Hybrid swarm intelligence optimization approach for optimal data storage position identification in wireless sensor networks.

Pappampalayam Sanmugam Periasamy,Ranganathan Mohanasundaram

doi:10.1155/2015/597486

Pappampalayam Sanmugam Periasamy, Ranganathan Mohanasundaram

Open Access

https://doi.org/10.1155/2015/597486

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Abstract

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.

Highlights

The approach here in wireless sensor network (WSN) with regard to data storage approach aims at identifying the best data storage positions which basically is the primary issue and which encompasses many challenges
In order to evaluate the performance of proposed particle swarm optimization (PSO) algorithm with fuzzy c-means (FCM) clustering, a wireless sensor network is implemented in simulator to execute some experiments for the data storage position
Sensor node and storage node are randomly deployed in a 400 × 400 square area, and the sink node is in the center

Summary

Introduction

The approach here in wireless sensor network (WSN) with regard to data storage approach aims at identifying the best data storage positions which basically is the primary issue and which encompasses many challenges. On the other hand an appropriate data storage approach can efficiently minimize delays occurring in processing queries and energy consumed and lengthen the lifespan of the sensor network as mentioned in [3]. Apt and well-suited approaches that are inherently efficient are imperative to adjust data position which further can help minimize costs of storage and enable identifying query as mentioned in [4]. Producers as well as consumers rate of data and respective distances from the path leading to storage node are two essential aspects influencing data storage-related communication cost. In a practical sensor network, the storage node is closer to the producers and consumers; the cheaper one is to store and query a fixed quantity of data. An effective formulation would be to place data adaptively based on network state so that the communication cost is reduced once the data storage position is fixed which can be found in [5]

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