Name
Title | ||
|---|---|---|
Recover Fault Services via Complex Service-to-Node Mappings in Wireless Sensor Networks |
Abstract | ||
|---|---|---|
With the motivation of seamlessly extending wireless sensor networks to the external environment, service-oriented architecture comes up as a promising solution. However, as sensor nodes are failure prone, this consequently renders the whole wireless sensor network to seriously faulty. When a particular node is faulty, the service on it should be migrated into those substitute sensor nodes that are in a normal status. Currently, two kinds of approaches exist to identify the substitute sensor nodes: the most common approach is to prepare redundancy nodes, though the involved tasks such as maintaining redundancy nodes, i.e., relocating the new node, lead to an extra burden on the wireless sensor networks. More recently, other approaches without using redundancy nodes are emerging, and they merely select the substitute nodes in a sensor node's perspective i.e., migrating the service of faulty node to it's nearest sensor node, though usually neglecting the requirements of the application level. Even a few work consider the need of the application level, they perform at packets granularity and don't fit well at service granularity. In this paper, we aim to remove these limitations in the wireless sensor network with the service-oriented architecture. Instead of deploying redundancy nodes, the proposed mechanism replaces the faulty sensor node with consideration of the similarity on the application level, as well as on the sensor level. On the application level, we apply the Bloom Filter for its high efficiency and low space costs. While on the sensor level, we design an objective solution via the coefficient of a variation as an evaluation for choosing the substitute on the sensor level. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/s10922-014-9302-z | Journal of Network and Systems Management |
Keywords | Field | DocType |
WSN,Faulty recovery,Context awareness,Knowledge granularity,Bloom Filter | Sensor node,Key distribution in wireless sensor networks,Computer science,Network packet,Visual sensor network,Computer network,Brooks–Iyengar algorithm,Redundancy (engineering),Mobile wireless sensor network,Wireless sensor network,Distributed computing | Journal |
Volume | Issue | ISSN |
23 | 3 | 1064-7570 |
Citations | PageRank | References |
2 | 0.37 | 26 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qian Li | 1 | 32 | 8.29 |
| Wenjia Niu | 2 | 178 | 30.33 |
| Gang Li | 3 | 381 | 62.77 |
| Endong Tong | 4 | 39 | 5.37 |
| yue hu | 5 | 2 | 0.37 |
| ping liu | 6 | 2 | 0.37 |
| Li Guo | 7 | 102 | 10.23 |