Stochastic game-based dynamic information delivery system for wireless cooperative networks
| Autor: | Hannan Bin Liaqat, Muhammad Aksam Iftikhar, Ali Kashif Bashir, Amjad Ali, Sangheon Pack, Li Feng |
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| Rok vydání: | 2019 |
| Předmět: |
Computer Science::Computer Science and Game Theory
Dynamic network analysis Computer Networks and Communications Computer science Reliability (computer networking) Throughput 02 engineering and technology law.invention symbols.namesake Relay law 0202 electrical engineering electronic engineering information engineering Wireless business.industry Node (networking) Stochastic game 020206 networking & telecommunications Lyapunov optimization Hardware and Architecture Nash equilibrium symbols 020201 artificial intelligence & image processing Stochastic optimization business Software Computer network |
| Zdroj: | Future Generation Computer Systems. 95:277-291 |
| ISSN: | 0167-739X |
| Popis: | The haptic communications is considered as the prime application running on the Tactile Internet. Therefore, Tactile Internet required to be highly reliable, provide a very low latencies, and required sufficient capacities at intermediate nodes to allow a large number of devices to communicate with each other simultaneously and autonomously. Moreover, the wireless cooperative network (WCN), is considered as one of the major component of the 5G technologies due to it promising advantages, such as improving wireless transmission capacity and reliability. However, the selfish nature of relay nodes may depress such enhancement and is not favored by the source node. In this paper, we propose an incentive-based dynamic flow allocation (FA) and forwarding strategy selection (FSS) scheme under time-varying selfishness. In the proposed scheme, the source node determines the FA to maximize the average network throughput under the constraints of network stability and selfishness boundaries, while each selfish relay executes the FSS to optimize its own profit with regard to the dynamic network state. Moreover, to cope with the conflicting interests between selfish relays a stochastic game model is employed to design a competition for haptic information forwarding and Nash equilibrium is proven also a combined Q -learning-based algorithm is proposed to guide the relays’ forwarding strategies. Furthermore, by considering the stochastic property of the network state, the FA for the source is formulated as a stochastic optimization problem. Finally, by exploiting the concept of virtual selfishness queue, the problem is solved by using the Lyapunov optimization theory. Performance of the proposed scheme is evaluated with traditional FA approach and data queue-based FA approach. Numerical results exhibit that our scheme not only sustains a large network throughput but also achieves low latency and avoids the occurrence of a completely selfish relay in the long term. |
| Databáze: | OpenAIRE |
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