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The last decade has seen an exponential rise in the use of wireless sensor networks (WSNs) in various
applications. While these have been primarily used on their own, researchers are now looking into ways of integrating these WSNs with other existing communication technologies. One such network is the satellite network which provides significant ad...
Citations
... Також не менш важливим є завдання ефективного використання наявного обмеженого енергетичного ресурсу мобільних пристроїв. Тому варто розглянути сценарій використання спрямованих антен [3][4][5][6], що дозволить покращити вказані вище параметри. Питання оптимального вибору антенних систем стає все актуальнішим, особливо при застосуванні у НПМ. ...
... Specifically, the architectures and applications of satellite-based WSNs and the roles of the satellite systems were studied in [4]. The work in [11] addressed four architectures of satellite-based WSNs and analyzed the performance of average end-to-end packet delay, packet loss rate and overall energy consumption. In addition, Reference [12] presented the model to evaluate the capacity of the remote sensor and satellite network and attempted to optimize the integrated wireless sensor and satellite network schedules. ...
With the growing demand, Wireless Multimedia Sensor Networks (WMSNs) play an increasingly important role, which enhances the capacity of typical Wireless Sensor Networks (WSNs). Additionally, integrating satellite systems into WMSNs brings about the beneficial synergy, especially in rural and sparsely populated areas. However, the available spectrum resource is scarce, which contradicts the high-speed content required for multimedia. Cognitive radio is a promising solution to address the conflict. In this context, we propose a novel spectrum-sharing method for the integrated wireless multimedia sensor and cognitive satellite network based on the dynamic frequency allocation. Specifically, the Low Earth Orbit (LEO) satellite system plays the role of the auxiliary to connect sensor nodes and the remote control host, and it shares the same frequency with the Geostationary Earth Orbit (GEO) system in the downlink. Because the altitudes of GEO and LEO satellites differ greatly, the beam size of GEO is much larger than that of LEO, which provides the opportunity for LEO beam to reuse the frequency that was allocated to the GEO beam. A keep-out region is defined to guarantee the spectral coexistence based on the interference analysis in the worst case. In addition, a dynamic frequency allocation algorithm is presented to deal with the dynamic configuration caused by the satellite motion. Numerical results demonstrate that the dynamic spectrum-sharing method can improve the throughput.
... To compute the optimal capacity approximation (27), θ i can be determined as θ i ≈ λ 2 i (T), and λ i (T) is approximately expressed as Equations (12) and (13) respectively for the hybrid 1D beam model and modified hybrid 1D beam model. Since λ (l−1)M+m (T 2D ) of the hybrid 2D beam model are affected by L and M and computed repeatedly in (27), we use the integral of the inverse function [51] to get θ i for the hybrid 2D beam model, ...
This paper investigates the performance of integrated wireless sensor and multibeam satellite networks (IWSMSNs) under terrestrial interference. The IWSMSNs constitute sensor nodes (SNs), satellite sinks (SSs), multibeam satellite and remote monitoring hosts (RMHs). The multibeam satellite covers multiple beams and multiple SSs in each beam. The SSs can be directly used as SNs to transmit sensing data to RMHs via the satellite, and they can also be used to collect the sensing data from other SNs to transmit to the RMHs. We propose the hybrid one-dimensional (1D) and 2D beam models including the equivalent intra-beam interference factor b from terrestrial communication networks (TCNs) and the equivalent inter-beam interference factor a from adjacent beams. The terrestrial interference is possibly due to the signals from the TCNs or the signals of sinks being transmitted to other satellite networks. The closed-form approximations of capacity per beam are derived for the return link of IWSMSNs under terrestrial interference by using the Haar approximations where the IWSMSNs experience the Rician fading channel. The optimal joint decoding capacity can be considered as the upper bound where all of the SSs’ signals can be jointly decoded by a super-receiver on board the multibeam satellite or a gateway station that knows all of the code books. While the linear minimum mean square error (MMSE) capacity is where all of the signals of SSs are decoded singularly by a multibeam satellite or a gateway station. The simulations show that the optimal capacities are obviously higher than the MMSE capacities under the same conditions, while the capacities are lowered by Rician fading and converge as the Rician factor increases. α and β jointly affect the performance of hybrid 1D and 2D beam models, and the number of SSs also contributes different effects on the optimal capacity and MMSE capacity of the IWSMSNs.
... [16] introduced specific performance metrics reference packet loss rate, average packet delay, and energy consumption to evaluate the functionality of hybrid sensor-satellite networks. [17] presented hybrid sensor-satellite networks, sensor-satellite direct communication, connections via a gateway node employing random node layout and cluster-based node layout with data aggregation. [18] formulated a general model to evaluate the IWSSNs capacity to optimize the schedules. ...
This paper investigates an efficient transmission scheme for the remote wireless sensors to receive information which is rarely discussed in the integrated remote wireless sensor and multibeam satellite networks (IWSMSNs). The networks can be employed to exchange sensing information for emergency scenario, ocean scenario, and so on, which are isolated from available terrestrial networks. As the efficient transmission link is important to the IWSMSNs, we propose a hybrid full frequency (HFF) precoding by taking advantage of frequency reuse and multiple-input multiple-output (MIMO) precoding. Considering energy efficiency and sinks fairness are crucial to transmission link, thus the HFF precoding problems are formulated as transmit power minimization (TPM) and max-min fair (MMF) received signal to interference plus noise ratio (SINR) problems, which can be transformed to indefinite quadratic optimization programs. Then this paper presents a semi-definite programming (SDP) algorithm to solve the problems for the IWSMSNs. The promising potential of HFF for the real IWSMSNs is demonstrated through simulations.
... They used the bundle layer to solve the problem of data transmission efficiently. In [28], Verma et al. studied the performance of different integrated sensor and satellite network architectures. The packet loss rate and average end-to-end packet delay were compared in different network architectures. ...
This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN.
... For example, in MONET project [10], the aggregate data rate generated by network nodes can exceed this maximum rate of 492 kb/s, where nodes send data and images of 1-Mb average size and set up visioconference sessions of 256 kb/s periodically. Considering the sensing data rate for a typical sensor within a range 10-250 kb/s [14], [15], simultaneous sensory data can itself generate traffic peaks. To support the traffic load and also ensure quick data delivery, multiple terminals are typically deployed in the area of observation, where they act as packet gateways 1 to the satellite network and as data sinks for the WSN that collects the data. ...
Data collection is a fundamental task of wireless sensor networks to support a variety of applications, such as remote monitoring, and emergency response, where collected information is relayed to an infrastructure network via packet gateways for processing and decision making. In large-scale monitoring scenarios, data packets need to be relayed over multihop paths to the gateways, and sensors are often randomly deployed, causing local node density differences. As a result, imbalance in data traffic load on the gateways is likely to occur. Furthermore, due to dynamic network conditions and differences in sensor data generation rates, congestion on some data paths is also often experienced. Numerous studies have focused on the problem of in-network traffic load balancing, whereas a few works have aimed at equalizing the loads on gateways. However, there is a potential tradeoff between these two problems. In this paper, the dual objective of gateway and in-network load balancing is addressed, and the reactive and adaptive load-balancing (RALB) algorithm is presented. RALB is proposed as a generic solution for multihop networks and mesh topologies, particularly in large-scale remote monitoring scenarios, to balance traffic loads.
... The reason is that terrestrial network currently covers only 10% of the world and has created a need to switch toward satellite networks which would help to cover the remaining 90% of the world, making it the most attractive aspect of satellite sensor connectivity. In recent years, the research of combing wireless sensor network with satellite communication represents a good opportunity [9][10][11]. The wireless sensor satellite communication market comprises services such as environmental and habitat monitoring, satellite remote sensing for ocean research, and structural health monitoring. ...
This paper presents the performance analysis of wireless sensor networks- (WSNs-) based satellite collocation system as cooperative transmission is applied. A scenario of satellite cluster is considered, where multiple satellites are collocated with each other. Considering that the performance of satellite systems can be improved as the spot beam is split into virtual beams, the optimized system capacity can be expected by applying the geometrical arrangement of the antennas of transmitters and receivers. In the following simulation experiments, the system capacity is investigated as various system configurations are applied. It is found that the optimal value of system capacity exists as expected, and the simulation observations are illustrated as practical limitations are considered.
... The overall network architecture is as shown in Fig. 1 wherein the various network components are highlighted along with the expected flow of data within the integrated network. Typically, the WSN consists of several wireless sensor nodes which are deployed within the sensing region in a star topology cluster-based node layout scheme [18], as shown in Fig. 1, wherein the sensing region is divided into multiple clusters and each Sensor Node (SN) within the cluster is randomly distributed within the transmission range of the Cluster Head (CH) node. This proves to be more efficient than a non-cluster based node layout scheme where all the sensor nodes are randomly deployed within the sensing region and directly communicate with the gateway node, since the overall load is being evenly distributed among various clusters thereby increasing the operating lifetime of the network components within the WSN [13]. ...
... The network architecture of the WSN-sa network is adopted from [11] which propose node layout scheme for the integrated netwo architecture for the WSN-satellite integrated this paper to study the effects on the performance when security and data implemented is shown inFig. 1 where the W based network with each cluster having a c and a satellite gateway node. For simplicity, the cluster head node is placed at the cen cluster, wherein the sensor nodes are arranged like manner. ...
... Data aggregation energy of 5 nJ/bit is used to determine the amount of energy spent in aggregating N sensor data packets of 1024 bits each [13]. The energy required to transmit a single sensor data packet of 1024 bits from the cluster head node to the gateway node is 204.8 µJ [11]. It is interesting to note fromFig. ...
Recently there has been an exponential rise in the use of Wireless Sensor Networks (WSNs) in various applications. While WSNs have been primarily used as independent networks, researchers are now looking into ways of integrating them with other existing networks. One such network is the satellite network which provides a reliable communication backbone to remote areas that lack appropriate terrestrial infrastructure. However, due to the integration of the two networks with different transmission and operational characteristics interoperability and security become major concerns. This paper presents an ns-2 based simulation framework of a WSN-satellite integrated network that is used to evaluate the effects of data aggregation and security mechanisms on overall network performance. The average end-to-end packet delay, overall energy consumption and aggregation efficiency are considered for this analysis. This paper also looks into the effects of implementing hop-by-hop security and end-to-end security and justifies the need for end-to-end security in the WSN-satellite integrated networks.
