A new proxy caching scheme for parallel video servers

Chen, Hao; Jin, Hai; Sun, Jianhua; Liao, Xiaofei; Deng, Dafu

doi:10.1109/iccnmc.2003.1243086

Cited by 5 publications

(1 citation statement)

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“…The ω balances the global search and the local search; and it is introduced to minimize linearly with time from a value of 1.4–0.5 which can be found in [16]. For this itself global search initiates with a large weight and then decreases with time to favor local search over global search which can be found in [17, 18]. …”

Section: Ods Algorithmmentioning

confidence: 99%

Hybrid Swarm Intelligence Optimization Approach for Optimal Data Storage Position Identification in Wireless Sensor Networks

Mohanasundaram

Periasamy²

2015

The Scientific World Journal

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The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches.

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Section: Ods Algorithmmentioning

confidence: 99%