|Appears in Collections:||Computing Science and Mathematics Book Chapters and Sections|
|Title:||Improving Wide Area P2P Service Discovery Mechanisms using Complex Queries|
|Editors:||Prasad, Anand R.|
Buford, John F.
Gurbani, Vijay K.
|Citation:||Furness J & Kolberg M (2011) Improving Wide Area P2P Service Discovery Mechanisms using Complex Queries. In: Prasad Anand R., Buford John F., Gurbani Vijay K. (ed.). Future Internet Services and Service Architectures. The River Publishers Series in Communications, Aalborg, Denmark: River Publishers, pp. 183-203.|
|Series/Report no.:||The River Publishers Series in Communications,|
|Abstract:||With smartphones and other network enabled consumer devices becoming increasingly popular, the number of available services and their complexity is growing considerably. With an increasingly large and dynamic environment it is important that users have a comprehensive yet efficient mechanism to discover these services. Many existing wide-area service discovery mechanisms are centralised and do not scale to large amounts of users. Peer-to-peer networks however have been prove to scale well, and can be used to provide not just a platform on which peers can offer and use services without relying on a centralised resource, but also as a means of service discovery. There are various wide-area peer-to-peer service discovery mechanisms that allow discovery of services via their attributes, however the majority are limited to keyword matching and do not support other types of complex queries. This chapter starts with a review of complex queries and existing approaches which provide support for such queries. We illustrate the use of blind search in Distributed Hash Tables (DHTs) to provide support for all types of complex queries, such as wild- card search, range queries, and even regular expressions. Using blind search allows for processing the search query at every node within the network, supporting queries as complex as required. However due to the nature of broadcast trees search performance suffers under high churn levels; to combat this we note that data is already replicated within the network for redundancy. This can be further used to improve the success rate of blind search when under high churn. Finally, we present novel results considering churn level vs replication of data.|
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