Service and device discovery of nodes in a wireless sensor network

Emerging wireless communication standards and more capable sensors and actuators have pushed further development of wireless sensor networks. Deploying a large number of sensor\ud nodes requires a high-level framework enabling the devices to present themselves and the resources they hold. The device and the resources can be described as services, and in this paper, we review a number of well-known service discovery protocols. Bonjour stands out with its auto-configuration, distributed architecture, and sharing of resources. We also present a lightweight implementation in order to demonstrate that an emerging standards-based device and service discovery protocol can actually be deployed on small wireless sensor nodes

Decentralized mobility models for data collection in wireless sensor networks

Controlled mobility in wireless sensor networks provides many benefits towards enhancing the network performance and prolonging its lifetime. Mobile elements, acting as mechanical data carriers, traverse the network collecting data using single-hop communication, instead of the more energy demanding multi-hop routing to the sink. Scaling up from single to multiple mobiles is based more on the mobility models and the coordination methodology rather than increasing the number of mobile elements in the network. This work addresses the problem of designing and coordinating decentralized mobile elements for scheduling data collection in wireless sensor networks, while preserving some performance measures, such as latency and amount of data collected. We propose two mobility models governing the behaviour of the mobile element, where the incoming data collection requests are scheduled to service according to bidding strategies to determine the winner element. Simulations are run to measure the performance of the proposed mobility models subject to the network size and the number of mobile elements.<br /

EMEEDP: Enhanced Multi-hop Energy Efficient Distributed Protocol for Heterogeneous Wireless Sensor Network

In WSN (Wireless Sensor Network) every sensor node sensed the data and transmit it to the CH (Cluster head) or BS (Base Station). Sensors are randomly deployed in unreachable areas, where battery replacement or battery charge is not possible. For this reason, Energy conservation is the important design goal while developing a routing and distributed protocol to increase the lifetime of WSN. In this paper, an enhanced energy efficient distributed protocol for heterogeneous WSN have been reported. EMEEDP is proposed for heterogeneous WSN to increase the lifetime of the network. An efficient algorithm is proposed in the form of flowchart and based on various clustering equation proved that the proposed work accomplishes longer lifetime with improved QOS parameters parallel to MEEP. A WSN implemented and tested using Raspberry Pi devices as a base station, temperature sensors as a node and xively.com as a cloud. Users use data for decision purpose or business purposes from xively.com using internet.Comment: 6 pages, 4 figures. arXiv admin note: substantial text overlap with arXiv:1409.1412 by other author

Comparison between Routing Technologies of Wireless Sensor Networks

WSNs have crafted new prospects across the field of human activities, embracing monitoring and control of environmental systems, animal tracking, forest fire tracking, medical care, battlefield surveillance, calamity management. These different applications involves data collection from different millions of sensors and propagating to base stations via sink nodes. WSN makes this communication possible by forwarding data directly to base station that exhaust energy reserves. Use of multi-hop data transmission reduces loss of energy and increase lifetime of network. This paper discusses various routing techniques used in multi-hop WSN to select best path

An analysis of the use of multiple transmission power levels on wireless sensor networks

The energy consumption in wireless sensor networks is the critical concern of different studies, especially because of the great effort, or even the impossibility, to replace the battery of their motes. Consequently, it is fundamental to investigate and evaluate the energy spent by every individual task executed by the motes in order to provide an efficient use of their batteries. In this work, we employ different metrics to present a thorough study of how the use of multiple transmission power levels affects multihop wireless sensor networks. This work is motivated by the current employment of the multiple transmission power levels, on both academic works and commercial solutions, which is a novel feature of some radio transceivers commonly used in wireless sensor network motes. Aiming for reliable and extensive analysis, this study employs simulations in different scenarios and models of commonly employed electronic components. The contribution of this works is a detailed investigation of the impact caused by the use of different transmission power levels employing different metrics, offering a wide perspective on the subject. In general, the results of this study indicate that the use of multiple power levels grants both positive and negative results, according to the scenario and metrics analyzed43COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESnão tem5th International electronic conference on sensors and application

A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles

The evolution in micro-electro-mechanical systems technology (MEMS) has triggered the need for the development of wireless sensor network (WSN). These wireless sensor nodes has been used in many applications at many areas. One of the main issues in WSN is the energy availability, which is always a constraint. In a previous research, a relocating algorithm for mobile sensor network had been introduced and the goal was to save energy and prolong the lifetime of the sensor networks using Particle Swarm Optimization (PSO) where both of sensing radius and travelled distance had been optimized in order to save energy in long-term and shortterm. Yet, the previous research did not take into account obstacles’ existence in the field and this will cause the sensor nodes to consume more power if obstacles are exists in the sensing field. In this project, the same centralized relocating algorithm from the previous research has been used where 15 mobile sensors deployed randomly in a field of 100 meter by 100 meter where these sensors has been deployed one time in a field that obstacles does not exist (case 1) and another time in a field that obstacles existence has been taken into account (case 2), in which these obstacles has been pre-defined positions, where these two cases applied into two different algorithms, which are the original algorithm of a previous research and the modified algorithm of this thesis. Particle Swarm Optimization has been used in the proposed algorithm to minimize the fitness function. Voronoi diagram has also used in order to ensure that the mobile sensors cover the whole sensing field. In this project, the objectives will be mainly focus on the travelling distance, which is the mobility module, of the mobile sensors in the network because the distance that the sensor node travels, will consume too much power from this node and this will lead to shortening the lifetime of the sensor network. So, the travelling distance, power consumption and lifetime of the network will be calculated in both cases for original algorithm and modified algorithm, which is a modified deployment algorithm, and compared between them. Moreover, the maximum sensing range is calculated, which is 30 meter, by using the binary sensing model even though the sensing module does not consume too much power compared to the mobility module. Finally, the comparison of the results in the original method will show that this algorithm is not suitable for an environment where obstacle exist because sensors will consume too much power compared to the sensors that deployed in environment that free of obstacles. While the results of the modified algorithm of this research will be more suitable for both environments, that is environment where obstacles are not exist and environment where obstacles are exist, because sensors in this algorithm .will consume almost the same amount of power at both of these environments

A Hole Avoiding Routing Protocol with Relative Neighborhood Graph for Wireless Sensor Network

[[abstract]]In wireless sensor networks, ¿holes¿ are hardly to know its location and avoid either because of various actual geographical environments. A hole can be dynamically formed due to unbalanced deployment, failure or power exhaustion of sensors, animus interference, or physical barriers such as buildings or mountains. Hence, we hope to propose the RNG Hole Avoiding Routing protocol, RNGHAR which can model ¿holes¿ existed in wireless sensor network and event packets can avoid meeting a ¿hole¿ in advance instead of bypassing a hole when it meets the hole. This paper proposes a novel algorithm RNGHAR which uses RNG (relative neighborhood graph) modeling holes then we can collect hole information in order to construct in advance hole avoiding routing path. Hence event packets will be guided to overcome the hole and move along the shortest path from source node to the sink node. Simulation studies show that my proposed method achieves good performance in terms of average hop count, packet delivery success rate and power consumption in comparison with the existing protocols.[[sponsorship]]IEEE Taipei Section; National Science Council; Ministry of Education; Tamkang University; Asia University; Providence University; The University of Aizu; Lanzhou University[[conferencetype]]國際[[conferencetkucampus]]淡水校園[[conferencedate]]20091203~20091205[[iscallforpapers]]Y[[conferencelocation]]Taipei, Taiwa