex way. In enterprise scenarios it becomes highly important to hide the details of the underlying sensor networks from the applications and to guarantee a minimum level of reliability of the system. One of the challenges faced to achieve this level of reliability is to overcome the failures frequently faced by sensor networks due to their tight integration with the environment. Failures can generate false information, which may trigger incorrect business processes, resulting in additional costs. Sensor networks are inherently fault prone due to the shared wireless communication medium. Thus, sensor nodes can lose synchrony and their programs can reach arbitrary states. Since on-site maintenance is not feasible, sensor network applications should be local and communication-efficient self-healing. Also, as per my knowledge, no such general framework exist that addresses all the fault issues one may encounter in a WSN, based on the extensive, exhaustive and comprehensive literature survey in the related areas of research. As one of the main goals of enterprise applications is to reduce the costs of business processes, a complete and more general Fault Tolerance and management framework for a general WSN, irrespective of the node types and deployment conditions is proposed which would help to mitigate the propagation of failures in a business environment, reduce the installation and maintenance costs and to gain deployment flexibility to allow for unobtrusive installation