Techniques and Challenges of Data Centric Storage Scheme in Wireless Sensor Network
Abstract
:1. Introduction
2. Taxonomy and Design Drivers
2.1. Multi-Dimensional Attribute
2.2. Range versus Point Queries
2.3. Similarity Search
2.4. Data Aggregation
2.5. Non-Uniformity of Sensor Network Field
2.6. Multi-Replication
2.7. Load Balancing
3. DCS Scheme Families
3.1. Geographic Hash Table
3.2. Similarity Data Storage (SDS)
3.3. Similarity Search Algorithm
3.4. Dynamic Load Balancing
3.5. Load Balanced Data-Centric Storage
3.6. Tug-of-War
3.7. Quadratic Adaptive Replication
3.8. Double Rulings
3.9. Distributed Erasure Coding in DCS
3.10. Distributed Index for Features
3.11. Practical Data-Centric Storage
3.12. Hierarchical Voronoi Graph Based Routing
3.13. Data Storage and Range Query for Multidimensional Attribute
4. Classification Based on Taxonomy and Design Drivers
4.1. Range Query
4.2. Similarity Search
Attribute | Keywords | Weight |
---|---|---|
Object | Car, Plane, Truck, etc. | 0.3 |
Model | F-16, F-17, etc. | 0.2 |
Color | Red, Purple, etc | 0.1 |
Direction | North, South, etc | 0.1 |
Division | Air-Force, etc. | 0.1 |
Pressure | Integer | 0.1 |
Speed | Float | 0.1 |
.. | .. | .. |
- Case 1: IT is non-empty and vIT s is the most similar local data in IT.
- ○ Sub-case 1: If vIT s is larger than vq, then all data in IT+1 must be even greater than vq. But in IT-1 there may be a that is closer to vq.
- ○ Sub-case 2: If vIT s is smaller than vq, then all data in IT-1 must not be more similar to than vIT s is. But in IT+1 there may be a vIT+1 s that is closer to vq.
- Case 2: IT is empty (i.e., no data stored). vq has to be sent to both neighbors (i.e., IT−1 and IT+1) of IT to find the most similar data.
4.3. Data Aggregation
4.4. Sensor Network Field Non-Uniformity
4.5. Multi-Replication
Schemes | Policy | RoutingAmong Replica Nodes | Remark | |
---|---|---|---|---|
1 | SR-GHT [1] | Hierarchical Grid Replication Mechanism (4d) | Recursive Hierarchical | As data never replicated to all nodes, basic data lost problem exists |
2 | SDS [19] | Head node stores copy of all client data | N/A | Single point of head zone failure. Head zone energy depletes quicker than others |
3 | ToW [27] | Hierarchical Grid Replication Mechanism (4d) | Combing | Extends SR-GHT by adding two modes of operation. It inherits drawbacks from SR-GHT |
4 | SSA [22] | Create mirror of index node using Mirror Hilbert Curve & Mirror Mapping Function | Not Specified | It doesn’t explain how data would be mirrored rather just a proposal is mentioned by couple of lines |
5 | RDCS [36] | Each zone has at most one replica node of mirror node | GPSR | Selection of mirror node is not specified clearly. |
6 | QAR [16] | Hierarchical Grid Replication Mechanism with Quadratic Evolution (d2) | Combing | Inherits drawbacks from SR-GHT |
6 | Double Rulings [28] | Stores data replica at a curve instead of one or multiple isolated sensors | Greedy Routing on a Curve | Can only employ 2 global replicas while tow and qar are adaptable to traffic load with multiple replicas |
7 | Dynamic Random Replication [41] | Replicate data in randomly selected set of data replication nodes | Minimum Spanning Tree | Two major limitations: static WSN and consideration of homogenous spatial applications |
4.6. Load Balancing
Functionalities | Schemes | Method Used |
---|---|---|
Intra-Zone Load Balance | DLB [23] | Cover-up Scheme |
Inter-Zone Load Balance | SDS [19] | Measuring Storage Usage Status ( ) |
DLB [23] | Extended Grid (Cover up grid) | |
HVGR [33] | Proportional Assignment of Storage Task to Regions | |
LB-DCS [24] | Sampling Density, Broadcast, Stripes, FatStripes | |
KDDCS [42] | Weighted Split Median | |
Routing Load Balance | SDS [19] | Distributing Routing Load to All Possible Routes Equals to |
4.7. Routing Algorithm
Routing Algorithm | Schemes | |
---|---|---|
Point-to-Point Routing | GPSR | MDA [35], GHT [1], DLB [23], DIM [13], D-GHT [43], LB-DCS [24], Q-NIGHT [25], SSA [22], Tug-of-War [27], RDCS [36] |
Logical Stateless Routing (LSR) | KDDCS [42] | |
CAR-POOLING | SDS [19] | |
COMBING | Tug-of-War [27] | |
Recursive Hierarchical Routing | SR-GHT [1] | |
Tree Based Hierarchical Routing | GPSR | DIFS [30], DIM [13] |
PATH BASED TREE STRUCTURE | PathDCS [32] | |
HIERARCHICAL VORONOI GRAPH BASED ROUTING | HVGR [33] | |
VPCR | GEM [44] |
5. Conclusion
Title | Routing Category | Dimension (attribute) | Range vs. Point Query | Data Aggregation | Similarity Search | Multi Replication | Load Balance | |
---|---|---|---|---|---|---|---|---|
1 | Geographic Hash Table (GHT) [1] | Point-to-PointRouting | Single | Point | No | No | No | No |
2 | Data Storage and Range Query Mechanism for Multi-dimensional Attributes. [35] | Point-to-PointRouting | Multi | Range | No | No | No | No |
3 | Distributed Spatial-Temporal Data Storage Scheme. [19] | Point-to-PointRouting | Multi | Range | No | Yes | No | Yes |
4 | Load Balanced and Efficient Hierarchical Data-Centric Storage. [33] | Point-to-Point Routing | Single | Point | No | No | No | Yes |
5 | Dynamic Load Balancing Approach [23] | Point-to-Point Routing | Single | Point | No | No | No | Yes |
6 | Load Balanced Data-Centric Storage (LB-DCS) [24] | Point-to-Point Routing | Single | Point | No | No | No | Yes |
7 | Tug-of-War [27] | Point-to-Point Routing | Single | Point | No | No | Yes | No |
8 | Efficient Mechanism for Similarity Search [22] | Point-to-Point Routing | Single | Both | No | Yes | No | Yes |
9 | DIFS: A Distributed Index for Features in Sensor Network [30] | DCS Based on Tree-Structure | Single | Range | No | No | No | No |
10 | PathDCS [32] | DCS Based on Tree-Structure | Single | Point | No | No | No | No |
11 | DIM [13] | DCS Based on Tree-Structure | Multi | Both | No | No | No | No |
12 | GEM [44] | DCS Based on Tree-Structure | Single | Range | No | No | No | No |
13 | KDDCS [42] | DCS Based on Tree-Structure | Single | Range | No | No | No | Yes |
14 | RDCS [36] | Point-to-Point Routing | Single | Range | Yes | No | No | No |
15 | Modeling Data Aggregation [38] | Point-to-Point Routing | Single | N/A | Yes | No | Yes | No |
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Ahmed, K.; Gregory, M.A. Techniques and Challenges of Data Centric Storage Scheme in Wireless Sensor Network. J. Sens. Actuator Netw. 2012, 1, 59-85. https://doi.org/10.3390/jsan1010059
Ahmed K, Gregory MA. Techniques and Challenges of Data Centric Storage Scheme in Wireless Sensor Network. Journal of Sensor and Actuator Networks. 2012; 1(1):59-85. https://doi.org/10.3390/jsan1010059
Chicago/Turabian StyleAhmed, Khandakar, and Mark A. Gregory. 2012. "Techniques and Challenges of Data Centric Storage Scheme in Wireless Sensor Network" Journal of Sensor and Actuator Networks 1, no. 1: 59-85. https://doi.org/10.3390/jsan1010059