Hop Count Information Research Articles

A Optimized 3D DV-Hop Localization Algorithm Based on Hop Count and Differential Evolution Methods

The location problem is a fundamental problem in underwater wireless sensor networks. This paper focuses on the distance vector hopping (DV-Hop) localization algorithm, which is most widely used in underwater wireless sensor networks (UWSNs). The algorithm does not require distance measurement and is simple to implement, but the research on DV-Hop algorithm in 3D space is not mature, which leads to large positioning errors. Based on the error analysis of the 3D DV-Hop algorithm, this paper proposes a 3D differential evolutionary hop count DV-Hop (DEHDV-Hop) algorithm to reduce the localization error. We define a continuous hop value based on the number relationship of adjacent nodes and solve the upper bound of the hop count under this definition. The discrete values of the global hop count are converted to continuous values using the broadcasted node information. The concept of trust is introduced by analyzing the error between the actual and estimated distances between anchor nodes. The method of obtaining the average hop distance of unknown nodes in the original algorithm is replaced so that the estimated distance is calculated using the new hop count and hop distance. Finally, the hop count information is segmented, a new fitness function is constructed, and the coordinates of the unknown nodes are solved iteratively using a differential evolutionary algorithm.

Learning IP network representations

We present DIP, a deep learning based framework to learn structural properties of the Internet, such as node clustering or distance between nodes. Existing embedding-based approaches use linear algorithms on a single source of data, such as latency or hop count information, to approximate the position of a node in the Internet. In contrast, DIP computes low-dimensional representations of nodes that preserve structural properties and non-linear relationships across multiple, heterogeneous sources of structural information, such as IP, routing, and distance information. Using a large real-world data set, we show that DIP learns representations that preserve the real-world clustering of the associated nodes and predicts distance between them more than 30% better than a meanbased approach. Furthermore, DIP accurately imputes hop count distance to unknown hosts (i.e., not used in training) given only their IP addresses and routable prefixes. Our framework is extensible to new data sources and applicable to a wide range of problems in network monitoring and security.

Localization and Location Verification in Non-Homogeneous One-Dimensional Wireless Ad-Hoc Networks

In this paper, we study the hop-count properties of one-dimensional wireless ad-hoc networks, where the nodes are placed independently and identically according to a Poisson distribution with an arbitrary density function. We derive exact equations to calculate the probability mass function of two hop-count random variables: the number of hops needed for a node located at an arbitrary location in the network to receive a message from a node located at one end of the linear network, and the number of hops needed for a node located at one end of the network to receive a message from a node at an arbitrary location. Based on the derived formulas, we then propose localization and location verification methods. Through simulations, we show that our proposed localization method not only has a competitive performance for a range-free method, but also outperforms range-based methods with a local distance measurement error of 10% or more. Furthermore, the proposed location verification protocol is shown to have better results compared to the existing verification systems that also use the hop-count information. An important feature of our methods is that they are applicable to arbitrary densities. This is unlike the existing methods that are limited only to the case of uniform node densities. Using simulations, we also evaluate the proposed schemes in the presence of Rician fading and show that their performance is rather robust with respect to the change in the fading parameter. Moreover, the hop-count equations derived in this work can be used in analyzing other aspects of broadcasting protocols such as quality of service and delay.

Localization Based on Adaptive Regulated Neighborhood Distance for Wireless Sensor Networks With a General Radio Propagation Model

Many range-free localization algorithms estimate the distance in between two nodes based on the hop-count information, which, however, is a coarse proximity measure. Recently, the regulated neighborhood distance (RND) has been proposed as a new proximity measure, and can greatly improve the localization accuracy, compared with those hop-count-based algorithms. However, the RND algorithm and most previous hop-based approaches are based on the disk communication model, and cannot be directly applied into the practical world with some general radio propagation model. In this paper, we revisit the RND-based localization with a general propagation model, where the received transmission power is modeled as a random variable and its expectation is a nonincreasing function of the distance between a transmitter and receiver pair. In particular, we define the neighborhood based on the packet reception ratio (PRR), and propose an optimal PRR threshold selection algorithm to adaptively adjust the RND-based distance estimation. We verify the effectiveness of the adaptive RND-based localization for the log-normal shadowing model and a polynomial fitting model from our field experiments. Simulation results show that the adaptive selection of the best PRR threshold helps to improve localization accuracy. Furthermore, the proposed adaptive RND-based localization can achieve higher localization accuracy, compared with the classical DV-hop localization with the same network configurations.

An Improved Dv-Hop Localization Algorithm Based On Machine Learning For Wireless Sensor Network

The DV-Hoplocalization method has a series of superiorities, such as high distributiveness and expandability, which is perfectly fit for large-scale deployment. Moreover, it may lead to reasonable positioning accuracy merely in isotropous dense network. In practical environment, most scenes are anisotropic, with unevenly distributed nodes. In this paper, kernel PCR method is applied to collect and utilize the correlation between hop count and real distance, so as to build an optimal relationship model, converting hop count information between nodes into the value of real distance, so that DV-Hop method may be applicable to different environment. Compared with existing similar and typical methods, the method proposed in this paper has higher environment adaptability, as well as higher positioning accuracy and stability.

Wireless Sensor Network Localization Algorithm Based on Hop-Count and Distributed Learning

The wireless sensor network localization algorithm in this paper combines hop-count information and distributed learning. The network is classified into many classes based on sensors’ location, and then the class that each sensor falls into is specified. There are a certain number of beacon nodes with position coordinate in network, and they use their own locations as training data in performing above classification. This positioning method merely uses the partial hop-count information between target sensor and reference node in specifying the class of each node. The final simulation experiment will analyze the excellent performance of this method under different system parameters.

OPTIMAL SCHEDULING ALGORITHM FOR THROUGHPUT MAXIMIZATION IN MULTIHOP WIRELESS NETWORKS

In this paper, focus on designing a scheduling scheme for achieve maximum throughput. Although, it does not require per-flow or perdestination information and also, this paper consider the problem of link scheduling in Multihop Wireless Networks under general interference constraints. The main goal is to achieve maximum throughput and better delay performance at low complexity. Previously, we use Max Weight Scheduling Algorithm (Per-Hop Queue and Per-Link Queue Scheduling) for Throughput maximization. These algorithms does not require per-flow information but it need local hop count information and use simple data Queue for each link in the network. Some time occurring buffer overflow (that is data queue overflow) because each link maintain simple data Queue. Our proposed scheme overcomes this problem and produces better delay performance and throughput at low complexity. Our proposed scheme combines MaxWeightScheduling and Greedy Algorithm, which reduce buffer overflow and achieve maximum throughput at low complexity. The performance of the proposed scheme is analyzed by various setting NS2 simulation. Prove that proposed scheme is optimal one and produce efficient throughput at low complexity.

VAPR: Void-Aware Pressure Routing for Underwater Sensor Networks

Underwater mobile sensor networks have recently been proposed as a way to explore and observe the ocean, providing 4D (space and time) monitoring of underwater environments. We consider a specialized geographic routing problem called pressure routing that directs a packet to any sonobuoy on the surface based on depth information available from on-board pressure gauges. The main challenge of pressure routing in sparse underwater networks has been the efficient handling of 3D voids. In this respect, it was recently proven that the greedy stateless perimeter routing method, very popular in 2D networks, cannot be extended to void recovery in 3D networks. Available heuristics for 3D void recovery require expensive flooding. In this paper, we propose a Void-Aware Pressure Routing (VAPR) protocol that uses sequence number, hop count and depth information embedded in periodic beacons to set up next-hop direction and to build a directional trail to the closest sonobuoy. Using this trail, opportunistic directional forwarding can be efficiently performed even in the presence of voids. The contribution of this paper is twofold: a robust soft-state routing protocol that supports opportunistic directional forwarding; and a new framework to attain loop freedom in static and mobile underwater networks to guarantee packet delivery. Extensive simulation results show that VAPR outperforms existing solutions.

Throughput-Optimal Scheduling in Multihop Wireless Networks Without Per-Flow Information

In this paper, we consider the problem of link scheduling in multihop wireless networks under general interference constraints. Our goal is to design scheduling schemes that do not use per-flow or per-destination information, maintain a single data queue for each link, and exploit only local information, while guaranteeing throughput optimality. Although the celebrated back-pressure algorithm maximizes throughput, it requires per-flow or per-destination information. It is usually difficult to obtain and maintain this type of information, especially in large networks, where there are numerous flows. Also, the back-pressure algorithm maintains a complex data structure at each node, keeps exchanging queue-length information among neighboring nodes, and commonly results in poor delay performance. In this paper, we propose scheduling schemes that can circumvent these drawbacks and guarantee throughput optimality. These schemes use either the readily available hop-count information or only the local information for each link. We rigorously analyze the performance of the proposed schemes using fluid limit techniques via an inductive argument and show that they are throughput-optimal. We also conduct simulations to validate our theoretical results in various settings and show that the proposed schemes can substantially improve the delay performance in most scenarios.

A Fine-grained Hop-count Based Localization Algorithm for Wireless Sensor Networks

In recent years, many localization algorithms have been proposed for wireless sensor networks, in which the hop-count based localization schemes are attractive due to the advantage of low cost. However, these approaches usually utilize discrete integers to calculate the hop-counts between nodes. Such coarse-grained hop-counts make no distinction among one-hop nodes. More seriously, as the hop-counts between nodes increase, the cumulative deviation of hop-counts would become unacceptable. In order to solve this problem, we propose the concept of fine-grained hop-count. It is a kind of float-type hop-count, which refines the coarse-grained one close to the actual distance between nodes. Based on this idea, we propose a fine-grained hop-count based localization algorithm (AFLA). In AFLA, we first refine the hop-count information to obtain finegrained hop-counts, then use the Apollonius circle method to achieve initial position estimations, and finally further improve the localization precision through confidence spring model (CSM). We conduct the comprehensive simulations to demonstrate that AFLA can achieve 30% higher average accuracy than the existing hop-count based algorithm in most scenarios and converge much faster than the traditional mass-spring model based scheme. Furthermore, AFLA is robust to achieve an approximate 35% accuracy even in noisy environment with a DOI of 0.4. Besides, we also construct a Testbed that consists of 17 MICAz motes to verify the performance of AFLA in real environment.

Relative velocity based vehicle-to-vehicle routing protocol over ad-hoc networks

In this paper, we introduce a new routing protocol supporting high mobility over VANET which is using hop counts and relative velocity between vehicles to find the best routing transmission path. By exchanging vehicles' relative velocities, the more stable and reliable paths are searched as compared to traditional MANET protocols using only hop count information at the time of routing path set-up. To evaluate proposed routing protocol, we compared it with original Ad hoc On-demand Multipath Distance Vector (AOMDV) on NS2. The simulation results showed that proposed routing protocol achieves better performance from about 10% to 50% in terms of normalized routing overhead and packet delivery ratio, when video sequences are transferred on channels. The proposed routing protocol can be useful for the Vehicle-to-Vehicle (V2V) transmission of traffic monitoring data, audio, and video streaming services without the additional global position devices.

비등방성 네트워크에서 위치 추정의 정확도를 높이기 위한 향상된 Range-Free 위치 인식 기법

DV-Hop is one of the well known range-free localization algorithms. The algorithm works well in case of isotropic network since the sensor and anchor nodes are placed in the entire area. However, it results in large errors in case of anisotropic networks where the hop count between nodes is not linearly proportional to the Euclidean distance between them. Hence, we proposed a novel range-free algorithm for anisotropic networks to improve the localization accuracy. In the paper, the Euclidean distance between anchor node and unknown node is estimated by the average hop distance calculated at each hop count with hop count and distance information between anchor nodes. By estimating the unknown location of nodes with the estimated distance estimated by the average hop distance calculated at each hop, the localization accuracy is improved. Simulation results show that the proposed algorithm has more accuracy than DV-Hop.

Broadcast based on layered diffusion in wireless ad hoc and sensor networks

AbstractBroadcast is a fundamental operation in wireless ad hoc and sensor networks. This paper proposes a simple and efficient broadcast protocol, called Broadcast based on Layered Diffusion (BLD), which is a stateless broadcast protocol with very low message overheads and very low computation requirements. In BLD, nodes do not need to exchange neighborhood information for building a broadcast backbone, but make their rebroadcast decisions locally. The design idea of BLD is to emulate the triangular tessellation for complete area coverage of the network field. It does not require nodes' location information for such tessellation emulation but only exploits the hop count information for each node to make local rebroadcast decision and timing. Simulation results show the effectiveness and efficiency of the BLD protocol and its robustness to localization errors and transmission errors. Copyright © 2009 John Wiley & Sons, Ltd.

Secure Neighborhood Creation in Wireless Ad Hoc Networks using Hop Count Discrepancies

A fundamental requirement for nodes in ad hoc and sensor networks is the ability to correctly determine their neighborhood. Many applications, protocols, and network wide functions rely on correct neighborhood discovery. Malicious nodes that taint neighborhood information using wormholes can significantly disrupt the operation of ad hoc networks. Protocols that depend only on cryptographic techniques (e.g, authentication and encryption) may not be able to detect or prevent such attacks. In this paper we propose SECUND, a protocol for creating a SECUre NeighborhooD, that makes use of discrepancies in routing hop count information to detect true neighbors and remove those links to nodes that appear to be neighbors, but are not really neighbors. SECUND is simple, localized and needs no special hardware, localization, or synchronization. We evaluate SECUND using simulations and demonstrate its effectiveness in the presence of multiple and multi-ended wormholes. Lastly, we present approaches to improve the efficiency of the SECUND process.

Range-free wireless sensor networks localization based on hop-count quantization

Localization is one of the most important research issues in Wireless Sensor Networks (WSNs). Recently, hop-count-based localization has been proposed as a cost-effective alternative to many expensive hardware-based localization algorithms. The basic idea of many hop-count-based localization algorithms is to seek a transformation from hop-count information to distance (e.g. DV-hop algorithm of Niculescu and Nath in Global Telecommunications Conference, vol. 5, pp. 2926---2931, 2001) or location (e.g. MDS algorithm of Shang et al. in International Symposium on Mobile Ad Hoc Networking and Computing, pp. 201---212, 2003) information. Traditionally, hop-counts between any pair of nodes can only take on integer value regardless of relative positions of nodes in the hop. We argue that by partitioning a node's one-hop neighbor set into three disjoint subsets according to their hop-count values, the integer hop-count can be transformed into a real number accordingly. The transformed real number hop-count is then a more accurate representation of a node's relative position than an integer-valued hop-count. In this paper, we present a novel algorithm termed HCQ (hop-count quantization) to perform such transformation. We then use the transformed real number hop-count to solve WSNs localization problems based on the MDS (multidimensional scaling) method. Simulation results show that the performance of the MDS algorithm using the real number hop-count outperforms those which use integer hop-count values.

Analysis of Hop-Count-Based Source-to-Destination Distance Estimation in Wireless Sensor Networks With Applications in Localization

In wireless sensor networks (WSNs), estimation of the true distance between a source and its destination based on the hop counts between them is an important research problem. The basic idea of several hop-count-based distance-estimation algorithms is to seek an analytical/heuristic transformation from the observed destination's hop-count information to an unknown source-to-destination distance (s2d-distance). We observe that the neighbors of a destination can have different hop counts with respect to the same source, and such information can be used to improve the s2d-distance estimation. Based on this observation, we propose a new s2d-distance estimation algorithm termed hop-count-based neighbor partition (HCNP). Unlike many existing methods, the proposed algorithm not only uses the hop-count information of a destination but also exploits the hop-count information of the destination's neighbors to estimate the s2d-distance. We analyze its statistical property and compare it with other s2d-distance estimation algorithms that only use a destination's hop-count information. We also derive an approximation of the lower bound on the minimum node density required for the HCNP algorithm to achieve a prescribed accuracy. To demonstrate the usefulness of the proposed method, we apply the HCNP algorithm in the localization of WSNs. Comparative studies with the state-of-the-art hop-count-based localization methods show that the proposed approach is superior.

A novel approach toward source-to-sink distance estimation in wireless sensor networks

Estimation of the Euclidean distance between a source node and a sink node by using the hop-counts between them is an interesting research problem in WSNs (wireless sensor networks). In this paper, we propose a novel source-to-sink distance estimation method based on the observation that the neighbors of a sink can have different hop-counts relative to the same source. The proposed method not only uses the hop-count information of a sink, but also exploits the hop-count information of the sink's neighbors. Simulation results show that the proposed method outperforms other well-known hop-count-based sourceto- sink distance estimation methods.

The hop count shift problem and its impacts on protocol design in wireless ad hoc networks

The hop count information has been exploited in the design of networking protocols in wireless ad hoc multi-hop networks. The hop count setup process normally assumes a perfect disk communication model and uses a simple controlled flooding approach. However, the practical communication model may not be such a disk communication model but time-varying and lossy. Sometimes transmissions can be successful beyond the nominal transmission range, i.e., the radius of such a disk model. The defacto hop count which are setup via time-varying and lossy radio channels may be different from the one based on the disk communication model. This paper introduces the hop count shift problem in realistic radio channels and investigates its impacts, via extensive simulations, on some representative hop count based protocols. Our simulation results suggest that these protocols' performance generally suffers from the hop count shift problem, and the degradation is dependent on how the practical communication model deviates from the disk communication model. We also propose a strategy to combat the hop count shift problem and conduct simulations to show its effectiveness. The study of this paper necessitates reexaminations for the design of new hop count setup mechanism and the hop count based networking protocols.

Layered Diffusion-based Coverage Control in Wireless Sensor Networks

Coverage is an important performance metric for many applications, such as surveillance in wireless sensor networks. Coverage control is used to select as few active nodes as possible from all deployed sensor nodes, such that sufficient coverage of the monitored area can be guaranteed while reducing the energy consumption of each individual sensor node to prolong the network lifetime. This paper classifies three types of coverage control protocols based on the available information about nodes' distances or locations, and reviews several representative protocols for each type. We also propose a new distributed and localized coverage control protocol, called Layered Diffusion-based Coverage Control (LDCC). The LDCC protocol does not require information about the node location coordinates when selecting active nodes. Instead, it exploits hop count information, which is easily obtained in a WSN, to select active sensor nodes. Furthermore, the LDCC protocol is very simple and does not require any sophisticated computation such as distance or covered area computation. Our simulation results show that the LDCC protocol achieves a high coverage ratio while incurring very low message overhead compared with other existing protocols. Furthermore, simulation results suggest that in a large-scale sensor network with medium to large localization errors, LDCC performs even better than location-based coverage control protocols.

센서 네트워크에서 AODV 라우팅 정보 변조공격에 대한 분석

센서 네트워크는 유비쿼터스 컴퓨팅 구현을 위한 기반 네트워크 중의 하나로 그 중요성이 점차 부각되고 있으며, 네트워크 특성상 보안 기술 또한 기반 기술과 함께 중요하게 인식되고 있다. 현재까지 진행된 센서 네트워크 보안 기술은 암호화에 의존하는 인증 구조나 키 관리 구조에 대한 연구가 주를 이루었다. 그러나 센서 노드는 쉽게 포획이 가능하고 암호화 기술을 사용하는 환경에서도 키가 외부에 노출되기 쉽다. 공격자는 이를 이용하여 합법적인 노드로 가장하여 내부에서 네트워크를 공격할 수 있다. 따라서 네트워크의 보안을 보장하기 위해서는 실행 가능한 내부 공격 및 그 영향에 대한 분석이 필요하며 이를 통해 내부 공격에 대비한 안전한 메커니즘이 개발되어야 한다. 본 논문에서는 애드 혹 네트워크의 대표적인 라우팅 프로토콜이며, 센서 네트워크에서도 적용 가능한 AODV (Ad-hoc On-Demand Distance Vector) 프로토콜 분석을 통해 라우팅시 가능한 내부 공격을 모델링하고 이를 탐지할 수 있는 메커니즘을 제안하였다. 모델링한 공격은 AODV 프로토콜에서 사용하는 메시지를 변조하여 정상 노드들이 공격자를 통한 경로를 선택하게 만드는 것을 목표로 한다. 이러한 공격은 패킷스니핑 및 선택적 혹은 전 트래픽의 필터링과 변조 공격의 기본이 될 수 있다. 시뮬레이션을 통해 내부 공격이 정상 트래픽에 미치는 영향을 분석하였고, 흡수 정보를 이용한 간단한 탐지 메커니즘을 제안하였다. Sensor networks consist of many tiny sensor nodes that collaborate among themselves to collect, process, analyze, and disseminate data. In sensor networks, sensor nodes are typically powered by batteries, and have limited computing resources. Moreover, the redeployment of nodes by energy exhaustion or their movement makes network topology change dynamically. These features incur problems that do not appear in traditional, wired networks. Security in sensor networks is challenging problem due to the nature of wireless communication and the lack of resources. Several efforts are underway to provide security services in sensor networks, but most of them are preventive approaches based on cryptography. However, sensor nodes are extremely vulnerable to capture or key compromise. To ensure the security of the network, it is critical to develop suity mechanisms that can survive malicious attacks from "insiders" who have access to the keying materials or the full control of some nodes. In order to protect against insider attacks, it is necessary to understand how an insider can attack a sensor network. Several attacks have been discussed in the literature. However, insider attacks in general have not been thoroughly studied and verified. In this paper, we study the insider attacks against routing protocols in sensor networks using the Ad-hoc On-Demand Distance Vector (AODV) protocol. We identify the goals of attack, and then study how to achieve these goals by modifying of the routing messages. Finally, with the simulation we study how an attacker affects the sensor networks. After we understand the features of inside attacker, we propose a detect mechanism using hop count information.