Uniform Deployment Research Articles

Initializing Sensor Networks of Non-uniform Density in the Weak Sensor Model

Assumptions about node density in the sensor networks literature are frequently too strong. Neither adversarially chosen nor uniform random deployment seem realistic in many intended applications of sensor nodes. We define smooth distributions of sensor nodes to be those where the minimum density is guaranteed to achieve connectivity in random deployments, but higher densities may appear in certain areas. We study basic problems for smooth distribution of nodes. Most notably, we present a Weak Sensor Model-compliant distributed protocol for hop-optimal network initialization (NI), a fundamental problem in sensor networks. In order to prove lower bounds, we observe that all nodes must communicate with some other node in order to join the network, and we call the problem of achieving such a communication the group therapy (GT) problem. We show a tight lower bound for the GT problem in radio networks for any class of protocols, and a stronger lower bound for the important class of randomized uniform-oblivious protocols. Given that any NI protocol also solves GT, these lower bounds apply to NI. We also show that the same lower bound holds for a related problem that we call independent set , when nodes are distributed uniformly, even in expectation.

Wireless energy transfer in sensor networks with adaptive, limited knowledge protocols

We investigate the problem of efficient wireless energy transfer in Wireless Rechargeable Sensor Networks (WRSNs). In such networks a special mobile entity (called the Mobile Charger) traverses the network and wirelessly replenishes the energy of sensor nodes. In contrast to most current approaches, we envision methods that are distributed, adaptive and use limited network information. We propose three new, alternative protocols for efficient charging, addressing key issues which we identify, most notably (i) to what extent each sensor should be charged, (ii) what is the best split of the total energy between the charger and the sensors and (iii) what are good trajectories the Mobile Charger should follow. One of our protocols (LRP) performs some distributed, limited sampling of the network status, while another one (RTP) reactively adapts to energy shortage alerts judiciously spread in the network. We conduct detailed simulations in uniform and non-uniform network deployments, using three different underlying routing protocol families. In most cases, both our charging protocols significantly outperform known state of the art methods, while their performance gets quite close to the performance of the global knowledge method (GKP) we also provide.

Unified Cooperative Control of Multiple Agents on a Sphere for Different Spherical Patterns

In this technical note, we consider the cooperative control of multiple agents on a sphere, provide the appropriate attraction-repulsion interactions between agents with introduction of the state-dependent repulsive coefficients, and design the unified control laws for agents to achieve three fundamental spherical configurations or patterns: rendezvous, uniform deployment, and formation, using both the first- and second-order models. We present the analysis of the stability, scaling and geometric patterns of the models on the sphere under different attraction-repulsion parameters, with illustration of the geometrical patterns and the geometrical isomerism by simulations. The closed-loop dynamics of agents are invariant with respect to group rotation actions on the sphere.

GENDEP: Location-Aware Key Management for General Deployment of Wireless Sensor Networks

Limited capabilities of tiny sensor node make it difficult to build a secure wireless sensor network. To cope with this problem, location-aware key predistribution schemes have been studied but without considering irregularity of real sensing fields. They were designed for ideal sensing fields divided into uniform regular polygons but false is the real sensing field, where we face irregular obstacles, undulations, and boundaries. In this paper, we tackle this problem from practical sense and first introduce the general deployment model, comparable to the previous uniform deployment model. To construct a secure WSN in the general deployment model, we present a new framework called GenDep, which consists of two phases: group placement and key management. In the group placement phase, we find an optimal position for sensor groups so that both connectivity and global coverage are satisfied for secure communications. In the key management phase, we devise a new structure called extended groups to partition the whole deployment area into irregular subareas. GenDep can build secure and flexible WSNs by using the existing key predistribution schemes even designed in the uniform deployment model. To ensure practicality of GenDep, we also conduct rigorous analysis and simulation in this paper.

Chain-type wireless sensor network node scheduling strategy

In order to reduce power consumption of sensor nodes and extend network survival time in the wireless sensor network (WSN), sensor nodes are scheduled in an active or dormant mode. A chain-type WSN is fundamentally different from other types of WSNs, in which the sensor nodes are deployed along elongated geographic areas and form a chain-type network topology structure. This paper investigates the node scheduling problem in the chain-type WSN. Firstly, a node dormant scheduling mode is analyzed theoretically from geographic coverage, and then three neighboring nodes scheduling criteria are proposed. Secondly, a hybrid coverage scheduling algorithm and dead areas are presented. Finally, node scheduling in mine tunnel WSN with uniform deployment (UD), non-uniform deployment (NUD) and optimal distribution point spacing (ODS) is simulated. The results show that the node scheduling with UD and NUD, especially NUD, can effectively extend the network survival time. Therefore, a strategy of adding a few mobile nodes which activate the network in dead areas is proposed, which can further extend the network survival time by balancing the energy consumption of nodes.

Coverage and Throughput Analysis with a Non-Uniform Small Cell Deployment

Small cell network (SCN) offers, for the first time, a low-cost and scalable mechanism to meet the forecast data-traffic demand. In this paper, we propose a non-uniform SCN deployment scheme. The small cell base stations (BSs) in this scheme will not be utilized in the region within a prescribed distance away from any macrocell BSs, defined as the inner region. Based upon the analytical framework provided in this work, the downlink coverage and single user throughput are precisely characterized. Provided that the inner region size is appropriately chosen, we find that the proposed non-uniform SCN deployment scheme can maintain the same level of cellular coverage performance even with 50% less small cell BSs used than the uniform SCN deployment, which is commonly considered in the literature. Furthermore, both the coverage and the single user throughput performance will significantly benefit from the proposed scheme, if its average small cell density is kept identical to the uniform SCN deployment. This work demonstrates the benefits obtained from a simple non-uniform SCN deployment, thus highlighting the importance of deploying small cells selectively.

Adaptive Deployment Scheme and Multi-path Routing Protocol for WMSNs

Multi-path routing protocols have many advantages in wireless multimedia sensor networks. To succeed in setting up multiple paths in the wireless multimedia sensor network, the Adaptive Deployment Scheme of sensor Nodes which is based upon multi-path routing protocol (ADSN) is proposed in the paper. ADSN deploys the sensor nodes on the basis of the number of paths, camera nodes’ positions and the sink’s position etc. Compared to the uniform deployment scheme, ADSN can save 67% sensor nodes when setting up multiple paths. And it can avoid the hotspot area in the vicinity of the sink. Energy Equalization Multi-path Routing protocol (EEMR) can consume the energy of sensor nodes more evenly and extends the network lifetime compared to TPGF. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3820

Achieving full-view coverage in camera sensor networks

Camera sensors are different from traditional scalar sensors, as cameras at different positions can form very different views of the object. However, traditional coverage model does not consider this intrinsic property of camera sensors. To address this issue, a novel model called full-view coverage is proposed. It uses the angle between the object's facing direction and the camera's viewing direction to measure the quality of coverage. An object is full-view covered if there is always a camera to cover it no matter which direction it faces and the camera's viewing direction is sufficiently close to the object's facing direction. An efficient method is proposed for full-view coverage detection in any given camera sensor networks, and a sufficient condition on the sensor density needed for full-view coverage in a random uniform deployment is derived. In addition, the article shows a necessary and sufficient condition on the sensor density for full-view coverage in a triangular lattice-based deployment. Based on the full-view coverage model, the article further studies the barrier coverage problem. Existing weak and strong barrier coverage models are extended by considering direction issues in camera sensor networks. With these new models, weak/strong barrier coverage verification problems are introduced, and new detection methods are proposed and evaluated.

Benefits of Distribution-Level Power Electronics for Supporting Distributed Generation Growth

It is expected that distribution networks will be required to accommodate large amounts of distributed generation (DG). Keeping power flows and voltages within their limits will require either traditional infrastructure upgrades or active compensation. The form of active compensation (e.g., series, shunt, back to back, multiterminal), quantity, and rating of the compensator should be chosen to realize the best cost-benefit ratio. Distributed-generator and compensator placement algorithms are used with a power-flow and constraint satisfaction algorithm to analyze a large number of case studies (using real U.K. network data). From these cases, assessments of compensator performance are made and summarized statistically. When considering incremental deployment across all networks, with the site of greatest benefit chosen at each increment, it is found that static synchronous compensators provide the most favorable cost-benefit ratio. In contrast, multiterminal voltage-source converters tend to provide the greatest flexibility when considering uniform deployment across all networks. It is also observed that traditional reinforcement enhances the benefits provided by active compensation.

Node Placement Strategy in Wireless Sensor Network

The performance and quality of services in wireless sensor networks (WSNs) depend on coverage and connectivity. Node placement is a fundamental issue closely related to the coverage and connectivity in sensor networks. Node placement influences the target position, coverage area, and connectivity in sensor networks. In random deployment, sensor nodes are deployed randomly in a non-invasive way. The deployment process may cause issues like coverage holes, overlapping, and connectivity failure. Enhancing coverage and connectivity are important for sensor networks to provide a reliable communication within sensing. Placing many sensor nodes in a WSN application region area is not the best solution due to cost and it results in multiple sensors used. Mobile sensor node is used as an alternative to overcome the random deployment problem. The virtual force based self node deployment is used in the mobility sensor to improve the coverage and connectivity area. Virtual Force Algorithm (VFA) approach using virtual repulsive and attractive forces is used to find the optimal node placement to minimize the problems. Simulation results proofed that a uniform deployment achieved using VFA approach with an optimal sensing range to cover the region of interest.

Coverage and Energy Consumption Control in Mobile Heterogeneous Wireless Sensor Networks

In this paper, we investigate the coverage and energy consumption control in mobile heterogeneous wireless sensor networks (WSNs). By term heterogeneous, we mean that sensors in the network have various sensing radius, which is an inherent property of many applied WSNs. Two sensor deployment schemes are considered-uniform and Poisson schemes. We study the asymptotic coverage under uniform deployment scheme with i.i.d. and 1-D random walk mobility model, respectively. We propose the equivalent sensing radius (ESR) for both cases and derive the critical ESR correspondingly. Our results show that the network performance largely depends on ESR. By controlling ESR, we can always promise the network achieve full coverage, regardless of the total number of sensors or the sensing radius of a single senor under random mobility patterns, which is a much easier and more general way to operate coverage control. Meanwhile, we can operate a tradeoff control between coverage performance and energy consumption by adjusting ESR. We demonstrate that 1-D random walk mobility can decrease the sensing energy consumption under certain delay tolerance, though requires larger ESR. Also, we characterize the role of heterogeneity in coverage and energy performance of WSNs under these two mobility models, and present the discrepancy of the impact of heterogeneity under different models. Under the Poisson deployment scheme, we investigate dynamic k-coverage of WSNs with 2-D random walk mobility model. We present the relation between network coverage and the sensing range, which indicates how coverage varies according to sensing capability. Both k -coverage at an instant and over a time interval are explored and we derive the expectation of fraction of the whole operational region that is k-covered, which also identifies the coverage improvement brought by mobility.

Gaussian versus Uniform Distribution for Intrusion Detection in Wireless Sensor Networks

In a Wireless Sensor Network (WSN), intrusion detection is of significant importance in many applications in detecting malicious or unexpected intruder(s). The intruder can be an enemy in a battlefield, or a malicious moving object in the area of interest. With uniform sensor deployment, the detection probability is the same for any point in a WSN. However, some applications may require different degrees of detection probability at different locations. For example, an intrusion detection application may need improved detection probability around important entities. Gaussian-distributed WSNs can provide differentiated detection capabilities at different locations but related work is limited. This paper analyzes the problem of intrusion detection in a Gaussian-distributed WSN by characterizing the detection probability with respect to the application requirements and the network parameters under both single-sensing detection and multiple-sensing detection scenarios. Effects of different network parameters on the detection probability are examined in detail. Furthermore, performance of Gaussian-distributed WSNs is compared with uniformly distributed WSNs. This work allows us to analytically formulate detection probability in a random WSN and provides guidelines in selecting an appropriate deployment strategy and determining critical network parameters.

Evolution of grid-wide access to database resident information in ATLAS using Frontier

The ATLAS experiment deployed Frontier technology worldwide during the initial year of LHC collision data taking to enable user analysis jobs running on the Worldwide LHC Computing Grid to access database resident data. Since that time, the deployment model has evolved to optimize resources, improve performance, and streamline maintenance of Frontier and related infrastructure. In this presentation we focus on the specific changes in the deployment and improvements undertaken, such as the optimization of cache and launchpad location, the use of RPMs for more uniform deployment of underlying Frontier related components, improvements in monitoring, optimization of fail-over, and an increasing use of a centrally managed database containing site specific information (for configuration of services and monitoring). In addition, analysis of Frontier logs has allowed us a deeper understanding of problematic queries and understanding of use cases. Use of the system has grown beyond user analysis and subsystem specific tasks such as calibration and alignment, extending into production processing areas, such as initial reconstruction and trigger reprocessing. With a more robust and tuned system, we are better equipped to satisfy the still growing number of diverse clients and the demands of increasingly sophisticated processing and analysis.

Multi-hop distance estimation method based on regulated neighbourhood measure

Range-free localisation methods are suitable for large scale wireless ad hoc and sensor networks because of their less-demanding hardware requirements. Many existing connectivity- or hop-count-based range-free localisation methods suffer from the hop-distance ambiguity problem where a node has a same distance estimation to all of its one-hop neighbours. In this study, the authors define a new measure, called regulated neighbourhood distance (RND), to address this problem by relating the proximity of two neighbours to their neighbour partitions. Furthermore, the authors propose a new RND-based range-free localisation method, and the simulation results show that it outperforms two existing peer algorithms in uniform and non-uniform network deployments.

Theory and algorithms for hop-count-based localization with random geometric graph models of dense sensor networks

Wireless sensor networks can often be viewed in terms of a uniform deployment of a large number of nodes in a region of Euclidean space. Following deployment, the nodes self-organize into a mesh topology with a key aspect being self-localization . Having obtained a mesh topology in a dense, homogeneous deployment, a frequently used approximation is to take the hop distance between nodes to be proportional to the Euclidean distance between them. In this work, we analyze this approximation through two complementary analyses. We assume that the mesh topology is a random geometric graph on the nodes; and that some nodes are designated as anchors with known locations. First, we obtain high probability bounds on the Euclidean distances of all nodes that are h hops away from a fixed anchor node. In the second analysis, we provide a heuristic argument that leads to a direct approximation for the density function of the Euclidean distance between two nodes that are separated by a hop distance h . This approximation is shown, through simulation, to very closely match the true density function. Localization algorithms that draw upon the preceding analyses are then proposed and shown to perform better than some of the well-known algorithms present in the literature. Belief-propagation-based message-passing is then used to further enhance the performance of the proposed localization algorithms. To our knowledge, this is the first usage of message-passing for hop-count-based self-localization.

Exploiting limited density information towards near-optimal energy balanced data propagation

In this work, we investigate the problem of achieving energy-balanced data propagation in a distributed wireless sensor network. The energy balance property is essential for prolonging the network lifetime by maximizing the functional lifetime of a large portion of sensors. We propose a distributed, adaptive data propagation algorithm that exploits limited, local density information for achieving energy-balanced propagation while at the same time keeping energy dissipation at low levels.Apart from traditional studies considering uniform sensor distribution, we investigate heterogeneous sensor placement distributions. We conduct a detailed experimental evaluation and comparison with state-of-the-art energy-balanced protocols in order to demonstrate that our density-based protocol improves energy efficiency significantly while also having better energy balance properties.To illustrate that our protocol has near-optimal performance, we compare our protocol with a centralized, off-line optimum solution derived by a linear program which maximizes the network lifetime and show that it achieves near-optimal performance for uniform sensor deployments.

A novel range-free localization based on regulated neighborhood distance for wireless ad hoc and sensor networks

Range-free localization methods are suitable for large scale wireless ad hoc and sensor networks due to their less-demanding hardware requirements. Many existing connectivity- or hop-count-based range-free localization methods suffer from the hop-distance ambiguity problem where a node has a same distance estimation to all of its one-hop neighbors. In this paper, we define a new measure, called regulated neighborhood distance (RND), to address this problem by relating the proximity of two neighbors to their neighbor partitions. Furthermore, we propose a new RND-based range-free localization method, and compare our localization algorithm with peer classical algorithms in different network scenarios, which include grid deployment, random uniform deployment, non-uniform deployment and uniform deployment with a coverage hole. Simulation results show that ours can achieve better and reliable localization accuracy in these network scenarios.

On the GDOP and Accuracy for Indoor Positioning

Position accuracy and geometric dilution of precision (GDOP) analysis are presented for indoor mesh positioning systems in multipath and non-line-of-sight (NLOS) propagation environments. Concise analytical formulas are derived for the position error statistics in the presence of biased ranging errors and uniform random spatial anchor node deployment. Simulation and experimental verification are conducted and the results demonstrate that the analytical formulas match the simulated and experimental results well. It is shown that the system can achieve accuracy of around half a meter.

A Failure Self-recovery Strategy with Balanced Energy Consumption for Wireless Ad Hoc Networks

In energy constrained wireless sensor networks, it is significant to make full use of the limited energy and maximize the network lifetime even when facing some unexpected situation. In this paper, all sensor nodes are grouped into clusters, and for each cluster, it has a mobile cluster head to manage the whole cluster. We consider an emergent situation that one of the mobile cluster heads is broken down, and hence the whole cluster is consequently out of work. An efficient approach is proposed for recovering the failure cluster by selecting multiple static sensor nodes as the cluster heads to collect packets and transmit them to the sink node. Improved simulated annealing algorithm is utilized to achieve the uniform deployment of the cluster heads. The new cluster heads are dynamically changed in order to keep balanced energy consumption. Among the new cluster heads, packets are transmitted through multi-hop forwarding path which is cost-lowest path found by Dijkstra's algorithm. A balanced energy consumption model is provided to help find the cost-lowest path and prolong the lifetime of the network. The forwarding path is updated dynamically according to the cost of the path and residual energy of the node in that path. The experimental results show that the failure cluster is recovered and the lifetime of the cluster is prolonged.

The Optimal Transmission Range for Strip-Based Wireless Sensor Networks

Strip-based sensor networks consist of a large amount of sensor nodes, which is characterized by multihop communication patterns. The nodes closer to the base station are required to forward more data than the nodes farther from the base station, leading to the problem of the energy hole and leaving the the areas of the network unmonitored. This paper analyzes energy consumption model of the uniform deployment and the nonuniform deployment and proves that there is an optimal transmission distance for these deployment strategies. The analysis shows clearly that the nonuniform deployment is more energy effect and more energy balance, which extend the network lifetime compared with the uniform deployment strategy.