Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In this article,  formalize  locally distributed predicates , a concept previously introduced to address specific challenges associated with modular robotics and distributed debugging. A locally distributed predicate (LDP) is a novel construction for representing and detecting distributed properties in sparse-topology systems. Our previous work on LDPs presented empirical validation; here  show a formal model for two variants of the LDP algorithm, LDP-Basic and LDP-Snapshot, and establish performance bounds for these variants.  prove that LDP-Basic can detect strong stable predicates, that LDP-Snapshot can detect all stable predicates, and discuss their applicability to various distributed programming domains and to spatial computing in general. LDP detection in bounded-degree networks is shown to be scale-free, making the approach particularly attractive for specific topologies, even though LDPs are less efficient than snapshot algorithms in general distributed systems.
['Michael De Rosa', 'Seth Copen Goldstein', 'Peter Lee', 'Jason Campbell', 'Padmanabhan Pillai']
I am writing a research paper on a idea Detecting Locally Distributed Predicates
[{"from": "human", "value": "I am writing a research paper on a idea Detecting Locally Distributed Predicates"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In this article,  formalize  locally distributed predicates , a concept previously introduced to address specific challenges associated with modular robotics and distributed debugging. A locally distributed predicate (LDP) is a novel construction for representing and detecting distributed properties in sparse-topology systems. Our previous work on LDPs presented empirical validation; here  show a formal model for two variants of the LDP algorithm, LDP-Basic and LDP-Snapshot, and establish performance bounds for these variants.  prove that LDP-Basic can detect strong stable predicates, that LDP-Snapshot can detect all stable predicates, and discuss their applicability to various distributed programming domains and to spatial computing in general. LDP detection in bounded-degree networks is shown to be scale-free, making the approach particularly attractive for specific topologies, even though LDPs are less efficient than snapshot algorithms in general distributed systems."}]