Rship Approach: Forward discovery queries using similarity, history and random Rships.
Updating Rships can be the activity performed while migration of servants.
Acquiring Rships can be performed as conduction process.
Discovery result backtracking would make system to learn much quicker.
Tradeoffs are overheads in all above operations.
Does above works better than Distributed Hash Table? Consider two cases for comparision: a) when the queries are similar and b) when queries are random.
Flooding: Obviously, it is going to take too much bandwidth, so it arises scalability issues.
Distributed Hash Table Algorithms: In this systems, every entity(file) and peer are assigned a unique key by a hash function. The keys along with the network addresses of peer storing the files are evenly distributed among all participating peers. Each peer maintains a routing table and queries are forwarded to only those peers which are listed in the routing table.
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