Deployment Region Research Articles

Defining breeding and deployment regions for radiata pine in southern Australia

Productivity of forest tree plantations can be maximised by matching genetically improved planting stock to environments where it performs best. Radiata pine (Pinus radiata D. Don) breeding and deployment of genetically improved stock in Australia are currently based on the National Plantation Inventory (NPI) regions. These regions are not based on environmental drivers and biological patterns of genotype by environment interaction (G × E), so they may not deliver optimal genetic gains across plantation areas in Australia. This study used diameter at breast height data from trial sites with common parents to estimate site–site and age–age additive genetic correlations, and compile them into a database. A custom-built script in R was developed, which models the correlation estimates by minimising the weighted error sum of squares from the model to the estimates. First, parameters for the Lambeth’s age–age correlation model were derived to adjust for differences in age between sites. Second, estimates of average site–site additive genetic correlations between and within NPI regions were compared with currently assumed values. Third, to identify new breeding and deployment regions, sites were sequentially divided into groups based on critical values of climate and soil variables. Sites were first split into two clusters based on mean daily minimum temperature of wettest quarter, at a threshold of 9.0 °C, and then within the cool cluster, based on rainfall in March, at a threshold of 68 mm. Variances among breeding values were compared for different site classifications as a measure of potential genetic gain. The results from this study are currently being used to redefine the breeding and deployment regions for radiata pine grown in Australia.

Multi-User Massive MIMO Communication Systems Based on Irregular Antenna Arrays

In practical mobile communication engineering applications, surfaces of antenna array deployment regions are usually uneven. Therefore, massive multi-input–multi-output (MIMO) communication systems usually transmit wireless signals by irregular antenna arrays. To evaluate the performance of irregular antenna arrays, the matrix correlation coefficient and the ergodic received gain are defined for massive MIMO communication systems with mutual coupling effects. Furthermore, the lower bound of the ergodic achievable rate, symbol error rate, and average outage probability is first derived for multi-user massive MIMO communication systems using irregular antenna arrays. Asymptotic results are also derived when the number of antennae approaches infinity. Numerical results indicate that there exists a maximum achievable rate when the number of antennae keeps increasing in massive MIMO communication systems using irregular antenna arrays. Moreover, the irregular antenna array outperforms the regular antenna array in the achievable rate of massive MIMO communication systems when the number of antennae is larger than or equal to a given threshold.

Joint location and power optimisation of femto base stations to improve indoor coverage: a geometric approach

AbstractFemto base station (FBS) deployment with existing Macro Base Stations improves Quality of Service of end users in dead‐zone while simultaneously increasing co‐channel femto–femto interference. This necessitates judicious planning before FBS deployment. In this paper, a novel geometric approach to model any 3‐D deployment region along with two particle swarm optimisation based joint location and power optimisation algorithms: LOA‐POA and LPOA are proposed. The geometric plan of the deployment region (with multiple multistoried buildings) with 3‐D coordinates of serving‐MBS has been generated and provided as input to LOA‐POA and LPOA, to identify positions and transmission powers of the FBSs required to maximise coverage. For a significantly large deployment region of 1600 sq. m., the LPOA identifies locations and transmission powers of four co‐channel FBSs within 140 s while LOA‐POA identifies the same for five FBSs within 40 s. Simulation exhibits requisite coverage after FBS installation. Comparison of these algorithms has been carried out with existing works considering different wall materials. LPOA is observed to provide most economic solution but with higher convergence time than LOA‐POA. Copyright © 2016 John Wiley & Sons, Ltd.

On the Definition and Existence of a Minimum Variance Unbiased Estimator for Target Localization

The problem of target localization with ideal, binary detectors is considered in one-dimensional space for both the censored and noncensored scenarios. In the censored setting, the problem is equivalent to estimating the center of a uniform distribution, and does not admit a minimum-variance unbiasedestimator (MVUE). However, it is proven that if the detection range is known and the sensor deployment region is large, both censored and noncensored cases will have an MVUE within the class of functions that are invariant to Euclidean motion. In addition, it is shown that when the detection range is unknown, for the censored case one can still form an MVUE whereas in the noncensored case, an MVUE does not exist. Numerical tests support the theoretical findings of this letter.

Processing of Deployment Using an Adaptive Self-Spreading Algorithm Based on Electrostatic Field for Mobile Sensor

The deployment of mobile sensor networks is a hotspot issue. This paper is dedicated to proposing a distributed, adaptive, and scalable mobile sensor network algorithm based on the theory in electrostatic field. In the algorithm, the obstacles and nodes in the deployment region were regarded as the charged particles, which were driven by the Coulomb Force exerted by the other particles and obstacles, and eventually all the nodes were distributed throughout the entire network while repelled by the obstacles and other nodes simultaneously. Based on the classical virtual potential field algorithm, the boundary conditions, the static equilibrium conditions and the controllable coverage rate were expanded in the present algorithm, which are also the primary innovation points and contributions of this paper. The efficiency of the proposed algorithm was evaluated by performing simulations under four frequently-used scenarios, namely, deployment under normal conditions, deployment with obstacles, re-deployment due to unpredicted node failures, and deployment with regions of interest. Moreover, the performance of the algorithm was assessed using coverage and uniformity as the criteria. The simulation results indicate that the algorithm runs well under all these four frequently-used scenarios. In a completely unknown deployment area, the designated goal can also be achieved using the proposed algorithm owing to its adaptivity.

A Framework for the Optimal <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-Coverage Deployment Patterns of Wireless Sensors

The strategy for node deployment to achieve multiple connectivity and coverage plays an important role in various wireless senor network applications. To alleviate the operational cost, the number of nodes to be deployed needs to be reduced. While the optimal $k$ -connectivity deployment patterns ( $k \le 6$ ) and the multiple $k$ -coverage problem ( $k \le 3$ ) have been extensively studied for 2-D networks, a general method to identify the optimal deployment pattern for any given sensor coverage requirement has yet to be found. Considering the ease of sensor deployment and operation, the deployment patterns should be identical and symmetric in the deployment region. This implies that the Voronoi diagram of the optimal deployment is a regular tessellation. Based on the fact that there exist only three regular tessellations, we propose a framework, namely, range elimination scheme (RES), to compute the optimal $k$ -coverage deployment pattern for any given $k$ value to accommodate various wireless sensor application requirements. We apply RES to show the optimal $k$ -coverage deployment patterns for $4 \le k \le 9$ . Our analytical and simulation results show that our proposed framework successfully identifies the optimal deployment patterns and significantly reduces the number of sensors to be deployed.

Base Station Placement for Wireless Sensor Network Positioning System via Lexicographical Stratified Programming

This paper investigates optimization-based base station (BS) placement. An optimization model is defined and the BS placement problem is transformed to a lexicographical stratified programming (LSP) model for a given trajectory, according to different accuracy requirements. The feasible region for BS deployment is obtained from the positioning system requirement, which is also solved with signal coverage problem in BS placement. The LSP mathematical model is formulated with the average geometric dilution of precision (GDOP) as the criterion. To achieve an optimization solution, a tolerant factor based complete stratified series approach and grid searching method are utilized to obtain the possible optimal BS placement. Because of the LSP model utilization, the proposed algorithm has wider application scenarios with different accuracy requirements over different trajectory segments. Simulation results demonstrate that the proposed algorithm has better BS placement result than existing approaches for a given trajectory.

A Cluster Algorithm for Wireless Sensor Networks Based on Energy Efficiency

In order to solve the energy limited problem of sensor nodes in the wireless sensor networks (WSN), a fast clustering algorithm based on energy efficiency for wire1ess sensor networks is presented in this paper. In the system initialization phase, the deployment region is divided into several clusters rapidly. The energy consumption ratio and degree of the node are chosen as the selection criterion for the cluster head. Re-election of the cluster head node at this time became a local trigger behavior. Because of the range of the re-election is within the cluster, which greatly reduces the complexity and computational load to re-elect the cluster head node. Theoretical analysis indicates that the timing complexity of the clustering algorithm is O(1), which shows that the algorithm overhead is small and has nothing to do with the network size n. Simulation results show that clustering algorithm based on energy efficiency can provide better load balancing of cluster heads and less protocol overhead. Clustering algorithm based on energy efficiency can reduce energy consumption and prolong the network lifetime compared with LEACH protocol.

Minimizing Movement for Target Coverage and Network Connectivity in Mobile Sensor Networks

Coverage of interest points and network connectivity are two main challenging and practically important issues of Wireless Sensor Networks (WSNs). Although many studies have exploited the mobility of sensors to improve the quality of coverage andconnectivity, little attention has been paid to the minimization of sensors’ movement, which often consumes the majority of the limited energy of sensors and thus shortens the network lifetime significantly. To fill in this gap, this paper addresses the challenges of the Mobile Sensor Deployment (MSD) problem and investigates how to deploy mobile sensors with minimum movement to form a WSN that provides both target coverage and network connectivity. To this end, the MSD problem is decomposed into two sub-problems: the Target COVerage (TCOV) problem and the Network CONnectivity (NCON) problem. We then solve TCOV and NCON one by one and combine their solutions to address the MSD problem. The NP-hardness of TCOV is proved. For a special case of TCOV where targets disperse from each other farther than double of the coverage radius, an exact algorithm based on the Hungarian method is proposed to find the optimal solution. For general cases of TCOV, two heuristic algorithms, i.e., the Basic algorithm based on clique partition and the TV-Greedy algorithm based on Voronoi partition of the deployment region, are proposed to reduce the total movement distance ofsensors. For NCON, an efficient solution based on the Steiner minimum tree with constrained edge length is proposed. Thecombination of the solutions to TCOV and NCON, as demonstrated by extensive simulation experiments, offers a promising solutionto the original MSD problem that balances the load of different sensors and prolongs the network lifetime consequently.

Security Assistance in Africa: The Case for Less

Abstract: US strategic approaches in the African Great Lakes region are primarily based on security assistance for training and equipping African forces for operations in East, North, and West Africa. This assistance risks causing more incidents of violence. A new strategy, based on a comprehensive approach to the security challenges in the region, as well as the deployment of international boots on the ground--American or others--is needed to reduce violence and to minimize the risk of new terrorist safe havens appearing in central Africa. ********* One of the main security interests of the United States in Africa is to counter the violent extremism perpetrated by organizations such as the al-Shabaab in Somalia, Boko Haram in Nigeria and al-Qaeda in the Islamic Maghreb (AQIM). (1) In order to do so, current US military strategy aims at training and equipping African forces for peacekeeping and counterterrorist operations. (2) Violent extremism in the Great Lakes region in central Africa (here understood as the Democratic Republic of the Congo (DRC), Burundi, Rwanda, and Uganda) is rare; nonetheless, over the past seven years, the United States has trained tens of thousands of troops in the region for deployment to other parts of Africa. Burundi and Uganda, for example, have almost 12,000 troops currendy deployed as part of the African Union Mission in Somalia (AMISOM), and Rwanda has more than 3,500 troops deployed in Sudan as part of the African Union/United Nations Hybrid Operation in Darfur (UNAMID). The Great Lakes region is highly unstable and characterized by a long history of violence, weak governments, a great number of armed groups, and regional power struggles. The most violent and unstable state is the DRC, where 7 million people currently require humanitarian assistance and nearly 2.8 million are internally displaced. (3) After three decades of authoritarian rule and widespread human rights violations by the government of President Mobutu Sese Seko (1965-1997), two regional wars (1996-1997 and 1998-2003), several insurgencies, and perpetual local conflicts, the DRC is currently one of the world's five most fragile states. (4) The ungoverned territory in the eastern part of the country is utilized as a safe haven by a variety of domestic and foreign armed groups, including several from neighboring Burundi, Rwanda, and Uganda. Over time, conflicts have been fueled across borders, creating an intricate web of violence within the region. This article argues improving the capacity of the armed forces in this unstable region to conduct peacekeeping and counter-terrorism operations against violent extremists, current US military strategy actually risks escalating violent conflict in the Great Lakes. Not only would such an escalation be devastating for the populations living in the region, it would also be counterproductive for the United States, increasing the risk that terrorist safe havens will increase in central Africa. There are two major problems with the current strategic approach. First, states in the region are fragile, making security cooperation perilous. Second, bilateral approaches in this region, which is characterized by intricate entanglements, risks disturbing the balance of power and increasing the risk of violent conflict. By changing the current US strategy of bilateral security assistance and small-footprint interventions to one of putting international boots on the ground--American or others--the same amount of US resources might have more success in countering violent extremists in Africa. The United States should therefore support a regional intervention, either by the United Nations or the African Union. United States in the Great Lakes Region The United States military strategy in Africa rests on the principle that efforts to meet security challenges in Africa is best led and conducted by African partners. (5) The United States thus relies on providing security assistance and small-footprint interventions. …

Formal verification and validation of a movement control actor relocation algorithm for safety–critical applications

Wireless sensor and actor networks (WSAN) are captivating significant attention because of their suitability for safety---critical applications. Efficient actor placement in such applications is extremely desirable to perform effective and timely action across the deployment region. Nonetheless, harsh application environment inherently favors random placement of actors that leads to high concentration deployment and strangles coverage. Moreover, most of the published schemes lack rigorous validation and entirely rely on informal techniques (e.g., simulation) for evaluating nonfunctional properties of algorithms. This paper presents a localized movement control actor relocation (MCAR) algorithm that strives to improve connected coverage while minimizing movement overhead. MCAR pursues post-deployment actor repositioning in such a way that actors repel each other for better coverage while staying connected. We employ complementary formal and informal techniques for MCAR verification and validation. We model WSAN as a dynamic graph and transform MCAR to corresponding formal specification using Z notation. The resulting specification is analyzed and validated using Z eves tool. We simulate the specification to quantitatively demonstrate the efficiency of MCAR. Simulation results confirm the efficiency of MCAR in terms of movement overhead and connected coverage compared to contemporary schemes. The results show that MCAR can reduce distance movement up to 32 % while improving coverage up to 29 % compared to published schemes.

A locality-based range-free localization algorithm for anisotropic wireless sensor networks

Location discovery is one of the fundamental services in Internet of things built with wireless sensor networks (WSNs). In this paper, we propose AnSuper, a novel range-free localization algorithm that provides accurate location estimates in anisotropic WSNs. In AnSuper, every anchor first selects a set of friendly anchors to which its distance estimates can be accurately obtained. These anchors are then broadcasted to neighboring common nodes, with which they can obtain accurate distance estimates to the anchors by using a novel locality-based algorithm and consequently calculate their positions. We discuss how to suppress error accumulation in the localization process. AnSuper can handle multiple anisotropy factors, including uneven nodal distribution and irregularity of the deployment region. Simulation results show that, compared with state-of-the-art solutions, AnSuper improves localization accuracy by more then 30 %.

Enlarged Deployment Regions to Circumvent the Conditional Dependence and Composite Hypothesis Problems in Sensor Detection Systems

It is usually difficult to design randomly deployed sensor systems to detect a signal emitter in a region of interest because measurements are conditionally dependent in general and the alternative hypothesis is composite. To circumvent these problems, this paper presents two system design approaches: in Approach 1, a modified decay function is considered; in Approach 2, a modified region of interest and a suitable distribution for the emitter location are considered; and both approaches use enlarged sensor deployment regions. It is shown that both approaches cause the measurements to become conditionally independent and identically distributed, cause the alternative hypothesis to become simple, and generate designs that ensure a detection performance. This paper further evaluates how conservative each approach is and compares them, helping a designer choose the most suitable approach for a situation.

Range‐only distributed navigation protocol for uniform coverage in wireless sensor networks

In this study, the authors propose a novel range-only distributed motion coordination to achieve square-grid blanket coverage for self-deployments of networked multi-robot systems. They specifically address the research question of maximising coverage and minimising local uniformity index (i.e. to achieve uniform coverage) for each sensor node while simultaneously maintaining the connectivity of the whole network in the absence of central coordinated controller. Under the umbrella of intelligent controls, the motion coordination scheme employed in this study is because of the nearest neighbour techniques which are employed for the purpose of clustering and autonomous coordination among sensor nodes in local area (vicinity), that is, to achieve distributed coverage. The author's research indicates that simple motion coordination schemes have led to intelligent ensemble behaviours at group levels. Compared to the existing algorithms, the superiorities of their decentralised protocol are because of its reliability and robustness against inevitable node failures, scalability and flexibility in the sense of the growth of the networks as well as its uniformity across most of steady-state positions of sensor nodes leading to better network management. They present extensive computer simulations to investigate the effectiveness of their proposed algorithm for self-deployment in challenging deployment regions.

Network Connectivity in Non-Convex Domains With Reflections

Recent research has demonstrated the importance of boundary effects on the overall connection probability of wireless networks but has largely focused on convex deployment regions. We consider here a scenario of practical importance to wireless communications, in which one or more nodes are located outside the convex space where the remaining nodes reside. We call these `external nodes', and assume that they play some essential role in the macro network functionality e.g. a gateway to a dense self-contained mesh network cloud. Conventional approaches with the underlying assumption of only line-of-sight (LOS) or direct connections between nodes, fail to provide the correct analysis for such a network setup. To this end we present a novel analytical framework that accommodates for the non-convexity of the domain and explicitly considers the effects of non-LOS nodes through reflections from the domain boundaries. We obtain analytical expressions in 2D and 3D which are confirmed numerically for Rician channel fading statistics and discuss possible extensions and applications.

Barrier Coverage by Sensors with Adjustable Ranges

One of the most fundamental tasks of wireless sensor networks is to provide coverage of the deployment region. We study the coverage of a line interval with a set of wireless sensors with adjustable coverage ranges. Each coverage range of a sensor is an interval centered at that sensor whose length is decided by the power the sensor chooses. The objective is to find a range assignment with the minimum cost. There are two variants of the optimization problem. In the discrete variant, each sensor can only choose from a finite set of powers, whereas in the continuous variant, each sensor can choose power from a given interval. For the discrete variant of the problem, a polynomial-time exact algorithm is designed. For the continuous variant of the problem, NP-hardness of the problem is proved and followed by an ILP formulation. Then, constant-approximation algorithms are designed when the cost for all sensors is proportional to r κ for some constant κ ≥ 1, where r is the covering radius corresponding to the chosen power. Specifically, if κ = 1, we give a 1.25-approximation algorithm and a fully polynomial-time approximation scheme; if κ > 1, we give a 2-approximation algorithm. We also show that the approximation analyses are tight.

Multipath Grid-Based Enabled Geographic Routing for Wireless Sensor Networks

This work proposes an efficient disjoint multipath geographic routing algorithm for dense wireless sensor networks (WSN), called Multipath Grid-based Enabled Geographic Routing (MGEGR). The proposed algorithm relies on the construction of a 2-D logical grid in the geographical region of deployment. The objective of the proposed scheme is to determine optimal or near-optimal (within a defined constant) multiple disjoint paths (multipath) from a source node to the sink, in order to enhance the reliability of the network. The determined multiple disjoint paths would be used by the source node in a round-robin way to balance the traffic across the disjoint paths, and to avoid discovered paths with cell holes. The proposed scheme limits the use of broadcasting to the process of gateway election within each cell, and the process of maintaining the table of neighbors of each gateway. Our simulation results show the effectiveness and scalability of our routing scheme with increased network size compared to on-demand routing protocols.

Least Favorable Distributions for the Design of Randomly Deployed Sensor Detection Systems

The design of a detection system in which sensors are randomly located to detect a low-power signal emitter in a random location tends to be difficult because the measurements are conditionally dependent in general and the alternative hypothesis is composite. It is shown that there are conditions that allow a system designer to deal with these problems by assuming a least favorable distribution for the emitter location that not only makes the alternative hypothesis simple and ensures a detection performance, but also causes the measurements to become conditionally i.i.d., making models more amenable for analysis. Since a design based on a least favorable distribution may be considered too conservative, this paper proposes the use of a most favorable distribution for the emitter location and uses the theory of asymptotic relative efficiency (ARE) to evaluate how conservative the design based on a least favorable distribution is. It is further shown that, if the system designer can place sensors in an enlarged deployment region, then there are situations in which the design based on a least favorable distribution becomes less and less conservative as the dimensions of the region of interest increase.

SECURING CLUSTER BASED ADHOC NETWORK THROUGH BALANCED CLUSTERING WITH DISTRIBUTION AUTHORITIES OF KEY DISTRIBUTION AND KEY MANAGEMENT USING DEPLOYMENT KNOWLEDGE.

In this paper, we address key management in cluster -based mobile ad hoc networks (MANETs). We present a fully-distributed IDbased multiple secrets key management scheme (IMKM) . This scheme is implemented via a combination of I D-based multiple secrets and threshold cryptography. Ensuring secure communi cation in an ad hoc network is extremely challengin g because of the dynamic nature of the network and the lack of centralized m anagement. Our proposed analysis includes the effec t of packet generation model, random deployment of sensors, dynamic cluster head assignment, data compression, and energy consumptio n model at the sensors. a new protocol called Equalized Cluster Head Election Routing Protocol (ECHERP), which pursues energy co nservation through balanced clustering, is proposed. Performance evalu ation of ECHERP is carried out through simulation t ests. We also present a novel key predistribution scheme that uses deployment kno wledge to divide deployment regions into overlappin g clusters, each of which has its own distinct key space. Through careful constru ction of these clusters, network resilience is impr oved, we focus on the management of encryption keys in large-scale clustered WSNs. W e propose a novel distributed key management scheme based on Exclusion Basis Systems (EBS); a combinatorial formulation of the g roup key management problem. Initially, clusters ar e formed in the network and the cluster heads are selected based on the energy cost, coverage and processing capacity. The sink as signs cluster key to every cluster and an EBS key set to every cluster head. T he EBS key set contains the pairwise keys for intra -cluster and inter-cluster communication. During data transmission towards the sink, the data is made to pass through two phases of encryption thus ensuring security in the network. Our results include perfor mance evaluation in terms of security metrics in cl ustered WSN and a detailed analysis of resource utilization.

Percolation Theory-Based Exposure-Path Prevention for Wireless Sensor Networks Coverage in Internet of Things

Deriving the critical density to achieve region coverage for random sensor deployment is a fundamentally important problem in the area of Internet of Things (IoT). Most of the existing works on sensor coverage mainly concentrate on the full coverage models, which ensure that all points in the deployment region are covered at the expense of high complexity and cost. In contrast, many applications of IoT focus on the exposure-path prevention, which does not require full coverage sensor deployment, and instead it only needs the partial coverage, because the exposure paths are prevented as long as no moving objects or phenomena can go through a deployment region without being detected. Finally, we focus on the partial coverage by applying the percolation theory to solve the exposure path problem for the network of sensors in IoT. Most of the existing percolation-based schemes apply the continuum-percolation theory, which, however, suffers from the loose lower and upper bounds on the critical density. To overcome this problem, we propose a bond-percolation theory based scheme by mapping the exposure path problem into a bond percolation model. Using this model, we derive the critical densities for both omnidirectional sensor networks and directional sensor networks under random sensor deployment where sensors are deployed according to a two-dimensional Poisson process. The rigorous modeling/analyses and extensive simulations show that our proposed scheme can yield much tighter upper and lower bounds on the critical densities as compared with those generated by continuum-percolation.