The least-used key selection method for information retrieval in large-scale Cloud-based service repositories

Abstract

As the number of devices connected to the Internet of Things (IoT) increases significantly, it leads to an exponential growth in the number of services that need to be processed and stored in the large-scale Cloud-based service repositories. An efficient service indexing model is critical for service retrieval and management of large-scale Cloud-based service repositories. The multilevel index model is the state-of-art service indexing model in recent years to improve service discovery and combination. This paper aims to optimize the model to consider the impact of unequal appearing probability of service retrieval request parameters and service input parameters on service retrieval and service addition operations. The least-used key selection method has been proposed to narrow the search scope of service retrieval and reduce its time. The experimental results show that the proposed least-used key selection method improves the service retrieval efficiency significantly compared with the designated key selection method in the case of the unequal appearing probability of parameters in service retrieval requests under three indexing models.

An adaptive key selection method for the multilevel index model for effective service management in the cloud

“…Based on the guideline, a least-used key selection method was proposed. 12 However, it only works under an ideal condition that the frequency of service invocations is fixed and known. Therefore, it does not solve the problem of retrieval efficiency degradation caused by drift of "hot" services.…”

“…In our previous paper, 12 the unequal frequency of service invocations in GPMIM was studied. One of its key contributions is that it provides a guideline for key selection under the condition of unequal frequency of service invocations.…”

“…The guideline has been proved theoretically and validated experimentally. Based on the guideline, a least‐used key selection method was proposed 12 . However, it only works under an ideal condition that the frequency of service invocations is fixed and known.…”

“…Gu et al 12 studied the case of unequal invocation frequency of services, proposed a key selection strategy for fixed service invocation frequency to improve service retrieval efficiency, and verified the effectiveness of the least‐used key selection method. However, Reference 12 does not address the problem of hot services changing over time, which can degrade the retrieval efficiency. In a multilevel index model, the distribution of service invocation parameters is based on how often the user invokes the service, which is usually determined by the user's interests.…”

“…Some services are “cold” and are rarely invoked. Gu et al 12 studied the case of uneven service invocation and proposed a least‐using key selection method to deal with this situation. It has been theoretically proven to be correct and experimentally validated.…”