The Hybrid Algorithm for Data Collection over a Tree Topology in WSN

Wireless sensor networks have wide range of application such as analysis of traffic, monitoring of environmental, industrial process monitoring, technical systems, civilian and military application. Data collection is a basic function of wireless sensor networks (WSN) where sensor nodes determine attributes about a phenomenon of concern and transmits their readings to a common base station(sink node). In this paper, we use contention-free Time Division Multiple Access (TDMA) support scheduling protocols for such data collection applications over tree-based routing topology. We represent a data gathering techniques to get the growing capacity, routing protocol all along with algorithms planned for remote wireless sensor networks. This paper describes about the model of sensor networks which has been made workable by the junction of micro-electro-mechanical systems technologies, digital electronics and wireless communications. Firstly the sensing tasks and the potential sensor network applications are explored, and assessment of factors influencing the design of sensor networks is provided. In our propose work using data compression and packet merging techniques; or taking advantage of the correlation in the sensor readings. Consider continuous monitoring applications where perfect aggregation is achievable, i.e., every node is capable of aggregate the entire packets expected from its children as well as that generate by itself into a particular packet before transmit in the direction of its sink node or base station or parent node. Keyword: Aggregation, Data Converge-cast, Data fusion, Energy Efficiency, Routing and TDMA

Distributed Coverage Area Reporting for Wireless Sensor Networks

In order to efficiently deal with subscriptions or other location dependent information, it is key that the wireless sensor network informs the gateways what geographical area is serviced by which gateway. The gateways are then able to e.g. efficiently route subscriptions which are only valid in particular regions of the deployment. \ud \ud In our distributed approach of establishing a description of WSN coverage area per gateway, we let nodes keep track of the convex hull of the coverage area. In this way, gateways are efficiently informed of the service areas, while we limit the amount of information each node needs to store, transmit and receive

Gossip Algorithms for Distributed Signal Processing

Gossip algorithms are attractive for in-network processing in sensor networks because they do not require any specialized routing, there is no bottleneck or single point of failure, and they are robust to unreliable wireless network conditions. Recently, there has been a surge of activity in the computer science, control, signal processing, and information theory communities, developing faster and more robust gossip algorithms and deriving theoretical performance guarantees. This article presents an overview of recent work in the area. We describe convergence rate results, which are related to the number of transmitted messages and thus the amount of energy consumed in the network for gossiping. We discuss issues related to gossiping over wireless links, including the effects of quantization and noise, and we illustrate the use of gossip algorithms for canonical signal processing tasks including distributed estimation, source localization, and compression.Comment: Submitted to Proceedings of the IEEE, 29 page

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

Rate-distortion Balanced Data Compression for Wireless Sensor Networks

This paper presents a data compression algorithm with error bound guarantee for wireless sensor networks (WSNs) using compressing neural networks. The proposed algorithm minimizes data congestion and reduces energy consumption by exploring spatio-temporal correlations among data samples. The adaptive rate-distortion feature balances the compressed data size (data rate) with the required error bound guarantee (distortion level). This compression relieves the strain on energy and bandwidth resources while collecting WSN data within tolerable error margins, thereby increasing the scale of WSNs. The algorithm is evaluated using real-world datasets and compared with conventional methods for temporal and spatial data compression. The experimental validation reveals that the proposed algorithm outperforms several existing WSN data compression methods in terms of compression efficiency and signal reconstruction. Moreover, an energy analysis shows that compressing the data can reduce the energy expenditure, and hence expand the service lifespan by several folds.Comment: arXiv admin note: text overlap with arXiv:1408.294

Design of Combined Coverage Area Reporting and Geo-casting of Queries for Wireless Sensor Networks

In order to efficiently deal with queries or other location dependent information, it is key that the wireless sensor network informs gateways what geographical area is serviced by which gateway. The gateways are then able to e.g. efficiently route queries which are only valid in particular regions of the deployment. The proposed algorithms combine coverage area reporting and geographical routing of queries which are injected by gateways.\u