Opportunistic Networks

Anna Förster obtained her MSc degree in computer science and aerospace engineering from the Free University of Berlin, Germany, in 2004 and her PhD degree in self-organising sensor networks from the University of Lugano, Switzerland, in 2009. She also worked as a junior business consultant for McKinsey&Company, Berlin, between 2004 and 2005. From 2010 to 2014, she was a researcher and lecturer at SUPSI (the University of Applied Sciences of Southern Switzerland). Since 2015, she leads the Sustainable Communication Networks group at the University of Bremen. Currently, she serves as Director of the Bremen Spatial Cognition Center (BSCC) and as a board member of the Center for Computing Technology (TZI).Her main research interests lie in the domain of the Internet of Things. She is mostly interested in self-awareness and resilience, user friendliness and user adoption, self-organisation, and machine learning for IoT applications. All considered scenarios and applications serve the Sustainable Development Goals and contribute to a more sustainable and peaceful future.Pietro Manzoni is a computer engineering professor at the "Universitat Politècnica de València," Spain. He received a master’s degree in computer science from the "Università degli Studi" of Milan, Italy, in 1989 and a Ph.D. in Computer Science from the "Politecnico di Milano," Italy, in 1995. From November 1992 to February 1993, he was an intern at Bellcore Labs, Red Bank, New Jersey, USA. From February 1994 to November 1994, he was a visiting researcher at the ICSI (International Computer Science Institute) Berkeley, California, USA.His research focuses on using Mobile Wireless Networks to create dynamic systems. Currently, he is developing solutions for the Internet of Things using LPWAN networks and Pub/Sub systems. These solutions have various applications, including environmental intelligence by integrating TinyML-based solutions, sustainable and green IoT, and Smart Tourism. Additionally, he is interested in exploring different aspects of network pluralism and finding ways to provide integrated connectivity in the edge-cloud continuum.Enrique Hernández Orallo is a Professor in the Department of Computer Engineering at the Universitat Politècnica de València (Spain). He earned an MSc and a PhD in Computer Science from the Universitat Politècnica de València in 1992 and 2001 respectively. From 1991 to 2005 he worked at several companies in real-time and computer networks projects.He is a member of the Computer Networks Research Group (GRC) and has participated in over 10 Spanish and European research projects and is the author of about 100 journal and conference papers and co-author of two successful books of C++ in the Spanish language. His areas of interest include performance evaluation, mobile and pervasive computing, data science and real-time systems.Dr.-Ing. Koojana Kuladinithi is currently serving as the deputy head of the Institute of Communication Networks at Hamburg University of Technology since November 2016. Additionally, she holds the position of deputy coordinator for the international master's program of Information and Communication Technology offered at the same university.She earned her BSc and MSc in Electronics & Telecommunication Engineering from the University of Moratuwa, Sri Lanka. She then completed her PhD on "Wireless Multihop Ad hoc Networks: Evaluation of Radio Disjoint Multipath Routing" at the University of Bremen, Germany. Her journey in the field of research began in 2002 when she joined the ComNets group at the University of Bremen as a research scientist specializing in enhancing mobility management protocols. Over the years, she has made significant contributions to the scientific community with numerous publications, including patents, and remains an active participant in the IETF. As a senior researcher at the Institute of Communication Networks of the Hamburg University of Technology, her primary focus is enhancing network protocols, optimizing and modeling Wireless Sensor Network (WSN) protocols, and opportunistic communications.Asanga Udugama is a senior lecturer at the Sustainable Communication Networks Group of the University of Bremen, Germany. He obtained his BBA from Colombo University, Sri Lanka, M.Eng. from the Munster Technological University, Cork, Ireland, and PhD from the University of Bremen. Throughout his academic career, he has made numerous contributions to research in computer networks through patents, publications, talks, teaching, and student supervision. He primarily focuses his research efforts on improving and assessing opportunistic and information-centric networking protocols for the Internet of Things, with a particular emphasis on sustainability, achieved through modeling and practical implementations.

• I Foundations of Opportunistic Networks.- 1 Mobility of Opportunistic Networks.- 1.1 Scale and density .- 1.2 Collecting mobility traces .- 1.3 From mobility traces to location information.- 1.4 From mobility traces to contact information.- 1.4.1 Converting GPS traces into contact traces.- 1.4.2 Direct gathering of contact traces.- 1.5 Mobility metrics.- 1.6 Large-Scale Mobility Characteristics in OppNets.- 1.7 Impact of mobility on opportunistic networks.- 1.8 Chapter summary.- Problems.- 2 Data Dissemination in Opportunstic Networks.- 2.1 Terms and metrics.- 2.2 Optimal dissemination.- 2.3 Flooding protocols.- 2.3.1 Epidemic Routing.- 2.3.2 Spray and Wait.- 2.3.3 Optimal Stopping Theory.-  2.4 Mobility based protocols.- 2.4.1 Geocasting protocols.- 2.4.2 Speed/direction based protocols.- 2.4.3 Encounter based protocols.- 2.5 Social awareness based protocols.- 2.6 Data content based protocols.- 2.7 Network coding based protocols.- 2.8 Caching in Opportunistic Networks.- 2.9 Chapter summary.- Problems.- 3 Security in Opportunistic Networks.- 3.1 Overview.- 3.2 Types of Attacks.- 3.2.1 Masquerade.- 3.2.2 Eavesdropping ..- 3.2.3 Sabotage.- 3.2.4 Data Manipulation.- 3.2.5 Physical Attacks.- 3.2.6 Free-riding.- 3.3 Attacks Evaluation.- 3.3.1 Evaluation Methodology and Setup.- 3.3.2 Effects of the Attacks.- 3.4 Chapter summary.- Problems.- Part II Evaluation of Opportunistic Networks 4 Overview of Evaluation of Opportunistic Networks.- 4.1 Overview .- 4.2 Methods for evaluating Opportunistic Networks.- 4.3 Metrics for evaluating Opportunistic Networks.- 4.4 Chapter summary.- Problems .- 5 Theoretical Models for Opportunistic Networks.- 5.1 General assumptions and their validity.- 5.2 Markov Chain Models.-  5.2.1 Modeling epidemic diffusion in OppNet.- 5.2.2 Limitations and applications of Markov Chain Models.- 5.3 Compartmental models.- 5.3.1 Basic epidemic model.- 5.3.2 Epidemic model for an open area.- 5.3.3 Limitations and applicationsof Compartmental Models.-  5.4 Other methods.- 5.5 Chapter summary.- Problems.- 6 Simulation models for Opportunistic Networks.- 6.1 Simulation model stack for opportunistic networks.- 6.4 Mobility Models and Contact Traces.- 6.4.1 Terminology.- 6.4.2 Properties of mobility models.- 6.4.3 Contact traces.- 6.4.4 Discussion of mobility models.- 6.5 Simulation Speedup.- 6.6 Chapter summary.- Problems .- 7 Simulation tools for Opportunistic Networks.- 7.1 Discrete event-based simulation.- 7.2 OMNeT++ and the Opportunistic Network Simulator (OPS).- 7.3 The ONE.- 7.4 Network Simulator 3 (ns-3).- 7.5 Comparison of simulators.- 7.6 Mobility tools .- 7.7 Chapter summary .- Problems .- 8 Benchmarking Opportunistic Networks.- 8.1 Benchmarks for OppNets.- 8.2 Metrics for comparing opportunistic protocols.- 8.3 Comparing opportunistic protocols.- 8.4 Chapter summary.- Problems.- Part III Implementation of Opportunistic Networks 9 Connectivity Technologies for OpportunisticNetworks.- 9.1 Mobile Ad Hoc Networks.- 9.2 Communication Technologies.- 9.2.1 LoRa.- 9.2.2 Radio Frequency Identification (RFID).- 9.2.3 Bluetooth Low Energy (BLE).- 9.2.4 Wi-Fi Direct.- 9.2.5 ZigBee.- 9.2.6 802.11p.- 9.2.7 Satellite communication.- 9.3 Toward 5G and 6G Networks.- 9.4 Related software and libraries.- 9.4.1 Exposure Notifications System (ENS).- 9.4.2 Apple Multipeer Connectivity.