TY - GEN
T1 - Implementing atomic data through indirect learning in dynamic networks
AU - Konwar, Kishori M.
AU - Musial, Peter M.
AU - Nicolaou, Nicolas C.
AU - Shvartsman, Alex A.
N1 - DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.
PY - 2007
Y1 - 2007
N2 - Developing middleware services for dynamic distributed systems, e.g., ad-hoc networks, is a challenging task given that such services deal with dynamically changing membership and asynchronous communication. Algorithms developed for static settings are often not usable in such settings because they rely on (logical) all-to-all node connectivity through routing protocols, which may be unfeasible or prohibitively expensive to implement in highly dynamic settings. This paper explores the indirect learning, via periodic gossip, approach to information dissemination within a dynamic, distributed data service implementing atomic read/write memory service. The indirect learning scheme is used to improve the liveness of the service in the settings with uncertain connectivity. The service is formally proved to guarantee atomicity in all executions. Conditional performance analysis of the new service is presented, where this analysis has the potential of being generalized to other similar dynamic algorithms. Under the assumption that the network is connected, and assuming reasonable timing conditions, the bounds on the duration of read/write operations of the new service are calculated. Finally, the paper proposes a deployment strategy where indirect learning leads to an improvement in communication costs relative to a previous solution that assumes all-to-all connectivity.
AB - Developing middleware services for dynamic distributed systems, e.g., ad-hoc networks, is a challenging task given that such services deal with dynamically changing membership and asynchronous communication. Algorithms developed for static settings are often not usable in such settings because they rely on (logical) all-to-all node connectivity through routing protocols, which may be unfeasible or prohibitively expensive to implement in highly dynamic settings. This paper explores the indirect learning, via periodic gossip, approach to information dissemination within a dynamic, distributed data service implementing atomic read/write memory service. The indirect learning scheme is used to improve the liveness of the service in the settings with uncertain connectivity. The service is formally proved to guarantee atomicity in all executions. Conditional performance analysis of the new service is presented, where this analysis has the potential of being generalized to other similar dynamic algorithms. Under the assumption that the network is connected, and assuming reasonable timing conditions, the bounds on the duration of read/write operations of the new service are calculated. Finally, the paper proposes a deployment strategy where indirect learning leads to an improvement in communication costs relative to a previous solution that assumes all-to-all connectivity.
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U2 - 10.1109/NCA.2007.30
DO - 10.1109/NCA.2007.30
M3 - Conference contribution
AN - SCOPUS:46749134366
SN - 0769529224
SN - 9780769529226
T3 - Proceedings - 6th IEEE International Symposium on Network Computing and Applications, NCA 2007
SP - 223
EP - 230
BT - Proceedings - 6th IEEE International Symposium on Network Computing and Applications, NCA 2007
T2 - 6th IEEE International Symposium on Network Computing and Applications, NCA 2007
Y2 - 12 July 2007 through 14 July 2007
ER -