Communication Radius Research Articles

On Characterizing the Local Pooling Factor of Greedy Maximal Scheduling in Random Graphs

The study of the optimality of low-complexity greedy scheduling techniques in wireless communications networks is a very complex problem. The Local Pooling (LoP) factor provides a single-parameter means of expressing the achievable capacity region (and optimality) of one such scheme, greedy maximal scheduling (GMS). The exact LoP factor for an arbitrary network graph is generally difficult to obtain, but may be evaluated or bounded based on the network graph's particular structure. In this paper, we provide rigorous characterizations of the LoP factor in large networks modeled as Erd\H{o}s-R\'enyi (ER) and random geometric (RG) graphs under the primary interference model. We employ threshold functions to establish critical values for either the edge probability or communication radius to yield useful bounds on the range and expectation of the LoP factor as the network grows large. For sufficiently dense random graphs, we find that the LoP factor is between 1/2 and 2/3, while sufficiently sparse random graphs permit GMS optimality (the LoP factor is 1) with high probability. We then place LoP within a larger context of commonly studied random graph properties centered around connectedness. We observe that edge densities permitting connectivity generally admit cycle subgraphs which forms the basis for the LoP factor upper bound of 2/3. We conclude with simulations to explore the regime of small networks, which suggest the probability that an ER or RG graph satisfies LoP and is connected decays quickly in network size.

Influence of node mobility on virus spreading behaviors in multi-hop network

Multi-hop network has received growing attention recently with the widely use of wireless network communication technology. At the same time, the security of multi-hop network is facing more serve challenges. Unfortunately, classic techniques for computer virus spreading model cannot be applied to multi-hop network because of ignoring dynamic topology of network. In this paper, classic susceptible-infected (SI) model, susceptible-infected-susceptible (SIS) model and susceptible-infected-removed (SIR) model are applied to multi-hop network based on random way-point (RWP) model, and contact duration of virus is introduced. Virus spreading behaviors are examined through contact duration of virus, communication radius of node, distribution density of node, and the number of initial infected nodes. Simulation results show that node mobility has significant effect on virus spreading behaviors. In particular, a special node speed that can lead network to appear the fastest-spreading virus phenomenon is found. The special speed is approximately equal to the ratio of communication radius of node to contact duration of virus. Distribution density of node and the number of initial infected nodes almost do not affect the special speed.

A Forward-connection Topology Evolution Model in Wireless Sensor Networks

The stability and reliability of the topology structure play an important role in the efficiency of the data collecting for wireless sensor networks. In this paper, a topology evolution model is proposed. The model considers the directionality of the data flow, and adopts the forward connectionism to ensure the neighbor nodes of each node. Furthermore, the model considers the balanced energy overhead in each communication path, adopts the energy balanced mechanism to compute the connection probability to the neighbor nodes. Meanwhile, the process of topology evolution is distributed and the communication radiuses of all sensor nodes are limited. A theoretical analysis exhibits that the model has power-law distribution of node degrees. Simulation shows that the proposed topology evolution model make energy overhead more balanced, and prolongs the lifetime of the network.

An Improved DV-Hop Localization Algorithm Based on Hop Distance and Hops Correction

In order to solve the problem that the DV-Hop algorithm has large error in the network topology environment of random distribution of nodes, this paper proposes a WSN localization algorithm based on hop distance correction. The algorithm uses the method of multi communication radius to correct the hop number within 1 hops, which makes it more consistent with the real situation; Then, the weighted factor is obtained by error of the average distance per hop of anchor node; Finally, the total least squares method is used to calculate the coordinates of the unknown nodes to improve the positioning accuracy of DV-Hop positioning algorithm. The simulation results show that the improved algorithm has a better accuracy and stability than the original DV-Hop algorithm.

Adaptive event sensing in networks of autonomous mobile agents

Given a connected region in two-dimensional space where events of a certain kind occur according to a certain time-varying density, we consider the problem of setting up a network of autonomous mobile agents to detect the occurrence of those events and possibly record them in as effective a manner as possible. We assume that agents can communicate with one another wirelessly within a fixed communication radius, and moreover that initially no agent has any information regarding the event density. We introduce a new distributed algorithm for agent control based on the notion of an execution mode, which essentially lets each agent roam the target region either at random or following its local view of a density-dependent gradient. Agents can switch back and forth between the two modes, and the precise manner of such changes depends on the setting of various parameters that can be adjusted as a function of the application at hand. We provide simulation results on some synthetic applications especially designed to highlight the algorithm's behavior relative to the possible execution modes.

HSKAS: A Novel Hierarchical Shared Key Authentication Scheme in Wireless Sensor Networks

Wireless sensor networks (WSNs) are often deployed in hostile environments, thus being subjected to great security risks. However, due to the influence of environment and dynamic topology, the communication radiuses of all nodes are no strictly consistent, which may cause different neighbor number and redundant neighbors for one central node. In this paper, we present a key agreement scheme without the trusted third parties by exploiting the special characteristics of Hopfield neural network: the two nodes converge in a steady state from their respective initial states after iterating finite times, while maintaining the confidentiality of the key by quantifying the key to strings. Compared to existing solution, the proposed method requires less memory and has lower communication overhead to key agreement.

Node Self-Deployment Algorithm Based on an Uneven Cluster with Radius Adjusting for Underwater Sensor Networks.

Existing move-restricted node self-deployment algorithms are based on a fixed node communication radius, evaluate the performance based on network coverage or the connectivity rate and do not consider the number of nodes near the sink node and the energy consumption distribution of the network topology, thereby degrading network reliability and the energy consumption balance. Therefore, we propose a distributed underwater node self-deployment algorithm. First, each node begins the uneven clustering based on the distance on the water surface. Each cluster head node selects its next-hop node to synchronously construct a connected path to the sink node. Second, the cluster head node adjusts its depth while maintaining the layout formed by the uneven clustering and then adjusts the positions of in-cluster nodes. The algorithm originally considers the network reliability and energy consumption balance during node deployment and considers the coverage redundancy rate of all positions that a node may reach during the node position adjustment. Simulation results show, compared to the connected dominating set (CDS) based depth computation algorithm, that the proposed algorithm can increase the number of the nodes near the sink node and improve network reliability while guaranteeing the network connectivity rate. Moreover, it can balance energy consumption during network operation, further improve network coverage rate and reduce energy consumption.

Connection times in large ad-hoc mobile networks

We study connectivity properties in a probabilistic model for a large mobile ad-hoc network. We consider a large number of participants of the system moving randomly, independently and identically distributed in a large domain, with a space-dependent population density of finite, positive order and with a fixed time horizon. Messages are instantly transmitted according to a relay principle, that is, they are iteratively forwarded from participant to participant over distances smaller than the communication radius until they reach the recipient. In mathematical terms, this is a dynamic continuum percolation model. We consider the connection time of two sample participants, the amount of time over which these two are connected with each other. In the above thermodynamic limit, we find that the connectivity induced by the system can be described in terms of the counterplay of a local, random and a global, deterministic mechanism, and we give a formula for the limiting behaviour. A prime example of the movement schemes that we consider is the well-known random waypoint model. Here, we give a negative upper bound for the decay rate, in the limit of large time horizons, of the probability of the event that the portion of the connection time is less than the expectation.

An improved centroid localization algorithm based on iterative computation for wireless sensor network

Wireless sensor network (WSN) is a basic component of internet and it plays an important role in many application areas, such as military surveillance, environmental monitoring and medical treatment. Node localization is one of the interesting issues in the field of WSN. Now, most of the existing node localization algorithms can be divided into two categories. One is range-based measurement and the other is range-free measurement. The localization algorithm of range-based measurement can achieve better location accuracy than the localization algorithm of range-free measurement. However, they are generally very energy consuming. Therefore, the range-free measurements are most widely used in practical applications. According to the application of localization algorithm in WSN by range-free measurements, an improved centroid localization algorithm based on iterative computation for wireless sensor network is proposed. In this algorithm, the position relationship of the closed area surrounded by the anchor nodes inside the unknown node's communication range and the unknown node is obtained by approximate point-in-triangulation test at first. Different position relationships determine different stopping criteria for iteration. Then, the centroid coordinates of the closed area surrounded by the anchor nodes inside the unknown node's communication range and the received signal strength (RSSI) between the centroid node and the unknown node are calculated. The anchor node with the weakest RSSI would be replaced by the centroid node. By this method, the closed area surrounded by the anchor nodes inside the unknown node's communication range is reduced. The location accuracy is increased by the cyclic iterative method. With the change of the anchor node ratio, the communication radius of the unknown node and the effect of RSSI error, the algorithm performance is investigated by using simulated data. The simulation results validate that although the improved centroid localization algorithm performance will be lost when the number of the anchor nodes inside the unknown node communication range decreases, the new approach can achieve good performance under the condition of few anchor nodes inside the unknown node communication range and this method is of strong robusticity against RSSI error disturbance.

Location‐based distributed caching for device‐to‐device communications underlaying cellular networks

AbstractDevice‐to‐device (D2D) communications have been viewed as a promising data offloading solution in cellular networks because of the explosive growth of multimedia applications. Because of the nature of distributed device location, distributed caching becomes an important function of D2D communications. By taking advantage of the caching capacity of the device, in this work, we explore the device storage and file frequent reuse to realize distributed content dissemination, that is, storing contents in mobile devices (named helpers). Specifically, we first investigate the average and lower bound of helper amount by dividing the network into small areas where the nodes are within each other's communication radius. Then, optimal helper amount is derived based on average helper amount and network topology. Subsequently, a location‐based distributed helper selection scheme for distributed caching is proposed based on the given optimal helper amount. In particular, nodes are selected as helpers according to their locations and degrees, and contents are placed in the manner for maximizing total user utility. Extensive simulation results demonstrate the factors that affect the optimal helper amount and the total user utility. Copyright © 2015 John Wiley & Sons, Ltd.

A Coral Reef Algorithm Based on Learning Automata for the Coverage Control Problem of Heterogeneous Directional Sensor Networks.

Coverage control is one of the most fundamental issues in directional sensor networks. In this paper, the coverage optimization problem in a directional sensor network is formulated as a multi-objective optimization problem. It takes into account the coverage rate of the network, the number of working sensor nodes and the connectivity of the network. The coverage problem considered in this paper is characterized by the geographical irregularity of the sensed events and heterogeneity of the sensor nodes in terms of sensing radius, field of angle and communication radius. To solve this multi-objective problem, we introduce a learning automata-based coral reef algorithm for adaptive parameter selection and use a novel Tchebycheff decomposition method to decompose the multi-objective problem into a single-objective problem. Simulation results show the consistent superiority of the proposed algorithm over alternative approaches.

VPIT: An Improved Range-Free Localization Algorithm Using Voronoi Diagrams for Wireless Sensor Networks

Localization systems have been identified as key issues in the development and operation of wireless sensor networks. The global positioning system (GPS) solves the problem about localization, but it is not suitable for wireless sensor networks. Due to range-free localization approaches requiring low equipped hardware and easy to implement, it is widely used in WSNs localization system. When the node communication radius increases, the accuracy of area-based localization is reduced. It is important to improve the localization accuracy in this situation. In this paper, to improve the accuracy of the node localization, we propose a new range-free localization using Voronoi diagrams based approximate point-in-triangulation test (APIT) algorithm. We compare our algorithm with APIT. Simulation results show that the VPIT improved the precision of localization by narrowing the node's geometry region.

Synchronization in Moving Pulse-Coupled Oscillator Networks

This paper presents the synchronization of a population of identical moving pulse-coupled oscillators (MPCOs) that are confined to move in a plane with mutual interactions, which are controlled by some pre-determined state threshold values and only take effect inside some known communication radii. The states are allowed to evolve in a nonlinear and periodical manner in accordance with a smooth, monotonically increasing and concave down function. Sufficient conditions are established for synchronization and the general effects of system parameters on the synchronization rate are further probed into. It is found that increasing signal strength causes the synchronization rate to initially decrease, then remain almost constant, then increase again until it finally decreases. Furthermore, with increasing speed modulus the synchronization rate initially decreases then increases. The synchronization rate, however, decreases with an increasing communication radius. Finally, as a real-world application, the proposed model is used to synchronize the different clocks in an ultra-wide bandwidth wireless ad hoc network.

Quasi Random Deployment Strategy for Reliable Communication Backbones in Wireless Sensor Networks

Topology construction and topology maintenance are significant sub-problems of topology control. Spanning tree based algorithms for topology control are basically transmission range based type construction algorithms. The construction of an effective backbone, however, is indirectly related to the placement of nodes. Also, the dependence of network reliability on the communication path undertaken by the message, subject to the place of event, remains unattended. To address this problem, we employ communication backbones (Prim’s algorithm and breadth first search (BFS)) and compute reliability based on the availability of paths for consistent message delivery from the place of event to the sink location in event driven wireless sensor networks. Our article analyses the communication reliability of a wireless sensor network in context to a topology governed by random and deterministic deployment methods. To comprehend the effect of topology on the communication reliability of a wireless network; “the within communication radii” constraint is satisfied. ANOVA is performed to validate the effect of node placement schemes on the reliability subject to varying radio ranges. It is observed that a ‘quasi’ random placement of nodes increases the communication reliability of the existing algorithms employed for analysis.

Cooperative Sensor Selection Optimization and Power-Efficient Gathering for Multihop Wireless Sensor Networks

Since a single sensor may be in a fading dip, cooperative sensing among multiple sensors which experience uncorrelated fading is required to guarantee reliable sensing performance. This paper proposes a cooperative sensor selection and power-efficient gathering (CSSPEG) strategy in multihop wireless sensor networks to avoid the “hot spot” problem. Intracluster communication radiuses have different sizes, in which the clusters closer to the base station have smaller size. Furthermore, intracluster member allocation scheme uses cooperative sensor selection and power-efficient gathering strategy. Simulation results show that the proposed CSSPEG can efficiently balance the energy consumption of cluster heads and prolong the lifetime of the network.

Modeling and simulating traffic congestion propagation in connected vehicles driven by temporal and spatial preference

Differing from the traditional traffic, connected vehicles enable information sharing between vehicles at vicinity to facilitate cooperative path planning, which may positively affect the congestion propagation process. In this paper, we propose to modeling and simulating traffic congestion propagation in such new situation where the path planning is driven by a temporal or spatial preference with aims at investigating the effects of various factors on traffic congestion, e.g. traffic light, mobility pattern, traffic density and communication radius. Simulations show that the traffic congestion is indeed affected by the concerned factors; however, the traffic congestion fails to be mitigated persistently as the communication radius increases beyond a certain threshold. The result is helpful for understanding the traffic congestion propagation in connected vehicles.

A Hierarchical Scheduling Scheme in WSNs Based on Node-Failure Pretreatment

One of the most important challenges in designing wireless sensor networks is how to recover a broken network within a very short time as the active nodes are failed or out-of-energy. Focusing on this problem, a hierarchical scheduling scheme based on node-failure pretreatment is proposed, in which the global optimization method is used to find the minimum connected tree and the local multilayer recovery algorithm is used to find a candidate sensor node instead of the failed one. Three highlights of this scheme are as follows: (1) The importance of sensor nodes is defined in terms of their locations in minimum connected tree and coverage acreage. (2) The neighborhood radius of failed sensor node varies with its importance, and then its candidate-node set is dynamically constructed. (3) A novel multilayer recovery strategy including node recovery and regional recovery is presented. Simulation results show that hierarchical scheduling scheme finds the optimal candidate sensor node in less time to make the repaired network with lowest energy consumption. Though the less sensor nodes are activated, the network lifetime is slightly shorter. Moreover, this scheme can be applied in the problem that the communication radius of sensor node is less than two times of its sensing radius.

Accurate Range-Free Localization for Anisotropic Wireless Sensor Networks

Position information plays a pivotal role in wireless sensor network (WSN) applications and protocol/algorithm design. In recent years, range-free localization algorithms have drawn much research attention due to their low cost and applicability to large-scale WSNs. However, the application of range-free localization algorithms is restricted because of their dramatic accuracy degradation in practical anisotropic WSNs, which is mainly caused by large error of distance estimation. Distance estimation in the existing range-free algorithms usually relies on a unified per hop length (PHL) metric between nodes. But the PHL between different nodes might be greatly different in anisotropic WSNs, resulting in large error in distance estimation. We find that, although the PHL between different nodes might be greatly different, it exhibits significant locality ; that is, nearby nodes share a similar PHL to anchors that know their positions in advance. Based on the locality of the PHL, a novel distance estimation approach is proposed in this article. Theoretical analyses show that the error of distance estimation in the proposed approach is only one-fourth of that in the state-of-the-art pattern-driven scheme (PDS). An anchor selection algorithm is also devised to further improve localization accuracy by mitigating the negative effects from the anchors that are poorly distributed in geometry. By combining the locality-based distance estimation and the anchor selection, a range-free localization algorithm named <underline>S</underline>elective <underline>M</underline>ultilateration (SM) is proposed. Simulation results demonstrate that SM achieves localization accuracy higher than 0.3 r , where r is the communication radius of nodes. Compared to the state-of-the-art solution, SM improves the distance estimation accuracy by up to 57% and improves localization accuracy by up to 52% consequently.

Shuttle-run synchronization in mobile ad hoc networks

In this work, we study the collective dynamics of phase oscillators in a mobile ad hoc network whose topology changes dynamically. As the network size or the communication radius of individual oscillators increases, the topology of the ad hoc network first undergoes percolation, forming a giant cluster, and then gradually achieves global connectivity. It is shown that oscillator mobility generally enhances the coherence in such networks. Interestingly, we find a new type of phase synchronization/clustering, in which the phases of the oscillators are distributed in a certain narrow range, while the instantaneous frequencies change signs frequently, leading to shuttle-run-like motion of the oscillators in phase space. We conduct a theoretical analysis to explain the mechanism of this synchronization and obtain the critical transition point.

A Distributed and Local-World Topology Evolution Model for Wireless Sensor Network

In this paper, a new evolution model based on complex network among the cluster heads in wireless sensor network is proposed. The evolution model considered distributed and local-world mechanism during the evolving process. The theoretical analysis of this model exhibits a power-law degree distribution with mean-field theory, which provides good fault-tolerance. The degree exponent is not a fixed number, which changes with the distribution of the cluster heads and the energy as well as the communication radius. Furthermore, the degree exponent can lead to an upper limit -2 when the distribution of the cluster heads and the energy are both uniform distribution. Analysis and simulation show that the network exhibits well robustness and a power-law degree distribution.