An efficient 3D localization algorithm for compensating stratification effect in underwater acoustic sensor network

Due to the limited resources of sensor nodes, an energyefficient routing algorithm of Wireless Sensor Networks is considered as one of the most important issues in improving network lifetime. To resolve this issue, several routing algorithms have been suggested, but the published studies have mainly focused on minimizing distances between sensor nodes or the number of hops. These researches have also assumed that all the sensor nodes participate in the sensing task. In this paper, we propose a new cluster head selection algorithm focusing on both the density of sensor nodes and sensing-awareness that has not been considered yet in other existing researches on cluster-based routing scheme. In the real sensor network environment, only a part of sensor nodes participates in data reporting, so consideration of sensing-awareness in a routing algorithm will have effect on network efficiency. Moreover, the density of sensor nodes that has resulted from geographical location of sensor nodes can be an important factor in cluster head selection. The simulation results show that the proposed algorithm, by considering these 2 factors simultaneously, reduces energy consumption and enhances network lifetime.

We consider a large-scale wireless network, but with a low density of nodes per unit area. Interferences are then less critical, contrary to connectivity. This paper studies the latter property for both a purely ad-hoc network and a hybrid network, where fixed base stations can be reached in multiple hops. We assume here that power constraints are modeled by a maximal distance above which two nodes are not (directly) connected. We find that the introduction of a sparse network of base stations does significantly help in increasing the connectivity, but only when the node density is much larger in one dimension than in the other. We explain the results by percolation theory. We obtain analytical expressions of the probability of connectivity in the 1D case. We also show that at a low spatial density of nodes, bottlenecks are unavoidable. Results obtained on actual population data confirm our findings.

The nodes in wireless sensor networks (WSNs) are responsible for communicating data which is primarily of three types viz. video, audio and text. In literature, a large number of energy aware and shortest path based route selection approaches have been proposed to enhance the routing efficiency in WSNs. Most of these route selection approaches are designed by assuming fixed type and size of data packets and results in the same path selection for all types of data. This path selection, does not consider data size and data priority, results in high contention losses, topology failures and non-uniformity in energy depletion of nodes. In this paper, a route selection approach which is based on the preservation of network connectivity for improving overall network lifetime has been proposed for applications where sensor nodes are required to transmit different types of data. The proposed approach preserve highly connected edges at the initial rounds of data communication in an energy efficient manner, such that network connectivity would be maintained even at later rounds of data communications. The proposed route selection approach, VDR, (Variable Data rate Routing) has been simulated with both proactive and reactive route maintenance strategies. The simulation results show that the proposed algorithm with both proactive and reactive route maintenance strategies result in better network lifetime, energy consumption, overall network connectivity, packet delivery ratio as compared to the existing State-of-the-Art energy efficient route selection approaches with proactive and reactive route maintenance strategies. The results also show that the proposed algorithm is scalable and performs better than the compared algorithms both at low node density and high node density.

In this paper, we devise the optimal caching placement to maximize the offloading probability for a two-tier wireless caching system, where the helpers and a part of users have caching ability. The offloading comes from the local caching, D2D sharing and the helper transmission. In particular, to maximize the offloading probability we reformulate the caching placement problem for users and helpers into a difference of convex (DC) problem which can be effectively solved by DC programming. Moreover, we analyze the two extreme cases where there is only help-tier caching network and only user-tier. Specifically, the placement problem for the helper-tier caching network is reduced to a convex problem, and can be effectively solved by the classical water-filling method. We notice that users and helpers prefer to cache popular contents under low node density and prefer to cache different contents evenly under high node density. Simulation results indicate a great performance gain of the proposed caching placement over existing approaches.

Intercell interference is one of the most challenging issues in femtocell deployment under the coverage of existing macrocell. Allocation of resources between femtocell and macrocell is essential to counter the effects of interference in dense femtocell networks. Advances in resource management strategies have improved the control mechanism for interference reduction at lower node density, but most of them are ineffective at higher node density. In this paper, a dynamic resource allocation management algorithm (DRAMA) for spectrum shared hybrid access OFDMA femtocell network is proposed. To reduce the macro-femto-tier interference and to improve the quality of service, the proposed algorithm features a dynamic resource allocation scheme by controlling them both centrally and locally. The proposed scheme focuses on Femtocell Access Point (FAP) owners' satisfaction and allows maximum utilization of available resources based on congestion in the network. A simulation environment is developed to study the quantitative performance of DRAMA in hybrid access-control femtocell network and compare it to closed and open access mechanisms. The performance analysis shows that higher number of random users gets connected to the FAP without compromising FAP owners' satisfaction allowing the macrocell to offload a large number of users in a dense heterogeneous network.

Passive tracking aims to track targets without assistant devices, that is, device-free targets. Passive tracking based on Radio Frequency (RF) Tomography in wireless sensor networks has recently been addressed as an emerging field. The passive tracking scheme using geometric theorems (GTs) is one of the most popular RF Tomography schemes, because the GT-based method can effectively mitigate the demand for a high density of wireless nodes. In the GT-based tracking scheme, the tracking scenario is considered as a two-dimensional geometric topology and then geometric theorems are applied to estimate crossing points (CPs) of the device-free target on line-of-sight links (LOSLs), which reveal the target’s trajectory information in a discrete form. In this paper, we review existing GT-based tracking schemes, and then propose a novel passive tracking scheme by exploiting the Intercept Theorem (IT). To create an IT-based CP estimation scheme available in the noisy non-parallel LOSL situation, we develop the equal-ratio traverse (ERT) method. Finally, we analyze properties of three GT-based tracking algorithms and the performance of these schemes is evaluated experimentally under various trajectories, node densities, and noisy topologies. Analysis of experimental results shows that tracking schemes exploiting geometric theorems can achieve remarkable positioning accuracy even under rather a low density of wireless nodes. Moreover, the proposed IT scheme can provide generally finer tracking accuracy under even lower node density and noisier topologies, in comparison to other schemes.

Clustering sensor nodes is an effective approach for large-scale wireless sensor networks to enhance their performance. In this paper, we proposed CMA (cluster merging algorithm with link optimization), a new clustering algorithm for wireless sensor networks with low density and short communication range of sensor nodes. CMA is a multipoint initiated topology discovery algorithm, which merges small clusters to larger clusters with multi-hop intra-cluster communication by means of neighborhood discovery. During this course, it also optimizes wireless links in clusters to form a well distributed network topology. Residual energy is an important factor for regrouping clusters during network lifetime in order to balance the energy consumption of nodes. With the application of the algorithm, networks can form clustered topology fast and cluster heads can be well elected again after growing energy consumption. The simulation results show that CMA can shorten the topology establish time and reduce network overhead during the course

The sensor nodes in a network are connected to the outer world via a base station. Base stations (BS) have some back up power and it is not suppose to fail due to shortage of battery power. The nodes which are away from the base station communicate to it via the nodes which are in proximity of BS. So, the nodes which are nearer to BS have additional communication responsibilities of forwarding data of distant nodes. Thus the nodes which are in proximity of BS will run out of battery power very soon and create bottleneck for communication. In this paper we have proposed that if the density of sensor nodes increases as we move towards base station this effect can be minimized. We found the required exact density of the sensor nodes at a particular distance from BS to avoid bottleneck phenomenon around it. We have considered the real life scenario where the nodes generate data only when there is an event of interest with a given probability of occurrence. The main contribution of this paper with our proposed strategy is lifetime offered per unit cost of deployment is almost double

The early detection and monitoring of forest fire is important for fire suppression quickly and reducing the loss of human and property. At present, forest fire monitoring techniques based on wireless sensor networks have drawn more and more attention from both academic and forestry field. In order to reduce the cost of monitoring system, it is necessary to monitor a biggest area with sensor nodes of given number. In this paper, based on the forest fire circular propagation model, the case where the sensors are located in a regular triangle grid is analyzed. Some results which relate the sensor node density to the forest fire monitoring quality are presented. The theoretical analysis and the results of Monte Carlo simulations show that, the expect value of the time to fire detection is proportional to the ration of node density to the fire propagation speed, and the expect value of burned area only depends on the node density, but it doesn’t depend on the distribution of the fire ignition and fire propagation model.

In this work we investigate the connectivity properties of ad hoc networks with stations (also called nodes) transmitting at either a constant or random power. It is assumed that the random power is uniformly distributed with a mean value equal to the constant power. Two nodes are bidirectionally connected if the signal to noise plus interference ratio (SINR) is larger than a given threshold. A numerical study is performed to evaluate the connectivity of the network in terms of node density and interference level. It is found that al low node densities connectivity increases when node transmitt at a constant power. In constrast, at high node densities the better connectivity is obtained when nodes transmitt at a random power.

Underwater acoustic sensor networks (UASNs), which adopt acoustic communication, have been widely used underwater, such as in oceans and rivers, for monitoring applications. However, the UASNs designed for urban lake monitoring are facing challenges and are seldom regarded. Based on the analysis of the features of the urban lakes and the monitoring requirements, a UASN system is designed in this article. The node deployment strategy is discussed to balance the node density and transmission bandwidth. Then a hybrid topology is proposed to meet the monitoring requirements, in which the nodes on the water surface construct a 2-D ring topology, and the nodes underwater construct a 3-D grid structure. Based on this topology, a media access control (MAC) protocol-improved handshake-based low delay (i-HALO) is designed which improves the existing handshaking mechanism with a dynamic adaptive backoff algorithm to avoid unnecessary back off. As the result, the high delay problem is addressed and the “one handshake, multiple transmission” is realized. The channel access delay is analyzed theoretically and the formula of waiting time for a frame before sending is given. The performance of throughput and transmission delay under different node densities and frame lengths are simulated. The results indicate that a node having about 13 neighbors will have the best performance on throughput, and when the frame length is longer than 100 bytes, the throughput and delay will have fluctuation. In comparison with existing protocols, i-HALO has a better performance on throughput, delay, frame reception rate (FRR), and fairness.

Wireless sensor networks have grown from homogeneous network architecture to heterogeneous networks for the improvement of network efficiency and lifetime. This paper exhibits a mobile cluster-head data collection (MCHDC) model for heterogeneous wireless networks. The MCHDC model illustrates the mobility pattern of mobile cluster-head nodes in a controlled environment with uniform and nonuniform deployment of mobile elements in the area of observation. It focuses on the threshold velocity for movement of mobile elements in the network area. In this paper the effects of data sending rate, network area, sensor node density, and cluster-head node density on energy efficiency of the network with the MCHDC model have been studied through simulations.

In some applications of wireless sensor networks (WSN), sensor nodes are mobile while the sinks are static. In such dynamic environment, situations may arise where many sensor nodes are forwarding data through the same sink node resulting in sink overloading. One of the obvious effects of sink overloading is packet loss. It also indirectly affects the network lifetime in loss-sensitive WSN applications. Therefore, proper placement of sinks in such dynamic environment has a great impact on the performance of WSN applications. Multiple sink placement may not also work in some situations as node density may not be uniform. This paper introduces a sink placement scheme that aims at gathering experiences about sensor node density in a region at different times and based on these observations, the scheme proposes candidate sink locations in order to reduce sink overloading. Next, based upon current sensor node density pattern, sinks at these locations are scheduled to active mode, while sinks at remaining candidate locations are scheduled to sleep mode. The second phase is repeated periodically. The scheme is implemented in a simulation environment and compared with another well-known strategy, namely Geographic Sink Placement (GSP). It has been observed that the proposed scheme exhibits better performance with respect to sink overloading and packet loss in comparison with GSP.

As the core component of the smart grid, advanced metering infrastructure (AMI) is responsible for automated billing, demand response, load forecasting, management, etc. The jamming attack poses a serious threat to the AMI communication networks, especially the neighborhood area network where wireless technologies are widely adopted to connect a tremendous amount of smart meters. An attacker can easily build a jammer using a software-defined radio and jam the wireless communications between smart meters and local controllers, causing failures of on-line monitoring and state estimation. Accurate jammer localization is the first step for defending AMIs against jamming attacks. In this paper, we propose JamCatcher, a mobile jammer localization scheme for defending the AMI. Unlike existing jammer localization schemes, which only consider stationary jammers and usually require a high density of anchor nodes, the proposed scheme utilizes a tracker and can localize a mobile jammer with sparse anchor nodes. The time delay of data transmission is also considered, and the jammer localization process is divided into two stages, i.e., far-field chasing stage and near-field capturing stage. Different localization algorithms are developed for each stage. The proposed method has been tested with data from both simulation and real-world experiment. The results demonstrate that JamCatcher outperforms existing jammer localization algorithms with a limited number of anchor nodes in the AMI scenario.

Due to the infrastructure-less, dynamic and broadcast nature of radio transmissions, communications in mobile ad hoc networks (MANETs) are susceptible to malicious traffic analysis. After traffic analysis, an attacker determines a target node and conducts an intensive attack against it, called target-oriented attack. The traffic analysis and the target-oriented attacks are known as quite severe problems in MANETs, including position-based routing protocols, with respect to the degradation of both throughput and security of the routing. Also position information of routing nodes is very sensitive data in MANETs where even nodes not knowing either other establish a network temporarily. Therefore we propose a new position-based routing protocol which keeps routing nodes anonymous, thereby preventing possible traffic analysis. To this end, a time variant temporary identifier temp ID is computed from time and position of a node and used for keeping the node anonymous. Only the position of a destination node is required for the route discovery, and temp ID is used for establishing the route for sending data: a receiver hand shake scheme is designed for determining the next hop on-demand with use of the temp ID. We evaluate the level of anonymity and performance of our scheme. The analysis shows that the proposed scheme ensures the anonymity of both route and nodes and the robustness against the target-oriented attack and several others. Also our scheme is applicable to networks with any density of nodes.