Geographic-Based Spray-and-Relay (GSaR): An Efficient Routing Scheme for DTNs

In this article, we design and evaluate the proposed Geographic-based Spray-and-Relay (GSaR) routing scheme in Delay/Disruption Tolerant Networks (DTNs). To the best of our knowledge, GSaR is the first spray based geographic routing scheme using the historical geographic information for making routing decision. Here, the term spray means only a limited number of message copies are allowed for replication in the network. By estimating a movement range of destination via the historical geographic information, GSaR expedites message being sprayed towards this range, meanwhile prevents that away from and postpones that out of this range. As such, the combination of them intends to fast and efficiently spray the limited number of message copies towards this range, and effectively spray them within range, in order to reduce the delivery delay and increase the delivery ratio. Furthermore, GSaR exploits Delegation Forwarding (DF) to enhance the reliability of routing decision and handle the local maximum problem, considered as the challenges for applying geographic routing scheme in sparse networks. We evaluate GSaR under three city scenarios abstracted from real world, with other routing schemes for comparison. Results show that GSaR is reliable for delivering messages before expiration deadline and efficient for achieving low routing overhead ratio. Further observation indicates that GSaR is also efficient in terms of a low and fair energy consumption over the nodes in the network

T-MQM: Testbed based Multi-metric Quality Measurement of Sensor Deployment for Precision Agriculture - A Case Study

Efficient sensor deployment is one of primary requirements of precision agriculture use case of Wireless Sensor Networks (WSNs) to provide qualitative and optimal coverage and connectivity. The application-based performance variations of the geometrical-model-based sensor deployment patterns restricts the generalization of a specific deployment pattern for all applications. Further, single or double metrics based evaluation of the deployment patterns focusing on theoretical or simulation aspects can be attributed to the difference in performance of real applications and the reported performance in literature. In this context, this paper proposes a Testbed based Multi-metric Quality Measurement (T-MQM) of sensor deployment for precision agriculture use case of WSNs. Specifically, seven metrics are derived for qualitative measurement of sensor deployment patterns for precision agriculture. The seven metrics are quantified for four sensor deployment patterns to measure the quality of coverage and connectivity. Analytical and simulation based evaluations of the measurements are validated through testbed experiment based evaluations which are carried out in ‘INDRIYA’ WSNs testbed. Towards realistic research impact, the investigative evaluation of the geometrical-model-based deployment patterns presented in this article could be useful for practitioners and researchers in developing performance guaranteed applications for precision agriculture and novel coverage and connectivity models for deployment patterns

Error estimates for a mixed finite element discretization of a two-phase porous media flow model with dynamic capillarity

\u3cp\u3eWe analyze a fully discrete numerical scheme for the model describing two-phase immiscible flow in porous media with dynamic effects in the capillary pressure. We employ the Euler implicit method for the time discretization. The spatial discretization is based on the mixed finite element method (MFEM). Specifically, the lowest order Raviart–Thomas elements are applied. In this paper, the error estimates for the saturation, fluxes and phase pressures in L \u3csup\u3e∞\u3c/sup\u3e (0,T;L \u3csup\u3e2\u3c/sup\u3e (Ω)) are derived for the temporal and spatial discretization to show the convergence of the scheme. Finally, we present some numerical results to support the theoretical findings. \u3c/p\u3