Predicting topology propagation messages in mobile ad hoc networks: The value of history

This research was funded by the Spanish Government under contracts TIN2016-77836-C2-1-R,TIN2016-77836-C2-2-R, and DPI2016-77415-R, and by the Generalitat de Catalunya as Consolidated ResearchGroups 2017-SGR-688 and 2017-SGR-990.The mobile ad hoc communication in highly dynamic scenarios, like urban evacuations or search-and-rescue processes, plays a key role in coordinating the activities performed by the participants. Particularly, counting on message routing enhances the communication capability among these actors. Given the high dynamism of these networks and their low bandwidth, having mechanisms to predict the network topology offers several potential advantages; e.g., to reduce the number of topology propagation messages delivered through the network, the consumption of resources in the nodes and the amount of redundant retransmissions. Most strategies reported in the literature to perform these predictions are limited to support high mobility, consume a large amount of resources or require training. In order to contribute towards addressing that challenge, this paper presents a history-based predictor (HBP), which is a prediction strategy based on the assumption that some topological changes in these networks have happened before in the past, therefore, the predictor can take advantage of these patterns following a simple and low-cost approach. The article extends a previous proposal of the authors and evaluates its impact in highly mobile scenarios through the implementation of a real predictor for the optimized link state routing (OLSR) protocol. The use of this predictor, named OLSR-HBP, shows a reduction of 40–55% of topology propagation messages compared to the regular OLSR protocol. Moreover, the use of this predictor has a low cost in terms of CPU and memory consumption, and it can also be used with other routing protocols.Peer ReviewedPostprint (published version

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.... 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Towards Opportunistic Data Dissemination in Mobile Phone Sensor Networks

Recently, there has been a growing interest within the research community in developing opportunistic routing protocols. Many schemes have been proposed; however, they differ greatly in assumptions and in type of network for which they are evaluated. As a result, researchers have an ambiguous understanding of how these schemes compare against each other in their specific applications. To investigate the performance of existing opportunistic routing algorithms in realistic scenarios, we propose a heterogeneous architecture including fixed infrastructure, mobile infrastructure, and mobile nodes. The proposed architecture focuses on how to utilize the available, low cost short-range radios of mobile phones for data gathering and dissemination. We also propose a new realistic mobility model and metrics. Existing opportunistic routing protocols are simulated and evaluated with the proposed heterogeneous architecture, mobility models, and transmission interfaces. Results show that some protocols suffer long time-to-live (TTL), while others suffer short TTL. We show that heterogeneous sensor network architectures need heterogeneous routing algorithms, such as a combination of Epidemic and Spray and Wait

Mengenal pasti masalah pemahaman dan hubungannya dengan latar belakang matematik, gaya pembelajaran, motivasi dan minat pelajar terhadap bab pengawalan kos makanan di Sekolah Menengah Teknik (ert) Rembau: satu kajian kes.

Kajian ini dijalankan untuk mengkaji hubungan korelasi antara latar belakang Matematik, gaya pembelajaran, motivasi dan minat dengan pemahaman pelajar terhadap bab tersebut. Responden adalah seramai 30 orang iaitu terdiri daripada pelajar tingkatan lima kursus Katering, Sekolah Menengah Teknik (ERT) Rembau, Negeri Sembilan. Instrumen kajian adalah soal selidik dan semua data dianalisis menggunakan program SPSS versi 10.0 untuk mendapatkan nilai min dan nilai korelasi bagi memenuhi objektif yang telah ditetapkan. Hasil kajian ini menunjukkan bahawa hubungan korelasi antara gaya pembelajaran pelajar terhadap pemahaman pelajar adalah kuat. Manakala hubungan korelasi antara latar belakang Matematik, motivasi dan minat terhadap pemahaman pelajar adalah sederhana. Nilai tahap min bagi masalah pemahaman pelajar, latar belakang Matematik, gaya pembelajaran, motivasi dan minat terhadap bab Pengawalan Kos Makanan adalah sederhana. Kajian ini mencadangkan penghasilan satu Modul Pembelajaran Kendiri bagi bab Pengawalan Kos Makanan untuk membantu pelajar kursus Katering dalam proses pembelajaran mereka