Multi-Objective Optimization for Trustworthy Tactical Networks: A Survey and Insights
Abstract
Multi-objective optimization (MOO) is the process of optimizing multiple objective functions concurrently and systematically. Modern Army missions require a tactical network to achieve multiple objectives as multiple parties with different objectives are involved in collaborative mission execution. MOO problems have been studied extensively in the field of coalition formation based on evolutionary algorithms or game theoretic approaches. However, there has been no generic framework to consider MOO problems in tactical networks, particularly when the goals must be achieved based on the trustworthiness of participating entities. First, we provide a comprehensive survey of work on MOO formulation and solution techniques, particularly in coalition formation. Second, we extensively discuss MOO techniques and methods that have been used for coalition formation. We specifically investigate the use of trust in the process of coalition formation. Third, we look into tactical applications in which trust plays a pivotal role in mission success. Finally, we discuss future research directions of MOO design for trustworthy tactical networks.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2013
- Accession Number
- ADA588224
Entities
People
- Ananthram Swami
- Ingray Chen
- Jin-Hee Cho
- Kevin Chan
- Yating Wang
Organizations
- United States Army Research Laboratory