Experiences and issues for environmental engineering sensor network deployments

Sensor network research is a large and growing area of academic effort, examining technological and deployment issues in the area of environmental monitoring. These technologies are used by environmental engineers and scientists to monitor a multiplicity of environments and services, and, specific to this paper, energy and water supplied to the built environment. Although the technology is developed by Computer Science specialists, the use and deployment is traditionally performed by environmental engineers. This paper examines deployment from the perspectives of environmental engineers and scientists and asks what computer scientists can do to improve the process. The paper uses a case study to demonstrate the agile operation of WSNs within the Cloud Computing infrastructure, and thus the demand-driven, collaboration-intense paradigm of Digital Ecosystems in Complex Environments

Experiences and issues for environmental science sensor network deployments

Sensor network research is a large and growing area of academic effort, examining technological and deployment issues in the area of environmental monitoring. These technologies are used by environmental engineers and scientists to monitor a multiplicity of environments and services, and, specific to this paper, energy and water supplied to the built environment. Although the technology is developed by Computer Science specialists, the use and deployment is traditionally performed by environmental engineers. This paper examines deployment from the perspectives of environmental engineers and scientists and asks what computer scientists can do to improve the process. The paper uses a case study to demonstrate the agile operation of WSNs within the Cloud Computing infrastructure, and thus the demand-driven, collaboration-intense paradigm of Digital Ecosystems in Complex Environments

Extending sensor networks into the cloud using Amazon web services

Sensor networks provide a method of collecting environmental data for use in a variety of distributed applications. However, to date, limited support has been provided for the development of integrated environmental monitoring and modeling applications. Specifically, environmental dynamism makes it difficult to provide computational resources that are sufficient to deal with changing environmental conditions. This paper argues that the Cloud Computing model is a good fit with the dynamic computational requirements of environmental monitoring and modeling. We demonstrate that Amazon EC2 can meet the dynamic computational needs of environmental applications. We also demonstrate that EC2 can be integrated with existing sensor network technologies to offer an end-to-end environmental monitoring and modeling solution

On the feasibility of Bluetooth, Zigbee and IEEE 802.15.4 technologies on board high speed trains

This paper studies the feasibility of using low-power wireless technologies such as Bluetooth, IEEE 802.15.4 and ZigBee in high-speed railway scenarios that involve bidirectional land-to-train communication. The presented results have been obtained through experimental tests conducted at the high-speed railway line connecting Madrid to Barcelona. A multiplatform communication system has been installed in a high-speed train, circulating at velocities up to 300 km/h, whereas autonomous devices have been disseminated along of the railway path to communicate with the onboard devices. The conclusions drawn from this work will be used as guidelines for the future implementation of autonomous communication platforms for high-speed rail connectivity.Postprint (author’s final draft

Management system for IPv6-enabled wireless sensor networks

“Copyright © [2011] IEEE. Reprinted from Internet of Things (iThings/CPSCom), 2011 International Conference on and 4th International Conference on Cyber, Physical and Social Computing. ISBN 978-1-4577-1976-9 This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.”It is expected that in the near future smart objects will have an Internet connection – this is the Internet of Things vision. Most of these objects compatible with the IEEE 802.15.4 standard are characterized by small size, power constrains, and small computing resources. Connecting such devices to the Internet is considered simultaneously the biggest challenge and a great opportunity for the Internet growth. To achieve the Internet of things vision is necessary to support IPv6 protocol suite in all objects. Supporting IPv6 simplifies, simultaneously, the integration of these objects in the Internet and their management. Actually, despite of the relevance, there are no existing standard solutions to manage smart object networks. Managing this type of networks poses a unique challenge because smart object networks may be comprised of thousands of nodes, are highly dynamic and prone to failures. This paper presents a complete solution to manage smart object networks based on SNMPv1 protocol. The paper also presents the design and deployment of a laboratory testbed

Implementation and evaluation of Multi-hop routing in 6LoWPAN

6LoWPAN enables the transmission of IPv6 packets over LoWPAN networks. In order to make it possible, 6LoWPAN introduces an adaptation layer between network and link layers. This layer allows IPv6 packets to be adapted to the lower layers constraints. It provides fragmentation and reassembling of packets and header compression. It also can be involved in routing decisions. Depending on which layer is responsible of routing decisions 6LoWPAN divides routing in two categories: mesh under if the interested layer is the adaptation layer, route over if it is the network one. In this paper we compare the two routing solutions evaluating their performances in terms of end-to-end delay and round-trip time. All the performance evaluation has been realized in a real implementation of 6LoWPAN.Postprint (published version

A Review of 6LoWPAN Routing Protocols

Internet Engineering Task Force (IETF) working group has standardized the transmission ofinternet protocol version 6 (IPv6) packets over IEEE 802.15.4 low power wireless personal areanetwork (LoWPAN) as 6LoWPAN protocol. It provides the wireless sensor network (WSN) node withIP communication capabilities by putting an adaptation layer above the 802.15.4 link layer. Differentmechanisms performed by adaptation layer require the 6LoWPAN header encapsulation in the packet.Although routing is among the key issues of 6LoWPAN research, the way to encapsulate a new routingheader in the 6LoWPAN packet has yet been investigated thoroughly. In this paper, different ways ofrouting header encapsulation in 6LoWPAN protocol stack is discussed. The simplified version Ad-HocOn-Demand Distance Vector (AODV) such as On-Demand Distance Vector (LOAD) and DynamicMANET On-demand for 6LoWPAN (DYMO-low) have currently been proposed in 6LoWPANrouting. Hierarchical routing (HiLow) is another routing protocol that is used in 6LoWPAN to increasethe network scalability. Some comparisons of these routing protocols have been made in terms of theirrouting metric such as number of hops count. The used control messages for the route discovery indifferent routing protocols have also been investigated. These comparisons show that each routingprotocol has its own advantage depends on the involved applications. There are some tradeoffs ofrespective routing protocols. The routing protocol that uses hello message may provide more reliablebut results a higher delay in the packet routing

A survey on subjecting electronic product code and non-ID objects to IP identification

Over the last decade, both research on the Internet of Things (IoT) and real-world IoT applications have grown exponentially. The IoT provides us with smarter cities, intelligent homes, and generally more comfortable lives. However, the introduction of these devices has led to several new challenges that must be addressed. One of the critical challenges facing interacting with IoT devices is to address billions of devices (things) around the world, including computers, tablets, smartphones, wearable devices, sensors, and embedded computers, and so on. This article provides a survey on subjecting Electronic Product Code and non-ID objects to IP identification for IoT devices, including their advantages and disadvantages thereof. Different metrics are here proposed and used for evaluating these methods. In particular, the main methods are evaluated in terms of their: (i) computational overhead, (ii) scalability, (iii) adaptability, (iv) implementation cost, and (v) whether applicable to already ID-based objects and presented in tabular format. Finally, the article proves that this field of research will still be ongoing, but any new technique must favorably offer the mentioned five evaluative parameters.Comment: 112 references, 8 figures, 6 tables, Journal of Engineering Reports, Wiley, 2020 (Open Access