• Title/Summary/Keyword: Hierarchical Networks

Search Result 543, Processing Time 0.031 seconds

Traffic Offloading in Two-Tier Multi-Mode Small Cell Networks over Unlicensed Bands: A Hierarchical Learning Framework

  • Sun, Youming;Shao, Hongxiang;Liu, Xin;Zhang, Jian;Qiu, Junfei;Xu, Yuhua
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.9 no.11
    • /
    • pp.4291-4310
    • /
    • 2015
  • This paper investigates the traffic offloading over unlicensed bands for two-tier multi-mode small cell networks. We formulate this problem as a Stackelberg game and apply a hierarchical learning framework to jointly maximize the utilities of both macro base station (MBS) and small base stations (SBSs). During the learning process, the MBS behaves as a leader and the SBSs are followers. A pricing mechanism is adopt by MBS and the price information is broadcasted to all SBSs by MBS firstly, then each SBS competes with other SBSs and takes its best response strategies to appropriately allocate the traffic load in licensed and unlicensed band in the sequel, taking the traffic flow payment charged by MBS into consideration. Then, we present a hierarchical Q-learning algorithm (HQL) to discover the Stackelberg equilibrium. Additionally, if some extra information can be obtained via feedback, we propose an improved hierarchical Q-learning algorithm (IHQL) to speed up the SBSs' learning process. Last but not the least, the convergence performance of the proposed two algorithms is analyzed. Numerical experiments are presented to validate the proposed schemes and show the effectiveness.

HIERARCHICAL CLUSTER ANALYSIS by arboART NEURAL NETWORKS and its APPLICATION to KANSEI EVALUATION DATA ANALYSIS

  • Ishihara, Shigekazu;Ishihara, Keiko;Nagamachi, Mitsuo
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
    • /
    • 2002.05a
    • /
    • pp.195-200
    • /
    • 2002
  • ART (Adaptive Resonance Theory [1]) neural network and its variations perform non-hierarchical clustering by unsupervised learning. We propose a scheme "arboART" for hierarchical clustering by using several ART1.5-SSS networks. It classifies multidimensional vectors as a cluster tree, and finds features of clusters. The Basic idea of arboART is to use the prototype formed in an ART network as an input to other ART network that has looser distance criteria (Ishihara, et al., [2,3]). By sending prototype vectors made by ART to one after another, many small categories are combined into larger and more generalized categories. We can draw a dendrogram using classification records of sample and categories. We have confirmed its ability using standard test data commonly used in pattern recognition community. The clustering result is better than traditional computing methods, on separation of outliers, smaller error (diameter) of clusters and causes no chaining. This methodology is applied to Kansei evaluation experiment data analysis.

  • PDF

An Energy Saving Method using Hierarchical Filtering in Sensor Networks (센서 네트워크에서 계층적 필터링을 이용한 에너지 절약 방안)

  • Kim, Jin-Su
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.8 no.4
    • /
    • pp.768-774
    • /
    • 2007
  • This paper proposes how to reduce the amount of data transmitted in each sensor and cluster head in order to lengthen the lifetime of sensor network. This study proposes hierarchical filtering for reducing the sensor's energy dissipation. Hierarchical filtering is to divide sensor network by two tiers when filtering it. First tier performs filtering when transmitting the data from cluster member to cluster head, and second tier performs filtering when transmitting the data from cluster head to base station. This should increase the efficiency of filtering and decrease the inaccuracy of the data compared to the methods which enlarge the filter width to do more filtering.

  • PDF

A Secure, Hierarchical and Clustered Multipath Routing Protocol for Homogenous Wireless Sensor Networks: Based on the Numerical Taxonomy Technique

  • Hossein Jadidoleslamy
    • International Journal of Computer Science & Network Security
    • /
    • v.23 no.8
    • /
    • pp.121-136
    • /
    • 2023
  • Wireless Sensor Networks (WSNs) have many potential applications and unique challenges. Some problems of WSNs are: severe resources' constraints, low reliability and fault tolerant, low throughput, low scalability, low Quality of Service (QoS) and insecure operational environments. One significant solution against mentioned problems is hierarchical and clustering-based multipath routing. But, existent algorithms have many weaknesses such as: high overhead, security vulnerabilities, address-centric, low-scalability, permanent usage of optimal paths and severe resources' consumption. As a result, this paper is proposed an energy-aware, congestion-aware, location-based, data-centric, scalable, hierarchical and clustering-based multipath routing algorithm based on Numerical Taxonomy technique for homogenous WSNs. Finally, performance of the proposed algorithm has been compared with performance of LEACH routing algorithm; results of simulations and statistical-mathematical analysis are showing the proposed algorithm has been improved in terms of parameters like balanced resources' consumption such as energy and bandwidth, throughput, reliability and fault tolerant, accuracy, QoS such as average rate of packet delivery and WSNs' lifetime.

DDoS Attack Tolerant Network using Hierarchical Overlay (계층적 오버레이를 이용한 DDoS 공격 감내 네트워크)

  • Kim, Mi-Hui;Chae, Ki-Joon
    • The KIPS Transactions:PartC
    • /
    • v.14C no.1 s.111
    • /
    • pp.45-54
    • /
    • 2007
  • As one of the most threatening attacks, DDoS attack makes distributed multiple agents consume some critical resources at the target within the short time, thus the extent and scope of damage is serious. Against the problems, the existing defenses focus on detection, traceback (identification), and filtering. Especially, in the hierarchical networks, the traffic congestion of a specific node could incur the normal traffic congestion of overall lower nodes, and also block the control traffic for notifying the attack detection and identifying the attack agents. In this paper, we introduce a DDoS attack tolerant network structure using a hierarchical overlay for hierarchical networks, which can convey the control traffic for defense such as the notification for attack detection and identification, and detour the normal traffic before getting rid of attack agents. Lastly, we analyze the overhead of overlay construction, the possibility of speedy detection notification, and the extent of normal traffic transmission in the attack case through simulation.

Energy Efficient Two-Tier Routing Protocol for Wireless Sensor Networks (센서 네트워크에서 에너지 효율성을 고려한 two-tier 라우팅 프로토콜)

  • Ahn Eun-Chul;Lee Sung-Hyup;Cho You-Ze
    • The KIPS Transactions:PartC
    • /
    • v.13C no.1 s.104
    • /
    • pp.103-112
    • /
    • 2006
  • Since sensor node has a limited energy supply in a wireless sensor network, it is very important to maximize the network lifetime through energy-efficient routing. Thus, many routing protocols have been developed for wireless sensor networks and can be classified into flat and hierarchical routing protocols. Recent researches focus on hierarchical routing scheme and LEACH is a representative hierarchical routing protocol. In this paper, we investigated the problems of the LEACH and proposed a novel energy efficient routing scheme, called ENTER(ENergy efficient Two-tiEr Routing protocol), to resolve the problem. ENTER reduces an energy consumption and increases a network lifetime by organizing clusters by the same distributed algerian as in the LEACH and establishing paths among cluster-heads to transmit the aggregated data to the sink node. We compared the performance of the ENTER with the LEACH through simulation and showed that the ENTER could enhance the network lifetime by utilizing the resources more efficiently.

Automatic Categorization of Real World FAQs Using Hierarchical Document Clustering (계층적 문서 클러스터링을 이용한 실세계 질의 메일의 자동 분류)

  • 류중원;조성배
    • Proceedings of the Korean Institute of Intelligent Systems Conference
    • /
    • 2001.05a
    • /
    • pp.187-190
    • /
    • 2001
  • Due to the recent proliferation of the internet, it is broadly granted that the necessity of the automatic document categorization has been on the rise. Since it is a heavy time-consuming work and takes too much manpower to process and classify manually, we need a system that categorizes them automatically as their contents. In this paper, we propose the automatic E-mail response system that is based on 2 hierarchical document clustering methods. One is to get the final result from the classifier trained seperatly within each class, after clustering the whole documents into 3 groups so that the first classifier categorize the input documents as the corresponding group. The other method is that the system classifies the most distinct classes first as their similarity, successively. Neural networks have been adopted as classifiers, we have used dendrograms to show the hierarchical aspect of similarities between classes. The comparison among the performances of hierarchical and non-hierarchical classifiers tells us clustering methods have provided the classification efficiency.

  • PDF

Hierarchical CNN-Based Senary Classification of Steganographic Algorithms (계층적 CNN 기반 스테가노그래피 알고리즘의 6진 분류)

  • Kang, Sanhoon;Park, Hanhoon
    • Journal of Korea Multimedia Society
    • /
    • v.24 no.4
    • /
    • pp.550-557
    • /
    • 2021
  • Image steganalysis is a technique for detecting images with steganographic algorithms applied, called stego images. With state-of-the-art CNN-based steganalysis methods, we can detect stego images with high accuracy, but it is not possible to know which steganographic algorithm is used. Identifying stego images is essential for extracting embedded data. In this paper, as the first step for extracting data from stego images, we propose a hierarchical CNN structure for senary classification of steganographic algorithms. The hierarchical CNN structure consists of multiple CNN networks which are trained to classify each steganographic algorithm and performs binary or ternary classification. Thus, it classifies multiple steganogrphic algorithms hierarchically and stepwise, rather than classifying them at the same time. In experiments of comparing with several conventional methods, including those of classifying multiple steganographic algorithms at the same time, it is verified that using the hierarchical CNN structure can greatly improve the classification accuracy.

THERA: Two-level Hierarchical Hybrid Road-Aware Routing for Vehicular Networks

  • Abbas, Muhammad Tahir;SONG, Wang-Cheol
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.13 no.7
    • /
    • pp.3369-3385
    • /
    • 2019
  • There are various research challenges in vehicular ad hoc networks (VANETs) that need to be focused until an extensive deployment of it becomes conceivable. Design and development of a scalable routing algorithm for VANETs is one of the critical issue due to frequent path disruptions caused by the vehicle's mobility. This study aims to provide a novel road-aware routing protocol for vehicular networks named as Two-level hierarchical Hybrid Road-Aware (THERA) routing for vehicular ad hoc networks. The proposed protocol is designed explicitly for inter-vehicle communication. In THERA, roads are distributed into non-overlapping road segments to reduce the routing overhead. Unlike other protocols, discovery process does not flood the network with packet broadcasts. Instead, THERA uses the concept of Gateway Vehicles (GV) for the discovery process. In addition, a route between source and destination is flexible to changing topology, as THERA only requires road segment ID and destination ID for the communication. Furthermore, Road-Aware routing reduces the traffic congestion, bypasses the single point of failure, and facilitates the network management. Finally yet importantly, this paper also proposes a probabilistical model to estimate a path duration for each road segment using the highway mobility model. The flexibility of the proposed protocol is evaluated by performing extensive simulations in NS3. We have used SUMO simulator to generate real time vehicular traffic on the roads of Gangnam, South Korea. Comparative analysis of the results confirm that routing overhead for maintaining the network topology is smaller than few previously proposed routing algorithms.

An Efficient Resource Reservation Schemes using PMRSVP in Wireless Mobile Networks (무선 이동 망에서 PMRSVP를 이용한 효율적인 자원 관리)

  • Han, Seung-Jin;Park, Yang-Jae;Rim, Kee-Wook;Lee, Jung-Hyun
    • The KIPS Transactions:PartC
    • /
    • v.10C no.3
    • /
    • pp.355-366
    • /
    • 2003
  • Today's market share of mobile internet service is growing rapidly in internet due to the rapid advances in wireless mobile networks. To guarantee for QoS of Mobile Nodes in wireless mobile networks, we propose the Proxy MRSVP (PMRSVP) which is efficient resource reservation protocol. The PMRSVP using a modified regional registration restrains excessive message generation from existing protocols that propose an alternative plan of existing best effort service in wireless mobile networks. We show that signaling message generation quantities and resource registration costs of the PMRSVP are lower than MRSVP and Hierarchical MRSVP (HMRSVP) because as Mobile Agent (MA) plays a proxy role instead of Corresponding Host (CH). We evaluate resource reservation cost with registration cost of intradomain and interdomain of the proposed method in the paper by comparing to that of the MRSVP and HMRSVP.