Analyzing Traffic Share Loss in Competitive Internet Networks Using a Markov Chain Model - Virendra Kumar Tiwari; Ashish Jain; Ripusoodan Sharma; Dev Kumar Chouhan; Pramod Kumar Saket (Mathematics and Computer Science: Contemporary Developments Vol. 10, 2024)
In today’s digital era, the internet has become an essential tool for information access and data communication, with a rapidly expanding user base globally. Concurrently, the proliferation of commercial Internet Service Providers (ISPs) has intensified competition and led to an increased load on network infrastructures. This rising demand has driven networks to operate near capacity, resulting in frequent congestion and a high probability of service blocking. This paper investigates the dynamics of internet traffic distribution in a competitive market environment, focusing on share loss when two ISPs compete across distinct markets with varying service quality. A Markov chain model is employed to perform share loss analysis, with iso-share curves illustrating how traffic share distribution shifts because of network congestion and service quality competition. Through a comprehensive simulation study, the research reveals that blocking probabilities significantly impact an ISP’s ability to retain initial traffic share, highlighting the role of Quality of Service (QoS) in user retention. The Markov chain approach effectively models user behaviors in scenarios where traffic congestion influences the shift in market share, particularly under high network demand conditions. This study underscores the critical importance of efficient traffic management and resource allocation in minimizing service interruptions and maintaining competitive QoS in multi-operator markets. The findings have implications for ISPs seeking to optimize resource distribution and manage network congestion, with a particular focus on enhancing the reliability and performance of internet services.