An Adaptive Multilevel Indexing Method for Disaster Service Discovery

Abstract

With the globe facing various scales of natural disasters then and there, disaster recovery is one among the hottest research areas and the rescue and recovery services can be highly benefitted with the advancements of Information and Communications Technology (ICT). Enhanced rescue effect can be achieved through the dynamic networking of people, systems and procedures. A seamless integration of these elements along with the service-oriented systems can satisfy the mission objectives with the maximum effect. In disaster management systems, services from multiple sources are usually integrated and composed into a usable format in order to effectively drive the decision-making process. Therefore, a novel service indexing method is required to effectively discover desirable services from the large-scale disaster service repositories, comprising a huge number of services. With this in mind, this paper presents a novel multilevel indexing algorithm based on the equivalence theory in order to achieve effective service discovery in large-scale disaster service repositories. The performance and efficiency of the proposed model have been evaluated by both theoretical analysis and practical experiments. The experimental results proved that the proposed algorithm is more efficient for service discovery and composition than existing inverted index methods.

Performance formula‐based optimal deployments of multilevel indices for service retrieval

“…Inverted index is one of the most popular indices . It can narrow search space and improve retrieval efficiency.…”

“…However, unfortunately, there are few works addressing this issue except our previous works as far as we know.…”

“…Their services are stored in a sequence structure actually, or in other words, they do not address the issue of storage. As proved by Wu et al, sequence index is time‐consuming.…”

“…Wu et al propose four level indices, ie, L 4 I, L 3 I, L 2 I, and L 1 I, to deal with them. Since every service repository has different characteristics, Wu et al discuss three deployments in details. Each deployment corresponds to an index model.…”

An efficient algorithm for partially matched services in internet of services

“…There are number of approaches for discovery and selection of services in IoT environment [1,[5][6][7]. However, discovery and selection is a challenging process especially when there is a list of available services with similar functionality but different QoS parameters such as execution time, security, and cost in line with the increasing number of available services.…”