Abstract

In this paper, an improved version of the energy aware distributed unequal clustering protocol (EADUC) is projected. The EADUC protocol is commonly used for solving energy hole problem in multi-hop wireless sensor networks. In the EADUC, location of base station and residual energy are given importance as clustering parameters. Based on these parameters, different competition radii are assigned to nodes. Herein, a new approach has been proposed to improve the working of EADUC, by electing cluster heads considering number of nodes in the neighborhood in addition to the above two parameters. The inclusion of the neighborhood information for computation of the competition radii provides better balancing of energy in comparison with the existing approach. Furthermore, for the selection of next hop node, the relay metric is defined directly in terms of energy expense instead of only the distance information used in the EADUC and the data transmission phase has been extended in every round by performing the data collection number of times through use of major slots and mini-slots. The methodology used is of retaining the same clusters for a few rounds and is effective in reducing the clustering overhead. The performance of the proposed protocol has been evaluated under three different scenarios and compared with existing protocols through simulations. The results show that the proposed scheme outperforms the existing protocols in terms of network lifetime in all the scenarios.

Abstract

Software-defined networking (SDN) is a cornerstone of next-generation networks and has already led to numerous advantages for data-center networks and wide-area networks, for instance in terms of reduced management complexity and more fine-grained traffic engineering. However, the design and implementation of SDN within wireless sensor networks (WSN) have received far less attention. Unfortunately, because of the multi-hop type of communication in WSN, a direct reuse of the wired SDN architecture could lead to excessive commu- nication overhead. In this paper, we propose a cluster-based flow management approach that makes a trade-off between the granularity of monitoring by an SDN controller and the communication overhead of flow management. A network is partitioned into clusters with a minimum number of border nodes. Instead of having to handle the individual flows of all nodes, the SDN controller only manages incoming and outgoing traffic flows of clusters through border nodes. Our proof-of- concept implementations in software and hardware show that, when compared with benchmark solutions, our approach is significantly more efficient with respect to the number of nodes that must be managed and the number of control messages exchanged.

Abstract

Zavrak/0000-0001-6950-8927; Kara, Resul/0000-0001-8902-6837; Kayaalp, Fatih/0000-0002-8752-3335 WOS: 000426865100007 One of the main problems of water transportation pipelines is leak which can cause water resources loss, possible human injuries, and damages to the environment. There are many studies in the literature focusing on detection and localization of leaks in the water pipeline systems. In this study, we have designed a wireless sensor network-based real-time monitoring system to detect and locate the leaks on multiple positions on water pipelines by using pressure data. At first, the pressure data are collected from wireless pressure sensor nodes. After that, unlike from the previous works in the literature, both the detection and localization of leakages are carried out by using multi-label learning methods. We have used three multi-label classification methods which are RAkELd, BRkNN, and BR with SVM. After the evaluation and comparison of the methods with each other, we observe that the RAkELd method performs best on almost all measures with the accuracy ratio of 98%. As a result, multi-label classification methods can be used on the detection and localization of the leaks in the pipeline systems successfully.

Abstract

This paper presents an IoT (Internet of Things) system designed to allow the monitoring and control of parameters of the users’ vehicles, anytime and anywhere in the world, through the Internet. The system prototype was developed and tested using an electric vehicle (EV) and the respective sensor systems. The main components of the proposed IoT system are: a Bluetooth Low Energy (BLE) intra-vehicular wireless sensor network (IVWSN); a mobile device that acts both as the vehicle’s gateway, connecting the IVWSN to the Internet, and as the vehicle’s human machine interface (HMI); an online server/database, based on Firebase; a client, which can be either a mobile device or a personal computer; and a residential wireless sensor network (WSN). The use of a wireless network to collect sensor data inside of the vehicle introduces some advantages when compared with conventional wired networks, whereas the inclusion of a residential WSNs in the proposed IoT architecture allows the provision of additional features, such as automatic control of the EV battery charging process. Experimental results are provided to assess the performance of the developed IVWSN and HMI. This work has been supported by COMPETE: POCI-01-0145- FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013. info:eu-repo/semantics/publishedVersion

Abstract

Pipelines are widely used for the transportation of hydrocarbon fluids over millions of miles all over the world. The structures of the pipelines are designed to withstand several environmental loading conditions to ensure safe and reliable distribution from point of production to the shore or distribution depot. However, leaks in pipeline networks are one of the major causes of innumerable losses in pipeline operators and nature. Incidents of pipeline failure can result in serious ecological disasters, human casualties and financial loss. In order to avoid such menace and maintain safe and reliable pipeline infrastructure, substantial research efforts have been devoted to implementing pipeline leak detection and localisation using different approaches. This paper discusses pipeline leakage detection technologies and summarises the state-of-the-art achievements. Different leakage detection and localisation in pipeline systems are reviewed and their strengths and weaknesses are highlighted. Comparative performance analysis is performed to provide a guide in determining which leak detection method is appropriate for particular operating settings. In addition, research gaps and open issues for development of reliable pipeline leakage detection systems are discussed. Document type: Article