ISEP – CISTER – Outros
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Browsing ISEP – CISTER – Outros by Author "Cerqueira, Tiago"
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- A module for Data Centric Storage in ns-3Publication . Albano, Michele; Cerqueira, Tiago; Chessa, StefanoManagement of data in large wireless sensor networks presents many hurdles, mainly caused by the limited energy available to the sensors, and by the limited knowledge of the sensors regarding the topology of the network. The first problem has been targeted by the introduction of in-network storage of sensed data, which can save much communication energy. The second issue found some relief with the introduction of geographical protocols that do not need knowledge regarding the network at large. Data Centric Storage systems such as QNiGHT [1][2] assume that each sensor knows its own geographical location, and they use geographical routing such as the Enhanced Greedy Perimeter Stateless Routing (EGPSR) protocol, sketched in Figure 1, to deliver packets to the sensor closest to a given point in the sensing area.
- A module for the FTT-SE protocol in ns-3Publication . Oliveira, Fábio; Martínez, Ricardo Garibay; Cerqueira, Tiago; Albano, Michele; Ferreira, Luís LinoThe Flexible Time Triggered Switched Ethernet (FFT-SE) protocol allows the concurrent transmission of both real-time (i.e., synchronous and asynchronous) traffic and best-effort traffic over Ethernet. Communications within an FTT-SE network are done based on the reservation of fixed duration time slots called Elementary Cycles (ECs). The construction of the ECs and the media access control are managed by the master node. The FTTSE protocol uses the master/slave paradigm, in which the slave nodes make petitions for transmission to the master node, and the master node grants them access for transmission according to the scheduling algorithm chosen by the master node (e.g., Rate Monotonic, Earliest Deadline First, etc.).
- A module for the XDense architecture in ns-3Publication . Loureiro, João; Albano, Michele; Cerqueira, Tiago; Rangarajan, Raghuraman; Tovar, EduardoThe acquisition of data regarding some dynamic phenomena can require extremely dense deployments of sensors and high sampling rates. We propose XDense [1], a wired mesh grid sensor network architecture (see Figure 1a) tailored for scenarios that benefit from thousands of sensors per square meter. XDense has scalable network topology and it enables complex feature extraction in real-time from the observed phenomena, by exploiting distributed processing capabilities and inter-node communication, the latter being represented in Figure 1b.