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Optimal resource allocation for multiclass services in peer-to-peer networks via successive approximation
- Source :
- Operational Research
- Publication Year :
- 2021
- Publisher :
- Springer Berlin Heidelberg, 2021.
-
Abstract
- Peer-to-peer (P2P) networks support a wide variety of network services including elastic services such as file-sharing and downloading and inelastic services such as real-time multiparty conferencing. Each peer who acquires a service will receive a certain level of satisfaction if the service is provided with a certain amount of resource. The utility function is used to describe the satisfaction of a peer when acquiring a service. In this paper we consider optimal resource allocation for elastic and inelastic services and formulate a utility maximization model which is an intractable and difficult non-convex optimization problem. In order to resolve it, we apply the successive approximation method and approximate the non-convex problem to a serial of equivalent convex optimization problems. Then we develop a gradient-based resource allocation scheme to achieve the optimal solutions of the approximations. After a serial of approximations, the proposed scheme can finally converge to an optimal solution of the primal utility maximization model for resource allocation which satisfies the Karush–Kuhn–Tucker conditions.
- Subjects :
- 68M10
0209 industrial biotechnology
Mathematical optimization
Optimization problem
Computer science
Strategy and Management
0211 other engineering and technologies
Computational intelligence
02 engineering and technology
Management Science and Operations Research
Peer-to-peer
computer.software_genre
P2P networks
Nonlinear programming
020901 industrial engineering & automation
Resource (project management)
Management of Technology and Innovation
Resource allocation
Service (business)
Elastic and inelastic services
Numerical Analysis
Original Paper
68M20
021103 operations research
90C30
Computational Theory and Mathematics
Modeling and Simulation
Convex optimization
Successive approximation
Statistics, Probability and Uncertainty
computer
Subjects
Details
- Language :
- English
- ISSN :
- 18661505 and 11092858
- Database :
- OpenAIRE
- Journal :
- Operational Research
- Accession number :
- edsair.doi.dedup.....bbba866555220e5c76af4e9f30be29ee