Design, Analysis and Computation in Wireless and Optical Networks

abstract: In the realm of network science, many topics can be abstracted as graph problems, such as routing, connectivity enhancement, resource/frequency allocation and so on. Though most of them are NP-hard to solve, heuristics as well as approximation algorithms are proposed to achieve reasonably good results. Accordingly, this dissertation studies graph related problems encountered in real applications. Two problems studied in this dissertation are derived from wireless network, two more problems studied are under scenarios of FIWI and optical network, one more problem is in Radio- Frequency Identification (RFID) domain and the last problem is inspired by satellite deployment. The objective of most of relay nodes placement problems, is to place the fewest number of relay nodes in the deployment area so that the network, formed by the sensors and the relay nodes, is connected. Under the fixed budget scenario, the expense involved in procuring the minimum number of relay nodes to make the network connected, may exceed the budget. In this dissertation, we study a family of problems whose goal is to design a network with “maximal connectedness” or “minimal disconnectedness”, subject to a fixed budget constraint. Apart from “connectivity”, we also study relay node problem in which degree constraint is considered. The balance of reducing the degree of the network while maximizing communication forms the basis of our d-degree minimum arrangement(d-MA) problem. In this dissertation, we look at several approaches to solving the generalized d-MA problem where we embed a graph onto a subgraph of a given degree. In recent years, considerable research has been conducted on optical and FIWI networks. Utilizing a recently proposed concept “candidate trees” in optical network, this dissertation studies counting problem on complete graphs. Closed form expressions are given for certain cases and a polynomial counting algorithm for general cases is also presented. Routing plays a major role in FiWi networks. Accordingly to a novel path length metric which emphasizes on “heaviest edge”, this dissertation proposes a polynomial algorithm on single path computation. NP-completeness proof as well as approximation algorithm are presented for multi-path routing. Radio-frequency identification (RFID) technology is extensively used at present for identification and tracking of a multitude of objects. In many configurations, simultaneous activation of two readers may cause a “reader collision” when tags are present in the intersection of the sensing ranges of both readers. This dissertation ad- dresses slotted time access for Readers and tries to provide a collision-free scheduling scheme while minimizing total reading time. Finally, this dissertation studies a monitoring problem on the surface of the earth for significant environmental, social/political and extreme events using satellites as sensors. It is assumed that the impact of a significant event spills into neighboring regions and there will be corresponding indicators. Careful deployment of sensors, utilizing “Identifying Codes”, can ensure that even though the number of deployed sensors is fewer than the number of regions, it may be possible to uniquely identify the region where the event has taken place.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Planning the deployment of fault-tolerant wireless sensor networks

Since Wireless Sensor Networks (WSNs) are subject to failures, fault-tolerance becomes an important requirement for many WSN applications. Fault-tolerance can be enabled in different areas of WSN design and operation, including the Medium Access Control (MAC) layer and the initial topology design. To be robust to failures, a MAC protocol must be able to adapt to traffic fluctuations and topology dynamics. We design ER-MAC that can switch from energy-efficient operation in normal monitoring to reliable and fast delivery for emergency monitoring, and vice versa. It also can prioritise high priority packets and guarantee fair packet deliveries from all sensor nodes. Topology design supports fault-tolerance by ensuring that there are alternative acceptable routes to data sinks when failures occur. We provide solutions for four topology planning problems: Additional Relay Placement (ARP), Additional Backup Placement (ABP), Multiple Sink Placement (MSP), and Multiple Sink and Relay Placement (MSRP). Our solutions use a local search technique based on Greedy Randomized Adaptive Search Procedures (GRASP). GRASP-ARP deploys relays for (k,l)-sink-connectivity, where each sensor node must have k vertex-disjoint paths of length ≤ l. To count how many disjoint paths a node has, we propose Counting-Paths. GRASP-ABP deploys fewer relays than GRASP-ARP by focusing only on the most important nodes – those whose failure has the worst effect. To identify such nodes, we define Length-constrained Connectivity and Rerouting Centrality (l-CRC). Greedy-MSP and GRASP-MSP place minimal cost sinks to ensure that each sensor node in the network is double-covered, i.e. has two length-bounded paths to two sinks. Greedy-MSRP and GRASP-MSRP deploy sinks and relays with minimal cost to make the network double-covered and non-critical, i.e. all sensor nodes must have length-bounded alternative paths to sinks when an arbitrary sensor node fails. We then evaluate the fault-tolerance of each topology in data gathering simulations using ER-MAC

Oblivious Network Optimization and Security Modeling in Sustainable Smart Grids and Cities

Today\u27s interconnected world requires an inexpensive, fast, and reliable way of transferring information. There exists an increasingly important need for intelligent and adaptable routing of network flows. In the last few years, many researchers have worked toward developing versatile solutions to the problem of routing network flows in unpredictable circumstances. These attempts have evolved into a rich literature in the area of oblivious network design which typically route the network flows via a routing scheme that makes use of a spanning tree or a set of trees of the graph representation of the network. In the first chapter, we provide an introduction to network design. This introductory chapter has been designed to clarify the importance and position of oblivious routing problems in the context of network design as well as its containing field of research. Part I of this dissertation discusses the fundamental role of linked hierarchical data structures in providing the mathematical tools needed to construct rigorous versatile routing schemes and applies hierarchical routing tools to the process of constructing versatile routing schemes. Part II of this dissertation applies the routing tools generated in Part I to address real-world network optimization problems in the area of electrical power networks, clusters of micrograms, and content-centric networks. There is an increasing concern regarding the security and privacy of both physical and communication layers of smart interactive customer-driven power networks, better known as smart grids. Part III of this dissertation utilizes an advanced interdisciplinary approach to address existing security and privacy issues, proposing legitimate countermeasures for each of them from the standpoint of both computing and electrical engineering. The proposed methods are theoretically proven by mathematical tools and illustrated by real-world examples

Wireless Sensor Network MCDS Construction Algorithms With Energy Consideration for Extreme Environments Healthcare

With the enhancement of people's health awareness, more and more users are willing to wear portable micro-health monitoring equipment and communicate with remote medicine center for real-time diagnosis. Although, under normal circumstances, users' health status can be detected at any time, in extreme circumstances, such as earthquakes, how to make the medical center monitor user data for a long time for rescue will be of great significance. In this paper, we will study the networking of portable wearable devices based on wireless sensor networks. We mainly use minimal connected dominating sets (MCDSs) to organize nodes in extreme environments effectively, form virtual backbone networks, send data to the rescue or medical personnel, and maximize network lifetime. Specifically, we propose an adverse dominator selection procedure (ADSP), where the dominators are selected by their children-independent nodes. The ADSP has two versions, which are Independent node degree-based Adverse Dominator Selection Procedure (IADSP) and residual Energy-based Adverse Dominator Selection Procedure (EADSP). Based on IADSP and EADSP, two approximation MCDS construction algorithms named Independent node degree based MCDS (IMCDS) and Energy-efficient Independent neighbor-based MCDS (EIMCDS) are proposed, respectively. Both of them have the message complexity as O($N\Delta$ ). The performance ratio of IMCDS has an upper bound as O($\sqrt {N}$ ). The simulation results show that IMCDS and EIMCDS perform well in terms of CDS size, and the routing algorithm based on EIMCDS has better energy efficiency performance than that of IMCDS and classical routing protocol

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

Optimization of anchor nodes placement in wireless localization networks

This work focuses on optimizing node placement for time-of-flight-based wireless localization networks. Main motivation are critical safety applications. The first part of my thesis is an experimental study on in-tunnel vehicle localization. In- tunnel localization of vehicles is crucial for emergency management, especially for large trucks transporting dangerous goods such as inflammable chemicals. Compared to open roads, evacuation in tunnels is much more difficult, so that fire or other accidents can cause much more damage. We provide distance measurement error characterization inside road tunnels focusing on time of flight measurements. We design a complete system for in-tunnel radio frequency time-of- flight-based localization and show that such a system is feasible and accurate, and that few nodes are sufficient to cover the entire tunnel. The second part of my work focuses on anchor nodes placement optimization for time-of-flight-based localization networks where multilateration is used to obtain the target position based on its distances from fixed and known anchors. Our main motivation are safety at work applications, in particular, environments such as factory halls. Our goal is to minimize the number of anchors needed to localize the target while keeping the localization uncertainty lower than a given threshold in an area of arbitrary shape with obstacles. Our propagation model accounts for the presence of line of sight between nodes, while geometric dilution of precision is used to express the localization error introduced by multilateration. We propose several integer linear programming formulations for this problem that can be used to obtain optimal solutions to instances of reasonable sizes and compare them in terms of execution times by simulation experiments. We extend our approach to address fault tolerance, ensuring that the target can still be localized after any one of the nodes fails. Two dimensional localization is sufficient for most indoor applications. However, for those industrial environments where the ceiling is very high and the worker might be climbing or be lifted from the ground, or if very high localization precision is needed, three-dimensional localization may be required. Therefore, we extend our approach to three-dimensional localization. We derive the expression for geometric dilution of precision for 3D multilateration and give its geometric interpretation. To tackle problem instances of large size, we propose two novel heuristics: greedy placement with pruning, and its improved version, greedy placement with iterative pruning. We create a simulator to test and compare all our proposed approaches by generating multiple test instances. For anchor placement for multilateration-based localization, we obtain solutions with below 2% anchors overhead with respect to the optimum on average, with around 5s average execution time for 130 candidate positions. For the fault-tolerant version of the same problem, we obtain solutions of around 1% number of anchors overhead with respect to the optimum on average, with 0.4s execution time for 65 candidate positions, by using greedy heuristic with pruning. For 3D placement, the greedy heuristic with iterative pruning produced results of 0.05% of optimum on average, with average execution time of around 6s for 250 candidate positions, for the problem instances we tested

무인항공기 운영을 위한 덮개 모델 기반의 대규모 최적화 기법

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 산업공학과, 2021. 2. 문일경.There is increasing interest in the unmanned aerial vehicle (UAV) in various fields of the industry, starting from the surveillance to the logistics. After introducing the smart city, there are attempts to utilize UAVs in the public service sector by connecting individual components of the system with both information and physical goods. In this dissertation, the UAV operation problems in the public service sector is modeled in the set covering approach. There is a vast literature on the facility location and set covering problems. However, when operating UAVs in the system, the plan has to make the most of the flexibility of the UAV, but also has to consider its physical limitation. We noticed a gap between the related, existing approaches and the technologies required in the field. That is, the new characteristics of the UAV hinder the existing solution algorithms, or a brand-new approach is required. In this dissertation, two operation problems to construct an emergency wireless network in a disaster situation by UAV and one location-allocation problem of the UAV emergency medical service (EMS) facility are proposed. The reformulation to the extended formulation and the corresponding branch-and-price algorithm can overcome the limitations and improve the continuous or LP relaxation bounds, which are induced by the UAV operation. A brief explanation of the UAV operation on public service, the related literature, and the brief explanation of the large-scale optimization techniques are introduced in Chapter 1, along with the research motivations and contributions, and the outline of the dissertations. In Chapter 2, the UAV set covering problem is defined. Because the UAV can be located without predefined candidate positions, more efficient operation becomes feasible, but the continuous relaxation bound of the standard formulation is weakened. The large-scale optimization techniques, including the Dantzig-Wolfe decomposition and the branch-and-price algorithm, could improve the continuous relaxation bound and reduce the symmetries of the branching tree and solve the realistic-scaled problems within practical computation time. To avoid numerical instability, two approximation models are proposed, and their approximation ratios are analyzed. In Chapter 3, UAV variable radius set covering problem is proposed with an extra decision on the coverage radius. While implementing the branch-and-price algorithm to the problem, a solvable equivalent formulation of the pricing subproblem is proposed. A heuristic based on the USCP is designed, and the proposed algorithm outperformed the benchmark genetic algorithm proposed in the literature. In Chapter 4, the facility location-allocation problem for UAV EMS is defined. The quadratic variable coverage constraint is reformulated to the linear equivalent formulation, and the nonlinear problem induced by the robust optimization approach is linearized. While implementing the large-scale optimization techniques, the structure of the subproblem is analyzed, and two solution approaches for the pricing subproblem are proposed, along with a heuristic. The results of the research can be utilized when implementing in the real applications sharing the similar characteristics of UAVs, but also can be used in its abstract formulation.현재, 지역 감시에서 물류까지, 무인항공기의 다양한 산업에의 응용이 주목받고 있다. 특히, 스마트 시티의 개념이 대두된 이후, 무인항공기를 공공 서비스 영역에 활용하여 개별 사회 요소를 연결, 정보와 물자를 교환하고자 하는 시도가 이어지고 있다. 본 논문에서는 공공 서비스 영역에서의 무인항공기 운영 문제를 집합덮개문제 관점에서 모형화하였다. 설비위치결정 및 집합덮개문제 영역에 많은 연구가 진행되어 있으나, 무인항공기를 운영하는 시스템의 경우 무인항공기가 갖는 자유도를 충분히 활용하면서도 무인항공기의 물리적 한계를 고려한 운영 계획을 필요로 한다. 우리는 본 문제와 관련된 기존 연구와 현장이 필요로 하는 기술의 괴리를 인식하였다. 이는 다시 말해, 무인항공기가 가지는 새로운 특성을 고려하면 기존의 문제 해결 방법을 통해 풀기 어렵거나, 혹은 새로운 관점에서의 문제 접근이 필요하다는 것이다. 본 논문에서는 재난이 발생한 지역에 무인항공기를 이용하여 긴급무선네트워크를 구성하는 두가지 문제와, 무인항공기를 이용하여 응급의료서비스를 제공하는 시설의 위치설정 및 할당문제를 제안한다. 확장문제로의 재공식화와 분지평가법을 활용하여, 무인항공기의 활용으로 인해 발생하는 문제 해결 방법의 한계를 극복하고 완화한계를 개선하였다. 공공 서비스 영역에서의 무인항공기 운영, 관련된 기존 연구와 본 논문에서 사용하는 대규모 최적화 기법에 대한 개괄적인 설명, 연구 동기 및 기여와 논문의 구성을 1장에서 소개한다. 2장에서는 무인항공기 집합덮개문제를 정의한다. 무인항공기는 미리 정해진 위치 없이 자유롭게 비행할 수 있기 때문에 더 효율적인 운영이 가능하나, 약한 완화한계를 갖게 된다. Dantzig-Wolfe 분해와 분지평가법을 포함한 대규모 최적화 기법을 통해 완화한계를 개선할 수 있으며, 분지나무의 대칭성을 줄여 실제 규모의 문제를 실용적인 시간 안에 해결할 수 있었다. 수치적 불안정성을 피하기 위하여, 두 가지 선형 근사 모형이 제안되었으며, 이들의 근사 비율을 분석하였다. 3장에서는 무인항공기 집합덮개문제를 일반화하여 무인항공기 가변반경 집합덮개문제를 정의한다. 분지평가법을 적용하면서 해결 가능한 평가 부문제를 제안하였으며, 휴리스틱을 설계하였다. 제안한 풀이 방법들이 기존 연구에서 제안한 벤치마크 유전 알고리즘을 능가하는 결과를 나타내었다. 4장에서는 무인항공기 응급의료서비스를 운영하는 시설의 위치설정 및 할당문제를 정의하였다. 2차 가변반경 범위제약이 선형의 동치인 수식으로 재공식화되었으며, 강건최적화 기법으로 인해 발생하는 비선형 문제를 선형화하였다. 대규모 최적화 기법을 적용하면서, 평가 부문제의 구조를 분석하여 두 가지 풀이 기법과 휴리스틱을 제안하였다. 본 연구의 결과는 무인항공기와 비슷한 특징을 가지는 실제 사례에 적용될 수 있으며, 추상적인 문제로써 다양한 분야에 그대로 활용될 수도 있다.Abstract i Contents vii List of Tables ix List of Figures xi Chapter 1 Introduction 1 1.1 Unmanned aerial vehicle operation on public services 1 1.2 Facility location problems 3 1.3 Large-scale optimization techniques 4 1.4 Research motivations and contributions 6 1.5 Outline of the dissertation 12 Chapter 2 Unmanned aerial vehicle set covering problem considering fixed-radius coverage constraint 14 2.1 Introduction 14 2.2 Problem definition 20 2.2.1 Problem description 22 2.2.2 Mathematical formulation 23 2.2.3 Discrete approximation model 26 2.3 Branch-and-price approach for the USCP 28 2.3.1 An extended formulation of the USCP 29 2.3.2 Branching strategies 34 2.3.3 Pairwise-conflict constraint approximation model based on Jung's theorem 35 2.3.4 Comparison of the approximation models 40 2.3.5 Framework of the solution algorithm for the PCBP model 42 2.4 Computational experiments 44 2.4.1 Datasets used in the experiments 44 2.4.2 Algorithmic performances 46 2.5 Solutions and related problems of the USCP 61 2.6 Summary 64 Chapter 3 Unmanned aerial vehicle variable radius set covering problem 66 3.1 Introduction 66 3.2 Problem definition 70 3.2.1 Mathematical model 72 3.3 Branch-and-price approach to the UVCP 76 3.4 Minimum covering circle-based approach 79 3.4.1 Formulation of the pricing subproblem II 79 3.4.2 Equivalence of the subproblem 82 3.5 Fixed-radius heuristic 84 3.6 Computational experiments 86 3.6.1 Datasets used in the experiments 88 3.6.2 Solution algorithms 91 3.6.3 Algorithmic performances 94 3.7 Summary 107 Chapter 4 Facility location-allocation problem for unmanned aerial vehicle emergency medical service 109 4.1 Introduction 109 4.2 Related literature 114 4.3 Location-allocation model for UEMS facility 117 4.3.1 Problem definition 118 4.3.2 Mathematical formulation 120 4.3.3 Linearization of the quadratic variable coverage distance function 124 4.3.4 Linear reformulation of standard formulation 125 4.4 Solution algorithms 126 4.4.1 An extended formulation of the ULAP 126 4.4.2 Branching strategy 129 4.4.3 Robust disjunctively constrained integer knapsack problem 131 4.4.4 MILP reformulation approach 132 4.4.5 Decomposed DP approach 133 4.4.6 Restricted master heuristic 136 4.5 Computational experiments 137 4.5.1 Datasets used in the experiments 137 4.5.2 Algorithmic performances 140 4.5.3 Analysis of the branching strategy and the solution approach of the pricing subproblem 150 4.6 Summary 157 Chapter 5 Conclusions and future research 160 5.1 Summary 160 5.2 Future research 163 Appendices 165 A Comparison of the computation times and objective value of the proposed algorithms 166 Bibliography 171 국문초록 188 감사의 글 190Docto

Exploiting Structure In Combinatorial Problems With Applications In Computational Sustainability

Combinatorial decision and optimization problems are at the core of many tasks with practical importance in areas as diverse as planning and scheduling, supply chain management, hardware and software verification, electronic commerce, and computational biology. Another important source of combinatorial problems is the newly emerging field of computational sustainability, which addresses decision-making aimed at balancing social, economic and environmental needs to guarantee the long-term prosperity of life on our planet. This dissertation studies different forms of problem structure that can be exploited in developing scalable algorithmic techniques capable of addressing large real-world combinatorial problems. There are three major contributions in this work: 1) We study a form of hidden problem structure called a backdoor, a set of key decision variables that captures the combinatorics of the problem, and reveal that many real-world problems encoded as Boolean satisfiability or mixed-integer linear programs contain small backdoors. We study backdoors both theoretically and empirically and characterize important tradeoffs between the computational complexity of finding backdoors and their effectiveness in capturing problem structure succinctly. 2) We contribute several domain-specific mathematical formulations and algorithmic techniques that exploit specific aspects of problem structure arising in budget-constrained conservation planning for wildlife habitat connectivity. Our solution approaches scale to real-world conservation settings and provide important decision-support tools for cost-benefit analysis. 3) We propose a new survey-planning methodology to assist in the construction of accurate predictive models, which are especially relevant in sustainability areas such as species- distribution prediction and climate-change impact studies. In particular, we design a technique that takes advantage of submodularity, a structural property of the function to be optimized, and results in a polynomial-time procedure with approximation guarantees

Security in Distributed, Grid, Mobile, and Pervasive Computing

This book addresses the increasing demand to guarantee privacy, integrity, and availability of resources in networks and distributed systems. It first reviews security issues and challenges in content distribution networks, describes key agreement protocols based on the Diffie-Hellman key exchange and key management protocols for complex distributed systems like the Internet, and discusses securing design patterns for distributed systems. The next section focuses on security in mobile computing and wireless networks. After a section on grid computing security, the book presents an overview of security solutions for pervasive healthcare systems and surveys wireless sensor network security