Auction inspired service replication for context‐aware IoT environment. (1st February 2023) - Banerji, Nandan; Choudhury, Subhrabrata
Summary: In rise of the Internet of Things, services are so connected and touched by the users that services are requested very often with some quality of experience (QoE) standards. Even sometimes, they are called from different regions with varying demand densities. To meet that, the IoT middleware needs to replicate the services as per user's demand. Some intuitive approaches also made with context‐aware replication techniques. In this work, we focus on the context‐aware and proactive replication strategies for IoT services, so that the service response deadline can be met and consequently, the QoE can be satisfied. Sometimes nodes having enough resources are overlooked to participate in replication process. In that case, the system becomes bound to select less capable candidate nodes to replicate a service. We went with a price (auction) based strategy so that the users with enough available resources get motivated to participate in replication. This way, the system becomes cooperative among peers with an intention to earn some incentives. We consider service discovery time, service response time and service drop rate as performance metrics and compared with two state of the art proposals. It is found that the proposed method outperforms both.