A Novel Scheduling Algorithm Based on Game Theory and Multicriteria Decision Making in LTE Network. (2nd March 2015)

• Record Type: Journal Article
• Authors: Hindia, Mohammad Nour; Reza, Ahmed Wasif; Noordin, Kamarul Ariffin
• Other Names: Jacob Lillykutty Academic Editor.
• Is Part Of: International journal of distributed sensor networks. (2015)
• Publication Date: 2015-03-02
• Subjects: Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1155/2015/604752
• Languages: English
• ISSNs: 1550-1329

Abstract

Abstract : Fourth generation wireless networks provide mobile users with high data rate and quality of services, such as Long Term Evolution (LTE), which has been developed by the 3rd Generation Partnership Project (3GPP). However, 3GPP is not a standardized scheduling algorithm to utilize LTE properties in smart grid applications. This paper proposes a two-level scheduling scheme composed of cooperative game theory (bankruptcy and shapely) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS). The proposed algorithm improves resource allocation for three smart grid applications, namely, voice, video surveillance, and metering data. On the first level, bankruptcy and shapely value algorithm fairly distribute the resources among smart grid applications. On the second level, TOPSIS algorithm allocates the resources among application's users based on their criteria and the application's preferences. Moreover, the system's performance has been evaluated in terms of throughput, delay, and fairness index. The proposed algorithm is compared with existing algorithms, such as proportional fairness, modified largest weighted delay first, and exponential rule schemes. The results show a significant improvement compared to other algorithms. This paper presents a novel technique consisting of both TOPSIS and game theory algorithms to study three smart grid applications. The novel algorithm has proven to be an effective scheduling technique for smart grid applications.