Uniform Node Distribution Research Articles

Node Placement Strategies to Prolong Lifetime in One-Dimensional Linear Wireless Sensor Network

We investigate the node distribution strategy in one-dimensional linear wireless sensor networks(WSNs), which aims to avoid the energy hole around the sink. We set up the network model and analyze the energy consumption factors, such as data compression and aggregation, and propose energy balance strategies due to different placement scenarios. In the uniform node distribution scenerio, based on selected optimal hop distance, we can add more backup batteries to some nodes to balance the sensors‘ lifetime. In the hop distance variable scenario, we can select different optimal hop lengths. Simulation results show that, in a WSN with linear topology, aggregation and compression should be supplied with backup battery to balance energy consumptions and to maximize the network lifetime.

Balancing energy consumption with mobile agents in wireless sensor networks

For Wireless Sensor Networks (WSNs), an unbalanced energy consumption will decrease the lifetime of network. In this paper, we leverage mobile agent technology to investigate the problem of how to balance the energy consumption during data collection in WSNs. We first demonstrate that for a sensor network with uniform node distribution and constant data reporting, balancing the energy of the whole network cannot be realized when the distribution of data among sensor nodes is unbalanced. We design a method to mitigate the uneven energy dissipation problem by controlling the mobility of agents, which is achieved by an energy prediction strategy to find their positions. Finally, we propose energy balancing cluster routing based on a mobile agent (EBMA) for WSNs. To obtain better performance, the cluster structure is formed based on cellular topology taking into consideration the energy balancing of inter-cluster and intra-cluster environments. Extensive simulation experiments are carried out to evaluate EBMA with several performance criteria. Our simulation results show that EBMA can effectively balance energy consumption and perform high efficiency in large-scale network deployment.

On Prolonging Network Lifetime through Load-Similar Node Deployment in Wireless Sensor Networks

This paper is focused on the study of the energy hole problem in the Progressive Multi-hop Rotational Clustered (PMRC)-structure, a highly scalable wireless sensor network (WSN) architecture. Based on an analysis on the traffic load distribution in PMRC-based WSNs, we propose a novel load-similar node distribution strategy combined with the Minimum Overlapping Layers (MOL) scheme to address the energy hole problem in PMRC-based WSNs. In this strategy, sensor nodes are deployed in the network area according to the load distribution. That is, more nodes shall be deployed in the range where the average load is higher, and then the loads among different areas in the sensor network tend to be balanced. Simulation results demonstrate that the load-similar node distribution strategy prolongs network lifetime and reduces the average packet latency in comparison with existing nonuniform node distribution and uniform node distribution strategies. Note that, besides the PMRC structure, the analysis model and the proposed load-similar node distribution strategy are also applicable to other multi-hop WSN structures.

A pre-determined node deployment strategy to prolong network lifetime in wireless sensor network

Energy is one of the scarcest resources in a wireless sensor network (WSN). Therefore, the need to conserve energy is of utmost importance in WSN. There are many ways to conserve energy in such a network. One fundamental way of conserving energy is judicious deployment of sensor nodes within the network area so that the energy flow remains balanced throughout the network. This avoids the problem of occurrence of ‘energy holes’ and ensures prolonged network lifetime. We have investigated the problem of uniform node distribution and shown its incapability to deal with the energy hole problem. Next we have derived the principle of non-uniform node distribution that ensures energy balancing. Further, we have developed a non-uniform, location-wise pre-determined node deployment strategy based on this principle leading to an increase in network lifetime. Finally exhaustive simulation is performed to substantiate our claim of energy balancing and subsequent enhancement of network lifetime. The results are compared with an existing work to prove the efficacy of our scheme.

The Role of Nodes Distribution in Extending the Lifetime of Wireless Sensor Networks

One of the most important issues in sensor networks is prolonging the network lifetime. In this paper, we demonstrate that given a constant number of nodes, how distribution of nodes affects the lifetime. For this purpose, we first show that in a network with cluster-based routing protocol, nodes do not have equal importance, and their importance depends on their location, and we determine the most critical regions. We prove that the uniform distribution of nodes is not a good distribution. Finally, we propose a solution for the best distribution that concentrates the population of nodes on critical areas. Simulation results of our proposed distribution show a remarkable increase in network lifetime.

Energy equilibrium based on corona structure for wireless sensor networks

ABSTRACTAlthough multi‐hop routing can reduce communication consumption and extend network scale, energy hole is unavoidable to appear because of the relay nodes being overloaded due to take more tasks. In this paper, we formulate the energy equilibrium problem as an optimal corona division, where data fusion and data slice are both considered in data gathering process. For a circular multi‐hop sensor network with uniform node distribution and constant data reporting, we demonstrate that the energy equilibrium of the whole network is unable to be realized no matter whether data fusion and data slice are adopted. However, the maximum energy equilibrium for a given circular area can be achieved only if the area increases in geometric progression from the outer corona to the neighbor inner corona except for the outermost one. Moreover, we use a zone‐based allocation scheme to guarantee energy equilibrium of intra‐corona. The approach for computing the optimal parameters is presented in terms of maximizing network lifetime. Based on the mathematical model, we propose an energy equilibrium routing based on corona structure (EERCS). Simulating results validate that EERCS can effectively achieve energy equilibrium and prolong the lifetime of network. Copyright © 2010 John Wiley & Sons, Ltd.

Drawing complete binary trees inside rectilinear polygons

Most of graph drawing algorithms draw graphs on unbounded planes. However, there are applications that require graphs to be drawn on the plane inside a given polygon. In this paper, a new algorithm for planar orthogonal drawing of complete binary trees inside rectilinear polygons is presented. Uniform distribution of nodes of graphs on drawing regions is one of the aesthetics criteria in graph drawing. The goal of this paper is to produce planar orthogonal drawings with a relatively uniform node distribution and few edge bends. The proposed algorithm can be considered as a generalization of the H-tree layout method for rectilinear polygons. A new linear time algorithm is also given for bisecting rectilinear polygons into two equi-area rectilinear sub-polygons.

Configurable node density generation with application to hotspot modelling

Mobility models are very relevant mainly when studying the performance of wireless systems by means of computer simulations. The main problem arises when deciding the best mobility model for a particular application. In some cases, it is very important to emulate hotspots or, in general, zones with different user (or node) densities. Current models do not allow complete control over hotspots, or in other words, they do not allow any general node density to be defined in the simulation area. Usually, when hotspots are modelled, closed zones are created with different numbers of users in each area, thus ensuring a fixed node density in each area. However, this approach results in an unfair comparison among users since they cannot move across zones. This paper proposes a new mechanism to solve these drawbacks. Using this mechanism, any general node density can be emulated allowing nodes to move around the entire simulation area. Any mobility model can be applied together with this density control mechanism, provided that the mobility model ensures a uniform node distribution.

Design of genetic algorithms for topology control of unmanned vehicles

We present genetic algorithms (GAs) as a decentralised topology control mechanism distributed among active running software agents to achieve a uniform spread of terrestrial unmanned vehicles (UVs) over an unknown geographical area. This problem becomes more challenging under the harsh and bandwidth limited conditions of military applications. Using only local neighbour information, a GA guides each UV to select a 'fitter' speed and direction among exponentially large number of choices, converging towards a uniform node distribution. In an observed occurrence of a threat situation during a mission where UVs are to spread uniformly over an unknown terrain, if the number of UVs change with time (e.g., losing assets due to hostile forces), the remaining units should reposition themselves to compensate the loss in area coverage. Our simulation software results show that GAs can be an effective tool for providing a robust solution for topology control of UVs in military applications.

Optimizing Cluster Heads for Energy Efficiency in Large-Scale Heterogeneous Wireless Sensor Networks

Many complex sensor network applications require deploying a large number of inexpensive and small sensors in a vast geographical region to achieve quality through quantity. Hierarchical clustering is generally considered as an efficient and scalable way to facilitate the management and operation of such large-scale networks and minimize the total energy consumption for prolonged lifetime. Judicious selection of cluster heads for data integration and communication is critical to the success of applications based on hierarchical sensor networks organized as layered clusters. We investigate the problem of selecting sensor nodes in a predeployed sensor network to be the cluster heads to minimize the total energy needed for data gathering. We rigorously derive an analytical formula to optimize the number of cluster heads in sensor networks under uniform node distribution, and propose a Distance-based Crowdedness Clustering algorithm to determine the cluster heads in sensor networks under general node distribution. The results from an extensive set of experiments on a large number of simulated sensor networks illustrate the performance superiority of the proposed solution over the clustering schemes based on k-means algorithm.

On unbounded path-loss models: effects of singularity on wireless network performance

This paper addresses the following question: how reliable is it to use the unbounded path-loss model G(d) = d <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-α</sup> , where α is the path-loss exponent, to model the decay of transmitted signal power in wireless networks? G(d) is a good approximation for the path-loss in wireless communications for large values of d but is not valid for small values of d due to the singularity at 0. This model is often used along with a random uniform node distribution, even though in a group of uniformly distributed nodes some may be arbitrarily close to one another. The unbounded path-loss model is compared to a more realistic bounded path-loss model, and it is shown that the effect of the singularity on the total network interference level is significant and cannot be disregarded when nodes are uniformly distributed. A phase transition phenomenon occurring in the interference behavior is analyzed in detail. Several performance metrics are also examined by using the computed interference distributions. In particular, the effects of the singularity at 0 on bit error rate, packet success probability and wireless channel capacity are analyzed.

Biased Random Walks in Uniform Wireless Networks

A recurrent problem when designing distributed applications is to search for a node with known property. File searching in peer-to-peer (P2P) applications, resource discovery in service-oriented architectures (SOAs), and path discovery in routing can all be cast as a search problem. Random walk-based search algorithms are often suggested for tackling the search problem, especially in very dynamic systems-like mobile wireless networks. The cost and the effectiveness of a random walk-based search algorithm are measured by the excepted number of transmissions required before hitting the target. Hence, to have a low hitting time is a critical goal. This paper studies the effect of biasing random walk toward the target on the hitting time. For a walk running over a network with uniform node distribution, a simple upper bound that connects the hitting time to the bias level is obtained. The key result is that even a modest bias level is able to reduce the hitting time significantly. This paper also proposes a search protocol for mobile wireless networks, whose results are interpreted in the light of the theoretical study. The proposed solution is for unstructured wireless mobile networks.

Maximizing network lifetime based on transmission range adjustment in wireless sensor networks

In a wireless sensor network (WSN), the unbalanced distribution of communication loads often causes the problem of energy hole, which means the energy of the nodes in the hole region will be exhausted sooner than the nodes in other regions. This is a key factor which affects the lifetime of the networks. In this paper we propose an improved corona model with levels for analyzing sensors with adjustable transmission ranges in a WSN with circular multi-hop deployment (modeled as concentric coronas). Based on the model we consider that the right transmission ranges of sensors in each corona is the decision factor for optimizing the network lifetime after nodes deployment. We prove that searching optimal transmission ranges of sensors among all coronas is a multi-objective optimization problem (MOP), which is NP hard. Therefore, we propose a centralized algorithm and a distributed algorithm for assigning the transmission ranges of sensors in each corona for different node distributions. The two algorithms can not only reduce the searching complexity but also obtain results approximated to the optimal solution. Furthermore, the simulation results of our solutions indicate that the network lifetime approximates to that ensured by the optimal under both uniform and non-uniform node distribution.

A Smooth Gauss-Semi-Markov Mobility Model for Wireless Sensor Networks

Simulation is an indispensable tool in protocol design and evaluation. Typically, simulations of mobile wireless sensor networks rely upon mobility models. This paper presents a smooth Gauss-semi-Markov mobility model (SGM) that can reflect the realistic node movement and has more controllable parameters. Time stationary average speed and uniform spatial node distribution of SGM are proved by Markov process and renewal process theory. Thus, SGM model can be applied to simulation of mobile wireless sensor networks.

Bio-inspired topology control for knowledge sharing mobile agents

We present different approaches for knowledge sharing bio-inspired mobile agents to obtain a uniform distribution of the nodes over a geographical terrain. In this application, the knowledge sharing agents in a mobile ad hoc network adjust their speed and directions based on genetic algorithms (GAs). With an analytical model, we show that the best fitness value is obtained when the number of neighbors for a mobile agent is equal to the mean node degree. The genetic information that each mobile agent exchanges with other neighboring agents within its communication range includes the node’s location, speed, and movement direction. We have implemented a simulation software to study the effectiveness of different GA-based algorithms for network performance metrics including node densities, speed, and number of generations that a GA runs. Compared to random-walk and Hill Climbing approaches, all GA-based cases show encouraging results by converging towards a uniform node distribution.

Random walk with long jumps for wireless ad hoc networks

This paper considers a random walk-based search algorithm in which the random walk occasionally makes longer jumps. The algorithm is tailored to work over wireless networks with uniform node distribution. In a classical random walk each jump has the same mean length. On the contrary, in the proposed algorithm a node may decide to double the expected jump length by increasing the nominal transmission power and picking a neighbor beyond the nominal range. The aim of these long jumps is reducing the spatial correlation among short term subsequent node selections, thus improving the search performance, namely the hitting time. Two versions of the algorithm are studied, with and without lookahead. A protocol for implementing each version is also proposed. When there is no lookahead the proposed protocol allows for a finer transmission power transmission regulation. The paper studies, for three network topologies, the impact of the long jump probability on the hitting time and on the average total power required before the target is found.

Stochastic Properties of Mobility Models in Mobile Ad Hoc Networks

The stochastic model assumed to govern the mobility of nodes in a mobile ad hoc network has been shown to significantly affect the network's coverage, maximum throughput, and achievable throughput-delay trade-offs. In this paper, we compare several mobility models, including the random walk, random waypoint, and Manhattan models on the basis of the number of states visited in a fixed time, the time to visit every state in a region, and the effect of the number of wandering nodes on the time to first enter a set of states. These metrics for a mobility model are useful for assessing the achievable event detection rates in surveillance applications where wireless-sensor-equipped vehicles are used to detect events of interest in a city. We also consider mobility models based on Correlated Random Walks, which can account for time dependency, geographical restrictions, and nonzero drift. We demonstrate that these models are analytically tractable by using a matrix-analytic approach to derive new, closed-form results in both the time and transform-domains for the probability that a node is at any location at any time for both semi-infinite and finite 1D lattices. We also derive first entrance time distributions for these walks. We find that a correlated random walk 1) covers more ground in a given amount of time and takes a smaller amount of time to cover an area completely than a random walk with the same average transition rate, 2) has a smaller first entrance time to small sets of states than the random waypoint and random walk models, and 3) leads to a uniform distribution of nodes (except at the boundaries) in steady state.

센서 네트워크에서의 거리에 따른 동적 크기 다중홉 클러스터링 방법

제한된 자원을 가진 센서 노드들로 구성된 센서 네트워크에서 가장 중요한 이슈 중 하나는 주어진 에너지를 최대한 활용하여 네트워크 수명을 연장하는 것이다. 네트워크 수명을 연장하는 가장 대표적인 방법은 클러스터링 방법이며, 이는 단일홉 모드와 다중홉 모드로 분류된다. 단일홉 모드는 클러스터 내의 모든 센서 노드들이 CH(Cluster Head)와 단일홉 통신을 하는 것을 말하며, 반면 다중홉 모드는 중간 노드들의 중계를 통하여 센서 노드와 CH가 통신하는 방식을 말한다. 기존의 다중홉 클러스터링 방식에서 성능 상 가장 중요한 영향을 미치는 요소는 클러스터 크기이며, 노드의 분포가 균일하다고 가정하였다. 그러나 실제 네트워크에서의 노드 분포는 균일하지 않을 수 있으므로 이러한 환경에서의 최적의 클러스터 크기 계산은 아주 어렵다. 본 논문에서는 싱크 주변의 CH에 대한 트래픽 부하를 줄이기 위하여 싱크로부터의 거리를 기반으로 클러스터 크기를 동적으로 변화시키는 다중홉 클러스터링 방법을 제안한다. 또한 수학적 분석과 시뮬레이션을 통하여 제안된 동적크기 클러스터링 방식이 기존의 고정크기 클러스터링 보다 더 나은 성능을 가짐을 보였다. One of the most important issues on the sensor network with resource limited sensor nodes is prolonging the network lifetime by effectively utilizing the limited node energy. The most representative mechanism to achieve a long lived sensor network is the clustering mechanism which can be further classified into the single hop mode and the multi hop mode. The single hop mode requires that all sensor nodes in a cluster communicate directly with the cluster head(CH) via single hop md, in the multi hop mode, sensor nodes communicate with the CH with the help of other Intermediate nodes. One of the most critical factors that impact on the performance of the existing multi hop clustering mechanism is the cluster size and, without the assumption on the uniform node distribution, finding out the best cluster size is intractable. Since sensor nodes in a real sensor network are distributed non uniformly, the fixed size mechanism may not work best for real sensor networks. Therefore, in this paper, we propose a new dynamic size multi hop clustering mechanism in which the cluster size is determined according to the distance from the sink to relieve the traffic passing through the CHs near the sink. We show that our proposed scheme outperforms the existing fixed size clustering mechanisms by carrying out numerical analysis and simulations.

Minimizing Eavesdropping Risk by Transmission Power Control in Multihop Wireless Networks

To defend against reconnaissance activity in ad hoc wireless networks, we propose transmission power control as an effective mechanism for minimizing the eavesdropping risk. Our main contributions are given as follows. First, we cast the wth-order eavesdropping risk as the maximum probability of packets being eavesdropped when there are w adversarial nodes in the network. Second, we derive the closed-form solution of the first-order eavesdropping risk as a polynomial function of the normalized transmission radius. This derivation assumes a uniform distribution of user nodes. Then, we generalize the model to allow arbitrary user nodes distribution and prove that the uniform user distribution minimizes the first-order eavesdropping risk. This result plays an essential role in deriving analytical bounds for the eavesdropping risk given arbitrary user distributions. Our simulation results show that, for a wide range of nonuniform traffic patterns, the difference in their eavesdropping risk values from the corresponding lower bounds is 3 dB or less.

An adaptive meshless method for magnetic field computation

Design of electromagnetic (EM) actuators often involves solving a magnetic field problem. This paper presents an adaptive meshless method (MLM) that inherits many advantages of the finite-element method (FEM) but needs no explicit mesh structure for design of EM actuators. Specifically, the paper offers a technique to estimate the distribution of numerical errors and a scheme that automatically inserts additional nodes to improve computational accuracy and efficiency. It gives several examples. The first three numerical examples, where exact solutions are available, provide a means to validate the adaptiveMLM and evaluate its effectiveness against a regular MLM with a uniform node distribution. The other examples, where magnetic forces are computed from Lorenz???s law, illustrate the use of adaptive MLM for practical design of an EM actuator. The paper compares the computed forces against published experimental results.