Improving data centric storage with diffuse caching in wireless sensor networks

Abstract

In a sensor network that adopts data-centric storage (DCS), information of the same kind is kept in the same set of nodes. That is, when a sensor detects a certain event, no matter where it is, it sends the information to the designated location. When another node wants the information, it can send a query to that location to retrieve it. Unfortunately, existing protocols based on DCS are prone to the hot-spot problem where some nodes have to handle lots of messages. In this paper, we study how to apply diffuse caching on top of DCS. We diffuse popular information to other nodes so as to share the workloads. Our diffusing mechanism is adaptive that the distribution varies based on the popularity of the event type. We evaluate our protocol using simulations and the results show that our protocol successfully alleviates the hot-spot problem and reduces the message overheads.

Comparing and Analysis on Adaptive Information-brokerage Schemes in Wireless Sensor Networks

“…EHS [13] hashes an event type to a point in a face, and the nodes in the face are responsible for the data storage and retrieval. Reference [14] applies diffuse caching on top of DCS to solve the problem of hot spot. Another problem in GHTs is data retrieval may be failed when the nodes near the hashed points move.…”

Adaptive Information Brokerage in Wireless Sensor Networks with Mobile Sinks

“…EHS [7] hashes an event type to a point in a face, and the nodes in the face are responsible for the data storage and retrieval. Reference [8] applies diffuse caching on top of DCS to solve the problem of hot spot. Another problem in GHTs [5] is data retrieval may be failed when the nodes near the hashed points move.…”

A Virtual-Ring-Based Data Storage and Retrieval Scheme in Wireless Sensor Networks

“…GHTs [8] are a classic work of this category. One of the shortcomings in GHTs is that it brings a hotspot problem [9]. To solve the hotspot problem, a lot of works were done later.…”

“…Recently, a lot of in-network data storage and retrieval schemes [3][4][5][6][7][8][9][10][11][12][13] have been proposed. In most of the existing schemes, the frequencies of event and query are less considered, while in fact they play an important role on the efficiency of the schemes.…”