Entropy based routing for mobile, low power and lossy wireless sensors networks

[EN] Routing protocol for low-power and lossy networks is a routing solution specifically developed for wireless sensor networks, which does not quickly rebuild topology of mobile networks. In this article, we propose a mechanism based on mobility entropy and integrate it into the corona RPL (CoRPL) mechanism, which is an extension of the IPv6 routing protocol for low-power and lossy networks (RPL). We extensively evaluated our proposal with a simulator for Internet of Things and wireless sensor networks. The mobility entropy-based mechanism, called CoRPL+E, considers the displacement of nodes as a deciding factor to define the links through which nodes communicate. Simulation results show that the proposed mechanism, when compared to CoRPL mechanism, is effective in reducing packet loss and latency in simulated mobile routing protocol for low-power and lossy networks. From the simulation results, one can see that the CoRPL+E proposal mechanism provides a packet loss reduction rate of up to 50% and delays reduction by up to 25% when compared to CoRPL mechanism.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by SIDIA Institute of Science and Technology, by Coordenacao de Aperfeicxoamento de Pessoal de Nivel Superior (CAPES), by Fundacao de Amparo a Pesquisa do Estado do Amazonas (FAPEAM)-support programs (Programa Primeiros Projetos (PPP) and Programa de Tecnologia da Informacao na Amazonia (PROTI)-Amazonia-Mobilidade), by Camara Tecnica de Reconstrucao e Recuperacao de Infraestrutura (CT-INFRA) of Ministerio da Ciencia, Tecnologia, Inovacoes e Comunicacoes(MCTI)/Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq), and by Secretaria de Estado de Ciencia, Tecnologia e Inovacao Amazonas (SECTI-AM) and Government of Amazon State, Brazil.Carvalho, C.; Mota, E.; Ferraz, E.; Seixas, P.; Souza, P.; Tavares, V.; Lucena Filho, W.... (2019). Entropy based routing for mobile, low power and lossy wireless sensors networks. International Journal of Distributed Sensor Networks (Online). 15(7):1-19. https://doi.org/10.1177/1550147719866134S119157Blanco-Novoa, O., Fernández-Caramés, T., Fraga-Lamas, P., & Castedo, L. (2018). A Cost-Effective IoT System for Monitoring Indoor Radon Gas Concentration. Sensors, 18(7), 2198. doi:10.3390/s18072198Ding, X., Tian, Y., & Yu, Y. (2016). A Real-Time Big Data Gathering Algorithm Based on Indoor Wireless Sensor Networks for Risk Analysis of Industrial Operations. IEEE Transactions on Industrial Informatics, 12(3), 1232-1242. doi:10.1109/tii.2015.2436337Rashid, B., & Rehmani, M. H. (2016). Applications of wireless sensor networks for urban areas: A survey. Journal of Network and Computer Applications, 60, 192-219. doi:10.1016/j.jnca.2015.09.008Laurindo, S., Moraes, R., Nassiffe, R., Montez, C., & Vasques, F. (2018). An Optimized Relay Selection Technique to Improve the Communication Reliability in Wireless Sensor Networks. Sensors, 18(10), 3263. doi:10.3390/s18103263Airehrour, D., Gutierrez, J., & Ray, S. K. (2016). Secure routing for internet of things: A survey. Journal of Network and Computer Applications, 66, 198-213. doi:10.1016/j.jnca.2016.03.006Mesodiakaki, A., Zola, E., Santos, R., & Kassler, A. (2018). Optimal user association, backhaul routing and switching off in 5G heterogeneous networks with mesh millimeter wave backhaul links. Ad Hoc Networks, 78, 99-114. doi:10.1016/j.adhoc.2018.05.008Marszałek, Z., Woźniak, M., & Połap, D. (2018). Fully Flexible Parallel Merge Sort for Multicore Architectures. Complexity, 2018, 1-19. doi:10.1155/2018/8679579Fotouhi, H., Moreira, D., & Alves, M. (2015). mRPL: Boosting mobility in the Internet of Things. Ad Hoc Networks, 26, 17-35. doi:10.1016/j.adhoc.2014.10.009Barcelo, M., Correa, A., Vicario, J. L., Morell, A., & Vilajosana, X. (2016). Addressing Mobility in RPL With Position Assisted Metrics. IEEE Sensors Journal, 16(7), 2151-2161. doi:10.1109/jsen.2015.2500916Bouaziz, M., Rachedi, A., & Belghith, A. (2019). EKF-MRPL: Advanced mobility support routing protocol for internet of mobile things: Movement prediction approach. Future Generation Computer Systems, 93, 822-832. doi:10.1016/j.future.2017.12.015Fotouhi, H., Moreira, D., Alves, M., & Yomsi, P. M. (2017). mRPL+: A mobility management framework in RPL/6LoWPAN. Computer Communications, 104, 34-54. doi:10.1016/j.comcom.2017.01.020Iova, O., Picco, P., Istomin, T., & Kiraly, C. (2016). RPL: The Routing Standard for the Internet of Things... Or Is It? IEEE Communications Magazine, 54(12), 16-22. doi:10.1109/mcom.2016.1600397cmFotouhi, H., Alves, M., Zamalloa, M. Z., & Koubaa, A. (2014). Reliable and Fast Hand-Offs in Low-Power Wireless Networks. IEEE Transactions on Mobile Computing, 13(11), 2620-2633. doi:10.1109/tmc.2014.2307867Kamgueu, P. O., Nataf, E., & Ndie, T. D. (2018). Survey on RPL enhancements: A focus on topology, security and mobility. Computer Communications, 120, 10-21. doi:10.1016/j.comcom.2018.02.011Park, J., Kim, K.-H., & Kim, K. (2017). An Algorithm for Timely Transmission of Solicitation Messages in RPL for Energy-Efficient Node Mobility. Sensors, 17(4), 899. doi:10.3390/s17040899Stanoev, A., Filiposka, S., In, V., & Kocarev, L. (2016). Cooperative method for wireless sensor network localization. Ad Hoc Networks, 40, 61-72. doi:10.1016/j.adhoc.2016.01.003Wallgren, L., Raza, S., & Voigt, T. (2013). Routing Attacks and Countermeasures in the RPL-Based Internet of Things. International Journal of Distributed Sensor Networks, 9(8), 794326. doi:10.1155/2013/794326Raza, S., Wallgren, L., & Voigt, T. (2013). SVELTE: Real-time intrusion detection in the Internet of Things. Ad Hoc Networks, 11(8), 2661-2674. doi:10.1016/j.adhoc.2013.04.014Zhang, K., Liang, X., Lu, R., & Shen, X. (2014). Sybil Attacks and Their Defenses in the Internet of Things. IEEE Internet of Things Journal, 1(5), 372-383. doi:10.1109/jiot.2014.2344013Mayzaud, A., Sehgal, A., Badonnel, R., Chrisment, I., & Schönwälder, J. (2015). Mitigation of topological inconsistency attacks in RPL-based low-power lossy networks. International Journal of Network Management, 25(5), 320-339. doi:10.1002/nem.1898Navidi, W., & Camp, T. (2004). Stationary distributions for the random waypoint mobility model. IEEE Transactions on Mobile Computing, 3(1), 99-108. doi:10.1109/tmc.2004.126182

Surfing the Internet-of-Things: lightweight access and control of wireless sensor networks using industrial low power protocols

Internet-of-Things (IoT) is emerging to play an important role in the continued advancement of information and communication technologies. To accelerate industrial application developments, the use of web services for networking applications is seen as important in IoT communications. In this paper, we present a RESTful web service architecture for energy-constrained wireless sensor networks (WSNs) to enable remote data collection from sensor devices in WSN nodes. Specifically, we consider both IPv6 protocol support in WSN nodes as well as an integrated gateway solution to allow any Internet clients to access these nodes.We describe the implementation of a prototype system, which demonstrates the proposed RESTful approach to collect sensing data from a WSN. A performance evaluation is presented to illustrate the simplicity and efficiency of our proposed scheme

A Load Balancing Algorithm for Resource Allocation in IEEE 802.15.4e Networks

The recently created IETF 6TiSCH working group combines the high reliability and low-energy consumption of IEEE 802.15.4e Time Slotted Channel Hopping with IPv6 for industrial Internet of Things. We propose a distributed link scheduling algorithm, called Local Voting, for 6TiSCH networks that adapts the schedule to the network conditions. The algorithm tries to equalize the link load (defined as the ratio of the queue length over the number of allocated cells) through cell reallocation. Local Voting calculates the number of cells to be added or released by the 6TiSCH Operation Sublayer (6top). Compared to a representative algorithm from the literature, Local Voting provides simultaneously high reliability and low end-to-end latency while consuming significantly less energy. Its performance has been examined and compared to On-the-fly algorithm in 6TiSCH simulator by modeling an industrial environment with 50 sensors

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

Content Delivery Latency of Caching Strategies for Information-Centric IoT

In-network caching is a central aspect of Information-Centric Networking (ICN). It enables the rapid distribution of content across the network, alleviating strain on content producers and reducing content delivery latencies. ICN has emerged as a promising candidate for use in the Internet of Things (IoT). However, IoT devices operate under severe constraints, most notably limited memory. This means that nodes cannot indiscriminately cache all content; instead, there is a need for a caching strategy that decides what content to cache. Furthermore, many applications in the IoT space are timesensitive; therefore, finding a caching strategy that minimises the latency between content request and delivery is desirable. In this paper, we evaluate a number of ICN caching strategies in regards to latency and hop count reduction using IoT devices in a physical testbed. We find that the topology of the network, and thus the routing algorithm used to generate forwarding information, has a significant impact on the performance of a given caching strategy. To the best of our knowledge, this is the first study that focuses on latency effects in ICN-IoT caching while using real IoT hardware, and the first to explicitly discuss the link between routing algorithm, network topology, and caching effects.Comment: 10 pages, 9 figures, journal pape