This letter provides exact characterization of the contact and nearest-neighbor distance distributions for the n-dimensional (n-D) Matérn cluster process (MCP). We also provide novel upper and lower bounds to these distributions in order to gain useful insights about their behavior. The two and three dimensional versions of these results are directly applicable to the performance analyses of wireless networks modeled as MCP.
In many forest fire incidences, late detection of the fire has lead to severe damages to the forest and human property requiring more resources to gain control over the fire. An early warning and immediate response system can be a promising solution to avoid such massive losses. This paper considers a network consisting of multiple wireless sensors randomly deployed throughout the forest for early prompt detection of fire. We present a framework to model fire propagation in a forest and analyze the performance of considered wireless sensor network in terms of fire detection probability. In particular, this paper models sensor deployment as a Poisson point process (PPP) and models the forest fire as a dynamic event which expands with time. We also present various insights to the system including required sensor density and impact of wind velocity on the detection performance. We show that larger wind velocity may not necessarily imply bad sensing performance or the requirement of a denser deployment.
Wireless sensor network is a diverse network. One of the important limitation of the wireless sensor network is limited life-time, wireless nodes typically operates with small batteries for which replacement, when possible, is very difficult and expensive. Therefore nodes must operate without battery replacement for long time. Consequently, minimizing the energy consumption is a very important design consideration and energyefficient transmission schemes must be used for the data transfer in wireless sensor networks.This paper, proposes the energy efficient transmission scheme to minimize the per node energy consumption. In the proposed scheme after the cluster formation in the network potential cluster head will select the cooperative node to transfer data from one cluster to other. The results shows that by transmitting and/or receiving information jointly, tremendous energy saving is possible for larger transmission distances,even after considering the local energy cost necessary for joint information transmission and reception.
Ecosystem of a forest suffers from many adverse events such as wild-fire which can occur randomly anywhere in the forest and grows in size with time. This paper aims to analyze performance of a network of randomly deployed wireless sensors for the early detection of these time-critical and time-evolving events in a forest. We consider that the forest lies in a confined space (e.g. a circular region) and the wireless sensors, with fixed sensing range, are deployed within the boundary of forest itself. The sensing area of the network is modeled as a finite Boolean-Poisson model. In this model, the locations of sensors are modeled as a finite homogeneous Poisson Point Process (PPP) and the sensing area of each sensor is assumed to be a finite set. This paper aims to answer questions about the proximity of a typical sensor from a randomly occurred event and the total sensing area covered by sensors. We first derive the distribution of contact distance of a FHPPP and the expression of the capacity functional of a finite Boolean-Poisson model. Using these, we then derive the probability of sensing the event at time t, termed event-sensing probability.
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