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Grant: Discovery Grants Program - Individual

Concordia University

$41,000.00

Efficient algorithms for mobile agents in networks

FY 2024-25

Summary
This proposal focuses on efficient algorithms for agents interacting and moving on networks. These agents could be autonomous mobile robots, self-driving cars, drones, swarms of simple robots, software agents, or people in a social network. Many networks are dynamic rather than static. For instance, in wireless networks formed by mobile nodes, such as IoT devices, buses, satellites, or autonomous mobile robots, links are created or broken because of the mobility of nodes. In road networks, traffic changes impact the travel time of roads which in turn changes the weights of the links. The dynamic nature of the network increases greatly the challenge of solving problems such as routing, exploration, and transportation.  The very large  scale  of networks created by IoT devices or mobile robots causes more challenges. We need  distributed algorithms, in which agents can  collaborate with each other to complete tasks. Any communication between the agents should ideally be  local. How best can the agents communicate and collaborate to perform tasks such as  search or  transportation? What is the impact of the capabilities of the agents, in terms of memory, communication abilities, energy storage, computational abilities, and faulty behaviour? Finally in some settings, the agents may not collaborate, but instead behave selfishly and strategically. In particular, consider a residential network of houses in a city, and agents of different types residing at the nodes. If these agents move strategically to new locations to suit their own preferences for types of neighbours, what conditions in terms of number of agents of different types or network topology can result in a stable situation or equilibrium? What conditions favour diverse neighbourhoods as stable outcomes? Are there techniques to increase the diversity in social networks? The long-term objective of my research is to improve our understanding of the interplay between network structure, the dynamic nature of networks, and distributed computing by mobile agents moving on networks. In the next granting period, I will focus on three specific problems that can help illuminate the more general principles. My short-term objectives are to design and analyze efficient centralized and distributed local algorithms for: - collaborative  exploration by autonomous mobile robots in static and dynamic networks. - routing and transportation in static and dynamic road and communication networks. - increasing diversity in social networks.
Program
Discovery Grants Program - Individual
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
RGPIN-2022-04919
Name nom
Narayanan, Lata
Department département
Computer Science and Software Engineering
Organization id
70
Institution établissement
Concordia University
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2022
Award amount
41000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1507
Committee name en
Computer Science
Committee name fr
Sciences informatiques
Area of application code
1207
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Information, computer and communication technologies
Area of application fr
Technologie de l'information, des ordinateurs et des réseaux de communications
Research subject code
2713
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Algorithms
Research subject fr
Algorithmes
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Efficient algorithms for mobile agents in networks
Keywords
autonomous mobile robots; routing algorithms; trajectories; search; online and approximation algorithms; graph algorithms; social network algorithms; evolving networks; transportation by robots
Application summary
This proposal focuses on efficient algorithms for agents interacting and moving on networks. These agents could be autonomous mobile robots, self-driving cars, drones, swarms of simple robots, software agents, or people in a social network. Many networks are dynamic rather than static. For instance, in wireless networks formed by mobile nodes, such as IoT devices, buses, satellites, or autonomous mobile robots, links are created or broken because of the mobility of nodes. In road networks, traffic changes impact the travel time of roads which in turn changes the weights of the links. The dynamic nature of the network increases greatly the challenge of solving problems such as routing, exploration, and transportation.  The very large  scale  of networks created by IoT devices or mobile robots causes more challenges. We need  distributed algorithms, in which agents can  collaborate with each other to complete tasks. Any communication between the agents should ideally be  local. How best can the agents communicate and collaborate to perform tasks such as  search or  transportation? What is the impact of the capabilities of the agents, in terms of memory, communication abilities, energy storage, computational abilities, and faulty behaviour? Finally in some settings, the agents may not collaborate, but instead behave selfishly and strategically. In particular, consider a residential network of houses in a city, and agents of different types residing at the nodes. If these agents move strategically to new locations to suit their own preferences for types of neighbours, what conditions in terms of number of agents of different types or network topology can result in a stable situation or equilibrium? What conditions favour diverse neighbourhoods as stable outcomes? Are there techniques to increase the diversity in social networks? The long-term objective of my research is to improve our understanding of the interplay between network structure, the dynamic nature of networks, and distributed computing by mobile agents moving on networks. In the next granting period, I will focus on three specific problems that can help illuminate the more general principles. My short-term objectives are to design and analyze efficient centralized and distributed local algorithms for: - collaborative  exploration by autonomous mobile robots in static and dynamic networks. - routing and transportation in static and dynamic road and communication networks. - increasing diversity in social networks.