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Relay Selection for Machine-to-Machine Communication with the Same Source Requests in Heterogeneous Wireless Networks

Allah Gholi Ghasri, Monireh | 2022

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  1. Type of Document: Ph.D. Dissertation
  2. Language: Farsi
  3. Document No: 56162 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Hemmatyar, Ali Mohammad Afshin; Bayat, Siavash
  7. Abstract:
  8. Machine-to-machine communication (M2M) can be considered as one of the most important types of high-density communication in the Internet of Things (IoT). Therefore, how to send data using the cooperation of machines with each other and selecting the appropriate relay can play an effective role in improving the quality of network communication, especially when communication between sources and their destinations is weak. Since in the real world some of the applications used on a set of IoT machines require the similar bandwidth, we also followed this assumption. For this purpose, we went through three steps in this thesis. First, two new relay selection algorithms with static RF interface setting for simultaneous use of different interfaces are proposed for M2M communications called SORSA and MRSA. SORSA is a centralized algorithm that transforms the relay selection problem to a k-cardinality assignment problem, and can be solved using the Hungarian algorithm after completing the steps. MRSA is also a decentralized algorithm that uses matching theory to provide stable matching of relays. It is further proven that the SORSA results are optimal and the MRSA results are stable. The simulation results show an improvement in the results obtained from SORSA and MRSA by comparing the data rates obtained from the proposed and basic algorithms, when the number of channels is not limited. Therefore, SORSA improved by an average of 3% compared to MRSA and MRSA by 56% and 117%, respectively, compared to direct transmission and random relay selection. In the next steps, in order to effectively use the frequency spectra and increase the data transmission capacity on the network, the simultaneous use of different RF interfaces was considered when selecting the next-hop In this regard, in the second step, we present the optimization algorithm for selecting the relay simultaneously with the dynamic RF interface setting in M2M communication called the Dynamic Optimal Relay Selection and RF interface Setting Algorithm (DORSA). The simulation results show an improvement in the average data rate of DORSA with three interfaces (DORSA\_W-B-Z) up to a 10% compared to direct optimal transmission, SORSA and MRSA. Finally, we complete the third step by presenting a more comprehensive version of the previous algorithms as a new framework called Dynamic Optimal Next-hop Selection and RF interface Setting Algorithm (DONSA). In this framework, by optimally and dynamically setting of the RF interfaces in M2M communications and machine-to-base station (M2B), at the same time as selecting the next step in sending data, and considering the required bandwidth of machines, the data rate of networks with multiple base stations and sources with the same bandwidth, can be maximized. The simulations show that using this framework, the total average data rate of network sources can be increased up to 117%
  9. Keywords:
  10. Machine-to-Machine Communications ; Internet of Things ; Relay Node Selection ; Optimization Algorithms ; Matching Theory ; Static Radio Frequency Interfaces Setting ; Dynamic Radio Frequency Interface Setting ; Hungarian Algorithm ; Multiple Radio Frequency Interfaces ; k-Cardinality Assignment Problem

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